Garbage Collection and Performance
This topic describes issues related to garbage collection and memory usage. It addresses issues that pertain to the managed heap and explains how to minimize the effect of garbage collection on your applications. Each issue has links to procedures that you can use to investigate problems.
Performance Analysis Tools
The following sections describe the tools that are available for investigating memory usage and garbage collection issues. The procedures provided later in this topic refer to these tools.
Memory Performance Counters
You can use performance counters to gather performance data. For instructions, see Runtime Profiling. The .NET CLR Memory category of performance counters, as described in Performance Counters in the .NET Framework, provides information about the garbage collector.
Debugging with SOS
You can use the Windows Debugger (WinDbg) to inspect objects on the managed heap.
To install WinDbg, install Debugging Tools for Windows from the Download Debugging Tools for Windows page.
Garbage Collection ETW Events
Event tracing for Windows (ETW) is a tracing system that supplements the profiling and debugging support provided by the .NET Framework. Starting with the .NET Framework 4, garbage collection ETW events capture useful information for analyzing the managed heap from a statistical point of view. For example, the
GCStart_V1 event, which is raised when a garbage collection is about to occur, provides the following information:
Which generation of objects is being collected.
What triggered the garbage collection.
Type of garbage collection (concurrent or not concurrent).
ETW event logging is efficient and will not mask any performance problems associated with garbage collection. A process can provide its own events in conjunction with ETW events. When logged, both the application's events and the garbage collection events can be correlated to determine how and when heap problems occur. For example, a server application could provide events at the start and end of a client request.
The Profiling API
The common language runtime (CLR) profiling interfaces provide detailed information about the objects that were affected during garbage collection. A profiler can be notified when a garbage collection starts and ends. It can provide reports about the objects on the managed heap, including an identification of objects in each generation. For more information, see Profiling Overview.
Profilers can provide comprehensive information. However, complex profilers can potentially modify an application's behavior.
Application Domain Resource Monitoring
Starting with the .NET Framework 4, Application domain resource monitoring (ARM) enables hosts to monitor CPU and memory usage by application domain. For more information, see Application Domain Resource Monitoring.
Troubleshooting Performance Issues
The first step is to determine whether the issue is actually garbage collection. If you determine that it is, select from the following list to troubleshoot the problem.
Issue: An Out-of-Memory Exception Is Thrown
There are two legitimate cases for a managed OutOfMemoryException to be thrown:
Running out of virtual memory.
The garbage collector allocates memory from the system in segments of a pre-determined size. If an allocation requires an additional segment, but there is no contiguous free block left in the process's virtual memory space, the allocation for the managed heap will fail.
Not having enough physical memory to allocate.
|Determine whether the out-of-memory exception is managed.
Determine how much virtual memory can be reserved.
Determine whether there is enough physical memory.
If you determine that the exception is not legitimate, contact Microsoft Customer Service and Support with the following information:
The stack with the managed out-of-memory exception.
Full memory dump.
Data that proves that it is not a legitimate out-of-memory exception, including data that shows that virtual or physical memory is not an issue.
Issue: The Process Uses Too Much Memory
A common assumption is that the memory usage display on the Performance tab of Windows Task Manager can indicate when too much memory is being used. However, that display pertains to the working set; it does not provide information about virtual memory usage.
If you determine that the issue is caused by the managed heap, you must measure the managed heap over time to determine any patterns.
If you determine that the problem is not caused by the managed heap, you must use native debugging.
Issue: The Garbage Collector Does Not Reclaim Objects Fast Enough
When it appears as if objects are not being reclaimed as expected for garbage collection, you must determine if there are any strong references to those objects.
You may also encounter this issue if there has been no garbage collection for the generation that contains a dead object, which indicates that the finalizer for the dead object has not been run. For example, this is possible when you are running a single-threaded apartment (STA) application and the thread that services the finalizer queue cannot call into it.
|Check references to objects.
Determine whether a finalizer has been run.
Determine whether there are objects waiting to be finalized.
Issue: The Managed Heap Is Too fragmented
The fragmentation level is calculated as the ratio of free space over the total allocated memory for the generation. For generation 2, an acceptable level of fragmentation is no more than 20%. Because generation 2 can get very big, the ratio of fragmentation is more important than the absolute value.
Having lots of free space in generation 0 is not a problem because this is the generation where new objects are allocated.
Fragmentation always occurs in the large object heap because it is not compacted. Free objects that are adjacent are naturally collapsed into a single space to satisfy large object allocation requests.
Fragmentation can become a problem in generation 1 and generation 2. If these generations have a large amount of free space after a garbage collection, an application's object usage may need modification, and you should consider re-evaluating the lifetime of long-term objects.
Excessive pinning of objects can increase fragmentation. If fragmentation is high, too many objects could have been pinned.
If fragmentation of virtual memory is preventing the garbage collector from adding segments, the causes could be one of the following:
Frequent loading and unloading of many small assemblies.
Holding too many references to COM objects when interoperating with unmanaged code.
Creation of large transient objects, which causes the large object heap to allocate and free heap segments frequently.
When hosting the CLR, an application can request that the garbage collector retain its segments. This reduces the frequency of segment allocations. This is accomplished by using the STARTUP_HOARD_GC_VM flag in the STARTUP_FLAGS Enumeration.
|Determine the amount of free space in the managed heap.
Determine the number of pinned objects.
If you think that there is no legitimate cause for the fragmentation, contact Microsoft Customer Service and Support.
Issue: Garbage Collection Pauses Are Too Long
Garbage collection operates in soft real time, so an application must be able to tolerate some pauses. A criterion for soft real time is that 95% of the operations must finish on time.
In concurrent garbage collection, managed threads are allowed to run during a collection, which means that pauses are very minimal.
Ephemeral garbage collections (generations 0 and 1) last only a few milliseconds, so decreasing pauses is usually not feasible. However, you can decrease the pauses in generation 2 collections by changing the pattern of allocation requests by an application.
Another, more accurate, method is to use garbage collection ETW events. You can find the timings for collections by adding the time stamp differences for a sequence of events. The whole collection sequence includes suspension of the execution engine, the garbage collection itself, and the resumption of the execution engine.
You can use Garbage Collection Notifications to determine whether a server is about to have a generation 2 collection, and whether rerouting requests to another server could ease any problems with pauses.
|Determine the length of time in a garbage collection.
Determine what caused a garbage collection.
Issue: Generation 0 Is Too Big
Generation 0 is likely to have a larger number of objects on a 64-bit system, especially when you use server garbage collection instead of workstation garbage collection. This is because the threshold to trigger a generation 0 garbage collection is higher in these environments, and generation 0 collections can get much bigger. Performance is improved when an application allocates more memory before a garbage collection is triggered.
Issue: CPU Usage During a Garbage Collection Is Too High
CPU usage will be high during a garbage collection. If a significant amount of process time is spent in a garbage collection, the number of collections is too frequent or the collection is lasting too long. An increased allocation rate of objects on the managed heap causes garbage collection to occur more frequently. Decreasing the allocation rate reduces the frequency of garbage collections.
You can monitor allocation rates by using the
Allocated Bytes/second performance counter. For more information, see Performance Counters in the .NET Framework.
The duration of a collection is primarily a factor of the number of objects that survive after allocation. The garbage collector must go through a large amount of memory if many objects remain to be collected. The work to compact the survivors is time-consuming. To determine how many objects were handled during a collection, set a breakpoint in the debugger at the end of a garbage collection for a specified generation.
|Determine if high CPU usage is caused by garbage collection.
Set a breakpoint at the end of garbage collection.
This section describes guidelines that you should consider as you begin your investigations.
Workstation or Server Garbage Collection
Determine if you are using the correct type of garbage collection. If your application uses multiple threads and object instances, use server garbage collection instead of workstation garbage collection. Server garbage collection operates on multiple threads, whereas workstation garbage collection requires multiple instances of an application to run their own garbage collection threads and compete for CPU time.
An application that has a low load and that performs tasks infrequently in the background, such as a service, could use workstation garbage collection with concurrent garbage collection disabled.
When to Measure the Managed Heap Size
Unless you are using a profiler, you will have to establish a consistent measuring pattern to effectively diagnose performance issues. Consider the following points to establish a schedule:
If you measure after a generation 2 garbage collection, the entire managed heap will be free of garbage (dead objects).
If you measure immediately after a generation 0 garbage collection, the objects in generations 1 and 2 will not be collected yet.
If you measure immediately before a garbage collection, you will measure as much allocation as possible before the garbage collection starts.
Measuring during a garbage collection is problematic, because the garbage collector data structures are not in a valid state for traversal and may not be able to give you the complete results. This is by design.
When you are using workstation garbage collection with concurrent garbage collection, the reclaimed objects are not compacted, so the heap size can be the same or larger (fragmentation can make it appear to be larger).
Concurrent garbage collection on generation 2 is delayed when the physical memory load is too high.
The following procedure describes how to set a breakpoint so that you can measure the managed heap.
To set a breakpoint at the end of garbage collection
In WinDbg with the SOS debugger extension loaded, type the following command:
bp mscorwks!WKS::GCHeap::RestartEE "j (dwo(mscorwks!WKS::GCHeap::GcCondemnedGeneration)==2) 'kb';'g'"
where GcCondemnedGeneration is set to the desired generation. This command requires private symbols.
This command forces a break if RestartEE is executed after generation 2 objects have been reclaimed for garbage collection.
In server garbage collection, only one thread calls RestartEE, so the breakpoint will occur only once during a generation 2 garbage collection.
Performance Check Procedures
This section describes the following procedures to isolate the cause of your performance issue:
To determine whether the problem is caused by garbage collection
Examine the following two memory performance counters:
% Time in GC. Displays the percentage of elapsed time that was spent performing a garbage collection after the last garbage collection cycle. Use this counter to determine whether the garbage collector is spending too much time to make managed heap space available. If the time spent in garbage collection is relatively low, that could indicate a resource problem outside the managed heap. This counter may not be accurate when concurrent or background garbage collection is involved.
# Total committed Bytes. Displays the amount of virtual memory currently committed by the garbage collector. Use this counter to determine whether the memory consumed by the garbage collector is an excessive portion of the memory that your application uses.
Most of the memory performance counters are updated at the end of each garbage collection. Therefore, they may not reflect the current conditions that you want information about.
To determine whether the out-of-memory exception is managed
In the WinDbg or Visual Studio debugger with the SOS debugger extension loaded, type the print exception (pe) command:
If the exception is managed, OutOfMemoryException is displayed as the exception type, as shown in the following example.
Exception object: 39594518 Exception type: System.OutOfMemoryException Message: <none> InnerException: <none> StackTrace (generated):
If the output does not specify an exception, you have to determine which thread the out-of-memory exception is from. Type the following command in the debugger to show all the threads with their call stacks:
The thread with the stack that has exception calls is indicated by the
RaiseTheExceptionargument. This is the managed exception object.
28adfb44 7923918f 5b61f2b4 00000000 5b61f2b4 mscorwks!RaiseTheException+0xa0
You can use the following command to dump nested exceptions.
If you do not find any exceptions, the out-of-memory exception originated from unmanaged code.
To determine how much virtual memory can be reserved
In WinDbg with the SOS debugger extension loaded, type the following command to get the largest free region:
The largest free region is displayed as shown in the following output.
Largest free region: Base 54000000 - Size 0003A980
In this example, the size of the largest free region is approximately 24000 KB (3A980 in hexadecimal). This region is much smaller than what the garbage collector needs for a segment.
Use the vmstat command:
The largest free region is the largest value in the MAXIMUM column, as shown in the following output.
TYPE MINIMUM MAXIMUM AVERAGE BLK COUNT TOTAL ~~~~ ~~~~~~~ ~~~~~~~ ~~~~~~~ ~~~~~~~~~~ ~~~~ Free: Small 8K 64K 46K 36 1,671K Medium 80K 864K 349K 3 1,047K Large 1,384K 1,278,848K 151,834K 12 1,822,015K Summary 8K 1,278,848K 35,779K 51 1,824,735K
To determine whether there is enough physical memory
Start Windows Task Manager.
On the Performance tab, look at the committed value. (In Windows 7, look at Commit (KB) in the System group.)
If the Total is close to the Limit, you are running low on physical memory.
To determine how much memory the managed heap is committing
# Total committed bytesmemory performance counter to get the number of bytes that the managed heap is committing. The garbage collector commits chunks on a segment as needed, not all at the same time.
Do not use the
# Bytes in all Heapsperformance counter, because it does not represent actual memory usage by the managed heap. The size of a generation is included in this value and is actually its threshold size, that is, the size that induces a garbage collection if the generation is filled with objects. Therefore, this value is usually zero.
To determine how much memory the managed heap reserves
# Total reserved bytesmemory performance counter.
The garbage collector reserves memory in segments, and you can determine where a segment starts by using the eeheap command.
Although you can determine the amount of memory the garbage collector allocates for each segment, segment size is implementation-specific and is subject to change at any time, including in periodic updates. Your app should never make assumptions about or depend on a particular segment size, nor should it attempt to configure the amount of memory available for segment allocations.
In the WinDbg or Visual Studio debugger with the SOS debugger extension loaded, type the following command:
The result is as follows.
Number of GC Heaps: 2 ------------------------------ Heap 0 (002db550) generation 0 starts at 0x02abe29c generation 1 starts at 0x02abdd08 generation 2 starts at 0x02ab0038 ephemeral segment allocation context: none segment begin allocated size 02ab0000 02ab0038 02aceff4 0x0001efbc(126908) Large object heap starts at 0x0aab0038 segment begin allocated size 0aab0000 0aab0038 0aab2278 0x00002240(8768) Heap Size 0x211fc(135676) ------------------------------ Heap 1 (002dc958) generation 0 starts at 0x06ab1bd8 generation 1 starts at 0x06ab1bcc generation 2 starts at 0x06ab0038 ephemeral segment allocation context: none segment begin allocated size 06ab0000 06ab0038 06ab3be4 0x00003bac(15276) Large object heap starts at 0x0cab0038 segment begin allocated size 0cab0000 0cab0038 0cab0048 0x00000010(16) Heap Size 0x3bbc(15292) ------------------------------ GC Heap Size 0x24db8(150968)
The addresses indicated by "segment" are the starting addresses of the segments.
To determine large objects in generation 2
In the WinDbg or Visual Studio debugger with the SOS debugger extension loaded, type the following command:
If the managed heap is big, dumpheap may take a while to finish.
You can start analyzing from the last few lines of the output, because they list the objects that use the most space. For example:
2c6108d4 173712 14591808 DevExpress.XtraGrid.Views.Grid.ViewInfo.GridCellInfo 00155f80 533 15216804 Free 7a747c78 791070 15821400 System.Collections.Specialized.ListDictionary+DictionaryNode 7a747bac 700930 19626040 System.Collections.Specialized.ListDictionary 2c64e36c 78644 20762016 DevExpress.XtraEditors.ViewInfo.TextEditViewInfo 79124228 121143 29064120 System.Object 035f0ee4 81626 35588936 Toolkit.TlkOrder 00fcae40 6193 44911636 WaveBasedStrategy.Tick_Snap 791242ec 40182 90664128 System.Collections.Hashtable+bucket 790fa3e0 3154024 137881448 System.String Total 8454945 objects
The last object listed is a string and occupies the most space. You can examine your application to see how your string objects can be optimized. To see strings that are between 150 and 200 bytes, type the following:
!dumpheap -type System.String -min 150 -max 200
An example of the results is as follows.
Address MT Size Gen 1875d2c0 790fa3e0 152 2 System.String HighlightNullStyle_Blotter_PendingOrder-11_Blotter_PendingOrder-11 …
Using an integer instead of a string for an ID can be more efficient. If the same string is being repeated thousands of times, consider string interning. For more information about string interning, see the reference topic for the String.Intern method.
To determine references to objects
In WinDbg with the SOS debugger extension loaded, type the following command to list references to objects:
To determine the references for a specific object, include the address:
Roots found on stacks may be false positives. For more information, use the command
ebx:Root:19011c5c(System.Windows.Forms.Application+ThreadContext)-> 19010b78(DemoApp.FormDemoApp)-> 19011158(System.Windows.Forms.PropertyStore)-> … [omitted] 1c3745ec(System.Data.DataTable)-> 1c3747a8(System.Data.DataColumnCollection)-> 1c3747f8(System.Collections.Hashtable)-> 1c376590(System.Collections.Hashtable+bucket)-> 1c376c98(System.Data.DataColumn)-> 1c37b270(System.Data.Common.DoubleStorage)-> 1c37b2ac(System.Double) Scan Thread 0 OSTHread 99c Scan Thread 6 OSTHread 484
The gcroot command can take a long time to finish. Any object that is not reclaimed by garbage collection is a live object. This means that some root is directly or indirectly holding onto the object, so gcroot should return path information to the object. You should examine the graphs returned and see why these objects are still referenced.
To determine whether a finalizer has been run
Run a test program that contains the following code:
GC.Collect(); GC.WaitForPendingFinalizers(); GC.Collect();
If the test resolves the problem, this means that the garbage collector was not reclaiming objects, because the finalizers for those objects had been suspended. The GC.WaitForPendingFinalizers method enables the finalizers to complete their tasks, and fixes the problem.
To determine whether there are objects waiting to be finalized
In the WinDbg or Visual Studio debugger with the SOS debugger extension loaded, type the following command:
Look at the number of objects that are ready for finalization. If the number is high, you must examine why these finalizers cannot progress at all or cannot progress fast enough.
To get an output of threads, type the following command:
This command provides output such as the following.
OSID Special thread type 2 cd0 DbgHelper 3 c18 Finalizer 4 df0 GC SuspendEE
The finalizer thread indicates which finalizer, if any, is currently being run. When a finalizer thread is not running any finalizers, it is waiting for an event to tell it to do its work. Most of the time you will see the finalizer thread in this state because it runs at THREAD_HIGHEST_PRIORITY and is supposed to finish running finalizers, if any, very quickly.
To determine the amount of free space in the managed heap
!dumpheap -type Free -stat
This command displays the total size of all the free objects on the managed heap, as shown in the following example.
total 230 objects Statistics: MT Count TotalSize Class Name 00152b18 230 40958584 Free Total 230 objects
To determine the free space in generation 0, type the following command for memory consumption information by generation:
This command displays output similar to the following. The last line shows the ephemeral segment.
Heap 0 (0015ad08) generation 0 starts at 0x49521f8c generation 1 starts at 0x494d7f64 generation 2 starts at 0x007f0038 ephemeral segment allocation context: none segment begin allocated size 00178250 7a80d84c 7a82f1cc 0x00021980(137600) 00161918 78c50e40 78c7056c 0x0001f72c(128812) 007f0000 007f0038 047eed28 0x03ffecf0(67103984) 3a120000 3a120038 3a3e84f8 0x002c84c0(2917568) 46120000 46120038 49e05d04 0x03ce5ccc(63855820)
Calculate the space used by generation 0:
The result is as follows. Generation 0 is approximately 9 MB.
Evaluate expression: 9321848 = 008e3d78
The following command dumps the free space within the generation 0 range:
!dumpheap -type Free -stat 0x49521f8c 49e05d04
The result is as follows.
------------------------------ Heap 0 total 409 objects ------------------------------ Heap 1 total 0 objects ------------------------------ Heap 2 total 0 objects ------------------------------ Heap 3 total 0 objects ------------------------------ total 409 objects Statistics: MT Count TotalSize Class Name 0015a498 409 7296540 Free Total 409 objects
This output shows that the generation 0 portion of the heap is using 9 MB of space for objects and has 7 MB free. This analysis shows the extent to which generation 0 contributes to fragmentation. This amount of heap usage should be discounted from the total amount as the cause of fragmentation by long-term objects.
To determine the number of pinned objects
The statistics displayed includes the number of pinned handles, as the following example shows.
GC Handle Statistics: Strong Handles: 29 Pinned Handles: 10
To determine the length of time in a garbage collection
% Time in GCmemory performance counter.
The value is calculated by using a sample interval time. Because the counters are updated at the end of each garbage collection, the current sample will have the same value as the previous sample if no collections occurred during the interval.
Collection time is obtained by multiplying the sample interval time with the percentage value.
The following data shows four sampling intervals of two seconds, for an 8-second study. The
Gen2columns show the number of garbage collections that occurred during that interval for that generation.
Interval Gen0 Gen1 Gen2 % Time in GC 1 9 3 1 10 2 10 3 1 1 3 11 3 1 3 4 11 3 1 3
This information does not show when the garbage collection occurred, but you can determine the number of garbage collections that occurred in an interval of time. Assuming the worst case, the tenth generation 0 garbage collection finished at the start of the second interval, and the eleventh generation 0 garbage collection finished at the end of the fifth interval. The time between the end of the tenth and the end of the eleventh garbage collection is about 2 seconds, and the performance counter shows 3%, so the duration of the eleventh generation 0 garbage collection was (2 seconds * 3% = 60ms).
In this example, there are 5 periods.
Interval Gen0 Gen1 Gen2 % Time in GC 1 9 3 1 3 2 10 3 1 1 3 11 4 2 1 4 11 4 2 1 5 11 4 2 20
The second generation 2 garbage collection started during the third interval and finished at the fifth interval. Assuming the worst case, the last garbage collection was for a generation 0 collection that finished at the start of the second interval, and the generation 2 garbage collection finished at the end of the fifth interval. Therefore, the time between the end of the generation 0 garbage collection and the end of the generation 2 garbage collection is 4 seconds. Because the
% Time in GCcounter is 20%, the maximum amount of time the generation 2 garbage collection could have taken is (4 seconds * 20% = 800ms).
Alternatively, you can determine the length of a garbage collection by using garbage collection ETW events, and analyze the information to determine the duration of garbage collection.
For example, the following data shows an event sequence that occurred during a non-concurrent garbage collection.
Timestamp Event name 513052 GCSuspendEEBegin_V1 513078 GCSuspendEEEnd 513090 GCStart_V1 517890 GCEnd_V1 517894 GCHeapStats 517897 GCRestartEEBegin 517918 GCRestartEEEnd
Suspending the managed thread took 26us (
The actual garbage collection took 4.8ms (
Resuming the managed threads took 21us (
The following output provides an example for background garbage collection, and includes the process, thread, and event fields. (Not all data is shown.)
timestamp(us) event name process thread event field 42504385 GCSuspendEEBegin_V1 Test.exe 4372 1 42504648 GCSuspendEEEnd Test.exe 4372 42504816 GCStart_V1 Test.exe 4372 102019 42504907 GCStart_V1 Test.exe 4372 102020 42514170 GCEnd_V1 Test.exe 4372 42514204 GCHeapStats Test.exe 4372 102020 42832052 GCRestartEEBegin Test.exe 4372 42832136 GCRestartEEEnd Test.exe 4372 63685394 GCSuspendEEBegin_V1 Test.exe 4744 6 63686347 GCSuspendEEEnd Test.exe 4744 63784294 GCRestartEEBegin Test.exe 4744 63784407 GCRestartEEEnd Test.exe 4744 89931423 GCEnd_V1 Test.exe 4372 102019 89931464 GCHeapStats Test.exe 4372
GCStart_V1event at 42504816 indicates that this is a background garbage collection, because the last field is
1. This becomes garbage collection No. 102019.
GCStartevent occurs because there is a need for an ephemeral garbage collection before you start a background garbage collection. This becomes garbage collection No. 102020.
At 42514170, garbage collection No. 102020 finishes. The managed threads are restarted at this point. This is completed on thread 4372, which triggered this background garbage collection.
On thread 4744, a suspension occurs. This is the only time at which the background garbage collection has to suspend managed threads. This duration is approximately 99ms ((63784407-63685394)/1000).
GCEndevent for the background garbage collection is at 89931423. This means that the background garbage collection lasted for about 47seconds ((89931423-42504816)/1000).
While the managed threads are running, you can see any number of ephemeral garbage collections occurring.
To determine what triggered a garbage collection
In the WinDbg or Visual Studio debugger with the SOS debugger extension loaded, type the following command to show all the threads with their call stacks:
This command displays output similar to the following.
0012f3b0 79ff0bf8 mscorwks!WKS::GCHeap::GarbageCollect 0012f454 30002894 mscorwks!GCInterface::CollectGeneration+0xa4 0012f490 79fa22bd fragment_ni!request.Main(System.String)+0x48
If the garbage collection was caused by a low memory notification from the operating system, the call stack is similar, except that the thread is the finalizer thread. The finalizer thread gets an asynchronous low memory notification and induces the garbage collection.
If the garbage collection was caused by memory allocation, the stack appears as follows:
0012f230 7a07c551 mscorwks!WKS::GCHeap::GarbageCollectGeneration 0012f2b8 7a07cba8 mscorwks!WKS::gc_heap::try_allocate_more_space+0x1a1 0012f2d4 7a07cefb mscorwks!WKS::gc_heap::allocate_more_space+0x18 0012f2f4 7a02a51b mscorwks!WKS::GCHeap::Alloc+0x4b 0012f310 7a02ae4c mscorwks!Alloc+0x60 0012f364 7a030e46 mscorwks!FastAllocatePrimitiveArray+0xbd 0012f424 300027f4 mscorwks!JIT_NewArr1+0x148 000af70f 3000299f fragment_ni!request..ctor(Int32, Single)+0x20c 0000002a 79fa22bd fragment_ni!request.Main(System.String)+0x153
A just-in-time helper (
JIT_New*) eventually calls
GCHeap::GarbageCollectGeneration. If you determine that generation 2 garbage collections are caused by allocations, you must determine which objects are collected by a generation 2 garbage collection and how to avoid them. That is, you want to determine the difference between the start and the end of a generation 2 garbage collection, and the objects that caused the generation 2 collection.
For example, type the following command in the debugger to show the beginning of a generation 2 collection:
Example output (abridged to show the objects that use the most space):
79124228 31857 9862328 System.Object 035f0384 25668 11601936 Toolkit.TlkPosition 00155f80 21248 12256296 Free 79103b6c 297003 13068132 System.Threading.ReaderWriterLock 7a747ad4 708732 14174640 System.Collections.Specialized.HybridDictionary 7a747c78 786498 15729960 System.Collections.Specialized.ListDictionary+DictionaryNode 7a747bac 700298 19608344 System.Collections.Specialized.ListDictionary 035f0ee4 89192 38887712 Toolkit.TlkOrder 00fcae40 6193 44911636 WaveBasedStrategy.Tick_Snap 7912c444 91616 71887080 System.Double 791242ec 32451 82462728 System.Collections.Hashtable+bucket 790fa3e0 2459154 112128436 System.String Total 6471774 objects
Repeat the command at the end of generation 2:
Example output (abridged to show the objects that use the most space):
79124228 26648 9314256 System.Object 035f0384 25668 11601936 Toolkit.TlkPosition 79103b6c 296770 13057880 System.Threading.ReaderWriterLock 7a747ad4 708730 14174600 System.Collections.Specialized.HybridDictionary 7a747c78 786497 15729940 System.Collections.Specialized.ListDictionary+DictionaryNode 7a747bac 700298 19608344 System.Collections.Specialized.ListDictionary 00155f80 13806 34007212 Free 035f0ee4 89187 38885532 Toolkit.TlkOrder 00fcae40 6193 44911636 WaveBasedStrategy.Tick_Snap 791242ec 32370 82359768 System.Collections.Hashtable+bucket 790fa3e0 2440020 111341808 System.String Total 6417525 objects
doubleobjects disappeared from the end of the output, which means that they were collected. These objects account for approximately 70 MB. The remaining objects did not change much. Therefore, these
doubleobjects were the reason why this generation 2 garbage collection occurred. Your next step is to determine why the
doubleobjects are there and why they died. You can ask the code developer where these objects came from, or you can use the gcroot command.
To determine whether high CPU usage is caused by garbage collection
% Time in GCmemory performance counter value with the process time.
% Time in GCvalue spikes at the same time as process time, garbage collection is causing a high CPU usage. Otherwise, profile the application to find where the high usage is occurring.