IT Tage 2019 - Entity Framework Core - Performanzoptimierung

D34263c3a24b3b36a61735e3ce226468?s=47 Pawel Gerr
December 12, 2019

IT Tage 2019 - Entity Framework Core - Performanzoptimierung

D34263c3a24b3b36a61735e3ce226468?s=128

Pawel Gerr

December 12, 2019
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  1. 09. – 12.12.2019 Frankfurt am Main #ittage Entity Framework Core

    Pawel Gerr Performance Optimization
  2. Entity Framework Core Performance Optimization Example for today – Products

    DB Product group Products Prices Sellers Studio
  3. Entity Framework Core Performance Optimization My usual options for Entity

    Framework performance optimization 2nd level cache Hardware upgrade Materialized views Stored procedures Triggers Database Features Server Raw SELECT * FROM … Raw SQL Bulk operations Indices Entity Framework Requests reduction Query restructure … and some other (minor) features we will see later Use 3rd party libs if available CPU, Memory, I/O
  4. Entity Framework Core Performance Optimization Did „the change“ anything good?

    – My KPI Execution time (LINQ) SELECT * FROM … SELECT * FROM … SELECT * FROM … Number of requests Query statistics SELECT * FROM … “Shape” of SQL Execution plans Parse time Compile time Execution time (DB) Physical reads Logical reads Row count Round trip time SQL generation Execution time (DB) Materialization My key performance indicators
  5. Entity Framework Core Performance Optimization Reducing database requests

  6. Entity Framework Core Performance Optimization N+1 queries problem Execution of

    hundreds of requests for one use case Caused by: unintentional execution of queries in loops Possible solutions: • Better code structure (software architecture) • Avoid overgeneralization (shared/core projects) • Help each other to improve (review/feedback) • Know the insights of Entity Framework • Lazy loading • Limitations Reducing database requests
  7. Simplified case of indirect execution of database requests in a

    loop Library Main Entity Framework Core Performance Optimization Multiple requests in loops Reducing database requests var products = LoadProducts(); var prices = new List<Price>(); foreach (var product in products) { var price = GetPrice(product.Id); prices.Add(price); } public Price GetPrice(Guid productId) { MyDbContext ctx = …; return ctx.Prices.FirstOrDefault(p => p.ProductId == productId); } Executed N times
  8. Library Main Entity Framework Core Performance Optimization LINQ queries are

    loops Reducing database requests var products = LoadProducts(); var prices = products.Select(product => GetPrice(product.Id)) .ToList(); public Price GetPrice(Guid productId) { MyDbContext ctx = …; return ctx.Prices.FirstOrDefault(p => p.ProductId == productId); }
  9. Library Main Entity Framework Core Performance Optimization Approach 1 –

    Use-case specific methods Reducing database requests var productsWithPrices = LoadProductsWithPrices(); public List<ProductWithPrices> LoadProductsWithPrices() { return ctx.Products .Include(p => p.Prices) // merely symbolic, fetching prices is usually more complex .ToList(); }
  10. Library Main var products = LoadProducts(); var productIds = products.Select(p

    => p.Id); var prices = GetPrices(productIds); public List<Price> GetPrices(IEnumerable<Guid> productIds) { return ctx.Prices .Where(p => productIds.Contains(p.ProductId)) .ToList(); } Entity Framework Core Performance Optimization Approach 2 – load all required prices at once Reducing database requests
  11. Given: 100 products being in 5 studio Loading of all

    products “in one go” leads to 1 + 5 queries Library Main var productsByStudio = ctx.Products .Include(p => p.Studio) .ToLookup(p => p.Studio.Name); Entity Framework Core Performance Optimization Lazy loading Reducing database requests public static ILookup<TKey, TSource> ToLookup<TSource, TKey>( this IEnumerable<TSource> source, Func<TSource, TKey> keySelector) { ... } Use eager loading to prevent unnecessary requests IEnumerable<T> always forces query execution
  12. LINQ Entity Framework Core Performance Optimization Limitations of Entity Framework

    Core Access to navigational property in EF 2.2 leads to N+1 queries if query is not trivial • Loading of the first product of 5 studios leads to 1 + 5 queries • The issue has been fixed in EF 3.0 Reducing database requests var studios = ctx.Studios .Select(s => { Studio = s, FirstProduct = s.Products.FirstOrDefault() }) .ToList(); not trivial query
  13. Entity Framework Core Performance Optimization Finding the problem area Use

    profiling tools In case of Microsoft SQL Server: XEvent Profiler in SQL Server Management Studio SQL Server Profiler (deprecated, resource intensive) Azure Data Studio Logs coming from EF with EnableSensitiveDataLogging Reducing database requests Logging DbContextOptionsBuilder builder = ...; builder.UseSqlServer("...") // or any other database .UseLoggerFactory(loggerFactory) .EnableSensitiveDataLogging(); In development only because possible security leak!
  14. Entity Framework Core Performance Optimization Finding the problem area Look

    for repetitive lines and cycles Reducing database requests Repetive lines Cycles
  15. Entity Framework Core Performance Optimization Reducing query complexity

  16. Entity Framework Core Performance Optimization Cartesian explosion problem Fetching a

    lot of data from multiple tables at once • Increased memory consumption and execution time • High I/O load Caused by: loading of multiple navigational collection-properties Possible solutions: • Reduce Includes (eager loading) • Reduce access to navigational properties in projections (i.e. Select) Reducing query complexity Query splitting
  17. Entity Framework Core Performance Optimization Eager loading via Include EF

    2.2 is loading collections separately EF 3.0 loads all data using 1 SQL statement • Bigger result sets: 100 products with 5 prices each and 3 sellers (100 * 5 * 3) rows > (100 + 500 + 3) records • EF-forced ORDER BY clause produces considerable load Reducing query complexity Product Id Price Id Seller Id 1 1 1 1 1 2 1 1 3 1 2 1 1 2 2 1 2 3 SQL LINQ var products = ctx.Products .Include(p => p.Studio) .Include(p => p.Prices) .Include(p => p.Sellers) .ToList(); SELECT * FROM Products INNER JOIN Studios ... LEFT JOIN Prices ON ... LEFT JOIN Sellers ON ... ... ORDER BY Products.Id, Prices.Id, Sellers.Id Cartesian explosion
  18. Before Entity Framework Core Performance Optimization Using collections in projections

    Loading all data at once Statistics: • CPU: 31 • Duration: 75 • Reads: 5299 • Row Count: 12342 Reducing query complexity LINQ var studios = ctx.Studios .Select(s => new MyStudio { Id = s.Id, Name = s.Name, Infinity = s.Products.Where(p => p.Name.StartsWith("Infinity")), Endgame = s.Products.Where(p => p.Name.StartsWith("Endgame")) }) .ToList();
  19. Before Usually, loading collection separately requires more code but less

    resources on database Statistics: • CPU: 31 • Duration: 75 • Reads: 5299 • Row Count: 12342 After LINQ Entity Framework Core Performance Optimization Query splitting Reducing query complexity var studios = ctx.Studios.Select(p => new Studio() { Id = p.Id, Name = p.Name }).ToList(); var infinity = ctx.Products.Where(p => p.Name.StartsWith("Infinity")).ToList(); var endgame = ctx.Products.Where(p => p.Name.StartsWith("Endgame")).ToList(); var infinityLookup = infinity.ToLookup(p => p.StudioId); var endgameLookup = endgame.ToLookup(p => p.StudioId); foreach (var studio in studios) { studio.Infinity = infinityLookup[studio.Id]; sturio.Endgame = endgameLooup[studio.Id]; } Necessary, if change tracking is disabled 16 3 352 2322
  20. Entity Framework Core Performance Optimization Understanding queries

  21. LINQ 2 LINQ 1 Entity Framework Core Performance Optimization Which

    one is better? Understanding Queries var groups = ctx.ProductGroups .Select(g => new { g.Products.FirstOrDefault().Id, g.Products.FirstOrDefault().Name }) .ToList(); var groups = ctx.ProductGroups .Select(g => g.Products .Select(p => new { p.Id, p.Name }) .FirstOrDefault()) .ToList(); 2x “FirstOrDefault()” before selecting properties Selection of properties before “FirstOrDefault()”
  22. SQL 2 SQL 1 Entity Framework Core Performance Optimization Lets

    try with SQL … Understanding Queries SELECT ( SELECT TOP(1) p.Id FROM Products p WHERE g.Id = p.GroupId ) AS FirstProductId, ( SELECT TOP(1) p.Name FROM Products p WHERE g.Id = p.GroupId ) AS FirstProductName FROM ProductGroups g SELECT p.Id, p.Name FROM ProductGroups g LEFT JOIN ( SELECT Id, Name, GroupId FROM ( SELECT Id, Name, GroupId, ROW_NUMBER() OVER(PARTITION BY GroupId ORDER BY Id) AS row FROM Products ) p WHERE row <= 1 ) p ON g.Id = p.GroupId 2 sub-selects Window function “ROW_NUMBER”
  23. Entity Framework Core Performance Optimization Execution plans

  24. Entity Framework Core Performance Optimization Textual representation of all database

    operations • Type and the order of operations (JOIN, filter, projection, ...) • Indexes being used • Amount of data flowing between two operations • Costs of an operation and a subtree Some tools have built-in support for displaying execution plans as a graph Execution plans
  25. Entity Framework Core Performance Optimization Another try … Execution plans

    Execution plan 1 SQL 1 SELECT ( SELECT TOP(1) p.Id FROM Products p WHERE g.Id = p.GroupId ) AS FirstProductId, ( SELECT TOP(1) p.Name FROM Products p WHERE g.Id = p.GroupId ) AS FirstProductName FROM ProductGroups g
  26. Entity Framework Core Performance Optimization Execution plans Execution plan 2

    SQL 2 SELECT p.Id, p.Name FROM ProductGroups g LEFT JOIN ( SELECT Id, Name, GroupId FROM ( SELECT Id, Name, GroupId, ROW_NUMBER() OVER(PARTITION BY GroupId ORDER BY Id) AS row FROM Products ) p WHERE row <= 1 ) p ON g.Id = p.GroupId
  27. Entity Framework Core Performance Optimization Comparing • Compare estimated subtree

    costs • Deviance: estimated vs actual number of rows • Take statistics (like reads) into consideration Execution plans Query 1 wins!
  28. Entity Framework Core Performance Optimization Execution plans Crash course Table

    scan Clustered index scan Non-clustered index scan Clustered index seek Non-clustered index seek Scan No clustered index Seek Missing index? Fuzzy search? Bad discriminator? Filter Filtering Filtering Filtering Key lookup Missing (include) columns? RID lookup If no clustered index Sort “Stop & Go” operator! Required? Missing index? Sorting in .NET cheaper? Parallelism Expensive High query complexity
  29. Entity Framework Core Performance Optimization JOINs Execution plans DB may

    perform sort on its own • Resource-saving • Data sets must be ordered • The “default” • Kind-of 2 nested loops • Speed depends on: • Scan of data set A • Seek of data set B • Large and unsorted sets • 2 phases: • Builds hash table for set A • Matches hash values from B Should be looked at Merge join Nested loop join Hash match join
  30. Entity Framework Core Performance Optimization Learnings • Look for database

    requests in “loops” • Split complex queries if necessary • Learn to read execution plans - optimize queries accordingly Resources • Entity Framework Core: https://docs.microsoft.com/en-us/ef/core/ • Execution Plans: https://docs.microsoft.com/en-us/sql/relational-databases/performance/execution-plans • My EF playground: https://github.com/PawelGerr/EntityFrameworkCore-Demos Ask me @pawelgerr pawel.gerr@thinktecture.com