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EF Core 8: Use Any() over Count(*)
Date Added (UTC):
08 May 2024 @ 03:50
Date Updated (UTC):08 May 2024 @ 05:50
.NET Version(s): Tag(s):
Added By:
Senior Software Engineer
Benchmark Results:
Benchmark Code:
Originally imported from :
https://gist.github.com/sa-es-ir/bfd1e7a2e245835334c6824a727121c4on 08 May 2024 @ 05:50 (UTC) .
The original benchmark may have changed.
https://gist.github.com/sa-es-ir/bfd1e7a2e245835334c6824a727121c4
The original benchmark may have changed.
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Columns;
using BenchmarkDotNet.Configs;
using BenchmarkDotNet.Reports;
using DatabaseNight.Context;
using System.Linq;
namespace DatabaseNight;
[Config(typeof(Config))]
[HideColumns(Column.RatioSD, Column.AllocRatio)]
[MemoryDiagnoser(false)]
public class EFTuningService
{
private class Config : ManualConfig
{
public Config()
{
SummaryStyle = SummaryStyle.Default.WithRatioStyle(RatioStyle.Trend);
}
}
[Benchmark(Baseline = true)]
public bool Count()
{
var context = new ApplicationContext();
return context.Employees
.Count(x => x.DepartmentId == 7) > 0;
}
[Benchmark]
public bool Any()
{
var context = new ApplicationContext();
return context.Employees
.Any(x => x.DepartmentId == 7);
}
}
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// .NET 8 Lowered C# Code unavailable due to errors:
error CS0234: The type or namespace name 'Context' does not exist in the namespace 'DatabaseNight' (are you missing an assembly reference?)
error CS0246: The type or namespace name 'ApplicationContext' could not be found (are you missing a using directive or an assembly reference?)
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// .NET 8 IL Code unavailable due to errors:
error CS0234: The type or namespace name 'Context' does not exist in the namespace 'DatabaseNight' (are you missing an assembly reference?)
error CS0246: The type or namespace name 'ApplicationContext' could not be found (are you missing a using directive or an assembly reference?)
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|
Benchmark Description:
Setup:
**EF Core: 8.0.3**
**Employees: 25,000 rows**
Both methods can be used if we want to be sure there are some records in the table based on specific conditions but the interesting part happens on the database side!
The Count will be translated to SELECT COUNT(*) whereas Any goes for IF EXISTS, so what??
IF EXISTS stops the processing of the select query as soon as the first matching row is found, whereas SELECT COUNT(*) continues searching until all matches are found, wasting I/O and CPU cycles.
The point is, it's better to put logic in the database side for getting better performance, in the current scenario want to check for existence and we need a flag that says there is a record or not. So instead of getting a count and checking it on the application side, it's more rational to calculate this flag in the database.
If you want to run the benchmark yourself here is the repo:
[https://github.com/sa-es-ir/youtube-samples/tree/main/EFQueryOptimization](https://github.com/sa-es-ir/youtube-samples/tree/main/EFQueryOptimization)
The provided benchmark code is designed to measure and compare the performance of two different methods for determining if there are any employees in a specific department using Entity Framework (EF). The benchmark is set up using BenchmarkDotNet, a powerful .NET library for benchmarking, and it specifically targets the performance of querying a database using EF within a .NET application. Although the .NET version is not explicitly mentioned, BenchmarkDotNet supports a wide range of .NET versions, including .NET Core and .NET 5/6. The configuration and attributes used in the benchmark setup play a crucial role in how the tests are executed and how the results are reported.
### General Setup
- **BenchmarkDotNet Attributes**: The benchmark class is decorated with attributes to configure the benchmark run. `[Config(typeof(Config))]` specifies a custom configuration for the benchmark, where various settings can be adjusted, such as the summary style. `[HideColumns]` is used to hide specific columns in the output report, in this case, the Ratio Standard Deviation and Allocation Ratio columns. `[MemoryDiagnoser(false)]` indicates that memory diagnostics are enabled, but GC collections will not be included in the summary.
- **Custom Configuration (`Config` class)**: This class extends `ManualConfig` and customizes the summary style of the benchmark report. The `RatioStyle.Trend` setting is used to highlight performance trends between benchmarks.
### Benchmark Methods
#### 1. `Count()`
- **Purpose**: This method tests the performance of using the `.Count()` extension method to check if there are any employees in department 7. It does so by counting all employees in that department and then checking if the count is greater than 0.
- **Performance Aspect**: It measures how long it takes to execute a count operation on a database set, which can be inefficient for large datasets since it requires counting all matching entries before comparing the count to zero.
- **Expected Insights**: Running this benchmark will help understand the overhead of using `.Count()` for existence checks. It's generally expected that for large datasets, this approach might be slower due to the unnecessary counting of all entries.
#### 2. `Any()`
- **Purpose**: This method evaluates the performance of using the `.Any()` extension method to determine if there are any employees in department 7. Unlike `.Count()`, `.Any()` checks for the existence of any matching entry without counting the total number of matches.
- **Performance Aspect**: This benchmark aims to measure the efficiency of existence checks using `.Any()`, which is typically more optimized for such scenarios since it can return immediately upon finding the first match.
- **Expected Insights**: The expectation is that `.Any()` will outperform `.Count()` in scenarios where the goal is to check for the existence of records. It's more efficient because it doesn't require processing the entire dataset to return a result.
### Conclusion
By comparing the performance of `Count()` and `Any()`, this benchmark setup aims to highlight the importance of choosing the right method for database queries based on the specific requirements of the operation (e.g., counting all matches vs. checking for the existence of any match). The insights gained can guide developers in writing more efficient Entity Framework queries, especially in scenarios where performance is critical.