Transactions - The concepts - Part 3

Today, as we write application code we generally are not dealing with immutable state/data, we are applying application logic to state/data so that it transforms from one known state to another known state in a consistent, all or nothing fashion. Today, when performing this in code that does not involve Transaction Managers or Resource Managers, we use Try/Catch exception handling statements to mimick the "Commit" and "Rollback" concepts of transactions. The difficulties with such an approach is that as we scope certain types of work and/or scope more than a few simple actions into a unit of work, the level of complexity in nested try/catch code grows and can easy reach a point where it cannot truely provide the "Commit" and "Rollback" concepts of a Transaction.

For example, take the Try/Catch below

try
{
 // operation(stateX)
 // operation(stateY)
 // operation(stateZ)
}
catch
{
  // cleanup after states X, Y, and/or Z, as something has gone wrong and we need to get to a previously known state
}

The challenges with using try/catch in a Commit/Rollback style are some of the following:

- If stateX is shared between between more that one execution contexts, another execution context may read an inconsistent state and hence a "dirty" read, as the scoped unit of work may fail
- What if an operation on stateY deletes/alters a resource and how do we "Rollback" in the catch.
- How do we coordinate with resources that are transactional, i.e. if stateX represents a call to a transaction queuing/messaging or database system. How we coodinate between the different resources and unit of works!
- and there is lots of other problems

While all of the above can be eventually handled in code, with careful planning and structure, but what is the essence of what we are trying to achieve in the code and does it form a pattern! It is the "Commit" and "Rollback" concepts of a Transaction and if we factor the patterns, interfaces, contracts and interactions of Transacional Processing into the code we have more flexibility and agility. Please note I am not suggesting that every try/catch has a "Commit" or "Rollback" focus, but we sometimes use try/catch to group actions into a unit of work in which we determine the outcome of a unit of work by interrogation (using if statements) and do not negotiate/coordinate the outcome of the unit of work (as an example). Also, to provide the most flexibility and agility, we need for the actions that are grouped into a unit of work to be able to be aware of the (transactional) context. We also have the problem that try/catch is not context aware, i.e. it only knows a single execution context, and while dealing with a single execution context may suit us some times, we need to be able to handle both concurrency management and recovery control at the same time!

One approach to providing a cleaner implementation, is to factor out the interrogation and make it the negotiation/coordination of the outcome from the application logic and for an intermediary to work as a coordinator between the resources being used and the application logic. The coordinator controls the enlistment of resources within a scoped execution context (as defined by the application code) that we want to be transactional. We then need to define a number of common interfaces and interaction semantics, so that the use/enlistment of one or more resources in the scope/context of a unit of work is clearly defined. This can be achieved by having methods/semantics/behaviors common to all resources so that the different stages of moving/transforming from one known state to another known state as a unit of work or as a part of a unit of work, happens in an all or nothing fashion.

All of this fits quite nicely with the 2 phase commit (and even the one phase commit) protocol as to how the "Commit" or "Rollback" semantics of units of work can be achieved.

Oppps ....... Hmmmm .....  since I thought I was going to be able to do this is 3 to 4 postings, I seem to have underestimated and need one or two more. I think I will leave it here for now with this posting and follow up with a part 4,5,6

 

Transactions - The concepts - Part 2

In general, when we think of Transactions we tend to think of database transactions. Databases are a great example of how a data server can implement transactions and therefore handle concurrency, provide isolation and provide consistency. The concept of what constitutes a Transaction expands beyond that of a Database Transaction and with this we have more and more areas where the abstraction and contracts that make up a Transaction can help us with the problem of how to handle concurrency management and recovery, as we apply application logic to state and consistently move from one known state to another.

So when we look at a Transaction, what are main parts involved? At a base level it is composed of three parties, i.e. an Application, a resource manager and a transaction manager. So how they are involved in a transaction and what is their role in a transaction?

The Application is pretty self explanatory, it’s your code. Its role in a transaction is to define the scope of a transaction, perform read/write operations on a resource manger and specify whether it views the state as being consistent. A resource manager is a component that manages a stable data storage system (i.e. it always shows a consistent view of data/state), and participates in the two phase commit and recovery protocols with the transaction manager. A transaction manager tracks which resource managers participate in the transaction, provides an interface to the application – start, commit, rollback and also, coordinates the transaction outcome between the resource managers. The transaction manager has the responsibility of properly handling error conditions, on behalf of an application, recover from them and ensure that the resource managers are always in a consistent state.

With today’s technologies the Resource Managers that typically get used are those of databases systems and queue managers. But is there other times when you need to be transforming/moving from one state to another? There certainly are!

The basic premise of Transactions is the coordination/negotation of an outcome that groups actions into a unit of work that transforms from one known state to another. As the transformation of state, the coordination/negotation of an outcome, or the grouping of action into a unit of work are something we do very often in application logic, is this not a Transaction.

So when do we get involved in the transformation of state, the coordination/negotation of an outcome, or the grouping of action(s) into a unit of work? What are we trying to achieve, how do we generally do it today and is there a better way to do it?

I've kicked off Part 3, to share my views on this and hopefully provide some insight!

Transactions - The concepts - Part 1

When thinking about Transactions, I think it is fair to say that Transactions are one of the most powerful and frequently used paradigms in Enterprise Computing today. With Transactions, we have a collection of patterns that deal with how concurrency management and recovery control can be handled in possible shared/concurrent environments/contexts and it is this that ensures data/state correctness. It is the key concepts and abstractions of Transactions maintaining data/state consistency in possible concurrent state/data access environments (where failures may occur) that have allowed us as developers and architects to be largely released from having to deal with the tricky aspect of maintaining the correctness of state in concurrent environments in an enterprise application.

Two of the very interesting aspects of Transactions is how trusted they have become and how we perceive them. Concurrency Management and recovery control are some of the more tricky aspects of Enterprise Computing, but yet when leveraging the Transactional paradigm and executing units of work in a concurrent environment in the context of a transaction, we are not overly concerned about isolation or failure as much of the work is done for us by the Transaction Paradigm. This is a testament to the level of trust and adoption that Transactions have achieved as an abstraction and how it has evolved into a framework of runtime services that takes most of the responsibility for concurrency management and recovery control from us as developers and architects. The paradigm of Transactions can be seen as a set of patterns, Interfaces and Contracts that can be leveraged to simplify the transformation from one known state to another and without these Interfaces and Contracts; a lot of code, time and effort has to be spend in making sure that data/state transformations happen in a consistent and all or nothing fashion.

It is these key abstractions in the form of runtime services or frameworks that have provided great productive gains for us as developers and architects, as it allows us to focus on business logic and allows for the underlying runtime services to deal with concurrency management and recovery control. Therefore as we implement application logic, by applying units of work to state, we want the transformation from one state to another to be applied in a consistent (all or nothing) fashion, as well as wanting to be isolated from other parallel activities. As I mentioned in my How should we think of Transactions ? blog posting, I like to think of the Transaction paradigm as a collection of patterns, interfaces and contracts that can be leveraged to tackle the issue of data/state correctness as we group actions into unit of works to transform from one known state to another. Some of this collection of patterns, interfaces and contracts are short running transactions that in the main adhere to the ACID properties but there is a rich portfolio of transactional types that we do not focus on that much and/or maybe perceive as not meeting the ACID properties (see How should we think of Transactions ? and Volatile Transactions & In-Memory Transactions - do they have ACID, ACId or ACI properties? )

Today, the most common example of how the Transaction paradigm can provide concurrency management and recovery control is Database Management Systems (DBMS). Databases (aka DBMS) are themselves another key and often used architectural piece of Enterprise computing. Database Management Systems (DBMS) provide a paramount role in how an Enterprise may store, retrieve and share state/data. But we sometimes draw an association between Databases and Transactions that is so close that they are often perceived as being interchangeable, i.e. Transactions are DB Transactions and nothing else. The close associations between databases systems and transactional processing have been fundamental in bringing the concept of Transactional Processing to the fore, but in my honest opinion I think that the close association may have also brought a narrowing of perception of what are Transactions and Transactional Processing.

I have put together a series of blog postings to share my current views/thoughts! After talking to a few folks about Transactions, it is very interesting to hear the different views and I'm not sure if there is a one size fits all for what is a transaction, but this is the thing about a paradigm and a snappy acronym, it can have a life of its own   Maybe we interchange the paradigm, acronym’s and implementations into one fixed view and its this fixed view that maybe causing the issue!

 

Volatile Transactions & In-Memory Transactions - do they have ACID, ACId or ACI properties?

In my last blog posting, How should we think of Transactions ? I mentioned Volatile transactions and how I currently think they can be perceived in different ways! Do they have ACID, ACId or ACI properties?

In case you do not know what Volatile Transactions (aka In-Memory Transactions) are, they are transactions that do not persist to a durable store such as a hard disk (ouch! we have multiple definitions of durable to content with ). They are transactions that are done completely in memory and do not incur the I/O cost of writing to a hard disk a Transaction log or the actual known data/state.

What is interesting about Volatile transactions is that they are sometimes perceived as not being Transactional, because they are viewed as not meeting the ACID properties, especially the "D" property. I suspect the main reason for this view is because there are no Transaction logs and/or no data stored to hard disk.

So when you look at a typical definition of the ACID properties (like what I have listed below), some of the reasons why this view maybe held become apparent:

(NB. this is an amalgamation/synopsis of many definitions I have seen)

A - Atomicity - Transactions are atomic (all or nothing)

C - Consistency - The transaction is a correct transformation of state. Consistency constraints that are defined on the underlying data servers are preserved by a transaction.

I - Isolation - Each transaction should appear to execute independently of other transactions that may be executing concurrently in the same environment.

D - Durability - Once a transaction commits, it’s updates survive even, if the system goes down

ok, so a Volatile Transaction meets the ACI of the ACID properties, but not the D as defined above. But is this ("Once a transaction commits, it’s updates survive even, if the system goes down") a true reflection of what Durability means? Many similar variants of this definition gets used on a frequent based and they bring specifics to the definiton that are not about the failure of meeting the ACI properties or making the "Commited" value available/public but focus on the failure of media or a system. In my opinion the failure of media or a system is not an aspect of the paradigm or indeed part of the ACID properties, but an aspect of how the paradigm can be implemented and/or a requirement of the longevity of the state being persisted/determined. It is perhaps the fact that the best known implementation of the data server feature of the transactional paradigm is a database that has led us to shape the ACID properties to the specifics of databases. But perhaps the Transactional paradigm has more to offer than the correctness of data/state transformations on a database. The transaction paradigm has a core focus on simpilifing how we can achieve the correctness of data/state transformations where we may have to deal with concurrency management and recovery control and this can be applied to any transformation of state.

Perhaps a different way to look at the durability of ACID is where the definition of ACID as an acronym came from and how some of the leading experts in the industry define them. As far as I know the ACID acronym was first coined by Haerder and Reuter (1983). The definition I like to use is that by Gray and Reuter (1993). It is the following:

A - Atomicity - A transaction's changes to state are atomic: either all happens or none happen. These changes include database changes, messages, and all actions on transducers.

C - Consistency - A transaction is a correct transformation of the state. The actions taken as a group do not violate any of the integrity constraints associated with the state. This requires that the transaction be a correct program.

I - Isolation - Even though transactions execute concurrently, it appears to each transaction, T, that others executed either before T or after T, but not both

D - Durability - Once a transaction completes successfully (commits), its changes to the state survive failures.

When you read this definition of Durability (and the ACID properties overall), it in my option explains the feature richness of transactions and how it can be applied to the persistence of the transformation of state and also how it applies to the other properties such as A, C and I. The state survives failures by the data server ensuring that when the transaction commits a new durable state is persisted/stable/available/public and if something goes wrong (such as not be able to ensure Consistency) that the data server returns to the previous known state. In essence, this is a contract that guarantees the persistence and stability of the state and that the outcome of a transaction is known/public and usable in subsequent transactions, as a known/correct state. A good definition I have seen is that once a transaction is committed, it cannot be abrogated.

With Durability being about the persistence, stability and making public of “commited”/known state as we transform from one known/correct state to another, it allows us to leverage the transaction paradigm in many scenarios. For example when using Volatile Transactions, we are leveraging data servers that store data on Volatile media, such as RAM and providing the transaction paradigm in-memory. With the common misunderstanding that Transactions are exclusively for databases, the question arises about the “D” property.

For me the Durability aspect of a transaction is present in a Volatile transaction. The question is whether its “D” or “d”. Since most transactions are based on the X/Open Transaction processing model, the requirement for log managers or lock managers in resource managers (data servers) are not central or core to implementing the transactional paradigm at a base level. In relation to the usage of Volatile media for Transactions? in my opinion the requirement of the media used by the data server is that it is able to present a stable/persistent/public state once "Commit" has occured.  So I believe that Volatile Transactions meet all of the ACID properties and that its ACID with a "D"

phew! long post.

I guess the crux of the issue is the 2 uses of "durable" when talking about Transactions. One is the "D" in the ACID properties and the other is the property of the data/state/media being used (and how it is stored). The "D" in the ACID properties is more about making a "commited" value available and the other is about an implementation requirement of how long (and/or resilient) a known/committed state must be.

 

 

PDC 2005 - are you going to be there? Los Angelas - Sept. 11 - 16, 2005

So now the news is out, there is going to be a PDC 2005

There are currently no more details available , but you can signup for updates as the details develop. 

 

IIS6 and Windows 2003 (Part 3)

In my opinion 2 of the more important parts of the new architecture in IIS 6.0 are:

• the addition of a HTTP endpoint that is seperate and distinct from IIS, i.e. HTTP.SYS
• the new process model in IIS 6.0, which is called Worker Process Isolation Mode (WPIM).

The seperation of the HTTP endpoint from IIS is very interesting, as it allows any application to partake in the processing of HTTP traffic. This allows any application, including the WWW Service in IIS, to leverage a common component for the processing of HTTP traffic .

What allows HTTP.SYS to determine what HTTP traffiic to route to an application, is a set of API's that are called by an application, letting HTTP.SYS know what URI's it is interested in processing. In fact this is how IIS 6.0 works, and in the near future many of the upcoming applications and technologies will be able to provide and host web services in the same way. Examples include SQL Server 2005 and Indigo.

So with HTTP.SYS being part of the Windows 2003 and XP platforms and with its concept of seperating the URI Endpoint from its application processing logic (i.e. applications/processes) what does it mean? :

• Well 1st and foremost, as mentioned above it allows you to have more than one process/application have URI endpoints on the platform, all leveraging a common component that handles cross cutting concerns such as request queuing etc..
• It also allows for one central component to handle the parsing/verification or logging of HTTP traffic. This gives you a common infrastructure on which to reuse and leverage multiple times, as well as a centralised logging store of HTTP traffic to a system.
• As applications must register their interest in a URI namespace with HTTP.SYS, it is only these URL requests that get processed as valid URI's
• since the queuing of valid URL requests is seperated from the application/process, it allows for requests to be queued while health monitoring tasks (such as recycling and/or re-starting) are performed.

In the next posting, I will cover some of the configuration tools and API's for HTTP.SYS.

 

ps

At our last MSDN event/session here in Ireland, Nick Grattan  delivered a great session on how SQL Server 2005 is able to host web services  using HTTP.SYS.  Nick has pointed out on his blog, that after the session, I mentioned to him that HTTP.SYS was available on Windows XP with SP2 installed ( oppps, sorry!!! totally forgot to blog about it !). As I was not 100% certain where SQL Server would work with the HTTP.SYS on XP SP2, I took the example he has on his blog  and with a few changes on my particularly abused installination of SQL Sever 2005 I got WSDL back from the example URL that Nick lists in his blog, i.e. http://localhost/sql/adventureworks?wsdl . Btw, it was BETA 2 I did this on. (As an aside, if you need more information on this, I would suggest having a look at this MSDN article,   Overview of Native XML Web Services for Microsoft SQL Server 2005  and also there is going to be a webcast on web services in SQL Server 2005 on the 8th of december ). 

IIS6 and Windows 2003 (Part 2)

The most significant changes within the new architecture for IIS 6.0 are:

• a new process model called WPIM ( Worker Process Isolation Mode)
• Application Pooling and Recycling
• HTTP.SYS - it is a HTTP listener that is a kernel mode driver and is a common endpoint for HTTP traffic on the platform
• WWW Service Administration and Monitoring (W3ADM). It is part of the WWW Service.
• the IIS Metabase is in XML format

Below you will see how a HTTP request is processed by HTTP.SYS and passed onto the IIS architecture components.

When an HTTP request arrives at the kernel-mode HTTP Listener/Endpoint, it checks the validity of the request. If the request is invalid, the appropriate HTTP error is immediately returned to the requester. If the request is valid, HTTP.sys checks to see if it can handle the request from its cache. If the response is in the cache, HTTP.sys sends the response immediately. Otherwise, HTTP.sys puts the request in a separate request queue for each worker process (application).If the necessary worker process is not listening on the request queue, then HTTP.sys signals the W3ADM to start and configure a worker process based on the configuration information stored in XML format in the metabase.

If a worker process or a group of worker processes (called a Web garden) is already started and connected to the request queue, the worker process pulls the request from the queue, processes it through any ISAPI filter or extension and Web application code, and returns the response to the HTTP.sys and the requester.

The W3ADM also monitors the health of a worker process and if, for example, the process does not respond or has exceeded a threshold (e.g., the number of hours running or number of requests handled), WAS coordinates with the HTTP Listener to hold requests in the queue while W3ADM stops the worker process and restarts it.

 

Windows 64-bit Hands-On Training & Windows 64-bit Compatibility Workshops

From Jan till July of next year, the Route64 Training Tour is visiting over 20 cities providing:

• Windows 64-bit Hands-On Training is a 3-day training designed to provide the most comprehensive contents of of what it takes to fully leverage Windows on 64-bit processors. At the completion of this training, we expect attendees to be fully comfortable with developing on Windows 64-bit and in some cases to have fully ported their application. This training includes two tracks, the Server and Client Tracks. Read more about the tracks.
• Windows 64-bit Compatibility Workshop is a one-day training for ISVs and Enterprise developers who are looking at testing their 32-bit application on a Windows 64-bit. The workshop includes several hands-on sessions on three architectures to give you the opportunity to experiment with Windows 64-bit.
• Windows 64-bit Device Driver Workshop is a one-day training for IHVs and Enterprise developers who wants to start porting their 32-bit device driver on Windows 64-bit. This workshop is designed to present the key differences between a 32-bit environment and a 64-bit one. It includes several hands-on sessions on porting Device Drivers. Because of the complexity of running a Device Driver workshop, this workshop runs only in some selected cities.
  

So if you are looking to learn more about:

• Windows 64-bit & Hardware Architectures
• Migrating C/C++ Applications to Windows 64-bit
• Optimizing SQL Server on 64-bit
• OpenGL in a 64-bit environment
• COM Components in Windows 64-bit
• .NET Managed Code in Windows 64-bit

as well have opportunities on three different configuration of Windows 64-bit:

• Windows Server 2003 SP1 64-bit Edition on Itanium 2 processor
• Windows Server 2003 SP1 64-bit Edition on Xeon processor
• Windows XP 64-bit Edition on Xeon processor

You can find more details and how to register at the Route64 site ( http://www.route64.net/ )

Christian Weyer is going to speak at the IrishDev User group next month

Just spotted a reference to Dublin on the ASP.NET feed, so I had to have a look!

Excellent!! Christian Weyer is coming to town and talking at a IrishDev user Group  event and is covering a really good topic, "Visual Studio .NET's Web services wizardry reconsidered: implementing your Web services the other (the right?) way" .

This is really worth attending, as I have always found Christain's sessions to be very good and informative, especially his talks about Web Services and WSDL design.

Christian is a very strong proponent of the WSDL first and or Schema first approach to the developement of Web Services. WSDL/Schema first based development is something I 1st came across a few years ago and it was more out of necessatity (as I wanted to reuse schema) than design that led me down this road, but since then I have never looked back.

If you are interested in getting some more details on WSDL/Schema first based development, try some of the following links, I think they are very useful:

• Place XML Message Design Ahead of Schema Planning to Improve Web Service Interoperability
• Improving Web Service Interoperability
• Contract First Web Services Interoperability between Microsoft .NET and IBM WebSphere
• Building Interoperable Web Services: WS-I Basic Profile 1.0
• Understanding WSDL
• Splitting up WSDL: The Importance of targetNamespace
• Inside WSDL with .NET Attribution

and of course, Christain's blog is a good place as well!

Updated Finalization & Hosting

My original posts on Finalization and Hosting had some hokey XXXXX markers in place of content, where that content hadn't already been disclosed in some form.  Now that the Visual Studio 2005 Community Preview is available, I've gone back to those two posts and replaced the XXXXX markers with real text.

Also, it's obviously been a while since my last post.  I started writing something this weekend, but the weather here has been spectacular and I was compelled to go outside and play.  I'll try to have something in the next couple of weeks.

 

Hosting

Hosting

 

My prior three blogs were supposed to be on Hosting.   Each time I got side tracked, first on Exceptions, then on Application Compatibility and finally on Finalization.   I refuse to be side tracked this time… much.

 

Also, I need to explain why it’s taken so long to get this blog out.   Part of the reason is vacation.   I spent Thanksgiving skiing in Whistler.   Then I took a quick side trip to Scottsdale for a friend’s surprise birthday party and to visit my parents.   Finally, I spent over three weeks on Maui getting a break from the Seattle winter.

 

Another reason for the delay is writer’s block.   This topic is so huge.   The internal specification for the Whidbey Hosting Interfaces is over 100 pages.   And that spec only covers the hosting interfaces themselves.   There are many other aspects of hosting, like how to configure different security policy in different AppDomains, or how to use COM or managed C++ to stitch together the unmanaged host with the managed applications.   There’s no way I can cover the entire landscape.

 

Anyway, here goes.

 

Mostly I was tourist overhead at the PDC.   But one of the places I tried to pay for my ticket was a panel on Hosting.   The other panelists included a couple of Program Managers from the CLR, another CLR architect, representatives from Avalon / Internet Explorer, SQL Server, Visual Studio / Office, and – to my great pleasure – a representative from IBM for DB2.

 

One thing that was very clear at that panel is that the CLR team has done a poor job of defining what hosting is and how it is done.   Depending on your definition, hosting could be:

 

• Mixing unmanaged and managed code in the same process.

 

• Running multiple applications, each in its own specially configured AppDomain.

 

• Using the unmanaged hosting interfaces described in mscoree.idl.

 

• Configuring how the CLR runs in the process, like disabling the concurrent GC through an application config file.

 

Even though the hosting interfaces described in mscoree.idl are a small part of what could be hosting, I’m going to concentrate on those interfaces.

 

In V1 and V1.1 of the CLR, we provided some APIs that allowed an unmanaged process host to exercise some limited control over the CLR.   This limited control included the ability to select the version of the CLR to load, the ability to create and configure AppDomains from unmanaged code, access to the ThreadPool, and a few other fundamental operations.

 

Also, we knew we eventually needed to support hosts which manage all the memory in the process and which use non-preemptive scheduling of tasks and perhaps even light-weight fibers rather than OS threads.   So we added some rudimentary (and alas inadequate) APIs for fibers and memory control.   This invariably happens when you add features that you think you will eventually need, rather than features that someone is actually using and giving feedback on.

 

If you look closely at the V1 and V1.1 hosting APIs, you really see what we needed to support ASP.NET and a few other scenarios, like ones involving EnterpriseServices, Internet Explorer or VSA, plus some rudimentary guesses at what we might need to coexist properly inside SQL Server.

 

Obviously in Whidbey we have refined those guesses about SQL Server into hard requirements.   And we tried very hard to generalize each extension that we added for SQL Server, so that it would be applicable to many other hosting scenarios.   In fact, it’s amazing that the SQL Server team still talks to us – whenever they ask for anything, we always say No and give them something that works a lot better for other hosts and not nearly so well for SQL Server.

 

In our next release (Whidbey), we’ve made a real effort to clean up the existing hosting support and to dramatically extend it for a number of new scenarios.   Therefore I’m not going to spend any more time discussing those original V1 & V1.1 hosting APIs, except to the extent that they are still relevant to the following Whidbey hosting discussion.

 

Also I’m going to skip over all the general introductory topics like “When to host” since they were the source of my writer’s block.   Instead, I’m going to leap into some of the more technically interesting topics.   Maybe after we’ve studied various details we can step back and see some general guidelines.

 

 

Threading and Synchronization

 

One of the most interesting challenges we struggled with during Whidbey was the need to cooperate with SQL Server’s task scheduling.   SQL Server can operate in either thread mode or fiber mode.   Most customers run in thread mode, but SQL Server can deliver its best numbers on machines with lots of CPUs when it’s running in fiber mode.   That gap between thread and fiber mode has been closing as the OS addresses issues with its own preemptive scheduler.

 

A few years ago, I ran some experiments to see how many threads I could create in a single process.   Not surprisingly, after almost 2000 threads I ran out of address space in the process.   That’s because the default stack size on NT is 1 MB and the default user address space is 2 GB.   (Starting with V1.1, the CLR can load into LARGEADDRESSAWARE processes and use up to 3 GB of address space).   If you shrink the default stack size, you can create more than 2000 threads before hitting the address space limit.   I see stack sizes of 256 KB in the SQL Server process on my machine, clearly to reduce this impact on process address space.

 

Of course, address space isn’t the only limit you can hit.   Even on the 4 CPU server box I was experimenting with, the real memory on the system was inadequate for the working set being used.   With enough threads, I exceeded real memory and experienced paging.   (Okay, it was actually thrashing).   But nowadays there are plenty of servers with several GB of real – and real cheap – memory, so this doesn’t have to be an issue.

 

In my experiments, I simulated server request processing using an artificial work load that combined blocking, allocation, CPU-intensive computation, and a reasonable memory reference set using a mixture of both shared and per-request allocations.   In the first experiments, all the threads were ready to run and all of them had equal priority.   The result of this was that all threads were scheduled in a round-robin fashion on those 4 CPUs.   Since the Windows OS schedules threads preemptively, each thread would execute until it either needed to block or it exceeded its quantum.   With hundreds or even thousands of threads, each context switch was extremely painful.   That’s because most of the memory used by that thread was so cold in the cache, having been fully displaced by the hundreds of threads that ran before it.

 

As we all know, modern CPUs are getting faster and faster at raw computation.   And they have more and more memory available to them.   But access to that memory is getting relatively slower each year.   By that, I mean that a single memory access costs the equivalent of an increasing number of instructions.   One of the ways the industry tries to mitigate that relative slowdown is through a cache hierarchy.   Modern X86 machines have L1, L2 and L3 levels of cache, ordered from fastest and smallest to slowest and largest.

 

(Other ways we try to mitigate the slowdown is by increasing the locality of our data structures and by pre-fetching.   If you are a developer, hopefully you already know about locality.   In the unmanaged world, locality is entirely your responsibility.   In the managed world, you get some locality benefits from our environment – notably the garbage collector, but also the auto-layout of the class loader.   Yet even in managed code, locality remains a major responsibility of each developer).

 

Unfortunately, context switching between such a high number of threads will largely invalidate all those caches.   So I changed my simulated server to be smarter about dispatching requests.   Instead of allowing 1000 requests to execute concurrently, I would block 996 of those requests and allow 4 of them to run.   This makes life pretty easy for the OS scheduler!   There are four CPUs and four runnable threads.   It’s pretty obvious which threads should run.

 

Not only will the OS keep those same four threads executing, it will likely keep them affinitized to the same CPUs.   When a thread moves from one CPU to another, the new CPU needs to fill all the levels of cache with data appropriate to the new thread.   However, if we can remain affinitized, we can enjoy all the benefits of a warm cache.   The OS scheduler attempts to run threads on the CPU that last ran them (soft affinity).   But in practice this soft affinity is too soft.   Threads tend to migrate between CPUs far more than we would like.   When the OS only has 4 runnable threads for its 4 CPUs, the amount of migration seemed to drop dramatically.

 

Incidentally, Windows also supports hard affinity.   If a thread is hard affinitized to a CPU, it either runs on that CPU or it doesn’t run.   The CLR can take advantage of this when the GC is executing in its server mode.   But you have to be careful not to abuse hard affinity. You certainly don’t want to end up in a situation where all the “ready to run” threads are affinitized to one CPU and all the other CPUs are necessarily stalled.

 

Also, it’s worth mentioning the impact of hyper-threading or NUMA on affinity.   On traditional SMP, our choices were pretty simple.   Either our thread ran on its ideal processor, where we are most likely to see all the benefits of a warm cache, or it ran on some other processor.   All those other processor choices can be treated as equally bad for performance.   But with hyper-threading or NUMA, some of those other CPUs might be better choices than others.   In the case of hyper-threading, some logical CPUs are combined into a single physical CPU and so they share access to the same cache memory at some level in the cache hierarchy.   For NUMA, the CPUs may be arranged in partitions (e.g. hemispheres on some machines), where each partition has faster access to some memory addresses and slower access to other addresses.   In all these cases, there’s some kind of gradient from the very best CPU(s) for a thread to execute on, down to the very worst CPU(s) for that particular thread.   The world just keeps getting more interesting.

 

Anyway, remember that my simulated server combined blocking with other operations.   In a real server, that blocking could be due to a web page making a remote call to get rows from a database, or perhaps it could be blocking due to a web service request.   If my server request dispatcher only allows 4 requests to be in flight at any time, such blocking will be a scalability killer.   I would stall a CPU until my blocked thread is signaled.   This would be intolerable.

 

Many servers address this issue by releasing some multiple of the ideal number of requests simultaneously.   If I have 4 CPUs dedicated to my server process, then 4 requests is the ideal number of concurrent requests.   If there’s “moderate” blocking during the processing of a typical request, I might find that 8 concurrent requests and 8 threads is a good tradeoff between more context switching and not stalling any CPUs.   If I pick too high of a multiple over the number of CPUs, then context switching and cache effects will hurt my performance.   If I pick too low a multiple, then blocking will stall a CPU and hurt my performance.

 

If you look at the heuristics inside the managed ThreadPool, you’ll find that we are constantly monitoring the CPU utilization.   If we notice that some CPU resources are being wasted, we may be starving the system by not doing enough work concurrently.   When this is detected, we are likely to release more threads from the ThreadPool in order to increase concurrency and make better use of the CPUs.   This is a decent heuristic, but it isn’t perfect.   For instance, CPU utilization is “backwards looking.”   You actually have to stall a CPU before we will notice that more work should be executed concurrently.   And by the time we’ve injected extra threads, the stalling situation may already have passed.

 

The OS has a better solution to this problem.   IO Completion Ports have a direct link to the blocking primitives in Win32.   When a thread is processing a work item from a completion port, if that thread blocks efficiently through the OS, then the blocking primitive will notify the completion port that it should release another thread.   (Busy waiting instead of efficient blocking can therefore have a substantial impact on the amount of concurrency in the process).   This feedback mechanism with IO Completion Ports is far more immediate and effective than the CLR’s heuristic based on CPU utilization.   But in fairness I should point out that if a managed thread performs managed blocking via any of the managed blocking primitives (contentious Monitor.Enter, WaitHandle.WaitOne/Any/All, Thread.Join, GC.WaitForPendingFinalizers, etc.), then we have a similar feedback mechanism.   We just don’t have hooks into the OS, so we cannot track all the blocking operations that occur in unmanaged code.

 

Of course, in my simulated server I didn’t have to worry about “details” like how to track all OS blocking primitives.   Instead, I postulated a closed world where all blocking had to go through APIs exposed by my server.   This gave me accurate and immediate information about threads either beginning to block or waking up from a blocking operation.   Given this information, I was able to tweak my request dispatcher so it avoided any stalling by injecting new requests as necessary.

 

Although it’s possible to completely prevent stalling in this manner, it’s not possible to prevent context switches.   Consider what happens on a 1 CPU machine.   We release exactly one request which executes on one thread.   When that thread is about to block, we release a second thread.   So far, it’s perfect.   But when the first thread resumes from its blocking operation, we now have two threads executing concurrently.   Our request dispatcher can “retire” one of those threads as soon as it’s finished its work.   But until then we have two threads executing on a single CPU and this will impact performance.

 

I suppose we could try to get ruthless in this situation, perhaps by suspending one of the threads or reducing its priority.   In practice, it’s never a good idea to suspend an executing thread.   If that thread holds any locks that are required by other concurrent execution, we may have triggered a deadlock.   Reducing the priority might help and I suspect I played around with that technique.   To be honest, I can’t remember that far back.

 

We’ll see that SQL Server can even solve this context switching problem.

 

 

Oh yeah, SQL Server

 

So what does any of this have to do with SQL Server?

 

Not surprisingly, the folks who built SQL Server know infinitely more than me about how to get the best performance out of a server.   And when the CLR is inside SQL Server, it must conform to their efficient design.   Let’s look at their thread mode, first.   Fiber mode is really just a refinement over this.

 

Incoming requests are carried on threads.   SQL Server handles a lot of simultaneous requests, so there are a lot of threads in the process.   With normal OS “free for all” scheduling, this would result in way too many context switches, as we have seen.   So instead those threads are affinitized to a host scheduler / CPU combination.   The scheduler tries to ensure that there is one unblocked thread available at any time.   All the other threads are ideally blocked.   This gives us the nirvana of 100% busy CPUs and minimal context switches.   To achieve this nirvana, all the blocking primitives need to cooperate with the schedulers.   Even if an event has been signaled and a thread is considered by the application to be “ready to run”, the scheduler may not choose to release it, if the scheduler’s corresponding CPU is already executing another thread.   In this manner, the blocking primitive and the scheduler are tightly integrated.

 

When I built my simulated server, I was able to achieve an ideal “closed world” where all the synchronization primitives were controlled by me.   SQL Server attempts the same thing.   If a thread needs to block waiting for a data page to be read, or for a page or row latch to be released, that blocking occurs through the SQL Server scheduler.   This guarantees that exactly one thread is available to run on each CPU, as we’ve seen.

 

Of course, execution of managed code also hits various blocking points.   Monitor.Enter (‘lock’ in C# and ‘SyncLock’ in VB.NET) is a typical case.   Other cases include waiting for a GC to complete, waiting for class construction or assembly loading or type loading to occur, waiting for a method to be JITted, or waiting for a remote call or web service to return.   For SQL Server to hit their performance goals and to avoid deadlocks, the CLR must route all of these blocking primitives to SQL Server (or any other similar host) through the new Whidbey hosting APIs.

 

 

Leaving the Closed World

 

But what about synchronization primitives that are used for coordination with unmanaged code and which have precise semantics that SQL Server cannot hope to duplicate?   For example, WaitHandle and its subtypes (like Mutex, AutoResetEvent and ManualResetEvent) are thin wrappers over the various OS waitable handles.   These primitives provide atomicity guarantees when you perform a WaitAll operation on them.   They have special behavior related to message pumping.   And they can be used to coordinate activity across multiple processes, in the case of named primitives.   It’s unrealistic to route operations on WaitHandle through the hosting APIs to some equivalent host-provided replacements.

 

This issue with WaitHandle is part of a more general problem.   What happens if I PInvoke from managed code to an OS service like CoInitialize or LoadLibrary or CryptEncrypt?   Do those OS services block?   Well, I know that LoadLibrary will have to take the OS loader lock somewhere.   I could imagine that CoInitialize might need to synchronize something, but I have no real idea.   One thing I am sure of: if any blocking happens, it isn’t going to go through SQL Server’s blocking primitives and coordinate with their host scheduler.   The idealized closed world that SQL Server needs has just been lost.

 

The solution here is to alert the host whenever a thread “leaves the runtime”.   In other words, if we are PInvoking out, or making a COM call, or the thread is otherwise transitioning out to some unknown unmanaged execution, we tell the host that this is happening.   If the host is tracking threads as closely as SQL Server does, it can use this event to disassociate the thread from the host scheduler and release a new thread.   This ensures that the CPU stays busy.   That’s because even if the disassociated thread blocks, we’ve released another thread.   This newly released thread is still inside our closed world, so it will notify before it blocks so we can guarantee that the CPU won’t stall.

 

Wait a second.   The CLR did a ton of work to re-route most of its blocking operations through the host.   But we could have saved almost that entire ton of engineering effort if we had just detached the thread from the host whenever SQL Server called into managed code.   That way, we could freely block and we wouldn’t disrupt the host’s scheduling decisions.

 

This is true, but it won’t perform as well as the alternative.   Whenever a thread disassociates from a host scheduler, another thread must be released.   This guarantees that the CPU is busy, but it has sacrificed our nirvana of only having a single runnable thread per CPU.   Now we’ve got two runnable threads for this CPU and the OS will be preemptively context-switching between them as they run out of quantum.

 

If a significant amount of the processing inside a host is performed through managed code, this would have a serious impact on performance.

 

Indeed, if a significant amount of the processing inside a host is performed in unmanaged code, called via PInvokes or COM calls or other mechanisms that “leave the runtime”, this too can have a serious impact on performance.   But, for practical purposes, we expect most execution to remain inside the host or inside managed code.   The amount of processing that happens in arbitrary unmanaged code should be low, especially over time as our managed platform grows to fill in some of the current gaps.

 

Of course, some PInvokes or COM calls might be to services that were exported from the host.   We certainly don’t want to disassociate from the host scheduler every time the in-process ADO provider performs a PInvoke back to SQL Server to get some data.   This would be unnecessary and expensive.   So there’s a way for the host to control which PInvoke targets perform a “leave runtime” / “return to runtime” pair and which ones are considered to remain within the closed world of our integrated host + runtime.

 

Even if we were willing to tolerate the substantial performance impact of considering all of the CLR to be outside the host’s closed world (i.e. we disassociated from the host’s scheduler whenever we ran managed code), this approach would be inadequate when running in fiber mode.   That’s because of the nasty effects which thread affinity can have on a fiber-based system.

 

 

Fiber Mode

 

As we’ve seen, SQL Server and other “extreme” hosts can ensure that at any time each CPU has only a single thread within the closed world that is ready to run.   But when SQL Server is in thread mode, there are still a large number of threads that aren’t ready to run.   It turns out that all those blocked threads impose a modest cost upon the OS preemptive scheduler.   And that cost becomes an increasing consideration as the number of CPUs increases.   For 1, 2, 4 and probably 8 CPU machines, fiber mode isn’t worth the headaches we’re about to discuss.   But by the time you get to a larger machine, you might achieve something like a 20% throughput boost by switching to fiber mode.   (I haven’t seen real numbers in a year or two, so please take that 20% as a vague ballpark).

 

Fiber mode simply eliminates all those extra threads from any consideration by the OS.   If you stay within the idealized nirvana (i.e. you don’t perform a “leave runtime” operation), there is only one thread for each host scheduler / CPU.   Of course, there are many stacks / register contexts and each such stack / register context corresponds to an in-flight request.   When a stack is ready to run, the single thread switches away from whatever stack it was running and switches to the new stack.   But from the perspective of the OS scheduler, it just keeps running the only thread it knows about.

 

So in both thread mode and fiber mode, SQL Server uses non-preemptive host scheduling of these tasks.   This scheduling happens in user mode, which is a distinct advantage over the OS preemptive scheduling which happens in kernel mode.   The only difference is whether the OS scheduler is aware of all the tasks on the host scheduler, or whether they all look like a single combined thread – albeit with different stacks and register contexts.

 

But the impact of this difference is significant.   First, it means that there is an M:N relationship between stacks (logical CLR threads) and OS threads.   This is M:N because multiple stacks will execute on a single thread, and because the specially nominated thread that carries those stacks can change over time.   This change in the nominated thread occurs as a consequence of those “leave runtime” calls.   Remember that when a thread leaves the runtime, we inform the host which disassociates the thread from the host scheduler.   A new thread is then created or obtained from a short list of already-created threads.   This new thread then picks up the next stack that is ready to run.   The effect is that this stack has migrated from the original disassociated thread to the newly nominated thread.

 

This M:N relationship between stacks and OS threads causes problems everywhere that thread affinity would normally occur.   I’ve already mentioned CPU affinity when discussing how threads are associated with CPUs.   But now I’m talking about a different kind of affinity.   Thread affinity is the association between various programmatic operations and the thread that these operations must run on.   For example, if you take an OS critical section by calling EnterCriticalSection, the resulting ownership is tied to your thread.   Sometimes developers say that the OS critical section is scoped to your thread.   You must call LeaveCriticalSection from that same thread.

 

None of this is going to work properly if your logical thread is asynchronously and apparently randomly migrating between different physical threads.   You’ll successfully take the critical section on one logical thread.   If you attempt to recursively acquire this critical section, you will deadlock if a migration has intervened.   That’s because it will look like a different physical thread is actually the owner.

 

Imagine writing some hypothetical code inside the CLR:

 

EnterCriticalSection(pCS);

 

If (pGlobalBlock == NULL)

   pGlobalBlock = Alloc(count);

 

LeaveCriticalSection(pCS);

 

Obviously any real CLR code would be full of error handling, including a ‘finally’ clause to release the lock.   And we don’t use OS critical sections directly since we typically reflect them to an interested host as we’ve discussed.   And we instrument a lot of this stuff, including spinning during lock acquisition.   And we wrap the locks with lots of logic to avoid deadlocks, including GC-induced deadlocks.   But let’s ignore all of the goop that would be necessary for real CLR code.

 

It turns out that the above code has a thread affinity problem.   Even though SQL Server’s fiber scheduling is non-preemptive, scheduling decisions can still occur whenever we call into the host.   For reasons that I’ll explain later, all memory allocations in the CLR have the potential to call into the host and result in scheduling.   Obviously most allocations will be satisfied locally in the CLR without escalation to the host.   And most escalations to the host still won’t cause a scheduling decision to occur.   But from a correctness perspective, all allocations have the potential to cause scheduling.

 

Other places where thread affinity can bite us include:

 

• The OS Mutex and the managed System.Threading.Mutex wrapper.

 

• LoadLibrary and DllMain interactions.   As I’ve explained in my blog entry on Shutdown, DllMain notifications occur on a thread which holds the OS loader lock.

 

• TLS (thread local storage).   It’s worth mentioning that, starting with Windows Server 2003, there are new FLS (fiber local storage) APIs.   These APIs allow you to associate state with the logical rather than the physical thread.   When a fiber is associated with a thread for execution (SwitchToFiber), the FLS is automatically moved from the fiber onto the thread.   For managed TLS, we now move this automatically.   But we cannot do this unconditionally for all the unmanaged TLS.

 

• Thread culture or locale, the impersonation context or user identity, the COM+ transaction context, etc.   In some sense, these are just special cases of thread local storage.   However, for historical reasons it isn’t possible to solve these problems by moving them to FLS.

 

• Taking control of a thread for GC, Abort, etc. via the OS SuspendThread() service.

 

• Any use of ThreadId or Thread Handle.   This includes all debugging.

 

• “Hand-rolled” locks that we cannot discover or reason about, and which you have inadvertently based on the physical OS thread rather than the logical thread or fiber.

 

• Various PInvokes or COM calls that might end up in unmanaged code with affinity requirements.   For instance, MSHTML can only be called on STA threads which are necessarily affinitized.   Of course, there is no list of all the APIs that have odd threading behavior.   It’s a minefield out there.

 

Solving affinity issues is relatively simple.   The hard part is identifying all the places.   Note that the last two bullet items are actually the application’s responsibility to identify.   Some application code might appear to execute correctly when logical threads and OS threads are 1:1.   But when a host creates an M:N relationship, any latent application bugs will be exposed.

 

In many cases, the easiest solution to a thread affinity issue is to disassociate the thread from the host’s scheduler until the affinity is no longer required.   The hosting APIs provide for this, and we’ve taken care of it for you in many places – like System.Threading.Mutex.

 

Before we finish our discussion of locking, there’s one more aspect worth mentioning.   In an earlier blog, I have mentioned the limited deadlock detection and deadlock breaking which the CLR performs when executing class constructors or JITting.

 

Except for this limited case, the CLR doesn’t concern itself with application-level deadlocks.   If you write some managed code that takes a set of locks in random order, resulting in a potential deadlock, we consider that to be your application bug.   But some hosts may be more helpful.   Indeed, SQL Server has traditionally detected deadlocks in all data accesses.   When a deadlock occurs, SQL Server selects a victim and aborts the corresponding transaction.   This allows the other requests implicated in the deadlock to proceed.

 

With the new Whidbey hosting APIs, it’s possible for the host to walk all contentious managed locks and obtain a graph of the participants.   This support extends to locking through our Monitor and our ReaderWriterLock.   Clearly, an application could perform locking through other means.   For example, an AutoResetEvent can be used to simulate mutual exclusion.   But it’s not possible for such locks to be included in the deadlock algorithms, since there isn’t a strong notion of lock ownership that we can use.

 

Once the host has selected a deadlock victim, it must cause that victim to abort its forward progress somehow.   If the victim is executing managed code, some obvious ways to do this include failing the lock attempt (since the thread is necessarily blocking), aborting the thread, or even unloading the AppDomain.   We’ll return to the implications of this choice in the section on Reliability below.

 

Finally, it’s interesting to consider how one might get even better performance than what SQL Server has achieved.   We’ve seen how fiber mode eliminates all the extra threads, by multiplexing a number of stacks / register contexts onto a single thread.   What happens if we then eliminate all those fibers?   For a dedicated server, we can achieve even better performance by forcing all application code to maintain its state outside of a thread’s stack.   This allows us to use a single thread per CPU which executes user requests by processing them on its single dedicated stack.   All synchronous blocking is eliminated by relying on asynchronous operations.   The thread never yields while holding its stack pinned.   The amount of memory required to hold an in-flight request will be far less than a 256 KB stack reservation.   And the cost of processing an asynchronous completion through polling can presumably be less than the cost of a fiber context switch.

 

If all you care about is performance, this is an excellent way to build a server.   But if you need to accommodate 3rd party applications inside the server, this approach is questionable.   Most developers have a difficult time breaking their logic into segments which can be separately scheduled with no stack dependencies.   It’s a tedious programming model.   Also, the underlying Windows platform still contains a lot of blocking operations that don’t have asynchronous variants available.   WMI is one example.

 

 

Memory Management

 

Servers must not page.

 

Like all rules, this one isn’t strictly true.   It is actually okay to page briefly now and then, when the work load transitions from one steady state to another.   But if you have a server that is routinely paging, then you have driven that server beyond its capacity.   You need to reduce the load on the server or increase the server’s memory capacity.

 

At the same time, it’s important to make effective use of the memory capacity of a server.   Ideally, a database would store the entire database contents in memory.   This would allow it to avoid touching the disk, except to write the durable log that protects it from data loss and inconsistency in the face of catastrophic failure.   Of course, the 2 or 3 GB limit of Win32 is far too restrictive for most interesting databases.   (SQL Server can use AWE to escape this limit, at some cost).   And even the address limits of Win64 are likely to be exceeded by databases presently.   That’s because Win64 does not give you a full 64 bits of addressing and databases are already heading into the petabytes.

 

So a database needs to consider all the competing demands for memory and make wise decisions about which ones to satisfy.   Historically, those demands have included the buffer cache which contains data pages, compiled query plans, and all those thread stacks.   When the CLR is loaded into the process, significant additional memory is required for the GC heap, application code, and the CLR itself.   I’m not sure what techniques SQL Server uses to trade off the competing demands for memory.   Some servers carve memory up based on fixed ratios for the different broad uses, and then rely on LRU within each memory chunk.   Other servers assign a cost to each memory type, which indicates how expensive it would be to regenerate that memory.   For example, in the case of a data page, that cost is an IO.

 

Some servers use elaborate throttling of inbound requests, to keep the memory load reasonable.   This is relatively easy to do when all requests are comparable in terms of their memory and CPU requirements.   But if some queries access a single database page and other queries touch millions of rows, it would be hard to factor this into a throttling decision that is so far upstream from the query processor.   Instead, SQL Server tends to accept a large number of incoming requests and process them “concurrently.”   We’ve already seen in great detail why this concurrent execution doesn’t actually result in preemptive context switching between all the corresponding tasks.   But it is still the case that each request will hold onto some reference set of memory, even when the host’s non-preemptive scheduler has that request blocked.

 

If enough requests are blocked while holding onto significant unshared memory, then the server process may find itself over-committed on memory.   At this point, it could page – which hurts performance.   Or it could kill some of the requests and free up the resources they are holding onto.   This is an unfortunate situation, because we’ve presumably already devoted resources like the CPU to get the request to its current state of partial completion.   If we throw away the request, all that work was wasted.   And the client is likely to resubmit the request, so we will have to repeat all that work soon.

 

Nevertheless, if the server is over-committed and it’s not practical to recover more memory by e.g. shrinking the number of pages devoted to the buffer cache, then killing in-flight requests is a sound strategy.   This is particularly reasonable in database scenarios, since the transactional nature of database operations means that we can kill requests at any time and with impunity.

 

Unfortunately, the world of arbitrary managed execution has no transactional foundation we can rely on.   We’ll pick up this issue again below, in the section on Reliability.

 

It should be obvious that, if SQL Server or any other host is going to make wise decisions about memory consumption on a “whole process” basis, that host needs to know exactly how much memory is being used and for what purposes.   For example, before the host unloads an AppDomain as a way of backing out of an over-committed situation, the host needs some idea of how many megabytes this unload operation is likely to deliver.

 

In the reverse direction, the host needs to be able to masquerade as the operating system.   For instance, the CLR’s GC monitors system memory load and uses this information in its heuristics for deciding when to schedule a collection.   The host needs a way to influence these collection decisions.

 

 

SQL Server and ASP.NET

 

Clearly a lot of work went into threading, synchronization and memory management in SQL Server.   One obvious question to ask is how ASP.NET compares.   They are both server products from Microsoft and they both execute managed code.   Why didn’t we need to add all this support to the hosting interfaces in V1 of the CLR, so we could support ASP.NET?

 

I think it’s fair to say that ASP.NET took a much simpler approach to the problem of building a scalable server.   To achieve efficient threading, they rely on the managed ThreadPool’s heuristics to keep the CPUs busy without driving up too many context switches.   And since the bulk of memory allocations are due to the application, rather than the ASP.NET infrastructure (in other words, they aren’t managing large shared buffer pools for data pages), it’s not really possible for ASP.NET to act as a broker for all the different memory consumers.   Instead, they just monitor the total memory load, and recycle the worker process if a threshold is exceeded.

 

(Incidentally, V1 of ASP.NET and the CLR had an unfortunate bug with the selection of this threshold.   The default point at which ASP.NET would recycle the process was actually a lower memory load than the point at which the CLR’s GC would switch to a more aggressive schedule of collections.   So we were actually killing the worker process before the CLR had a chance to deliver more memory back to the application.   Presumably in Whidbey this selection of default thresholds is now coordinated between the two systems.)

 

How can ASP.NET get away with this simpler approach?

 

It really comes down to their fundamental goals.   ASP.NET can scale out, rather than having to scale up.   If you have more incoming web traffic, you can generally throw more web servers at the problem and load balance between them.   Whereas SQL Server can only scale out if the data supports this.   In some cases, it does.   There may be a natural partitioning of the data, like access to the HotMail mailbox for a particular incoming user.   But in too many other cases, the data cannot be sufficiently partitioned and the server must be scaled up.   On X86 Windows, the practical limit is a 32-way CPU with a hard limit of 3 GB of user address space.   If you want to keep increasing your work load on a single box, you need to use every imaginative trick – like fibers or AWE – to eke out all possible performance.

 

There’s also an availability issue.   ASP.NET can recycle worker processes quite quickly.   And if they have scaled out, recycling a worker process on one of the computers in the set will have no visible effect on the availability of the set of servers.   But SQL Server may be limited to a single precious process.   If that process must be recycled, the server is unavailable.   And recycling a database is more expensive than recycling a stateless ASP.NET worker process, because transaction logs must be replayed to move the database forwards or backwards to a consistent state.

 

The short answer is, ASP.NET didn’t have to do all the high tech fancy performance work.   Whereas SQL Server was forced down this path by the nature of the product they must build.

 

 

Reliability

 

Well, if you haven’t read my earlier blogs on asynchronous exceptions, or if – like me – you read the Reliability blog back in June and don’t remember what it said – you might want to review it quickly at http://blogs.msdn.com/cbrumme/archive/2003/06/23/51482.aspx .

 

The good news is that we’ve revisited the rules for ThreadAbortException in Whidbey, so that there is now a way to abort a thread without disturbing any backout code that it is currently running.   But it’s still the case that asynchronous exceptions can intrude at fairly arbitrary spots in the execution.

 

Anyway, the availability goals of SQL Server place some rather difficult requirements on the CLR.   Sure, we were pretty solid in V1 and V1.1.   We ran a ton of stress and – if you avoided stack overflow, running out of memory, and any asynchronous exceptions like Thread.Abort – we could run applications indefinitely.   We really were very clean.

 

One problem with this is that “indefinitely” isn’t long enough for SQL Server.   They have a noble goal of chasing 5 9’s and you can’t get there with loose statements like “indefinitely”.   Another problem is that we can no longer exclude OutOfMemoryException and ThreadAbortException from our reliability profile.   We’ve already seen that SQL Server tries to use 100% of memory, without quite triggering paging.   The effect is that SQL Server is always on the brink of being out of memory, so allocation requests are frequently being denied.   Along the same lines, if the server is loaded it will allow itself to become over-committed on all resources.   One strategy for backing out of an over-commitment is to abort a thread (i.e. kill a transaction) or possibly unload one or more AppDomains.

 

Despite this stressful abuse, at no time can the process terminate.

 

The first step to achieve this was to harden the CLR so that it was resilient to any resource failures.   Fortunately we have some extremely strong testers.   One tester built a system to inject a resource failure in every allocator, for every unique logical call stack.   This tests every distinct backout path in the product.   This technique can be used for unmanaged and managed (FX) code.   That same tester is also chasing any unmanaged leaks by applying the principles of a tracing garbage collector to our unmanaged CLR data structures.   This technique has already exposed a small memory leak that we shipped in V1 of the CLR – for the “Hello World” application!

 

With testers like that, you better have a strong development team too.   At this point, I think we’ve annotated the vast majority of our unmanaged CLR methods with reliability contracts.   These are a bit like Eiffel pre- and post-conditions and they provide machine-verifiable statements about each method’s behavior with respect to GC, exceptions, and other fundamental operations.   These contracts can be used during test coverage (and, in some cases, during static scans of the binary images) to test for conformance.

 

The bottom line is that the next release of CLR should be substantially more robust in the face of resource errors.   Leaving aside stack overflows and focusing entirely on the unmanaged runtime, we are shooting for perfection.   Even for stack overflow, we expect to get very, very close.   And we have the mechanisms in place that allow us to be rigorous in chasing after these goals.

 

But what about all of the managed code?

 

Will FX be as robust as the unmanaged CLR?   And how can we possibly hold 3rd party authors of stored procedures or user defined functions to that same high bar?   We want to enable a broad class of developers to write this sort of code, and we cannot expect them to perform many hundreds of hours of stress testing and fault injection on each new stored procedure.   If we’re chasing 5 9’s by requiring every external developer to write perfect code, we should just give up now.

 

Instead, SQL Server relies on something other than perfect code.   Consider how SQL Server worked before it started hosting the CLR:

 

The vast majority of execution inside SQL Server was via Transact SQL or TSQL.   Any application written in TSQL is inherently scalable, fiber-aware, and robust in the face of resource errors.   Any computation in TSQL can be terminated with a clean transaction abort.

 

Unfortunately, TSQL isn’t expressive enough to satisfy all application needs.   So the remaining applications were written in extended stored procedures or xprocs.   These are typically unmanaged C++.   Their authors must be extremely sophisticated, because they are responsible for integrating their execution with the unusual threading environment and resource rules that exist inside SQL Server.   Throw in the rules for data access and security (which I won’t be discussing in this blog) and it takes superhuman knowledge and skill to develop a bug-free xproc.

 

In other words, you had a choice of well-behaved execution and limited expression (TSQL), or the choice of arbitrary execution coupled with a very low likelihood that you would get it right (xprocs).

 

One of the shared goals of the SQL Server and CLR teams in Whidbey was to eliminate the need for xprocs.   We wanted to provide a spectrum of choices to managed applications.   In Whidbey, that spectrum consists of three buckets for managed code:

 

• Safe

Code in this bucket is the most constrained.   In fact, the host constrains it beyond what the CLR would normally allow to code that’s only granted SecurityPermissionFlag.Execution.   So this code must be verifiably typesafe and has a reduced grant set.   But it is further constrained from defining mutable static fields, from creating or controlling threads, from using the threadpool, etc.   The goal here is to guide the code to best practices for scalability and robustness within the SQL Server or similar hosted environments.   In the case of SQL Server, this means that all state should be stored in the database and that concurrency is controlled through transactions against the data.   However, it’s important to realize that these additional constraints are not part of the Security system and they may well be subvertible.   The constraints are simply speedbumps (not roadblocks) which guide the application code away from potentially non-scalable coding techniques and which encourage best practices.

 

• External Access

Code in this bucket should be sufficient for replacing most xprocs.   Such code must also be verifiably typesafe, but it is granted some additional permissions.   The exact set of permissions is presumably subject to change until Yukon ships, but it’s likely to allow access to the registry, the file system, and the network.

 

• Unsafe

This is the final managed escape hatch for writing code inside SQL Server.   This code does not have to be verifiable.   It has FullTrust (with the possible exception of UIPermission, which makes no sense within the database).   This means that it can do anything the most arbitrary xproc can do.   However, it is much more likely to work properly, compared to that xproc.   First, it sits on top of a framework that has been designed to work inside the database.   Second, the code has all the usual benefits of managed code, like a memory manager that’s based on accurate reachability rather than on programmer correctness.   Finally, it is executing on a runtime that understands the host’s special rules for resource management, synchronization, threading, security, etc.

 

For code in the Safe bucket, you may be wondering how a host could constrain code beyond SecurityPermissionFlag.Execution.   There are two techniques available for this:

 

1)       Any assembly in the ‘Safe’ subset could be scanned by a host-provided pre-verifier, to check for any questionable programming constructs like the definition of mutable static fields, or the use of reflection.   This raises the obvious question of how the host can interject itself into the binding process and guarantee that only pre-verified assemblies are loaded.   The new Whidbey hosting APIs contain a Fusion loader hook mechanism, which allows the host to abstract the notion of an assembly store, without disturbing all our normal loader policy.   You can think of this as the natural evolution of the AppDomain.AssemblyResolve event.   SQL Server can use this mechanism to place all application assemblies into the database and then deliver them to the loader on demand.   In addition to enabling pre-verification, the loader hooks can also be used to ensure that applications inside the database are not inadvertently broken or influenced by changes outside the database (e.g. changes to the GAC).   In fact, you could even copy a database from one machine to another and theoretically this could automatically transfer all the assemblies required by that database.

 

2)       The Whidbey hosting APIs provide controls over a new Host Protection Attribute (HPA) feature.   Throughout our frameworks, we’ve decorated various unprotected APIs with an appropriate HPA.   These HPAs indicate that the decorated API performs a sensitive operation like Synchronization or Thread Control.   For instance, use of the ThreadPool isn’t considered a secure operation.   (At some level, it is a risk for Denial of Service attacks, but DOS remains an open design topic for our managed platform).   If code is running outside of a host that enables these HPAs, they have no effect.   Partially trusted code, including code that only has Execution permission, can still call all these APIs.   But if a host does enable these attributes, then code with insufficient trust can no longer call these APIs directly.   Indirect calls are still permitted, and in this sense the HPA mechanism is similar to the mechanism for LinkDemands.

 

Although HPAs use a mechanism that is similar to LinkDemands, it’s very important to distinguish the HPA feature – which is all about programming model guidance – from any Security feature.   A great way to illustrate this distinction is Monitor.Enter.

 

Ignoring HPAs, any code can call Monitor.Enter and use this API to synchronize with other threads.   Naturally, SQL Server would prefer that most developers targeting their environment (including all the naïve ones) should rely on database locks under transaction control for this sort of thing.   Therefore they activate the HPA on this class:

 

    [ HostProtection(Synchronization=true, ExternalThreading=true) ]

    public sealed class Monitor

    {

        ...

        [MethodImplAttribute(MethodImplOptions.InternalCall)]

        public static extern void Enter (Object obj);

 

However, devious code in the ‘Safe’ bucket could use a HashTable as an alternate technique for locking.   If you create a synchronized HashTable and then perform inserts or lookups, your Object.Equals and GetHashCode methods will be called within the lock that synchronizes the HashTable.   The BCL developers were smart enough to realize this, and they added another HPA:

 

    public class Hashtable : IDictionary, ISerializable,

                               IDeserializationCallback, ICloneable

    {

        ...

        [HostProtection(Synchronization=true)]

        public static Hashtable Synchronized (Hashtable table) {

            if (table==null)

                throw new ArgumentNullException("table");

            return new SyncHashtable(table);

        }

 

Are there other places inside the frameworks where it’s possible to trick an API into providing synchronization for its caller?   Undoubtedly there are, but we aren’t going to perform exhaustive audits of our entire codebase to discover them all.   As we find additional APIs, we will decorate them with HPAs, but we make no guarantees here.

 

This would be an intolerable situation for a Security feature, but it’s perfectly acceptable when we’re just trying to increase the scalability and reliability of naively written database applications.

 

 

Escalation Policy

 

I chose the HPA on System.Threading.Monitor for a reason, in the above example.   If you’ve read my earlier blogs on Thread.Abort, you know that it’s dangerous to asynchronously abort another thread.   That thread could be executing a class constructor, in which case that class is now unavailable throughout the AppDomain.   That thread could be in the middle of an update to some shared application state, which would leave the application in an inconsistent state.

 

In V1 & V1.1, it was not really possible to write code that is robust in the face of asynchronous exceptions like Abort.   In Whidbey, we’re now introducing some constructs (Constrained Execution Regions and Critical Finalization) which make it possible to do this.   I’m not going to discuss those constructs in this blog.   But suffice it to say that, although it makes it possible to write entirely robust code, it doesn’t make it easy.   Without a higher level programmatic construct, like transactions, it’s very difficult to write entirely robust code.   You must acquire all the resources required for forward progress, tolerating exceptions during this acquisition phase.   Then you enter a forward progress phase, which either cannot fail or which unconditionally triggers some compensating backout code upon failure.   If compensation is triggered, it must guarantee that the system is returned to a consistent state before it completes.

 

If you’ve successfully written that sort of code, you know that it’s an onerous discipline.   There’s no way that we can expect the greater population of developers to write large bodies of bug-free code based on this plan.

 

That’s why, in V1 & V1.1, we recommend either using Abort on the current thread (in which case it is not asynchronous) or we recommend using it in conjunction with an AppDomain.Unload (in which case any inconsistent application state is likely to be discarded).

 

In Whidbey, it is possible to avoid inducing asynchronous Aborts onto threads that are performing backout (i.e. filter, finally, catch or fault blocks) or that hold locks.   Our definition of a lock is pretty broad.   It includes execution of a class constructor, since all .cctor execution is synchronized according to elaborate rules by the CLR.   It also includes Monitor.Enter, Mutex, ReaderWriterLock, etc.   Finally, it includes any “hand-rolled” locks that you build, so long as you properly identify them to us.

 

Our rationale here is that any thread holding a lock may be updating shared state.   If a thread isn’t holding a lock, then any update it performs against shared state must be atomic or at least it never leaves that shared state in an inconsistent state.   This is strictly a heuristic, but it’s a pretty good one.

 

If we believe this heuristic, it means that we can use Abort without consequently unloading an AppDomain, if that thread doesn’t hold any locks and isn’t performing any backout.   And it just so happens that the bulk of all managed code executing inside SQL Server is in the ‘Safe’ subset – which coincidentally is highly discouraged via HPAs from taking or holding locks.

 

In other words, code in the ‘Safe’ subset can almost always take an asynchronous exception without affecting any of the execution on other threads in the same AppDomain.   This is the case, even though that code was written by developers who don’t understand the deep issues involved with asynchronous exceptions.   It further means that if we should catch such a thread at a point where it isn’t safe to inject an asynchronous exception without also unloading the AppDomain, we can identify this window.   Once this window is identified, we can either hold off from injecting the exception until this unsafe window has closed, or we can unload the entire AppDomain to eliminate the application inconsistency.   The host can decide whether to hold off on the injection or alternatively to proceed with an AppDomain unload, based on criteria like how resource-constrained the host is.

 

The hosting APIs for making these decisions imperatively would be rather complicated.   So the Whidbey hosting APIs provide a declarative mechanism called an escalation policy.   This allows the host to express transitions and timeouts that take effect during error conditions.   For instance, SQL Server might state that any attempt to Abort a thread should delay if the victim thread holds a lock.   But if that delay exceeds 30 seconds, the Abort attempt should be escalated to an AppDomain.Unload.   Of course, the feature is more general than SQL Server’s needs.   Indeed, the V1 ASP.NET process recycling feature should now be expressible as a particular Whidbey escalation policy.

           

 

Winding down

 

As usual, I didn’t get around to many of the interesting topics.   For instance, those guidelines on when and how to host are noticeably absent.   And I didn’t explain how to do any simple stuff, like picking concurrent vs. non-concurrent vs. server GC.   The above text is completely free of any specific details of what our hosting APIs look like (partly because they are subject to change until Whidbey ships).   And I didn’t touch on any hosting topics outside of the hosting APIs, like all of the AppDomain considerations.   As you can imagine, there’s also plenty I could have said about Security.   For instance, the hosting APIs allow the host to participate in role-based security and impersonation of Windows identities…   Oh well.

 

Fortunately, one of the PMs involved in the Whidbey hosting effort is apparently writing a book on the general topic of hosting.   Presumably all these missing topics will be covered there.   And hopefully he won’t run into the same issues with writer’s block that I experienced on this topic.

 

(Indeed, the event that ultimately resolved my writer’s block was that my wife got the flu.   When she’s not around, my weekends are boring enough for me to think about work.   The reason I’m posting two blogs this weekend is that Kathryn has gone to Maui for the week and has left me behind.)

 

Finally, the above blog talks about SQL Server a lot.

 

Hopefully it’s obvious that the CLR wants to be a great execution environment for a broad set of servers.   In V1, we focused on ASP.NET.   Based on that effort, we automatically worked well in many other servers with no additional work.   For example, EnterpriseServices dropped us into their server processes simply by selecting the server mode of our GC.   Nothing else was required to get us running efficiently.   (Well, we did a ton of other work in the CLR to support EnterpriseServices.   But that work was related to the COM+ programming model and infrastructure, rather than their server architecture.   We had to do that work whether we ran in their server process or were instead loading EnterpriseServices into the ASP.NET worker process or some other server).

 

In Whidbey we focused on extending the CLR to meet SQL Server’s needs.   But at every opportunity we generalized SQL Server’s requirements and tried to build something that would be more broadly useful.   Just as our ASP.NET work enabled a large number of base server hosting scenarios, we hope that our SQL Server work will enable a large number of advanced server hosting scenarios.

 

If you have a “commercially significant” hosting problem, whether on the server or the client, and you’re struggling with how to incorporate managed code, I would be interested in hearing from you directly.   Feel free to drop me an email with the broad outline of what you are trying to achieve, and I’ll try to get you supported.   That support might be something as lame as some suggestions from me on how I would tackle the problem.   Or at the other extreme, I could imagine more formal support and conceivably some limited feature work.   That other extreme really depends on how commercially significant your product is and on how well our business interests align.   Obviously decisions like that are far outside my control, but I can at least hook you up with the right people if this seems like a sensible approach.

 

Okay, one more ‘Finally’.   From time to time readers of my blog send me emails asking if there are jobs available on the CLR team.   At this moment, we do.   Drop me an email if you are interested.   It’s an extremely challenging team to work on, but the problems are truly fascinating.

 

Finalization

Earlier this week, I wrote an internal email explaining how Finalization works in V1 / V1.1, and how it has been changed for Whidbey.   There’s some information here that folks outside of Microsoft might be interested in.

 

 

Costs

 

Finalization is expensive.   It has the following costs:

 

1)    Creating a finalizable object is slower, because each such object must be placed on a RegisteredForFinalization queue.   In some sense, this is a bit like having an extra pointer-sized field in your object that the system initializes for you.   However, our current implementation uses a slower allocator for every finalizable object, and this impact can be measured if you allocate small objects at a high rate.

 

2)    Each GC must do a weak pointer scan of this queue, to find out whether any finalizable objects are now collectible.   All such objects are then moved to a ReadyToFinalize queue.   The cost here is small.

 

3)    All objects in the ReadyToFinalize queue, and all objects reachable from them, are then marked.   This means that an entire graph of objects which would normally die in one generation can be promoted to the next generation, based on a single finalizable root to this graph.   Note that the size of this graph is potentially huge.

 

4)    The older generation will be collected at some fraction of the frequency of the younger generation.   (The actual ratio depends on your application, of course).   So promotion of the graph may have increased the time to live of this graph by some large multiple.   For large graphs, the combined impact of this item and #3 above will dominate the total cost of finalization.

 

5)    We currently use a single high priority Finalizer thread to walk the ReadyToFinalize queue.   This thread dequeues each object, executes its Finalize method, and proceeds to the next object.   This is the one cost of finalization which customers actually expect.

 

6)    Since we dedicate a thread to calling finalizers, we inflict an expense on every managed process.   This can be significant in Terminal Server scenarios where the high number of processes multiplies the number of finalizer threads.

 

7)    Since we only use a single thread for finalization, we are inherently non-scalable if a process is allocating finalizable objects at a high rate.   One CPU performing finalization might not keep up with 31 other CPUs allocating those finalizable objects.

 

8)    The single finalizer thread is a scarce resource.   There are various circumstances where it can become blocked indefinitely.   At that point, the process will leak resources at some rate and eventually die.   See http://blogs.msdn.com/cbrumme/archive/2004/02/02/66219.aspx for extensive details.

 

9)    Finalization has a conceptual cost to managed developers.   In particular, it is difficult to write correct Finalize methods as I shall explain.

 

Eventually we would like to address #5 thru #8 above by scheduling finalization activity over our ThreadPool threads.   We have also toyed with the idea of reducing the impact of #3 and #4 above, by pruning the graph based on reachability from your Finalize method and any code that it might call.   Due to indirections that we cannot statically explore, like interface and virtual calls, it’s not clear whether this approach will be fruitful.   Also, this approach would cause an observable change in behavior if resurrection occurs.   Regardless, you should not expect to see any of these possible changes in our next release.

 

 

Reachability

 

One of the guidelines for finalization is that a Finalize method shouldn’t touch other objects.   People sometimes incorrectly assume that this is because those other objects have already been collected.   Yet, as I have explained, the entire reachable graph from a finalizable object is promoted.

 

The real reason for the guideline is to avoid touching objects that may have already been finalized.   That’s because finalization is unordered.

 

So, like most guidelines, this one is made to be broken under certain circumstances.   For instance, if your object “contains” a private object that is not itself finalizable, clearly you can refer to it from your own Finalize method without risk.

 

In fact, a sophisticated developer might even create a cycle between two finalizable objects and coordinate their finalization behavior.   Consider a buffer and a file.   The Finalize method of the buffer will flush any pending writes.   The Finalize method of the file will close the handle.   Clearly it’s important for the buffer flush to precede the handle close.   One legitimate but brittle solution is to create a cycle of references between the buffer and the file.   Whichever Finalize method is called first will execute a protocol between the two objects to ensure that both side effects happen in order.   The subsequent Finalize call on the second object should do nothing.

 

I should point out that Whidbey solves the buffer and file problem differently, relying on the semantics of critical finalization.   And I should also point out that any protocol for sequencing the finalization of two objects should anticipate that one day we may execute these two Finalize methods concurrently on two different threads.   In other words, the protocol must be thread-safe.

 

 

Ordering

 

This raises the question of why finalization is unordered.

 

In many cases, no natural order is even possible.   Finalizable objects often occur in cycles.   You could imagine decorating some references between objects, to indicate the direction in which finalization should proceed.   This would add a sorting cost to finalization.   It would also cause complexity when these decorated references cross generation boundaries.   And in many cases the decorations would not fully eliminate cycles.   This is particularly true in component scenarios, where no single developer has sufficient global knowledge to create an ordering:

 

Your component would achieve its guarantees when tested by you, prior to deployment.   Then in some customer application, additional decorated references would create cycles and your guarantees would be lost.   This is a recipe for support calls and appcompat issues.

 

Unordered finalization is substantially faster.   Not only do we avoid sorting (which might involve metadata access and marking through intermediate objects), but we can also efficiently manage the RegisteredForFinalization and ReadyToFinalize queues without ever having to memcpy.   Finally, there’s value in forcing developers to write Finalize methods with minimal dependencies on any other objects.   This is key to our eventual goal of making Finalization scalable by distributing it over multiple threads.

 

Based on the above and other considerations like engineering complexity, we made a conscious decision that finalization should be unordered.

 

 

Partial Trust

 

There are no security permissions associated with the definition of a Finalize method.   As we’ve seen, it’s possible to mount a denial of service attack via finalization.   However, many other denial of service attacks are possible from partial trust, so this is uninteresting.

 

Customers and partners sometimes ask why partially trusted code is allowed to participate in finalization.   After all, Finalize methods are typically used to release unmanaged resources.   Yet partially trusted code doesn’t have direct access to unmanaged resources.   It must always go through an API provided by an assembly with UnmanagedCodePermission or some other effective equivalent to FullTrust.

 

The reason is that finalization can also be used to control pure managed resources, like object pools or caches.   I should point out that techniques based on weak handles can be more efficient than techniques based on finalization.   Nevertheless, it’s quite reasonable for partially trusted code to use finalization for pure managed resources.

 

SQL Server has a set of constraints that they place on partially trusted assemblies that are loaded into their environment.   I believe that these constraints prevent definition of static fields (except for initonly and literal static fields), use of synchronization, and the definition of Finalize methods.   However, these constraints are not related to security.   Rather, they are to improve scalability and reliability of applications by simplifying the threading model and by moving all shared state into the database where it can be transacted.

 

 

It’s hard to implement Finalize perfectly

 

Even when all Finalize methods are authored by fully trusted developers, finalization poses some problems for processes with extreme availability requirements, like SQL Server.   In part, this is because it’s difficult to write a completely reliable Finalize method – or a completely reliable anything else.

 

Here are some of the concerns specifically related to finalization.   I’ll explain later how some of these concerns are addressed in the context of a highly available process like SQL Server.

 

 

Your Finalize method must tolerate partially constructed instances

 

It’s possible for partially trusted code to subtype a fully trusted finalizable object (with APTCA) and throw an exception from the constructor.   This can be done before chaining to the base class constructor.   The result is that a zero-initialized object is registered for finalization.

 

Even if partially trusted code isn’t intentionally causing finalization of your partially constructed instances, asynchronous problems like StackOverflowException, OutOfMemoryException or AppDomainUnloadException can cause your constructor to be interrupted at a fairly arbitrary location.

 

 

Your Finalize method must consider the consequence of failure

 

It’s possible for partially trusted code to subtype a fully trusted finalizable object (with APTCA) and fail to chain to the base Finalize method.   This causes the fully trusted encapsulation of the resource to leak.

 

Even if partially trusted code isn’t intentionally causing finalization of your object to fail, the aforementioned asynchronous exceptions can cause your Finalize method to be interrupted at a fairly arbitrary location.

 

In addition, the CLR exposes a GC.SuppressFinalize method which can be used to prevent finalization of any object.   Arguably we should have made this a protected method on Object or demanded a permission, to prevent abuse of this method.   However, we didn’t want to add a member to Object for such an obscure feature.   And we didn’t want to add a demand, since this would have prevented efficient implementation of IDisposable from partial trust.

 

 

Your object is callable after Finalization

 

We’ve already seen how all the objects in a closure can access each other during finalization.   Indeed, if any one of those objects re-establishes its reachability from a root (e.g. it places itself into a static field or a handle), then all the other objects it reaches will also become re-established.   This is referred to as resurrection.   If you have a finalizable object that is publicly exposed, you cannot prevent your object from becoming resurrected.   You are at the mercy of all the other objects in the graph.

 

One possible solution here is to set a flag to indicate that your object has been finalized.   You can pepper your entire API with checks to this flag, throwing an ObjectDisposedException if you are subsequently called.   Yuck.

 

 

Your object is callable during Finalization

 

It’s true that the finalizer thread is currently single-threaded (though this may well change in the future).   And it’s true that the finalizer thread will only process instances that – at some point – were discovered to be unreachable from the application.   However, the possibility of resurrection means that your object may become visible to the application before its Finalize method is actually called.   This means that application threads and the finalizer thread can simultaneously be active in your object.

 

If your finalizable object encapsulates a protected resource like an OS handle, you must carefully consider whether you are exposed to threading attacks.   Shortly before we shipped V1, we fixed a number of handle recycling attacks that were due to race conditions between the application and Finalization.   See http://blogs.msdn.com/cbrumme/archive/2003/04/19/51365.aspx for more details.

 

 

Your Finalizer could be called multiple times

 

Just as there is a GC.SuppressFinalize method, we also expose a GC.ReRegisterForFinalize method.   And the same arguments about protected accessibility or security demands apply to the ReRegisterForFinalize method.

 

 

Your Finalizer runs in a delicate security context

 

As I’ve explained in prior blogs, the CLR flows the compressed stack and other security information around async points like ThreadPool.QueueUserWorkItem or Control.BeginInvoke.   Indeed, in Whidbey we include more security information by default.   However, we do not flow any security information from an object’s constructor to an object’s Finalize method.   So (to use an absurd example) if you expose a fully trusted type that accepts a filename string in its constructor and subsequently opens that file in its Finalize method, you have created a security bug.

 

 

Clearly it’s hard to write a correct Finalize method.   And the managed platform is supposed to make hard things easier.   I’ll return to this when I discuss the new Whidbey features of SafeHandles, Critical Finalizers and Constrained Execution Regions.

 

But what guarantees do I get if I don’t use any of those new gizmos?   What happens in a V1 or V1.1 process?

 

 

V1 & V1.1 Finalization Guarantees

 

If you allocate a finalizable object, we guarantee that it will be registered for finalization.   Once this has happened, there are several possibilities:

 

1)    As part of the natural sequence of garbage collection and finalization, the finalizer thread dequeues your object and finalizes it.

 

2)    The process can terminate without cooperating with the CLR’s shutdown code.   This can happen if you call TerminateProcess or ExitProcess directly.   In those cases, the CLR’s first notification of the shutdown is via a DllMain DLL_PROCESS_DETACH notification.   It is not safe to call managed code at that time, and we will leak all the finalizers.   Of course, the OS will do a fine job of reclaiming all its resources (including abandonment of any cross-process shared resources like Mutexes).   But if you needed to flush some buffers to a file, your final writes have been lost.

 

3)    The process can terminate in a manner that cooperates with the CLR’s shutdown code.   This includes calling exit() or returning from main() in any unmanaged code built with VC7 or later.   It includes System.Environment.Exit().   It includes a shutdown triggered from a managed EXE when all the foreground threads have completed.   And it includes shutdown of processes that are CLR-aware, like VisualStudio.   In these cases, the CLR attempts to drain both the ReadyToFinalize and the RegisteredForFinalization queues, processing all the finalizable objects.

 

4)    The AppDomain containing your object is unloaded.   Prior to Whidbey, the AppDomain will not unload until we have scanned the ReadyToFinalize and the RegisteredForFinalization queues, processing all the finalizable objects that live in the doomed AppDomain.

 

There are a few points to note here.

 

·       Objects are always finalized in the AppDomain they were created in.   A special case exists for any finalizable objects that are agile with respect to AppDomains.   To my knowledge, the only such type that exists is System.Threading.Thread.

 

·       I have heard that there is a bug in V1 and V1.1, where we get confused on AppDomain transitions in the ReadyToFinalize queue.   The finalization logic attempts to minimize AppDomain transitions by noticing natural partitions in the ReadyToFinalize queue.   I’m told there is a bug where we may occasionally skip finalizing the first object of a partition.   I don’t believe any customers have noticed this and it is fixed in Whidbey.

 

·       Astute readers will have noticed that during process shutdown and AppDomain unloading we actually finalize objects in the RegisteredForFinalization queue.   Such objects are still reachable and would not normally be subject to finalization.   Normally a Finalize method can rely on safely accessing finalizable state that is rooted via statics or some other means.   You can detect when this is no longer safe by checking AppDomain.IsFinalizingForUnload or Environment.HasShutdownStarted.

 

·       Since there is no ordering of finalization, critical infrastructure is being finalized along with application objects.   This means that WaitHandles, remoting infrastructure and even security infrastructure is disappearing underneath you.   This is a potential security concern and a definite reliability concern.   We have spot-fixed a few cases of this.   For example, we never finalize our Thread objects during process shutdown.

 

·       Finalization during process termination will eventually timeout.   If a particular Finalize method gets stuck, or if the queue isn’t reducing in size over time (i.e. you create 2 new finalizable instances out of each execution of your Finalize method), we will eventually timeout and terminate the process.   The exact timeouts depend on whether a profiler is attached and other details.

 

·       The thread that initiates process shutdown performs the duties of “watchdog.”   It is responsible for detecting timeouts during process termination.   If this thread is an STA thread, we cause it to pump COM calls in and out of the STA while it blocks as watchdog.   If the application has a deadlock that implicates the STA thread while it is executing these unmanaged COM calls, then the timeout mechanism is defeated and the process will hang.   This is fixed in Whidbey.

 

·       Subject to all of the above, we guarantee that we will dequeue your object and initiate a call to the Finalize method.   We do not guarantee that your Finalize method can be JITted without running out of stack or memory.   We do not guarantee that the execution of your Finalize method will complete without being aborted.   We do not guarantee that any types you require can be loaded and have their .cctors run.   All you get is a “best effort” attempt.   We’ll soon see how Whidbey extensions allow you to do better than this and guarantee full execution.

 

·       (If you want to know more about the shutdown of managed processes, see http://blogs.msdn.com/cbrumme/archive/2003/08/20/51504.aspx .)

 

 

SafeHandle

 

Whidbey contains some mechanisms that address many of the V1 and V1.1 issues with finalization.   Let’s start with SafeHandle, since it’s the easiest to understand.   Conceptually, this is just an encapsulation of an OS handle.   You should read the documentation of this feature for details.   Briefly, SafeHandle provides the following benefits:

 

1)    Someone else wrote it and is maintaining it.   Using it is much easier than building equivalent functionality yourself.

 

2)    It prevents races between an application thread and the finalizer thread in unmanaged code.   And it does this in a manner that leverages the type system.   Specifically, clients are forced to deal with SafeHandles rather than IntPtrs or value types which don’t have strong identity and lifetime semantics.

 

3)    It prevents handle-recycling attacks.   You can read more details about finalization races (#2 above) and this bullet on handle-recycling attacks by reading http://blogs.msdn.com/cbrumme/archive/2003/04/19/51365.aspx .   In that blog from last April, I allude to the existence of SafeHandle without giving details.

 

4)    It discourages promotion of large graphs of objects, by placing the finalizable resources in a tiny leaf instance.

 

5)    It participates with the PInvoke marshaler to ensure that unmarshaled instances will be registered for finalization.

 

6)    For the handful of bizarre APIs that aren’t covered by our standard marshaling styles, Constrained Execution Regions (CERs) can be used to guarantee that unmarshaled instances will be registered for finalization.

 

7)    It uses the new Critical Finalization mechanism to guarantee that leaks cannot occur.   This means that we not only guarantee we will initiate execution of your Finalize method, but we also make some strong guarantees that allow you to ensure that it actually completes execution.

 

8)    In order to guarantee that there will be no leaks, we necessarily leave the system open to denial of service and hangs.   This is the halting problem.   The Critical Finalization mechanism addresses this dilemma by making the leak protection explicit, restricting it to small regions of carefully written code, and by using the security system.   Only trusted code can achieve strong guarantees about leakage.   Such code is trusted not to create denial of service problems, whether maliciously or inadvertently, over small blocks of explicitly identified code.

 

9)    Since SafeHandle uses Critical Finalization, it solves the problem of sequencing buffer flushing before handle closing that I mentioned earlier.

 

So what is this Critical Finalization thing?

 

 

Critical Finalization (CF) and CERs

 

Any object that derives from CriticalFinalizerObject (including SafeHandle) obtains critical finalization.   This means:

 

1)    Before any objects of this type are created, the CLR will “prepare” any resources that will be necessary for the Finalize method to run.   Preparation includes JITting the code, running class constructors and – most importantly – traversing the static reachability of other methods and types that will be required during execution and making sure that they are likewise prepared.   However, the CLR cannot statically traverse through indirections like interface calls and virtual calls.   So there is a mechanism for the developer to guide the CLR through these opaque indirections.

 

2)    The CLR will never timeout on the execution of one of these Finalize methods.   As I mentioned, we rely on the limited amount of code written via this discipline combined with the trust decisions of the security system to avoid hangs here.

 

3)    When the Finalize method is called, it is called in a protected state that prevents the CLR from injecting Thread.Aborts or other optional asynchronous exceptions.   Because of our special preparation, we also prevent other asynchronous exceptions like OutOfMemoryExceptions due to JITting or type loading and TypeInitializationExceptions due to .cctors failures.   Of course, if the application tries to allocate an object it may get an OutOfMemoryException.   This is application-induced rather than system-induced and therefore is not considered the CLR’s responsibility.   The Finalize method can use standard exception handling to protect itself here.

 

4)    All normal finalizable objects are either executed or discarded without finalization, before any critical finalizers are executed.   This means that a buffer flush can precede the close of the underlying handle.

 

The first 3 bullet points above are not restricted to CF.   These bullet points apply to all CERs.   The fundamental difference between CF and other CERs is the funky flow control from the instantiation of an object to the execution of its Finalize method via registration on our finalization queues.   Other CERs can use normal block scopes in a single method to express the same reliability concepts.   For normal CERs, the preparation phase, the forward execution phase and the backout phases are all contained in a single method.

 

A full description of CERs is beyond the scope of a note that is ostensibly about finalization.   However, a brief description makes sense.

 

Essentially, CERs address issues with asynchronous exceptions.   I have already mentioned asynchronous exceptions, which is the CLR’s term for all the pesky problems that manifest themselves as surprising exceptions.   These are distinct from the application-level exceptions, which presumably are anticipated by and handled by the application.

 

You can read about asynchronous exceptions and the novel problems introduced by a managed execution environment that virtualizes resources so aggressively at http://blogs.msdn.com/cbrumme/archive/2003/06/23/51482.aspx .

 

In V1 and V1.1, the CLR does a poor job of distinguishing asynchronous exceptions from application exceptions.   In Whidbey, we are starting to make this separation but it remains one of the weak design points for our hosting and exception stories.

 

Anyway, I’m sure that many readers are familiar with the difficulty of writing reliable unmanaged code that is guaranteed to complete in the face of limited resources (e.g. memory or stack), free threading, and other facts of life.   And by now, if you’ve read all the blog articles I’ve mentioned, you are also familiar with the additional problems caused by a highly virtualized execution environment.

 

CERs allow you to declare regions of code where the CLR is constrained from injecting any system-generated errors.   And the author of the code is constrained from performing certain actions if he wants to avoid additional exceptions.   An obvious example is that he shouldn’t new up an object if he is not prepared to deal with an OutOfMemoryException from that operation.

 

In addition to CERs, Whidbey provides reliability contracts.   These contracts can be used to annotate methods with their guarantees and requirements with respect to reliability.   Using these contracts, it’s possible to compose reliable execution out of components written by different authors.   This is necessary for building reliable applications that make use of framework services.   If the reliability requirements and guarantees of the framework services were not themselves explicit, the client applications could not remain reliable on top of them.

 

 

Finalization in SQL Server and other high availability hosts

 

Back to finalization.

 

In a normal unhosted process, there isn’t a strong distinction between normal and critical finalization.   Normal processes won’t run out of memory, and if they do they should probably Fail Fast.   It’s unlikely that the risk of trying to continue execution after resource exhaustion is worth the increased risk of subsequent crashes, hangs or other corruptions.   Normal processes won’t experience Thread.Aborts that are injected across threads.   (As opposed to aborting the current thread, which is no more dangerous than throwing any other exception).

 

So the only real concern is whether all the finalizable objects will drain during process exit, before the timeouts kick in.   The timeouts are quite generous and in practice this is not a concern.

 

However, a hosted process like SQL Server is quite different.   Because of SQL Server’s availability requirements, it is vital that the process not FailFast for something innocuous like OutOfMemoryExceptions.   Indeed, SQL Server tries to run on the brink of memory exhaustion for performance reasons, so these memory exceptions are a constant fact of life in that environment.   Furthermore, SQL Server uses Thread.Abort explicitly across threads to terminate long-running requests and it uses Thread.Abort implicitly to unload AppDomains.   On a heavily loaded system, AppDomains may be unloaded to relieve resource pressure.

 

I have a lengthy blog on this topic, but I have not been able to post it because it talks about undisclosed Whidbey features.   At some point (no later than shipping Beta1), you will find it at http://blogs.msdn.com/cbrumme with a title of Hosting.   Until then, I’ll just mention that the Whidbey APIs support an escalation policy.   This is a declarative mechanism by which the host can express timeouts for normal finalization, normal AppDomain unload, normal Abort attempts, etc.   In addition to timeouts, the escalation policy can indicate appropriate actions whenever these timeouts expire.   So a normal AppDomain unload could (for example) be escalated to a rude AppDomain unload or a normal process exit or a rude process exit.

 

The distinction between polite/normal and rude involves several aspects beyond finalization.   If we just consider finalization, polite/normal means that we execute both normal and critical finalization.   Contrast this with a rude scenario where we will ignore the normal finalizers, which are discarded, and only execute the critical finalizers.   As you might expect, a similar distinction occurs between executing normal exception backout on threads, vs. restricting ourselves to any backout that is associated with CERs.

 

This allows a host to avoid solving the halting problem when performing normal finalization and exception backout, without putting the process at risk with respect to (critical) resource leakage or inconsistent state.

Apartments and Pumping in the CLR

I’ve already written the much-delayed blog on Hosting, but I can’t post it yet because it mentions a couple of new Whidbey features, which weren’t present in the PDC bits.   Obviously Microsoft doesn’t want to make product disclosures through my random blog articles.

 

I’m hoping this will be sorted out in another week or two.

 

While we’re waiting, I thought I would talk briefly(!) about pumping and apartments.   The CLR made some fundamental decisions about OLE, thread affinity, reentrancy and finalization.   These decisions have a significant impact on program correctness, server scalability, and compatibility with legacy (i.e. unmanaged) code.   So this is going to be a blog like the one on Shutdown from last August (see http://blogs.msdn.com/cbrumme/archive/2003/08/20/51504.aspx ).   There will be more detail than you probably care to know about one of the more frustrating parts of the Microsoft software stack.

 

First, an explanation of my odd choice of terms.   I’m using OLE as an umbrella which includes the following pieces of technology:

 

COM – the fundamental object model, like IUnknown and IClassFactory

DCOM – remoting of COM using IDL, NDR pickling and the SCM

Automation – IDispatch, VARIANT, Type Libraries, etc.

Active/X – Protocols for controls and their containers  

 

Next, some disclaimers:

 

I am not and have never been a GUI programmer.   So anything I know about Windows messages and pumping is from debugging GUI applications, not from writing them.   I’m not going to talk about WM_PENCTL notifications or anything else that requires UI knowledge.

 

Also, I’m going to point out a number of problems with OLE and apartments.   The history of the CLR and OLE are closely related.   In fact, at one point COM+ 1.0 was known internally as COM98 and the CLR was known internally as COM99.   We had some pretty aggressive ship targets back then!

 

In general, I love OLE and the folks who work on it.   Although it is inappropriate for the Internet, DCOM is still the fastest and most enterprise-ready distributed object system out there.   In a few ways the architecture of .NET Remoting is superior to DCOM, but we never had the time or resources to even approach the engineering effort that has gone into DCOM.   Presumably Indigo will eventually change this situation.   I also love COM’s strict separation of contract from implementation, the ability to negotiate for contracts, and so much more.

 

The bottom line is that OLE has had at least as much impact on Microsoft products and the industry, in its day, as .NET is having now.

 

But, like anything else, OLE has some flaws.   In contrast to the stark architectural beauty of COM and DCOM, late-bound Automation is messy.   At the time this was all rolled out to the world, I was at Borland and then Oracle.   As an outsider, it was hard for me to understand how one team could have produced such a strange combination.

 

Of course, Automation has been immensely successful – more successful than COM and DCOM.   My aesthetic taste is clearly no predictor of what people want.   Generally, people want whatever gets the job done, even if it does so in an ad hoc way.   And Automation has enabled an incredible number of application scenarios.

 

 

Apartments

 

If there’s another part of OLE that I dislike, it’s Single Threaded Apartments.   Presumably everyone knows that OLE offers three kinds of apartments:

 

Single Threaded Apartment (STA) – one affinitized thread is used to call all the objects residing in the apartment.   Any call on these objects from other threads must perform cross-thread marshaling to this affinitized thread, which dispatches the call.   Although a process can have an arbitrary number of STAs (with a corresponding number of threads), most client processes have a single Main STA and the GUI thread is the affinitized thread that owns it.

 

Multiple Threaded Apartment (MTA) – each process has at most one MTA at a time.   If the current MTA is not being used, OLE may tear it down.   A different MTA will be created as necessary later.   Most people think of the MTA as not having thread affinity.   But strictly speaking it has affinity to a group of threads.   This group is the set of all the threads that are not affinitized to STAs.   Some of the threads in this group are explicitly placed in the MTA by calling CoInitializeEx.   Other threads in this group are implicitly in the MTA because the MTA exists and because these threads haven’t been explicitly placed into STAs.   So, by the strict rules of OLE, it is not legal for STA threads to call on any objects in the MTA.   Instead, such calls must be marshaled from the calling STA thread over to one of the threads in the MTA before the call can legally proceed.

 

Neutral Apartment (NA) – this is a recent invention (Win2000, I think).   There is one NA in the process.   Objects contained in the NA can be called from any thread in the process (STA or MTA threads).   There are no threads associated with the NA, which is why it isn’t called NTA.   Calls into NA objects can be relatively efficient because no thread marshaling is ever required.   However, these cross-apartment calls still require a proxy to handle the transition between apartments.   Calls from an object in the NA to an object in an STA or the MTA might require thread marshaling.   This depends on whether or not the current thread is suitable for calling into the target object.   For example, a call from an STA object to an NA object and from there to an MTA object will require thread marshaling during the transition out of the NA into the MTA.

 

 

Threading

 

The MTA is effectively a free-threaded model.   (It’s not quite a free-threaded model, because STA threads aren’t strictly allowed to call on MTA objects directly).   From an efficiency point of view, it is the best threading model.   Also, it imposes the least semantics on the application, which is also desirable.   The main drawback with the MTA is that humans can’t reliably write free-threaded code.

 

Well, a few developers can write this kind of code if you pay them lots of money and you don’t ask them to write very much.   And if you code review it very carefully.   And you test it with thousands of machine hours, under very stressful conditions, on high-end MP machines like 8-ways and up.   And you’re still prepared to chase down a few embarrassing race conditions once you’ve shipped your product.

 

But it’s not a good plan for the rest of us.

 

The NA model is truly free-threaded, in the sense that any thread in the process can call on these objects.   All such threads must still transition through a proxy layer that maintains the apartment boundary.   But within the NA all calls are direct and free-threaded.   This is the only apartment that doesn’t involve thread affinity.

 

Although the NA is free-threaded, it is often used in conjunction with a lock to achieve rental threading.   The rental model says that only one thread at a time can be active inside an object or a group of objects, but there is no restriction on which thread this might be.   This is efficient because it avoids thread marshaling.   Rather than marshaling a call from one thread to whatever thread is affinitized to the target objects, the calling thread simply acquires the lock (to rent the context) and then completes the call on the current thread.   When the thread returns back out of the context, it releases the lock and now other threads can make calls.

 

If you call out of a rental context into some other object (as opposed to the return pathway), you have a choice.   You can keep holding the lock, in which case other threads cannot rent the context until you fully unwind.   In this mode, the rental context supports recursion of the current thread, but it does not support reentrancy from other threads.   Alternatively, the thread could release the lock when it calls out of the rental context, in which case it must reacquire the lock when it unwinds back and returns to the rental context.   In this mode, the rental context supports full reentrancy.

 

Throughout this blog, we’ll be returning to this fundamental decision of whether to support reentrancy.   It’s a complex issue.

 

If only recursion is supported on a rental model, it’s clear that this is a much more forgiving world for developers than a free-threaded model.   Once a thread has acquired the rental lock, no other threads can be active in the rented objects until the lock has been released.   And the lock will not be released until the thread fully unwinds from the call into the context.

 

Even with reentrancy, the number of places where concurrency can occur is limited.   Unless the renting thread calls out of the context, the lock won’t be released and the developer knows that other threads aren’t active within the rented objects.   Unfortunately, it might be hard for the developer to know all the places that call out of the current context, releasing the lock.   Particularly in a componentized world, or a world that combines application code with frameworks code, the developer can rarely have sufficient global knowledge.

 

So it sounds like limiting a rental context to same-thread recursion is better than allowing reentrancy during call outs, because the developer doesn’t have to worry about other threads mutating the state of objects in the rental context.   This is true.   But it also means that the resulting application is subject to more deadlocks.   Imagine what can happen if two rental contexts are simultaneously making calls to each other.   Thread T1 holds the lock to rent context C1.   Thread T2 holds the lock to rent context C2.   If T1 calls into C2 just as T2 calls into C1, and we are on the recursion plan, we have a classic deadlock.   Two locks have been taken in different sequences by two different threads.   Alternatively, if we are on a reentrancy plan, T1 will release the lock for C1 before contending for the lock on C2.   And T2 will release the lock for C2 before contending for the lock on C1.   The deadlock has been avoided, but T1 will find that the objects in C1 have been modified when it returns.   And T2 will find similar surprises when it returns to C2.

 

 

Affinity

 

Anyway, we now understand the free-threaded model of the MTA and NA and we understand how to build a rental model on top of these via a lock.   How about the single-threaded affinitized model of STAs?   It’s hard to completely describe the semantics of an STA, because the complete description must incorporate the details of pages of OLE pumping code, the behavior of 3rd party IMessageFilters, etc.   But generally an STA can be thought of as an affinitized rental context with reentrancy and strict stacking .   By this I mean:

 

• It is affinitized rental because all calls into the STA must marshal to the correct thread and because only one logical call can be active in the objects of the apartment at any time.   (This is necessarily the case, since there is only ever one thread).
• It has reentrancy because every callout from the STA thread effectively releases the lock held by the logical caller and allows other logical callers to either enter or return back to the STA.
• It has strict stacking because one stack (the stack of the affinitized STA thread) is used to process all the logical calls that occur in the STA.   When these logical calls perform a callout, the STA thread reentrantly picks up another call in, and this pushes the STA stack deeper.   When the first callout wants to return to the STA, it must wait for the STA thread’s stack to pop all the way back to the point of its own callout.

 

That point about strict stacking is a key difference between true rental and the affinitized rental model of an STA.   With true rental, we never marshal calls between threads.   Since each call occurs on its own thread, the pieces of stack for different logical threads are never mingled on an affinitized thread’s actual stack.   Returns back into the rental context after a callout can be processed in any order.   Returns back into an STA after a callout must be processed in a highly constrained order.

 

We’ve already seen a number of problems with STAs due to thread affinity, and we can add some more.   Here’s the combined list:

 

Marshaling calls between threads is expensive, compared to taking a lock.

 

Processing returns from callouts in a constrained fashion can lead to inefficiencies.   For instance, if the topmost return isn’t ready for processing yet, should the affinitized thread favor picking up a new incoming call (possibly leading to unconstrained stack growth) or should it favor waiting for the topmost return to complete (possibly idling the affinitized thread completely and conceivably resulting in deadlocks).

 

Any conventional locks held by an affinitized thread are worthless.   The affinitized thread is processing an arbitrary number of logical calls, but a conventional lock (like an OS CRITICAL_SECTION or managed Monitor) will not distinguish between these logical calls.   Instead, all lock acquisitions are performed by the single affinitized thread and are granted immediately as recursive acquisitions.   If you are thinking of building a more sophisticated lock that avoids this issue, realize that you are making that classic reentrancy vs. deadlock decision all over again.

 

Imagine a common server situation.   The first call comes in from a particular client, creates a few objects (e.g. a shopping cart) and returns.   Subsequent calls from that client manipulate that initial set of objects (e.g. putting some items into the shopping cart).   A final call checks out the shopping cart, places the order, and all the objects are garbage collected.   Now imagine that all those objects are affinitized to a particular thread.   As a consequence, the dispatch logic of your server must ensure that all calls from the same client are routed to the same thread.   And if that thread is busy doing other work, the dispatch logic must delay processing the new request until the appropriate affinitized thread is available.   This is complicated and it has a severe impact on scalability.

 

STAs must pump.   (How did I get this far without mentioning pumping?)

 

Any STA code that assumed a single-threaded world for the process, rather than just for the apartment, might not pump.   Such code breaks when we introduce the CLR into the process, as we will see.

 

 

Failure to Pump

 

Let’s look at those last two bullet points in more detail.   When your STA thread is doing nothing else, it needs to be checking to see if any other threads want to marshal some calls into it.   This is done with a Windows message pump.   If the STA thread fails to pump, these incoming calls will be blocked.   If the incoming calls are GUI SendMessages or PostMessages (which I think of as synchronous or asynchronous calls respectively), then failure to pump will produce an unresponsive UI.   If the incoming calls are COM calls, then failure to pump will result in calls timing out or deadlocking.

 

If processing one incoming call is going to take a while, it may be necessary to break up that processing with intermittent visits to the message pump.   Of course, if you pump you are allowing reentrancy to occur at those points.   So the developer loses all his wonderful guarantees of single threading.

 

Unfortunately, there’s a whole lot of STA code out there which doesn’t pump adequately.   For the most part, we see this in non-GUI applications.   If you have a GUI application that isn’t pumping enough, it’s obvious right there on the screen.   Those bugs tend to get fixed.

 

For non-GUI applications, a failure to pump may not be noticed in unmanaged code.   When that code is moved to managed (perhaps by re-compiling some VB6 code as VB.NET), we start seeing bugs.   Let’s look at a couple of real-world cases that we encountered during V1 of the CLR and how the lingering effects of these cases are still causing major headaches for managed developers and for Microsoft Support.   I’ll describe a server case first, and then a client case.

 

 

ADO and ASP Compatibility Mode

 

ADO.NET and ASP.NET are a winning combination.   But ASP.NET also supports an ASP compatibility mode.   In this mode, legacy ASP pages can be served up by the managed ASP.NET pipeline.   Such pages were written before we invented our managed platform, so they use ADO rather than ADO.NET for any data access.   Also, in this mode the DCOM threadpool is used rather than the managed System.Threading.ThreadPool.   Although all the threads in the managed ThreadPool are explicitly placed in the MTA (as you might hope and expect), the DCOM threadpool actually contains STA threads.

 

The purpose of this STA threadpool was to allow legacy STA COM objects in general, and VB6 objects in particular, to be moved from the client to the server.   The result suffers from the scaling problems I alluded to before, since requests are dispatched on up to 100 STA threads with careful respect for any affinity.   Also, VB6 has a variable scope which corresponds to “global” (I forget its name), but which is treated as per-thread when running on the server.   If there are more than 100 clients using a server, multiple clients will share a single STA thread based on the whims of the request dispatch logic.   This means that global variables are shared between sets of clients in a surprising fashion, based on the STA that they happen to correspond to.

 

A typical ASP page written in VBScript would establish a (hopefully pooled) database connection from ADO, query up a row, modify a field, and write the row back to the database.   Since the page was likely written in VB, any COM AddRef and Release calls on the ADO row and field value objects were supplied through the magic of the VB6 runtime.   This means they occur on the same thread and in a very deterministic fashion.

 

The ASP page contains no explicit pumping code.   Indeed, at no point was the STA actually pumped.   Although this is a strict violation of the rules, it didn’t cause any problems.   That’s because there are no GUI messages or inter-apartment COM calls that need to be serviced.

 

This technique of executing ASP pages on STAs with ADO worked fairly well – until we tried to extend the model to ASP.NET running in ASP compatibility mode.   The first problem that we ran into was that all managed applications are automatically multi-threaded.   For any application of reasonable complexity, there are sure to be at least a few finalizable objects.   These objects will have their Finalize methods called by one or more dedicated finalizer threads that are distinct from the application threads.

 

(It’s important that finalization occurs on non-application threads, since we don’t want to be holding any application locks when we call the Finalize method.   And today the CLR only has a single Finalizer thread, but this is an implementation detail.   It’s quite likely that in the future we will concurrently call Finalize methods on many objects, perhaps by moving finalization duties over to the ThreadPool.   This would address some scalability concerns with finalization, and would also allow us to make stronger guarantees about the availability of the finalization service).

 

Our COM Interop layer ensures that we almost only ever call COM objects in the correct apartment and context.   The one place where we violate COM rules is when the COM object’s apartment or context has been torn down.   In that case, we will still call IUnknown::Release on the pUnk to try to recover its resources, even though this is strictly illegal.   We’ve gone backwards and forwards on whether this is appropriate, and we provide a Customer Debug Probe so that you can detect whether this is happening in your application.

 

Anyway, let’s pretend that we absolutely always call the pUnk in the correct apartment and context.   In the case of an object living in an STA, this means that the Finalizer thread will marshal the call to the affinitized thread of that STA.   But if that STA thread is not pumping, the Finalizer thread will block indefinitely while attempting to perform the cross-thread marshaling.

 

The effect on a server is crippling.   The Finalizer thread makes no progress.   The number of unreleased pUnks grows without bounds.   Eventually some resource (usually memory) is exceeded and the process crashes.

 

One solution is to edit the original ASP page to pump the underlying STA thread that it is executing on.   A light-weight way to pump is to call Thread.CurrentThread.Join(0).   This causes the current thread to block until the current thread dies (which isn’t going to happen) or until 0 milliseconds have elapsed – whichever happens first.   I’ll explain later why this also performs some pumping and why this is a controversial aspect of the CLR.   A heavier-weight way to pump is to call GC.WaitForPendingFinalizers.   This not only performs pumping, but it also waits for the Finalization queue to drain.

 

If you are porting a page that produces a modest number of COM objects, doing a simple Join on each page may be sufficient.   If your page performs elaborate processing, perhaps creating an unbounded number of COM objects in a loop, then you may need to either add a Join within the loop or WaitForPendingFinalizers at the end of the page processing.   The only way to really know is to experiment with both techniques, measuring the growth of the Finalization queue and the impact on server throughput.

 

 

ADO’s Threading Model

 

There was another problem with using ADO from ASP.NET’s ASP compatibility mode.   Do you know what the threading model of ADO is?   Well, if you check the registry for some ADO CLSIDs on your machine, you may find them registered as ThreadingModel=Single or you may find them registered as ThreadingModel=Both.

 

If these classes are registered as Single, OLE will carefully ensure that their instances can only be called from the thread that they were created on.   This implies that the objects can assume a single-threaded view of the world and they do not need to be written in a thread-safe manner.   If these classes are registered as Both, OLE will ensure that their instances are only called from threads in the right apartment.   But if that apartment is the MTA, these objects better have been written in a thread-safe manner.   For example, they had better be using InterlockedIncrement and Decrement, or an equivalent, for reference counting.

 

Unfortunately, the ADO classes are not thread-safe.   Strictly speaking, they should never be registered as anything but Single.   You may find them registered as Both on your machine because this improves scalability and throughput for some key scenarios.   And those key scenarios happen to limit themselves to “one thread at a time” because of how ASP and VB6 work.

 

In fact, the legacy ADO classes don’t even support single-threaded access if there is reentrancy.   They will randomly crash when used in this manner (and this is exactly the manner in which ADO was driven in the early days of V1).   Here are the steps:

 

The page queries up an ADO row object, which enters managed code via COM Interop as an RCW (runtime-callable wrapper).

By making a COM call on this RCW, the page navigates to a field value.   This field value also enters managed code via COM Interop as an RCW.

The page now makes a COM call via ADO which results in a call out to the remote database.   At this point, the STA thread is pumped by the DCOM remote call.   Since this is a remote call, it’s going to take a while before it returns.

The garbage collector decides that it’s time to collect.   At this point, the RCW for the field value is still reachable and is reported.   The RCW for the row object is no longer referenced by managed code and is collected.

The Finalizer thread notices that the pUnk underlying the row’s RCW is no longer in use, and it makes the cross-apartment call from the Finalizer thread’s apartment (MTA) to the ADO row object’s apartment (STA).

Recall that the STA thread is pumping for the duration of the remote database call (#3 above).   It picks up the cross-thread call from the Finalizer (#5 above) and performs the Release on the Row object.   This is the final Release and ADO deletes the unmanaged Row object from memory.   This logical call unwinds and the Finalizer thread is unblocked (hurray).   The STA thread returns to pumping.

The remote database call returns back to the server machine.   The STA thread picks it up from its pumping loop and returns back to the page, unwinding the thread.

The page now updates the field value, which involves a COM call to the underlying ADO object.

ADO crashes or randomly corrupts memory.

 

What happened?   The ADO developers made a questionable design decision when they implemented COM reference counting throughout their hierarchy.   The field values refer to their owning row object, but they don’t hold a reference count on that row.   Instead, they assume that the row will live as long as all of its associated field values.   And yet, whenever the application makes an ADO call on a field value, the field value will access that (hopefully present) row.

 

This assumption worked fine in the days of ASP and VB6.   So nobody even noticed the bug until the CLR violated those threading assumptions – without violating the underlying OLE rules, of course.

 

It was impractical to fix this by opening up ADO and rewriting the code.   There are many different versions of ADO in existence, and many products that distribute it.   Another option was to add GC.KeepAlive(row) calls at the bottom of each page, to extend the lifetime of the row objects until the field values were no longer needed.   This would have been a nightmare for Support.

 

Instead, the ADO team solved the problem for managed code with a very elegant technique.   (I invented it, so of course I think it was elegant).   They opened up the assembly that was created by TlbImp’ing ADO.   Then they added managed references from the RCWs of the field values to the RCWs of their owning rows.   These managed references are completely visible to the garbage collector.   Now the GC knows that if the field values are reachable then the row values must also be reachable.   Problem solved.

 

 

No Typelib Registered

 

Incidentally, we ran into another very common problem when we moved existing client or server COM applications over to managed code.   Whenever an application uses a COM object, it tries hard to match the thread of the client to the ThreadingModel of the server.   In other words, if the application needs to use a ThreadingModel=Main COM object, the application tries to ensure that the creating thread is in an STA.   Similarly, if the application needs to use a ThreadingModel=Free COM object, it tries to create this object from an MTA thread.   Even if a COM object is ThreadingModel=Both, the application will try to access the object from the same sort of thread (STA vs. MTA) as the thread that created the object.

 

One reason for doing this is performance.   If you can avoid an apartment transition, your calls will be much faster.   Another reason has to do with pumping and reentrancy.   If you make a cross-apartment call into an STA, the STA better be pumping to pick up your call.   And if you make a cross-apartment call out of an STA, your thread will start pumping and your application becomes reentrant.   This is a small dose of free-threading, and many application assumptions start to break.   A final reason for avoiding apartment transitions is that they often aren’t supported.   For instance, most ActiveX scenarios require that the container and the control are in the same STA.   If you introduce an apartment boundary (even between two STAs), bizarre cases like Input Synchronous messages stop working properly.

 

The net result is that a great many applications avoid using COM objects across apartment boundaries.   And this means that – even if that COM object is nominally marshalable across an apartment boundary – this often isn’t being tested.   So an application might install itself without ensuring that the typelib of the COM component is actually registered.

 

When the application is moved to managed code, developers are frustrated to see InvalidCastExceptions on the managed side.   A typical sequence is that they successfully ‘new’ the COM object, implying that the CoCreate returned a pUnk which was wrapped in an RCW.   Then when they cast it to one of the interfaces that they know is supported, a casting exception is thrown.   This casting exception is due to a QueryInterface call failing with E_NOINTERFACE.   Yet this HRESULT is not returned by the COM object, which does indeed support the interface.   Instead, it is returned by a COM apartment proxy which sits between the RCW and that COM object.   The COM apartment proxy is simply failing to marshal the interface across the apartment boundary – usually because the COM object is using the OLEAUT marshaler and the Typelib has not been properly registered.

 

This is a common failure, and it’s unfortunate that a generic E_NOINTERFACE doesn’t lead to better debuggability for this case.

 

Finally, I can’t help but mention that the COM Interop layer added other perturbations to many unmanaged COM scenarios that seemed to be working just fine.   Common perturbations from managed code include garbage collection, a Finalizer thread, strict conformance to OLE marshaling rules, and the fact that managed objects are agile with respect to COM apartments and COM+ contexts (unless they derive from ServicedComponent).

 

For instance, Trident required that all calls on its objects occur on the correct thread.   But Trident also had an extension model where 3rd party objects could be aggregated onto their base objects.   Unfortunately, the aggregator performed blind delegation to the 3rd party objects.   And – even more unfortunate – this blind delegation did not exclude QI’s for IMarshal.   Of course, managed objects implement IMarshal to achieve their apartment and context agility.   So if Trident aggregated a managed object as an extention, the containing Trident object would attempt to become partially agile in a very broken way.

 

Hopefully we found and dealt with most of these issues before we shipped V1.

 

 

Not Pumping a Client

 

I said I would describe two cases where non-pumping unmanaged code caused problems when we moved to managed code.   The above explains, in great detail, how ADO and ASP compatibility mode caused us problems on the server.   Now let’s look at the non-GUI client case.

 

We all know that a WinForms GUI client is going to put the main GUI thread into an STA.   And we know that there’s a lot of pumping in a GUI application, or else not much is going to show on the screen.

 

Assume for a moment that a Console application also puts its main thread into an STA.   If that main thread creates any COM objects via COM Interop, and if those COM objects are ThreadingModel=Main or Both, then the application better be pumping.   If it fails to pump, we’ll have exactly the same situation with our server running ASP compatibility mode.   The Finalizer thread won’t be able to marshal calls into the STA to Release any pUnks.

 

On a well-loaded server, that failure is quickly noticed by the developer or by the folks in operations.   But on a client, this might be just a mild case of constipation.   The rate of creation of finalizable objects may be low enough that the problem is never noticed.   Or it may be noticed as a gradual build up of resources.   If the problem is reported to Microsoft Support, the customer generally categorizes it as a garbage collection bug.

 

So what is the apartment of a Console application’s main thread?   Well, it depends.

 

If you build a Console application in Notepad, the main thread is likely to start off in the MTA.   If you build a Console application with Visual Studio, then if you pick C# or VB.NET your main thread is likely to be in an STA.   If you build a Console application with Visual Studio and you choose managed C++, your main thread is likely to be in an MTA for V1 or V1.1.   I think it’s likely to be in an STA for our next release.

 

Wow.   Why are we all over the place on this?   Mostly, it’s because there is no correct answer.   Either the developer is not going to use any COM objects in his Console application, in which case the choice doesn’t really matter, or the developer is going to use some COM objects and this should inform his decision.

 

For instance, if the developer will use COM objects with ThreadingModel=Main, he probably wants to put his main thread into an STA so he can use the COM objects directly without cross-thread marshaling and all the issues that this would imply.   This means he should also pump that thread, if there are other threads (like the Finalizer!) active in the process.   Alternatively, if the developer intends to use COM objects with ThreadingModel=Free, he probably wants to put his main thread in the MTA so he can access those objects directly.   Now he doesn’t need to pump, but he does need to consider the implications of writing free-threaded code.

 

Either way, the developer has some responsibility.

 

Unfortunately, the choice of a default is typically made by the project type that he selects in Visual Studio, or is based on the CLR’s default behavior (which favors MTA).   And realistically the subtleties of apartments and pumping are beyond the knowledge (or interest) of most managed developers.   Let’s face it: nobody should have to worry about this sort of thing.

 

 

The Managed CoInitialize Mess

 

There are three ways to select an apartment choice for the main thread of your Console application.   All three of these techniques have concerns associated with them.

 

1)       You can place either an STAThreadAttribute or MTAThreadAttribute onto the main method.

 

2)       You can perform an assignment to System.Threading.CurrentThread.ApartmentState as one of the first statements of your main method (or of your thread procedure if you do a Thread.Start).

 

3)       You can accept the CLR’s default of MTA.

 

So what’s wrong with each of these techniques?

 

The first technique is the preferred method, and it works very well for C#.   After some tweaks to the VB.NET compiler before we shipped V1, it worked well for VB too.   Managed C++ still doesn’t properly support this technique.   The reason is that the entrypoint of a managed C++ EXE isn’t actually your ‘main’ routine.   Instead, it’s a method inside the C-runtime library.   That method eventually delegates to your ‘main’ routine.   But the CLR doesn’t scan through the closure of calls from the entrypoint when looking for the custom attribute that defines the threading model.   If the CLR doesn’t find it on the method that is the EXE’s entrypoint, it stops looking.   The net result is that your attribute is quietly ignored for C++.

 

I’m told that this will be addressed in Whidbey, by having the linker propagate the attribute from ‘main’ to the CRT entrypoint.   And indeed this is how the VB.NET compiler works today.

 

What’s wrong with the second technique?   Unfortunately, it is subject to a race condition.   Before the CLR can actually call your thread procedure, it may first call some module constructors, class constructors, AssemblyLoad notifications and AssemblyResolve notifications.   All of this execution occurs on the thread that was just created.   What happens if some of these methods set the thread’s ApartmentState before you get a chance?   What happens if they call Windows services like the clipboard that also set the apartment state?   A more likely scenario is that one of these other methods will make a PInvoke call that marshals a BSTR, SAFEARRAY or VARIANT.   Even these innocuous operations can force a CoInitializeEx on your thread and limit your ability to configure the thread from your thread procedure.

 

When you are developing your application, none of the above is likely to occur.   The real nightmare scenario is that a future version of the CLR will provide a JIT that inlines a little more aggressively, so some extra class constructors execute before your thread procedure.   In other words, you will ship an application that is balanced on a knife edge here, and this will become an App Compatibility issue for all of us.   (See http://blogs.msdn.com/cbrumme/archive/2003/11/10/51554.aspx for more details on the sort of thing we worry about here).

 

In fact, for the next release of the CLR we are seriously considering making it impossible to set the apartment state on a running thread in this manner.   At a minimum, you should expect to see a Customer Debug Probe warning of the risk here.

 

And the third technique from above has a similar problem.   Recall that threads in the MTA can be explicitly placed there through a CoInitializeEx call, or they can be implicitly treated as being in the MTA because they haven’t been placed into an STA.   The difference between these two cases is significant.

 

If a thread is explicitly in the MTA, any attempt to configure it as an STA thread will fail with an error of RPC_E_CHANGED_MODE.   By contrast, if a thread is implicitly in the MTA it can be moved to an STA by calling CoInitializeEx.   This is more likely than it may sound.   If you attempt a clipboard operation, or you call any number of other Windows services, the code you call may attempt to place your thread in the STA.   And when you accept the CLR default behavior, it currently leaves the thread implicitly in the MTA and therefore is subject to reassignment.

 

This is another place where we are seriously considering changing the rules in the next version of the CLR.   Rather than place threads implicitly in the MTA, we are considering making this assignment explicit and preventing any subsequent reassignment.   Once again, our motivation is to reduce the App Compat risk for applications after they have been deployed.

 

Speaking of race conditions and apartments, the CLR has a nasty bug which was introduced in V1 and which we have yet to remove.   I’ve already mentioned that any threads that aren’t in STAs or explicitly in the MTA are implicitly in the MTA.   That’s not strictly true.   These threads are only in the MTA if there is an MTA for them to be in.

 

There is an MTA if OLE is active in the process and if at least one thread is explicitly in the MTA.   When this is the case, all the other unconfigured threads are implicitly in the MTA.   But if that one explicit thread should terminate or CoUninitialize, then OLE will tear down the MTA.   A different MTA may be created later, when a thread explicitly places itself into it.   And at that point, all the unconfigured threads will implicitly join it.

 

But this destruction and recreation of the MTA has some serious impacts on COM Interop.   In fact, any changes to the apartment state of a thread can confuse our COM Interop layer, cause deadlocks on downlevel platforms, and lead to memory leaks and violation of OLE rules.

 

Let’s look at how this specific race condition occurs first, and then I’ll talk about the larger problems here.

 

An unmanaged thread CoInitializes itself for the MTA and calls into managed code.

While in managed code, that thread introduces some COM objects to our COM Interop layer in the form of RCWs, perhaps by ‘new’ing them from managed code.

The CLR notices that the current thread is in the MTA, and realizes that it must “keep the MTA alive.”   We signal the Finalizer thread to put itself explicitly into the MTA via CoInitializeEx.

The unmanaged thread returns out to unmanaged code where it either dies or simply calls CoUninitialize.   The MTA is torn down.

The Finalizer thread wakes up and explicitly CoInitializes itself into the MTA.   Oops.   It’s too late to keep the original MTA alive and it has the effect of creating a new MTA.   At least this one will live until the end of the process.

 

As far as I know, this is the only race condition in the CLR that we haven’t fixed.   Why have we ignored it all these years?   First, we’ve never seen it reported from the field.   This isn’t so surprising when you consider that the application often shares responsibility for keeping the MTA alive.   Many applications are aware of this obligation and – if they use COM – they always keep an outstanding CoInitialize on one MTA thread so the apartment won’t be torn down.   Second, I generally resist fixing bugs by adding inter-thread dependencies.   It would be all too easy to create a deadlock by making step 3 wait for the Finalizer thread to CoInitialize itself, rather than just signaling it to do so.   This is particularly true since the causality of calls from the Finalizer to other threads is often opaque to us, as I’ll explain later.   And we certainly don’t want to create a dedicated thread for this purpose.   Dedicated threads have a real impact on Terminal Server scenarios, where the cost of one thread in a process is multiplied by all the processes that are running.   Even if we were prepared to pay this cost, we would want to create this thread lazily.   But synchronizing with the creation of another thread is always a dangerous proposition.   Thread creation involves taking the OS loader lock and making DLL_THREAD_ATTACH notifications to all the DllMain routines that didn’t explicitly disable these calls.

 

The bottom line is that the fix is expensive and distasteful.   And it speaks to a more general problem, where many different components in a process may be individually spinning up threads to keep the MTA from being recycled.   A better solution is for OLE to provide an API to keep this apartment alive, without requiring all those dedicated threads.   This is the approach that we are pursuing for the long term.

 

In our general cleanup of the CLR’s treatment of CoInitialize, we are also likely to change the semantics of assigning the current thread’s ApartmentState to Unknown.   In V1 & V1.1 of the CLR, any attempt to set the state to Unknown would throw an ArgumentOutOfRangeException, so we’re confident that we can make this change without breaking applications.

 

If the CLR has performed an outstanding CoInitializeEx on this thread, we may treat the assignment to Unknown as a request to perform a CoUninitialize to reverse the operation.   Currently, the only way you can CoUninitialize a thread is to PInvoke to the OLE32 service.   And such changes to the apartment state are uncoordinated with the CLR.

 

Now why does it matter if the apartment state of a thread changes, without the CLR knowing?   It matters because:

 

1)       The CLR may hold RCWs over COM objects in the apartment that is about to disappear.   Without a notification, we cannot legally release those pUnks.   As I’ve already mentioned, we break the rules here and attempt to Release anyway.   But it’s still a very bad situation and sometimes we will end up leaking.

 

2)       The CLR will perform limited pumping of STA threads when you perform managed blocking (e.g. WaitHandle.WaitOne).   If we are on a recent OS, we can use the IComThreadingInfo interface to efficiently determine whether we should pump or not.   But if we are on a downlevel platform, we would have to call CoInitialize prior to each blocking operation and check for a failure code to absolutely determine the current state of the thread.   This is totally impractical from a performance point of view.   So instead we cache what we believe is the correct apartment state of the thread.   If the application performs a CoInitialize or CoUninitialize without informing us, then our cached knowledge is stale.   So on downlevel platforms we might neglect to pump an STA (which can cause deadlocks).   Or we may attempt to pump an MTA (which can cause deadlocks).

 

Incidentally, if you ever run managed applications under a diagnostic tool like AppVerifier, you may see complaints from that tool at process shutdown that we have leaked one or more CoInitialize calls.   In a well-behaved application, each CoInitialize would have a balancing CoUninitialize.   However, most processes are not so well-behaved.   It’s typical for applications to terminate the process without unwinding all the threads of the process.   There’s a very detailed description of the CLR’s shutdown behavior at http://blogs.msdn.com/cbrumme/archive/2003/08/20/51504.aspx .

 

The bottom line here is that the CLR is heavily dependent on knowing exactly when apartments are created and destroyed, or when threads become associated or disassociated with those apartments.   But the CLR is largely out of the loop when these operations occur, unless they occur through managed APIs.   Unfortunately, we are rarely informed.   For an extreme example of this, the Shell has APIs which require an STA.   If the calling thread is implicitly in the MTA, these Shell APIs CoInitialize that calling thread into an STA.   As the call returns, the API will CoUnitialize and rip down the apartment.

 

We would like to do better here over time.   But there are some pretty deep problems and most solutions end up breaking an important scenario here or there.

 

 

Back to Pumping

 

Enough of the CoInitialize mess.   I mentioned above that managed blocking will perform some pumping when called on an STA thread.

 

Managed blocking includes a contentious Monitor.Enter, WaitHandle.WaitOne, WaitHandle.WaitAny, GC.WaitForPendingFinalizers, our ReaderWriterLock and Thread.Join.   It also includes anything else in FX that calls down to these routines.   One noticeable place where this happens is during COM Interop.   There are pathways through COM Interop where a cache miss occurs on finding an appropriate pUnk to dispatch a call.   At those points, the COM call is forced down a slow path and we use this as an opportunity to pump a little bit.   We do this to allow the Finalizer thread to release any pUnks on the current STA, if the application is neglecting to pump.   (Remember those ASP Compat and Console client scenarios?)   This is a questionable practice on our part.   It causes reentrancy at a place where it normally could never occur in pure unmanaged scenarios.   But it allows a number of applications to successfully run without clogging up the Finalizer thread.

 

Anyway, managed blocking does not include PInvokes directly to any of the OS blocking services.   And keep in mind that if you PInvoke to the OS blocking services directly, the CLR will no longer be able to take control of your thread.   Operations like Thread.Interrupt, Thread.Abort and AppDomain.Unload will be indefinitely delayed.

 

Did you notice that I neglected to mention WaitHandle.WaitAll in the list of managed blocking opeprations?   That’s because we don’t allow you to call WaitAll from an STA thread.   The reason is rather subtle.   When you perform a pumping wait, at some level you need to call MsgWaitForMultipleObjectsEx, or a similar Msg* based variant.   But the semantics of a WAIT_ALL on an OS MsgWaitForMultipleObjectsEx call is rather surprising and not what you want at all.   It waits for all the handles to be signaled AND for a message to arrive at the message queue.   In other words, all your handles could be signaled and the application will keep blocking until you nudge the mouse!   Ugh.

 

We’ve toyed with some workarounds for this case.   For example, you could imagine spinning up an MTA thread and having it perform the blocking operation on the handles.   When all the handles are signaled, it could set another event.   The STA thread would do a WaitHandle.WaitOne on that other event.   This gives us the desired behavior that the STA thread wakes up when all handles are signaled, and it still pumps the message queue.   However, if any of those handles are “thread-owned”, like a Mutex, then we have broken the semantics.   Our sacrificial MTA thread now owns the Mutex, rather than the STA thread.

 

Another technique would be to put the STA thread into a loop.   Each iteration would ping the handles with a brief timeout to see if it could acquire them.   Then it would check the message queue with a PeekMessage or similar technique, and then iterate.   This is a terrible solution for battery-powered devices or for Terminal Server scenarios.   What used to be efficient blocking is now busily spinning in a loop.   And if no messages actually arrive, we have disturbed the fairness guarantees of the OS blocking primitives by pinging.

 

A final technique would be to acquire the handles one by one, using WaitOne.   This is probably the worst approach of all.   The semantics of an OS WAIT_ALL are that you will either get no handles or you will get all of them.   This is critical to avoiding deadlocks, if different parts of the application block on the same set of handles – but fill the array of handles in random order.

 

I keep saying that managed blocking will perform “some pumping” when called on an STA thread.   Wouldn’t it be great to know exactly what will get pumped?   Unfortunately, pumping is a black art which is beyond mortal comprehension.   On Win2000 and up, we simply delegate to OLE32’s CoWaitForMultipleHandles service.   And before we wrote the initial cut of our pumping code for NT4 and Win9X, I thought I would glance through CoWaitForMultipleHandles to see how it is done.   It is many, many pages of complex code.   And it uses special flags and APIs that aren’t even available on Win9X.

 

The code we finally wrote for the downlevel platforms is relatively simple.   We gather the list of hidden OLE windows associated with the current STA thread and try to restrict our pumping to the COM calls which travel through them.   However, a lot of the pumping complexity is in USER32 services like PeekMessage.   Did you know that calling PeekMessage for one window will actually cause SendMessages to be dispatched on other windows belonging to the same thread?   This is another example of how someone made a tradeoff between reentrancy and deadlocks.   In this case, the tradeoff was made in favor of reentrancy by someone inside USER32.

 

By now you may be thinking “Okay.   Pump more and I get reentrancy.   Pump less and I get deadlocks.”   But of course the world is more complicated than that.   For instance, the Finalizer thread may synchronously call into the main GUI STA thread, perhaps to release a pUnk there, as we have seen.   The causality from the Finalizer thread to the main GUI STA thread is invisible to the CLR (though the CLR Security Lead recently suggested using OLE channel hooks as a technique for making this causality visible).   If the main GUI STA thread now calls GC.WaitForPendingFinalizers in order to pump, there’s a possibility of a deadlock.   That’s because the GUI STA thread must wait for the Finalizer thread to drain its queue.   But the Finalizer thread cannot drain its queue until the GUI thread has serviced its incoming synchronous call from the Finalizer.

 

 

Reentrancy, Avalon, Longhorn and the Client

 

Ah, reentrancy again.   From time to time, customers inside or outside the company discover that we are pumping messages during managed blocking on an STA.   This is a legitimate concern, because they know that it’s very hard to write code that’s robust in the face of reentrancy.   In fact, one internal team completely avoids managed blocking, including almost any use of FX, for this reason.

 

Avalon was very upset, too.   I’m not sure how much detail they have disclosed about their threading model.   And it’s certainly not my place to reveal what they are doing.   Suffice it to say that their model is an explicit rental model that does not presume thread affinity.   If you’ve read this far, I’m sure you approve of their decision.

 

Avalon must necessarily coexist with STAs, but Avalon doesn’t want to require them.   The CLR and Avalon have a shared long term goal of driving STAs out of the platform.   But, realistically, this will take decades.   Avalon’s shorter term goal is to allow some useful GUI applications to be written without STAs.   Even this is quite difficult.   If you call the clipboard today, you will have an STA.

 

Avalon also has made a conscious design choice to favor deadlocks over reentrancy.   In my opinion, this is an excellent goal.   Deadlocks are easily debugged.   Reentrancy is almost impossible to debug.   Instead, it results in odd inconsistencies that manifest over time.

 

In order to achieve their design goals, Avalon requires the ability to control the CLR’s pumping.   And since we’ve had similar requests from other teams inside and outside the company, this is a reasonable feature for us to provide.

 

V1 of the CLR had a conscious goal of making as much legacy VB and C++ code work as was possible.   When we saw the number of applications that failed to pump, we had no choice but to insert pumping for them – even at the cost of reentrancy.   Avalon is in a completely different position.   All Avalon code is new code.   They are in a great position to define an explicit model for pumping, and then require that all new applications rigorously conform to that model.

 

Indeed, as much as I dislike STAs, I have a bigger concern about Longhorn and its client focus.   Historically, Microsoft has built a ton of great functionality and added it to the platform.   But that functionality is often mixed up with various client assumptions.   STAs are probably the biggest of those assumptions.   The Shell is an example of this.   It started out as a user-focused set of services, like the namespace.   But it’s growing into something that’s far more generally useful.   To the extent that the Shell wants to take its core concepts and make them part of the base managed Longhorn platform, it needs to shed the client focus.   The same is true of Office.

 

For instance, I want to write some code that navigates to a particular document through some namespace and then processes it in some manner.   And I want that exact same code to run correctly on the client and on the server.   On the client, my processing of that document should not make the UI unresponsive.   On the server, my processing of that document should not cause problems with scalability or throughput.

 

Historically, this just hasn’t been the case.   We have an opportunity to correct this problem once, with the major rearchitecture that is Longhorn.   But although Longhorn will have both client and server releases, I worry that we might still have a dangerous emphasis on the client.

 

This may be one of the biggest risks we face in Longhorn.

 

 

Winding Down

 

Finally, I feel a little bad about picking something I don’t like and writing about it.   But there’s a reason that this topic came up.   Last week, a customer in Japan was struggling with using mshtml.dll to crack some HTML files from inside ASP.NET.   It’s the obvious thing to do.   Clearly ‘mshtml’ stands for Microsoft HTML and clearly this is how we expect customers to process files in this format.

 

Unfortunately, MSHTML was written as client-side functionality.   In fact, I’m told that it drives its own initialization by posting Windows messages back to itself and waiting for them to be pumped.   So if you aren’t pumping an STA, you aren’t going to get very far.

 

There’s that disturbing historical trend at Microsoft to combine generally useful functionality with a client bias again!

 

We explained to the customer the risks of using client components on a server, and the pumping behavior that is inherent in managed blocking on an STA.   After we had been through all the grisly details, the customer made the natural observation:   None of this is written down anywhere.

 

Well, I still never talked about a mysterious new flag to CoWaitForMultipleHandles.   Or how custom implementations of IMessageFilter can cause problems.   Or the difference between Main and Single.   Or the relationship between apartments and COM+ contexts and ServicedComponents.   Or the amazing discovery that OLE32 sometimes requires you to pump the MTA if you have DCOM installed on Win9X.

 

But I’m sure that at this point I’ve said far more than most people care to hear about this subject.

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The PDC and Application Compatibility, but still no Hosting

The PDC has happened, which means two things.   I can post some of my (slightly self-censored) reactions to the show, and I can talk about what we ve disclosed about Whidbey and Longhorn more freely.   In this particular case, I had promised to talk about the deep changes we re making in Whidbey to allow you to host the CLR in your process.   As you ll see, I got side tracked and ended up discussing Application Compatibility instead.

 

But first, my impressions of the PDC:

 

The first keynote, with Bill, Jim & Longhorn, was guaranteed to be good.  It had all the coolness of Avalon, WinFS and Indigo, so of course it was impressive.  In fact, throughout all the sessions I attended, I was surprised by the apparent polish and maturity of Longhorn.  In my opinion, Avalon looked like it is the most mature and settled.  Indigo also looked surprisingly real.  WinFS looked good in the keynote, where it was all about the justification for the technology.  But in the drill-down sessions, I had the sense that it s not as far along as the others.

 

Hopefully all the attendees realize that Longhorn is still a long way off.   It s hard to see from the demos, but a lot of fundamental design issues and huge missing pieces remain.

 

Incidentally, I still can t believe that we picked WinFX to describe the extended managed frameworks and WinFS to describe the new storage system.   One of those names has got to go.

 

I was worried that the Whidbey keynote on Tuesday would appear mundane and old-fashioned by comparison.  But to an audience of developers, Eric's keynote looked very good indeed.  Visual Studio looked better than I've ever seen it.  The device app was so easy to write that I feel I could build a FedEx-style package tracking application in a weekend.  The high point of this keynote was ASP.NET.  I hadn't been paying attention to what they've done recently, so I was blown away by the personalization system and by the user-customizable web pages.  If I had seen a site like that, I would have assumed the author spent weeks getting it to work properly.   It s hard to believe this can all be done with drag-and-drop.

 

In V1, ASP.NET hit a home run by focusing like a laser beam on the developer experience.  Everyone put so much effort into building apps, questioning why each step was necessary, and refining the process.  It's great to see that they continue to follow that same discipline.  In the drill-down sessions, over and over again I saw that focus resulting in a near perfect experience for developers.   There are some other teams, like Avalon, that seem to have a similar religion and are obtaining similar results.   (Though Avalon desperately needs some tools support.   Notepad is fine for authoring XAML in demos, but I wouldn t want to build a real application this way).

 

Compared to ASP.NET, some other teams at Microsoft are still living in the Stone Age.   Those teams are still on a traditional cycle of building features, waiting for customers to build applications with those features, and then incorporating any feedback.   Beta is way too late to find out that the programming model is clumsy.   We shouldn t be shirking our design responsibilities like this.

 

Anyway, the 3rd keynote (from Rick Rashid & Microsoft Research) should have pulled it all together.  I think the clear message should have been something like:

 

Whidbey is coming next and has great developer features.  After that, Longhorn will arrive and will change everything.  Fortunately, Microsoft Research is looking 10+ years out, so you can be sure we will increasingly drive the whole industry.

 

This should have been an easy story to tell.  The fact is that MSR is a world class research institution.   Browse the Projects, Topics or People categories at http://research.microsoft.com and you ll see many name brand researchers like Butler Lampson and Jim Gray.   You will see tremendous breadth on the areas under research, from pure math and algorithms to speech, graphics and natural language.   There are even some esoterica like nanotech and quantum computing.   We should have used the number of published papers and other measurements to compare MSR with other research groups in the software industry, and with major research universities.   And then we should have shown some whiz-bang demos of about 2 minutes each.

 

Unfortunately, I think instead we sent a message that Interesting technology comes from Microsoft product groups, while MSR is largely irrelevant.   Yet nothing could be further from the truth.   Even if I restrict consideration to the CLR, MSR has had a big impact.   Generics is one of the biggest feature added to the CLR, C# or the base Frameworks in Whidbey.   This feature was added to the CLR by MSR team members, who now know at least as much about our code base as we do.   All the CLR s plans for significantly improved code quality and portable compilers depend on a joint venture between MSR and the compiler teams.   To my knowledge, MSR has used the CLR to experiment with fun things like transparent distribution, reorganizing objects based on locality, techniques for avoiding security stack crawls, interesting approaches to concurrency, and more.   SPOT (Smart Object Personal Technology) is a wonderful example of what MSR has done with the CLR s basic IL and metadata design, eventually leading to a very cool product.

 

In my opinion, Microsoft Research strikes a great balance between long term speculative experimentation and medium term product-oriented improvements.   I wish this had come across better at the PDC.

 

 

Trends

In the 6+ years I ve been at Microsoft, we ve had 4 PDCs.   This is the first one I ve actually attended, because I usually have overdue work items or too many bugs.   (I ve missed all 6 of our mandatory company meetings for the same reason).   So I really don t have a basis for comparison.

 

I guess I had expected to be beaten up about all the security issues of the last year, like Slammer and Blaster.  And I had expected developers to be interested in all aspects of security.   Instead, the only times the topic came up in my discussions is when I raised it.

 

However, some of my co-workers did see a distinct change in the level of interest in security.   For example, Sebastian Lange and Ivan Medvedev gave a talk on managed security to an audience of 700-800.   They reported a real upswing in awareness and knowledge on the part of all PDC attendees.

 

But consider a talk I attended on Application Compatibility.   At a time when most talks were overflowing into the hallways, this talk filled less than 50 seats of a 500 to 1000 seat meeting room.   I know that AppCompat is critically important to IT.   And it s a source of friction for the entire industry, since everyone is reluctant to upgrade for fear of breaking something.   But for most developers this is all so boring compared to the cool visual effects we can achieve with a few lines of XAML.

 

Despite a trend to increased interest in security on the part of developers, I suspect that security remains more of an IT operations concern than it does a developer concern.   And although the events of the last year or two have got more developers excited about security (including me!), I doubt that we will ever get developers excited about more mundane topics like versioning, admin or compatibility.   This latter stuff is dead boring.

 

That doesn t mean that the industry is doomed.   Instead, it means that modern applications must obtain strong versioning, compatibility and security guarantees by default rather than through deep developer involvement.   Fortunately, this is entirely in keeping with our long term goals for managed code.

 

With the first release of the CLR, the guarantees for managed applications were quite limited.   We guaranteed memory safety through an accurate garbage collector, type safety through verification, binding safety through strong names, and security through CAS.   (However, I think we would all agree that our current support for CAS still involves far too much developer effort and not enough automated guarantees.   Our security team has some great long-term ideas for addressing this.)

 

More importantly, we expressed programs through metadata and IL, so that we could expand the benefits of reasoning about these programs over time.   And we provided metadata extensibility in the form of Custom Attributes and Custom Signature Modifiers, so that others could add to the capabilities of the managed environment without depending on the CLR team s schedule.

 

FxCop ( http://www.gotdotnet.com/team/fxcop/ ) is an obvious example of how we can benefit from this ability to reason about programs.   All teams developing managed code at Microsoft are religious about incorporating this tool into their build process.   And since FxCop supports adding custom rules, we have added a large number of Microsoft-specific or product-specific checks.

 

 

Churn and Application Breakage

We also have some internal tools that allow us to compare different versions of assemblies so we can discover inadvertent breaking changes.   Frankly, these tools are still maturing.   Even in the Everett timeframe, they did a good job of blatant violations like the removal of a public method from a class or addition of a method to an interface.   But they didn t catch changes in serialization format, or changes to representation after marshaling through PInvoke or COM Interop.   As a result, we shipped some unintentional breaking changes in Everett , and until recently we were on a path to do so again in Whidbey.

 

As far as I know, these tools still don t track changes to CAS constructs, internal dependency graphs, thread-safety expectations, exception flow (including a static replacement for the checked exceptions feature), reliability contracts, or other aspects of execution.   Some of these checks will probably be added over time, perhaps by adding additional metadata to assemblies to reveal the developer s intentions and to make automated validation more tractable.   Other checks seem like research projects or are more appropriate for dynamic tools rather than static tools.   It s very encouraging to see teams inside and outside of Microsoft working on this.

 

I expect that all developers will eventually have access to these or similar tools from Microsoft or 3rd parties, which can be incorporated into our build processes the way FxCop has been.

 

Sometimes applications break when their dependencies are upgraded to new versions.   The classic example of this is Win95 applications which broke when the operating system was upgraded to WinXP.   Sometimes this is because the new versions have made breaking changes to APIs.   But sometimes it s because things are just different .   The classic case here is where a test case runs perfectly on a developer s machine, but fails intermittently in the test lab or out in the field.   The difference in environment might be obvious, like a single processor box vs. an 8-way.   Yet all too often it s something truly subtle, like a DLL relocating when it misses its preferred address, or the order of DllMain notifications on a DLL_THREAD_ATTACH.   In those cases, the change in environment is not the culprit.   Instead, the environmental change has finally revealed an underlying bug or fragility in the application that may have been lying dormant for years.

 

The managed environment eliminates a number of common fragilities, like the double-free of memory blocks or the use of a file handle or Event that has already been closed.   But it certainly doesn t guarantee that a multi-threaded program which appears to run correctly on a single processor will also execute without race conditions on a 32-way NUMA box.   The author of the program must use techniques like code reviews, proof tools and stress testing to ensure that his code is thread-safe.

 

The situation that worries me the most is when an application relies on accidents of current FX and CLR implementations.   These dependencies can be exceedingly subtle.

 

Here are some examples of breakage that we have encountered, listed in the random order they occur to me:

 

Between V1.1 and Whidbey, the implementation of reflection has undergone a major overhaul to improve access times and memory footprint.   One consequence is that the order of members returned from APIs like Type.GetMethods has changed.   The old order was never documented or guaranteed, but we ve found programs including our own tests which assumed stability here.

 

Structs and classes can specify Sequential, Explicit or AutoLayout.   In the case of AutoLayout, the CLR is free to place members in any order it chooses.   Except for alignment packing and the way we chunk our GC references, our layout here is currently quite predictable.   But in the future we hope to use access patterns to guide our layout for increased locality.   Any applications that predict the layout of AutoLayout structs and classes via unsafe coding techniques are at risk if we pursue that optimization.

 

Today, finalization occurs on a single Finalizer thread.   For scalability and robustness reasons, this is likely to change at some point.   Also, the GC already perturbs the order of finalization.   For instance, a collection can cause a generation boundary to intervene between two instances that are normally allocated consecutively.   Within a given process run, there will likely be some variation in finalization sequence.   But for two objects that are allocated consecutively by a single thread, there is a high likelihood of predictable ordering.   And we all know how easy it is to make assumptions about this sort of thing in our code.

 

In an earlier blog ( http://blogs.gotdotnet.com/cbrumme/PermaLink.aspx/e55664b4-6471-48b9-b360-f0fa27ab6cc0 ), I talked about some of the circumstances that impact when the JIT will stop reporting a reference to the GC.   These include inlining decisions, register allocation, and obvious differences like X86 vs. AMD64 vs. IA64.   Clearly we want the freedom to chase better code quality with JIT compilers and NGEN compilers in ways that will substantially change these factors.   Just yesterday an internal team reported a GC bug on multi-processor machines only that we quickly traced to confusion over lifetime rules and bad practice in the application.   One finalizable object was accessing some state in another finalizable object, in the expectation that the first object was live because it was the this argument of an active method call.

 

During V1.1 Beta testing, a customer complained about an application we had broken.   This application contained unmanaged code that reached back into its caller s stack to retrieve a GCHandle value at an offset that had been empirically discovered.   The unmanaged code then transitioned into managed and redeemed the supposed handle value for the object it referenced.   This usually worked, though it was clearly dependent on filthy implementation details.   Unfortunately, the System.EnterpriseServices pathways leading to the unmanaged application were somewhat variable.   Under certain circumstances, the stack was not what the unmanaged code predicted.   In V1, the value at the predicted spot was always a 0 and the redemption attempt failed cleanly.   In V1.1, the value at that stack location was an unrelated garbage value.   The consequence was a crash inside mscorwks.dll and Fail Fast termination of the process.

 

In V1 and V1.1, Object.GetHashCode() can be used to obtain a hashcode for any object.   However, our implementation happened to return values which tended to be small ascending integers.   Furthermore, these values happened to be unique across all reachable instances that were hashed in this manner.   In other words, these values were really object identifiers or OIDs.   Unfortunately, this implementation was a scalability killer for server applications running on multi-processor boxes.   So in Whidbey Object.GetHashCode() is now all we ever promised it would be: an integer with reasonable distribution but no uniqueness guarantees.   It s a great value for use in HashTables, but it s sure to disappoint some existing managed applications that relied on uniqueness.

 

In V1 and V1.1, all string literals are Interned as described in http://blogs.gotdotnet.com/cbrumme/PermaLink.aspx/7943b9be-cca9-41e1-8a83-3d7a0dbba270 .   I noted there that it is a mistake to depend on Interning across assemblies.   That s because the other assembly might start to compose a String value which it originally specified as a literal.   In Whidbey, assemblies can opt-in or opt-out of our Interning behavior.   This new freedom is motivated by a desire to support faster loading of assemblies (particularly assemblies that have been NGEN ed).   We ve seen some tests fail as a result.

 

I ve seen some external developers use a very fragile technique based on their examination of Rotor sources.   They navigate through one of System.Threading.Thread s private fields (DONT_USE_InternalThread) to an internal unmanaged CLR data structure that represents a running managed thread.   From there, they can pluck interesting information like the Thread::ThreadState bit field.   None of these data structures are part of our contract with managed applications and all of them are sure to change in future releases.   The only reason the ThreadState field is at a stable offset in our internal Thread struct today is that its frequency of access merits putting it near the top of the struct for good cache-line filling behavior.

 

Reflection allows highly privileged code to access private members of arbitrary types.   I am aware of dozens of teams inside and outside of Microsoft which rely on this mechanism for shipping products.   Some of these uses are entirely justified, like the way Serialization accesses private state that the type author marked as [Serializable()].   Many other uses rather questionable, and a few are truly heinous.   Taken to the extreme, this technique converts every internal implementation detail into a publicly exposed API, with the obvious consequences for evolution and application compatibility.

 

Assembly loading and type resolution can happen on very different schedules, depending on how your application is running.   We ve seen applications that misbehave based on NGEN vs. JIT, domain-neutral vs. per-domain loading, and the degree to which the JIT inlines methods.   For example, one application created an AppDomain and started running code in it.   That code subsequently modified the private application directory and then attempted to load an assembly from that directory.   Of course, because of inlining the JIT had already attempted to load the assembly with the original application directory and had failed.   The correct solution here is to disallow any changes to an AppDomain s application directory after code starts executing inside that AppDomain.   This directory should only be modifiable during the initialization of the AppDomain.

 

In prior blogs, I ve talked about unhandled exceptions and the CLR s default policy for dealing with them.   That policy is quite involved and hard to defend.   One aspect of it is that exceptions that escape the Finalizer thread or any ThreadPool threads are swallowed.   This keeps the process running, but it often leaves the application in an inconsistent state.   For example, locks may not have been released by the thread that took the exception, leading to subsequent hangs.   Now that the technology for reporting process crashes via Watson dumps is maturing, we really want to change our default policy for unhandled exceptions so that we Fail Fast with a process crash and a Watson upload.   However, any change to this policy will undoubtedly cause many existing applications to stop working.

 

Despite the flexibility of CAS, most applications still run with Full Trust.   I truly believe that this will change over time.   For example, in Whidbey we will have ClickOnce permission elevation and in Longhorn we will deliver the Secure Execution Environment or SEE.   Both of these features were discussed at the PDC.   When we have substantial code executing in partial trust, we re going to see some unfortunate surprises.   For example, consider message pumping.   If a Single Threaded Apartment thread has some partial trust code on its stack when it blocks (e.g. Monitor.Enter on a contentious monitor), then we will pump messages on that thread while it is blocked.   If the dispatching of a message requires a stack walk to satisfy a security Full Demand, then the partially trusted code further back on the stack may trigger a security exception.   Another example is related to class constructors.   As you probably know, .cctor methods execute on the first thread that needs access to a class in a particular AppDomain.   If the .cctor must satisfy a security demand, the success of the .cctor now depends on the accident of what other code is active on the thread s stack.   Along the same lines, the .cctor method may fail if there is insufficient stack space left on the thread that happens to execute it.   These are all well understood problems and we have plans for fixing them.   But the fixes will necessarily change observable behavior for a class of applications.

 

I could fill a lot more pages with this sort of list.   And our platform is still in its infancy.   Anyway, one clear message from all this is that things will change and then applications will break.

 

But can we categorize these failures and make some sense of it all?   For each failure, we need to decide whether the platform or the application is at fault for each case.   And then we need to identify some rules or mechanisms that can avoid these failures or mitigate them.   I see four categories.

 

 

Category 1:   The application explicitly screws itself

The easiest category to dispense with is the one where a developer intentionally and explicitly takes advantage of a behavior that s/he knows is guaranteed to change.   A perfect example of this is #8 above.   Anyone who navigates through private members to unmanaged internal data structures is setting himself up for problems in future versions.   The responsibility (or irresponsibility in this case) lies with the application.   In my opinion, the platform should have no obligations.

 

But consider #5 above.   It s clearly in this same category, and yet opinions on our larger team were quite divided on whether we needed to fix the problem.   I spoke to a number of people who definitely understood the incredible difficulty of keeping this application running on new versions of the CLR and EnterpriseServices.   But they consistently argued that the operating system has traditionally held itself to this sort of compatibility bar, that this is one of the reasons for Windows ubiquity, and that the managed platform must similarly step up.

 

Also, we have to be realistic here.   If a customer issue like this involves one of our largest accounts, or has been escalated through a very senior executive (a surprising number seem to reach Steve Ballmer), then we re going to pull out all the stops on a fix or a temporary workaround.

 

In many cases, our side-by-side support is an adequate and simple solution.   Customers can continue to run problematic applications on their old bits, even though a new version of these bits has also been installed.   For instance, the config file for an application can specify an old version of the CLR.   Or binding redirects could roll back a specific assembly.   But this technique falls apart if the application is actually an add-in that is dynamically loaded into a process like Internet Explorer or SQL Server.   It s unrealistic to lock back the entire managed stack inside Internet Explorer (possibly preventing newer applications that use generics or other Whidbey features from running there), just so older questionable applications can keep running.

 

It s possible that we could provide lock back at finer-grained scopes than the process scope in future versions of the CLR.   Indeed, this is one of the areas being explored by our versioning team.

 

Anyway, if we were under sufficient pressure I could imagine us building a one-time QFE (patch) for an important customer in this category, to help them transition to a newer version and more maintainable programming techniques.   But if you aren t a Fortune 100 company or Steve Ballmer s brother-in-law, I personally hope we would be allowed to ignore any of your applications that are in this category.

 

 

Category 2:   The platform explicitly screws the application

I would put #6, #7 and #11 above in a separate category.   Here, the platform team wants to make an intentional breaking change for some valid reason like performance or reliability.   In fact, #10 above is a very special case of this category.   In #10, we would like to break compatibility in Whidbey so that we can provide a stronger model that can avoid subsequent compatibility breakage.   It s a paradoxical notion that we should break compatibility now so we can increase future compatibility, but the approach really is sensible.

 

Anyway, if the platform makes a conscious decision to break compatibility to achieve some greater goal, then the platform is responsible for mitigation.   At a minimum, we should provide a way for broken applications to obtain the old behavior, at least for some transition period.   We have a few choices in how to do this, and we re likely to pick one based on engineering feasibility, the impact of a breakage, the likelihood of a breakage, and schedule pressure:

 

• Rely on side-by-side and explicit administrator intervention.   In other words, the admin notices the application no longer works after a platform upgrade, so s/he authors a config file to lock the application back to the old platform bits.   This approach is problematic because it requires a human being to diagnose a problem and intervene.   Also, it has the problems I already mentioned with using side-by-side on processes like Internet Explorer or SQL Server.

 

• For some changes, it shouldn t be necessary to lock back the entire platform stack.   Indeed, for many changes the platform could simultaneously support the old and new behaviors.   If we change our default policy for dealing with unhandled exceptions, we should definitely retain the old policy& at least for one release cycle.

 

• If we expect a significant percentage of applications to break when we make a change, we should consider an opt-in policy for that change.   This eliminates the breakage and the human involvement in a fix.   In the case of String Interning, we require each assembly to opt-in to the new non-intern ed behavior.

 

• In some cases, we ve toyed with the idea of having the opt-in be implicit with a recompile.   The logic here is that when an application is recompiled against new platform bits, it is presumably also tested against those new bits.   The developer, rather than the admin, will deal with any compatibility issues that arise.   We re well set up for this, since managed assemblies contain metadata giving us the version numbers of the CLR and the dependent assemblies they were compiled against.   Unfortunately, execution models like ASP.NET work against us here.   As you know, ASP.NET pages are recompiled automatically by the system based on dependency changes.   There is no developer available when this happens.

 

 

Windows Shimming

Before we look at the next two categories of AppCompat failure, it s worth taking a very quick look at one of the techniques that the operating system has traditionally used to deal with these issues.   Windows has an AppCompat team which has built something called a shimming engine.

 

Consider what happened when the company tried to move consumers from Win95/Win98/WinMe over to WinXP.   They discovered a large number of programs which used the GetVersion or the preferred GetVersionEx APIs in such a way that the programs refused to run on NT-based systems.

 

In fact, WinXP did such a good job of achieving compatibility with Win9X systems that in many cases the only reason the application wouldn t run was the version check that the program made at start up.   The fix was to change GetVersion or GetVersionEx to lie about the version number of the current operating system.   Of course, this lie should only be told to programs that need the lie in order to work properly.

 

I ve heard that this shim which lies about the operating system version is the most commonly applied shim we have.   As I understand it, at process launch the shimming engine tries to match the current process against any entries in its database.   This match could be based on the name, timestamp or size of the EXE, or of other files found relative to that EXE like a BMP for the splash screen in a subdirectory.   The entry in the database lists any shims that should be applied to the process, like the one that lies about the version.   The shimming engine typically bashes the IAT (import address table) of a DLL or EXE in the process, so that its imports are bound to the shim rather than to the normal export (e.g. Kernel32!GetVersionEx).   In addition, the shimming engine has other tricks it perform less frequently, like wrapping COM objects up with intercepting proxies.

 

It s easy to see how this infrastructure can allow applications for Win95 to execute on WinXP.   However, this approach has some drawbacks.   First, it s rather labor-intensive.   Someone has to debug the application, determine which shims will fix it, and then craft some suitable matching criteria that will identify this application in the shimming database.   If an appropriate shim doesn t already exist, it must be built.

 

In the best case, the application has some commercial significance and Microsoft has done all the testing and shimming.   But if the application is a line of business application that was created in a particular company s IT department, Microsoft will never get its hands on it.   I ve heard we re now allowing sophisticated IT departments to set up their own shimming databases for their own applications but this only allows them to apply existing shims to their applications.

 

And from my skewed point of view the worst part of all this is that it really won t work for managed applications.   For managed apps, binding is achieved through strong names, Fusion and the CLR loader.   Binding is practically never achieved through DLL imports.

 

So it s instructive to look at some of the techniques the operating system has traditionally used.   But those techniques don t necessarily apply directly to our new problems.

 

Anyway, back to our categories&

 

 

Category 3:   The application accidentally screws itself

Category 4:   The platform accidentally screws the application

Frankly, I m having trouble distinguishing these two cases.   They are clearly distinct categories, but it s a judgment call where to draw the line.   The common theme here is that the platform has accidentally exposed some consistent behavior which is not actually a guaranteed contract.   The application implicitly acquires a dependency on this consistent behavior, and is broken when the consistency is later lost.

 

In the nirvana of some future fully managed execution environment, the platform and tools would never expose consistent behavior unless it was part of a guarantee.   Let s look at some examples and see how practical this is.

 

In example #1 above, reflection used to deliver members in a stable order.   In Whidbey, that order changes.   In hindsight, there s a simple solution here.   V1 of the product could have contained a testing mode that randomized the returned order.   This would have exposed the developer to our actual guarantees, rather than to a stronger accidental consistency.   Within the CLR, we ve used this sort of technique to force us down code paths that otherwise wouldn t be exercised.   For example, developers on the CLR team all use NT-based (Unicode) systems and avoid Win9X (Ansi) systems.   So our Win9X Ansi/Unicode wrappers wouldn t typically get tested by developers.   To address this, our checked/debug CLR build originally considered the day of the week and used Ansi code paths every other day.   But imagine chasing a bug at 11:55 PM .   When the bug magically disappears on your next run at 1:03 AM the next morning, you are far too frazzled to think clearly about the reason.   Today, we tend to use low order bits in the size of an image like mscorwks.dll or the assembly being tested, so our randomization is now more friendly to testing.

 

In example #2 above, you could imagine a similar perturbation on our AutoLayout algorithms when executing a debug version of an application, or when launched from inside a tool like Visual Studio.

 

For example #4, the CLR already has internal stress modes that force different and aggressive GC schedules.   These can guarantee compaction to increase the likelihood of detecting stale references.   They can perform extensive checks of the integrity of the heap, to ensure that the write barrier and other mechanisms are effective.   And they can ensure that every instruction of JITted managed code that can synchronize with the GC will synchronize with the GC.   I suspect that these modes would do a partial job of eradicating assumptions about lifetimes reported by the JIT.   However, we will remain exposed to significantly different code generators (like Rotor s FJIT) or execution on significantly different architectures (like CPUs with dramatically more registers).

 

In contrast with the above difficulty, it s easy to imagine adding a new GC stress mode that perturbs the finalization queues, to uncover any hidden assumptions about finalization order.   This would address example #3.

 

 

Customer Debug Probes, AppVerifier and other tools

It turns out that the CLR already has a partial mechanism for enabling perturbation during testing and removing it on deployed applications.   This mechanism is the Customer Debug Probes feature that we shipped in V1.1.   Adam Nathan s excellent blog site has a series of articles on CDPs, which are collected together at http://blogs.gotdotnet.com/anathan/CategoryView.aspx/Debugging .   The original goal of CDPs was to counteract the black box nature of debugging certain failures of managed applications, like corruptions of the GC heap or crashes due to incorrect marshaling directives.   These probes can automatically diagnose common application errors, like failing to keep a marshaled delegate rooted so it won t be collected.   This approach is so much easier than wading through dynamically generated code without symbols, because we tell you exactly where your bugs are.   But we re now realizing that we can also use CDPs to increase the future compatibility of managed applications if we can perturb current behavior that is likely to change in the future.

Unfortunately, example #6 from above reveals a major drawback with the technique of perturbation.   When we built the original implementation of Object.GetHashCode, we simply never considered the difference between what we wanted to guarantee (hashing) and what we actually delivered (OIDs).   In hindsight, it is obvious.   But I m not convinced that we aren t falling into similar traps in our new features.   We might be a little smarter than we were five years ago, but only a little.

 

Example #10 worries me for similar reasons.   I just don t think we were smart enough to predict that changing the binding configuration of an AppDomain after starting to execute code in that AppDomain would be so fragile.   When a developer delivers a feature, s/he needs to consider security, thread-safety, programming model, key invariants of the code base like GC reporting, correctness, and so many other aspects.   It would be amazing if a developer consistently nailed each of these aspects for every new feature.   We re kidding ourselves if we think that evolution and unintentional implicit contracts will get adequate developer attention on every new feature.

 

Even if we had perfect foresight and sufficient resources to add perturbation for all operations, we would still have a major problem.   We can t necessarily rely on 3rd party developers to test their applications with perturbation enabled.   Consider the unmanaged AppVerifier experience.

 

The operating system has traditionally offered a dynamic testing tool called AppVerifier which can diagnose many common unmanaged application bugs.   For example, thanks to uploads of Watson process dumps from the field, most unmanaged application crashes can now be attributed to incorrect usage of dynamically allocated memory.   Yet AppVerifier can use techniques like placing each allocation in its own page or leaving pages unmapped after release, to deterministically catch overruns, double frees, and reads or writes of freed memory.

 

In other words, there is hard evidence that if every unmanaged application had just used the memory checking support of AppVerifier, then two out of every three application crashes would be eliminated.   Clearly this didn t happen.

 

Of course, AppVerifier can diagnose far more than just memory problems.   And it s very easy and convenient to use.

 

Since testing with AppVerifier is part of the Windows Logo compliance program, you would expect that it s used fairly rigorously by ISVs.   And, given its utility, you would expect that most IT organizations would use this tool for their internal applications.   Unfortunately, this isn t the case.   Many applications submitted for the Windows Logo actually fail to launch under AppVerifier.   In other words, they violate at least one of the rules before they finish initializing.

 

The Windows AppCompat team recognizes that proactive tools like AppVerifier are so much better than reactive mitigation like shimming broken applications out in the field.   That s why they made the AppVerifier tool a major focus of their poorly attended Application Compatibility talk that I sat in on at the PDC.   (Aha!   I really was going somewhere with all this.)

 

There s got to be a reason why developers don t use such a valuable tool.   In my opinion, the reason is that AppVerifier is not integrated into Visual Studio.   If the Debug Properties in VS allowed you to enable AppVerifier and CDP checks, we would have much better uptake.   And if an integrated project system and test system could monitor code coverage numbers, and suggest particular test runs with particular probes enabled, we would be approaching nirvana.

 

 

Winding Down

Looking at development within Microsoft, one trend is very clear:   Automated tools and processes are a wonderful supplement for human developers.   Whether we re talking about security, reliability, performance, application compatibility or any other measure of software quality, we re now seeing that static and dynamic analysis tools can give us guarantees that we will never obtain from human beings.   Bill Gates touched on this during his PDC keynote, when he described our new tools for statically verifying device driver correctness, for some definition of correctness.

 

This trend was very clear to me during the weeks I spent on the DCOM / RPCSS security fire drill.   I spent days looking at some clever marshaling code, eventually satisfying myself that it worked perfectly.   Then someone else wrote an automated attacker and discovered real flaws in just a few hours.   Other architects and senior developers scrutinized different sections of the code.   Then some researchers from MSR who are focused on automatic program validation ran their latest tools over the same code and gave us step-by-step execution models that led up to crashes.   Towards the end of the fire drill, a virtuous cycle was established.   The code reviewers noticed new categories of vulnerabilities.   Then the researchers tried to evolve their tools to detect those vulnerabilities.   Aspects of this process were very raw, so the tools sometimes produced a great deal of noise in the form of false positives.   But it s clear that we were getting real value from Day One and the future potential here is enormous.

 

One question that always comes up, when we talk about adding significant value to Visual Studio through additional tools, is whether Microsoft should give away these tools.   It s a contentious issue, and I find myself going backwards and forwards on it.   One school of thought says that we should give away tools to promote the platform and improve all the programs in the Windows ecology.   In the case of tools that make our customers applications more secure or more resilient to future changes in the platform, this is a compelling argument.   Another school of thought says that Visual Studio is a profit center like any other part of the company, and it needs the freedom to charge what the market will bear.

 

Given that my job is building a platform, you might expect me to favor giving away Visual Studio.   But I actually think the profit motive is a powerful mechanism for making our tools competitive.   If Visual Studio doesn t have P&L responsibility, their offering will deteriorate over time.   The best way to know whether they ve done all they can to make the best tools possible, is to measure how much their customers are willing to pay.   I want Borland to compete with Microsoft on building the best tools at the best price, and I want to be able to measure the results of that competition through revenue and market penetration.

 

In all this, I have avoided really talking about the issues of versioning.   Of course, versioning and application compatibility are enormously intertwined.   Applications break for many reasons, but the typical reason is that one component is now binding to a new version of another component.   We have a whole team of architects, gathered from around the company, who have been meeting regularly for about a year to grapple with the problems of a complete managed versioning story.   Unlike managed AppCompat, the intellectual investment in managed versioning has been enormous.

 

Anyway, Application Compatibility remains a relatively contentious subject over here.   There s no question that it s a hugely important topic which will have a big impact on the longevity of our platform.   But we are still trying to develop techniques for achieving compatibility that will be more successful than what Windows has done in the past, without limiting our ability to innovate on what is still a very young execution engine and set of frameworks.   I have deliberately avoided talking about what some of those techniques might be, in part because our story remains incomplete.

 

Also, we won t realize how badly AppCompat will bite us until we can see a lot of deployed applications that are breaking as we upgrade the platform.   At that point, it s easier to justify throwing more resources at the problem.   But by then the genie is out of the bottle& the deployed applications will already depend on brittle accidents of implementation, so recovery will be painfully breaking.   In a world where we are always under intense resource and schedule pressure, the needs of AppCompat must be balanced against performance, security, developer productivity, reliability, innovation and all the other must haves .

 

You know, I really do want to talk about Hosting.   It is a truly fascinating subject.   I m much more comfortable talking about non-preemptive fiber scheduling than I am talking about uninteresting topics like implicit contracts and compatibility trends.

 

But Hosting is going to have to wait at least a few more weeks.