book

Java Performance, 2nd Edition

by Scott Oaks

February 2020

Intermediate to advanced

448 pages

13h 15m

English

O'Reilly Media, Inc.

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Who Should (and Shouldn’t) Read This BookWhat’s New in the Second EditionConventions Used in This BookUsing Code ExamplesO’Reilly Online LearningHow to Contact UsAcknowledgments
A Brief OutlinePlatforms and ConventionsJava PlatformsHardware PlatformsThe Complete Performance StoryWrite Better AlgorithmsWrite Less CodeOh, Go Ahead, Prematurely OptimizeLook Elsewhere: The Database Is Always the BottleneckOptimize for the Common CaseSummary
Test a Real ApplicationMicrobenchmarksMacrobenchmarksMesobenchmarksUnderstand Throughput, Batching, and Response TimeElapsed Time (Batch) MeasurementsThroughput MeasurementsResponse-Time TestsUnderstand VariabilityTest Early, Test OftenBenchmark ExamplesJava Microbenchmark HarnessCommon Code ExamplesSummary
Operating System Tools and AnalysisCPU UsageThe CPU Run QueueDisk UsageNetwork UsageJava Monitoring ToolsBasic VM InformationThread InformationClass InformationLive GC AnalysisHeap Dump PostprocessingProfiling ToolsSampling ProfilersInstrumented ProfilersBlocking Methods and Thread TimelinesNative ProfilersJava Flight RecorderJava Mission ControlJFR OverviewEnabling JFRSelecting JFR EventsSummary
Just-in-Time Compilers: An OverviewHotSpot CompilationTiered CompilationCommon Compiler FlagsTuning the Code CacheInspecting the Compilation ProcessTiered Compilation LevelsDeoptimizationAdvanced Compiler FlagsCompilation ThresholdsCompilation ThreadsInliningEscape AnalysisCPU-Specific CodeTiered Compilation Trade-offsThe GraalVMPrecompilationAhead-of-Time CompilationGraalVM Native CompilationSummary
Garbage Collection OverviewGenerational Garbage CollectorsGC AlgorithmsChoosing a GC AlgorithmBasic GC TuningSizing the HeapSizing the GenerationsSizing MetaspaceControlling ParallelismGC ToolsEnabling GC Logging in JDK 8Enabling GC Logging in JDK 11Summary
Understanding the Throughput CollectorAdaptive and Static Heap Size TuningUnderstanding the G1 Garbage CollectorTuning G1 GCUnderstanding the CMS CollectorTuning to Solve Concurrent Mode FailuresAdvanced TuningsTenuring and Survivor SpacesAllocating Large ObjectsAggressiveHeapFull Control Over Heap SizeExperimental GC AlgorithmsConcurrent Compaction: ZGC and ShenandoahNo Collection: Epsilon GCSummary
Heap AnalysisHeap HistogramsHeap DumpsOut-of-Memory ErrorsUsing Less MemoryReducing Object SizeUsing Lazy InitializationUsing Immutable and Canonical ObjectsObject Life-Cycle ManagementObject ReuseSoft, Weak, and Other ReferencesCompressed OopsSummary
FootprintMeasuring FootprintMinimizing FootprintNative Memory TrackingShared Library Native MemoryJVM Tunings for the Operating SystemLarge PagesSummary
Threading and HardwareThread Pools and ThreadPoolExecutorsSetting the Maximum Number of ThreadsSetting the Minimum Number of ThreadsThread Pool Task SizesSizing a ThreadPoolExecutorThe ForkJoinPoolWork StealingAutomatic ParallelizationThread SynchronizationCosts of SynchronizationAvoiding SynchronizationFalse SharingJVM Thread TuningsTuning Thread Stack SizesBiased LockingThread PrioritiesMonitoring Threads and LocksThread VisibilityBlocked Thread VisibilitySummary

Java NIO OverviewServer ContainersTuning Server Thread PoolsAsync Rest ServersAsynchronous Outbound CallsAsynchronous HTTPJSON ProcessingAn Overview of Parsing and MarshalingJSON ObjectsJSON ParsingSummary
Sample DatabaseJDBCJDBC DriversJDBC Connection PoolsPrepared Statements and Statement PoolingTransactionsResult Set ProcessingJPAOptimizing JPA WritesOptimizing JPA ReadsJPA CachingSpring DataSummary
StringsCompact StringsDuplicate Strings and String InterningString ConcatenationBuffered I/OClassloadingClass Data SharingRandom NumbersJava Native InterfaceExceptionsLoggingJava Collections APISynchronized Versus UnsynchronizedCollection SizingCollections and Memory EfficiencyLambdas and Anonymous ClassesStream and Filter PerformanceLazy TraversalObject SerializationTransient FieldsOverriding Default SerializationCompressing Serialized DataKeeping Track of Duplicate ObjectsSummary

Overview

Coding and testing are generally considered separate areas of expertise. In this practical book, Java expert Scott Oaks takes the approach that anyone who works with Java should be adept at understanding how code behaves in the Java Virtual Machine—including the tunings likely to help performance. This updated second edition helps you gain in-depth knowledge of Java application performance using both the JVM and the Java platform.

Developers and performance engineers alike will learn a variety of features, tools, and processes for improving the way the Java 8 and 11 LTS releases perform. While the emphasis is on production-supported releases and features, this book also features previews of exciting new technologies such as ahead-of-time compilation and experimental garbage collections.

Understand how various Java platforms and compilers affect performance
Learn how Java garbage collection works
Apply four principles to obtain best results from performance testing
Use the JDK and other tools to learn how a Java application is performing
Minimize the garbage collector’s impact through tuning and programming practices
Tackle performance issues in Java APIs
Improve Java-driven database application performance