Hope I'm not wasting anyone's time, but

ServiceStack.OrmLite
1

Rider is reporting an excessive amount of memory usage (when debugging) from some OrmLite functions. I thought I’d report it in case any improvements in string usage can be achieved on OrmLiteUtils.GetFieldNames or any of the other reported methods.

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Rider’s AI Assistant has explained the following:

The issue stems from excessive allocations of the System.String type in the method ServiceStack.OrmLite.OrmLiteUtils.GetFieldNames as part of the process in JobsHostedService.ExecuteAsync. By analyzing the stack trace, we can conclude that the source of the problem lies in how OrmLiteUtils.GetFieldNames handles IDataReader and its operations. Since GetFieldNames is located at the top of the stack trace, it is responsible for a large allocation of strings, particularly during database interactions.

Analysis of the issue

  1. Allocation Source:

    • The OrmLiteUtils.GetFieldNames method likely processes field names from an IDataReader. This is a typical point where multiple strings are created to handle database column names, which may involve:
      • String concatenation or manipulation.
      • Calls to ToString() on objects.
      • Accumulation of strings in collections like List<string>.

  2. Accumulated Impact:

    • As per the issue description, 185 MB of string data was allocated in the Small Object Heap (SOH). This suggests that either:
      • There is a very high frequency of database calls looping through field names.
      • Inefficient or redundant allocations of string objects occur.

  3. JobsHostedService:

    • The calling TickAsync() in JobsHostedService.ExecuteAsync results in the execution of database operations, which in turn triggers the GetFieldNames method. The string creation from field names during data processing contributes significantly to memory allocations, particularly when handling large datasets or frequent queries.

Resolution of the issue

  1. Revisit GetFieldNames implementation:

    • Review the GetFieldNames method in the ServiceStack.OrmLite.OrmLiteUtils class to identify inefficiencies. Avoid redundant allocations by:
      • Reusing string instances where possible.
      • Removing unnecessary calls to methods such as .ToString() if the value is already a string.
      • Avoiding unnecessary concatenation of strings.

  2. Use String Interning:

    • If many identical strings are generated (e.g., column names are repeated), consider string interning to reduce memory usage. Interned strings use a single memory reference for multiple identical strings.

  3. Optimize DataReader Usage:

    • If GetFieldNames iterates over data fields multiple times, try reducing such iterations by reading all required field names in one pass and caching the results.

  4. Batch Processing:

    • If JobsHostedService interacts with a database frequently and performs repetitive tasks, consider batching operations to minimize the number of calls to GetFieldNames.

  5. Avoid Temporary String Allocations:

    • If GetFieldNames is concatenating or creating temporary strings (e.g., for debugging or logging), minimize such operations during runtime.

  6. Enable Diagnostic Tools:

    • Use diagnostic tools like a memory profiler (e.g., JetBrains dotMemory or Visual Studio Diagnostic Tools) to track the exact string allocation points in GetFieldNames. This will help in pinpointing specific inefficient code sections.

If none of the above resolves the issue and you cannot reduce the memory allocation because the load is inherently high, scaling or provisioning memory appropriately for the application may also be a valid consideration.

Final Note:

The key to resolving this issue is identifying inefficient string usage within ServiceStack.OrmLite.OrmLiteUtils.GetFieldNames. Start by focusing on avoiding redundant or unnecessary string allocations during database operations.

2

Did you look beyond the AI analysis and look at the source code for OrmLiteUtils.GetFieldNames() to see if the analysis is accurate?

This is the method they’re referring to:

i.e. just returning a list of column keys for the data result set.

You can report a runtime performance (i.e. release builds) issue at ServiceStack/Issues. Use BenchmarkDotNet for measuring the performance and memory usage.

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3

I did yes, but didn’t understand why it was using 185MB and why it was being reported in the first place so thought I’d mention it. Apologies for the waste of time.

4

It’s fine to report performance/memory issues, but only runtime performance issues are useful, i.e. we can’t control what Rider does under a debugger. If you use AI Analysis it should be double-checked to verify accuracy by using BenchmarkDotNet to reproduce and measure issues, which we can run ourselves to identify issues.

With that said I’ve replaced the string[] array allocation with a pooled StringBuilder for where it’s used to construct a cache key which should reduce allocations.

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5

Understood, and thanks for the intro to BenchmarkDotNet - hadn’t heard of it before :+1:

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