Prerequisites

This course is ideally suited to the professional Java programmer with at least 2 years experience, who would like to learn how to truly understand Java concurrency.

• Previous Training: java.lang.reflect.*.
• Required Experience: At least two years of professional Java programming.
• Preparation: Read Brian Goetz's "Java Concurrency in Practice".

Pricing Options

We have several options for you to join this course:

1. Virtual In-house Course:

Presented via video conference to your team of programmers by the author of the course. Price is €13400 for up to 10 students, above that is an additional €1200 per student.

• Example 1: Course with 8 students taught remotely via video conference, price is €13400. Price per student is €1675.
• Example 2: Course with 12 students taught remotely via video conference, price is €15800. Price per student is €1316.
• Example 3: Course with 24 students taught remotely via video conference, price is €30200. Price per student is €1258.

Please contact us if you have any questions.

2. In-person In-house Course:

Presented at your company in-person by one of our Certified JavaSpecialist Instructors. Price is €19750 for up to 10 students, above that is an additional €1975 per student, plus the travel expenses of the instructor. Note that for in-person in-house courses, we need a minimum of three consecutive training days.

• Example 1: Course with 8 students taught on-site at your company, price is €19750. Price per student is €2468.
• Example 2: Course with 12 students taught on-site at your company, price is €23700. Price per student is €1975.
• Example 3: Course with 18 students taught on-site at your company, price is €35550. Price per student is €1975.

Please contact us if you have any questions.

2. Open Enrollment Classroom Course:

We occasionally offer this course as a classroom course in Chania on the Island of Crete. Price for the course is €4250 per student.

We also offer this course as an open enrollment live remote course that you can attend from anywhere. Price is €2885 per student.

Please contact us if you have would like to make a booking or if you have any questions.

4. Self-Paced Course:

This course is currently not available as a self-paced course.

Please contact us if you have any questions.

* Prices exclude EU VAT and withholding taxes where applicable. Please contact us for an exact quote for your country.

Open Courses

Concurrency courses offered:

All our courses are offered as in-house courses. Please contact us on heinz@javaspecialists.eu.

* Price is excluding EU VAT where applicable. Please contact us for an exact quote for your country.

Detailed Outline

Java Concurrency Course

Day 1

• 1 Introduction
  • Welcome To The Course
    • How we deal with questions
    • Exercises with partial solutions
    • Certificate of Training
  • 1.1 History of concurrency
    • Processes vs Threads vs Virtual Threads
    • Moore's Law and Transistor Count
    • Concurrent vs Parallel Programming
    • Preemptive vs Cooperative vs Virtual Multithreading
    • Java Memory Model
  • 1.2 Benefits of threads
    • Programming is easier
      • Concurrent Programming
      • Parallel Programming
    • Better throughput
    • Simpler modeling
    • More responsive programs
  • 1.3 Risks of threads
    • Safety vs liveness
    • Safety hazards
    • Using basic synchronized
    • Caching of fields
    • Code reordering
    • Annotations for Concurrency
      • Class annotations
      • Field annotations
  • 1.4 Threads are everywhere
    • Timer
    • Servlets and JavaServer Pages
    • Remote Method Invocation (RMI)
    • Swing and AWT
    • HttpClient in Java 11
  • 1.5 Short Java Migration Primer
    • Java 7: underscores, diamond, try-with-resource
    • Java 8: lambdas, streams, compound collection methods
    • Java 11: JPMS, immutable collections, var
    • Java 17: switch expressions, text blocks, records, pattern matching, strong\nencapsulation, sealed classes
    • Java 19-previes: virtual threads
• 2 Thread Safety
  • Introduction to Thread Safety
    • Synchronization and shared data
    • Your program has latent defects
    • Object orientation and synchronization
    • Example of a simple data race
  • 2.1 What is thread safety?
    • Definition of thread safety
    • Stateless objects always thread-safe
  • 2.2 Atomicity
    • Byte code generated by simple count++
    • Demonstration of broken servlet
    • Lazy initialization check-then-act
    • Reordering of writes
    • Compound actions
      • Check-then-act
      • Read-write-modify
    • Using AtomicLong to keep state safe
    • Request counting with LongAdder
  • 2.3 Locking
    • Mutexes in Java
    • Atomics causing race conditions
    • Monitor locks
    • Effects of coarse-grained locking
    • Reentrancy
  • 2.4 Guarding state with locks
    • Serialized access to critical code
    • Examples of guards with compound actions
    • Making compound actions atomic
    • Synchronizing on non-final fields
    • Synchronizing on Value-Based Classes
    • Locking on monitor lock "this"
    • Maintaining invariants
    • Locking everything is not always enough
    • Synchronization on reads
    • Synchronized and Virtual Threads
  • 2.5 Liveness and performance
    • Coarse-grained vs fine-grained locking
    • Performance difference
    • Simplicity vs performance
• 3 Sharing Objects
  • 3.1 Visibility
    • Synchronization and visibility
    • Reason why changes are not visible
    • Problems that state data can cause
    • Non-atomic 64-bit numeric operations
    • Making fields visible with volatile
    • Volatile flushing
    • Volatile vs synchronized
    • Single-threaded write safety
    • Volatile Doesn't Guard Against Race Conditions
  • 3.2 Publication and escape
    • Ways we might let object escape
    • Publishing objects via fields
    • Publishing objects as method returns
    • Publishing objects to alien methods
    • Implicit links to outer class
      • Lambdas and method references
    • Safe construction practices
  • 3.3 Thread confinement
    • Unshared objects are safe
    • Thread confinement
      • ThreadLocal in Virtual Threads
    • Stack confinement
    • ThreadLocal
    • Instance confinement
  • 3.4 Immutability
    • Immutable is always thread safe
    • Definition of immutable
    • Immutable containing mutable object
    • Final fields
  • 3.5 Safe publication
    • Making objects and their state visible
    • Safe publication idioms
    • "Effectively" immutable objects
    • How to share objects safely
      • Thread-confined
      • Shared read-only
      • Shared thread-safe
      • Guarded
• 4 Composing Objects
  • 4.1 Designing a thread-safe class
    • Encapsulation
    • Primitive vs object fields
    • Thread-safe counter with invariant
    • Post-conditions
    • Pre-condition
    • Waiting for pre-condition to become true
  • 4.2 Instance confinement
    • Encapsulation
    • State guarded by private fields
    • Split locks
    • How instance confinement is good
    • Java monitor pattern
    • Lock confinement
    • Example of fleet management
  • 4.3 Delegating thread safety
    • Using thread safe components
    • Delegation with vehicle tracker
    • Delegating safety to ConcurrentMap
    • Independent fieldds
    • Invariables and delegation
      • Using AtomicLong for combining ints
    • Publishing underlying fields
  • 4.4 Adding functionality to existing thread-safe classes
    • Benefits of reuse
    • Modifying existing code
    • Subclassing to add functionality
    • Using composition to add fiunctionality
    • Client-side locking
  • 4.5 Documenting synchronization policies
    • Examples from the JDK
    • What should be documented
    • Synchronization policies
    • Documentation checklist
    • Interpreting vague documentation

Day 2

• 5 Building Blocks
  • 5.1 Synchronized collections
    • Old Java 1.0 thread-safe containers
    • Synchronized wrapper classes
    • Locking with compound actions
    • Adding functionality to thread-safe classes
    • Exceptions with iteration
    • Hidden iterators
    • Benefits and limitations with "synchronized"
  • 5.2 Concurrent collections
    • Scalability
    • ConcurrentHashMap
    • Additional atomic operations
    • ConcurrentSkipListMap
    • CopyOnWriteCollections
    • ConcurrentLinkedQueue
  • 5.3 Blocking queues and the producer-consumer pattern
    • How BlockingQueues work
    • Timed vs untimed methods
    • Java implementations of BlockingQueue
      • LinkedBlockingQueue
      • ArrayBlockingQueue
        • Circular array lists
      • PriorityBlockingQueue
      • DelayQueue
      • SynchronousQueue
      • TransferQueue
    • Example of producer-consumer
    • Deques
      • ArrayDeque
      • LinkedBlockingDeque
      • ConcurrentLinkedDeque (Java 7)
    • Work stealing
  • 5.4 Blocking and interruptible methods
    • Thread states during blocking
    • Interrupting blocking methods
    • Methods throwing InterruptedException
    • ManagedBlocker
    • Blocking Methods and Virtual Threads
  • 5.5 Synchronizers
    • Coordinating flow of threads
    • Semaphore
    • CountDownLatch
    • AbstractQueuedSynchronizer
    • CyclicBarrier
    • FutureTask
    • Phaser
• 6 Task Execution
  • 6.1 Executing tasks in threads
    • Identifying tasks
    • Indepence of tasks
    • Task boundaries
    • Single-threaded vs multi-threaded
    • Explicitely creating tasks
    • Disadvantage of unbounded thread creation
    • Creating virtual threads
  • 6.2 Virtual Threads
    • Starting Virtual Threads
    • Virtual Thread Characteristics
    • Carrier Threads
    • Platform Threads State Machine
    • Virtual Threads State Machine
    • Thread.Builder
      • Thread.Builder.OfPlatform
      • Thread.Builder.OfVirtual
  • 6.3 The Executor framework
    • Executor interface
    • Motivation for using Executor
    • Executors Facade pools
    • Decoupling task submission from execution
    • Thread pool benefits
    • Virtual Thread Executor vs Pool
    • Submitting Callable
    • Executor lifecycle, state machine
      • Shutdown() vs ShutdownNow()
      • AutoCloseable (Project Loom)
    • Memory leaks with ThreadLocal
    • Delayed and periodic tasks
      • Difference between java.util.Timer and ScheduledExecutor
  • 6.4 Finding exploitable parallelism
    • Breaking up a single client request
    • Sequential vs parallel
    • Callable and Future
    • Callable controlling lifecycle
    • Example showing page renderer with future
    • Limitations of parallelizing heterogeneous tasks
    • CompletionService
    • Time limited tasks
    • CompletableFuture
      • Chaining of CompletionStages
      • Modeling control flow
      • Using separate pools for stages
      • HttpClient in Java 11
      • CompletableFuture Tips
    • Parallel Request with Virtual Threads
      • Structured Concurrency
      • Managing Error Conditions
      • Timeouts in Requests
  • 6.5 Using Parallel Streams
    • Processing in parallel
    • When to use / avoid
    • Common Fork/Join Pool
• 7 Cancellation
  • 7.1 Task cancellation
    • Reasons for wanting to cancel a task
    • Cooperative vs preemptive cancellation
    • Using flags to signal cancellation
    • Cancellation policies
    • 7.1.1 Interruption
      • WAITING state of thread
      • Origins of interruptions
      • How does interrupt work?
      • Methods that put thread in WAITING state
      • Policies in dealing with InterruptedException
      • Thread.interrupted() method
      • Interruptions in Virtual Threads
    • 7.1.2 Interruption policies
      • Task vs Thread
      • Different meanings of interrupt
      • Preserving the interrupt status
    • 7.1.3 Responding to interruption
      • Letting the method throw the exception
      • Restoring the interrupt and exiting
      • Ignoring the interrupt status
      • Saving the interrupt for later
    • 7.1.4 Example: timed run
      • Telling a long run to eventually give up
      • Canceling busy jobs
    • 7.1.5 Dealing with non-interruptible blocking
      • Reactions of IO libraries to interrupts
      • Interrupting locks
  • 7.2 Stopping a thread-based service
    • Graceful shutdown
    • Providing lifecycle methods
    • Example: A logging service
    • Asynchronous logging caveats
    • ExecutorService shutdown
    • Poison pills
    • One-shot execution service
  • 7.3 Handling abnormal thread termination
    • Using UncaughtExceptionHandler
    • ThreadGroup for uncaught exceptions
    • Dealing with exceptions in Swing
  • 7.4 JVM shutdown
    • Orderly shutdown
    • Abrupt shutdown
    • Shutdown hooks
    • Daemon threads

Day 3

• 8 Applying Thread Pools
  • 8.1 Tasks and Execution Policies
    • Homogenous, independent and thread-agnostic tasks
    • Thread starvation deadlock
    • Long-running tasks
  • 8.2 Sizing thread pools
    • Danger of hardcoding worker number
    • Problems when pool is too large or small
    • Formula for calculating how many threads to use
    • CPU-intensiv vs IO-intensive task sizing
    • Examples of various pool sizes
    • Mixing different types of tasks
      • Platform vs Virtual Thread Pools
  • 8.3 Configuring ThreadPoolExecutor
    • corePoolSize, maximumPoolSize, keepAliveTime, workQueue
    • Using default Executors.new* methods
    • Managing queued tasks
    • PriorityBlockingQueue
    • Saturation policies
      • Abort
      • Caller runs
      • Discard
      • Discard oldest
    • Thread factories
  • 8.4 Extending ThreadPoolExecutor
    • Using hooks for extension
    • beforeExecute
    • afterExecute
    • terminate
    • Exceptions from ThreadPoolExecutor
  • 8.5 Parallelizing recursive algorithms
    • Converting sequential tasks to parallel
    • Using Fork/Join to execute tasks
• 9 Fork/Join
  • Breaking up work into chunks
  • ForkJoinPool and ForkJoinTask
  • Work-stealing in ForkJoinPool
  • ForkJoinTask state machine
  • RecursiveTask vs RecursiveAction
  • Parallel Fibonacci Calculator
  • Fork/Join vs. Compute
  • Parallel merge sort
  • Canceling a task
  • Visibility guarantees with fork/join
  • Placing limits on forking
  • BigInteger.parallelMultiply()
  • Use cases of fork/join
• 10 Avoiding Liveness Hazards
  • 10.1 Deadlock
    • The drinking philosophers
    • Causing a deadlock amongst philosophers
    • Resolving deadlocks
    • Discovering deadlocks
    • Lock-ordering deadlocks
    • Defining a global ordering
    • Dynamic lock order deadlocks
    • Defining order on dynamic locks
    • Checking whether locks are held
    • Imposing a natural order
    • Deadlock between cooperating objects
    • Open calls and alien methods
      • Example in Vector
    • Resource deadlocks
    • Thread-starvation deadlocks
  • 10.2 Avoiding and diagnosing deadlocks
    • Avoiding multiple locks
    • Using open calls
    • Unit testing for lock ordering deadlocks
    • Adding a sleep to cause deadlocks
    • Verifying thread deadlocks
    • Timed lock attempts
    • Deadlock analysis with thread dumps
    • Thread Dump Caveats
    • Deadlocks in Virtual Threads
  • 10.3 Livelock
• 11 Testing Concurrent Programs
  • How to test concurrent code
  • BankAccount Example
  • Simple race condition
  • Types of concurrent tests
  • 11.1 Testing for correctness
    • Checking for data races
    • Automatic tooling
      • JChord
      • JavaRaceFinder
      • FindBugs
      • IntelliJ IDEA
      • False positives
    • Testing through bulk updates
    • Server HotSpot interference
    • Testing pitfalls
    • Controlling HotSpot and JIT
    • Turning off optimizations
    • Randomizing bulk operations
    • Testing field visibility
    • Single updates, with time delays
    • Pros and cons of various approaches
    • Examples of testing broken code
    • Testing for deadlocks
  • 11.2 Testing for performance
    • HotSpot tricks
      • Loop unrolling
      • Useless code elimination
      • Inlining of method calls
      • Lock eliding
      • Lock coarsening
      • Eliminating object creation
    • HotSpot interference in microbenchmarks
    • HotSpot method call threshold
    • HotSpot compile time
    • Getting the fastest most optimized code
    • MathRandomTest

Day 4

• 12 Performance and Scalability
  • 12.1 Thinking about performance
    • Effects of serial sections and locking
    • Performance vs scalability
    • How fast vs how much
    • Evaluating performance tradeoffs
  • 12.2 Amdahl's and Little's laws
    • Formula for Amdahl's Law
    • Utilization according to Amdahl
    • Maximum useful cores
    • Problems with Amdahl's law in practice
    • Formula for Little's Law
    • Applying Little's Law in practice
    • How threading relates to Little's Law
  • 12.3 Costs introduced by threads
    • Cache invalidation
    • Locking and unlocking
    • Memory barriers
  • 12.4 Reducing lock contention
    • Exclusive locks
    • Narrowing lock scope
    • Using ConcurrentHashMap
    • Performance comparisons
    • Reducing lock granularity
    • Lock splitting
      • in LinkedBlockingQueue
      • in ConcurrentLinkedQueue
    • Lock striping
      • in ConcurrentHashMap
      • in LongAdder
    • Alternatives to Exclusive Locks
      • ReadWriteLock
      • StampedLock
      • Concurrent collections
      • CopyOnWrite collections for mostly reads
      • Immutable objects
      • Atomic classes
      • LongAdder and LongAccumulator
    • How to monitor CPU utilization
    • Reasons why CPUs might not be loaded
    • How to find "hot locks"
    • Hotspot options for lock performance
• 13 Explicit Locks
  • 13.1 Lock and ReentrantLock
    • ReentrantLock implementation
    • Using the owned lock
    • Using try-finally
    • tryLock and timed locks
    • Using try-lock to avoid deadlocks
    • Interruptible locking
  • 13.2 Performance considerations
    • Java 5 vs Java 6 performance
    • Throughput on contended locks
    • Uncontended performance
    • Heavily contended locks
  • 13.3 Fairness
    • Standard non-fair locking
    • Round-robin by OS
    • Barging
    • Fair Owned Locks in Java
    • Throughput of fair locks
  • 13.4 Synchronized vs ReentrantLock
    • Memory semantics
    • Ease of use
    • Prefer synchronized
    • Which to use with Virtual Threads
  • 13.5 Read-write locks
    • ReadWriteLock interface
    • Understanding system to avoid starvation
    • ReadWriteLock vs synchronzied/volatile
    • Up and downgrading locks
  • 13.6 StampedLock
    • What is StampedLock?
    • Pessimistic Exclusive Lock
    • Pessimistic Non-Exclusive Lock
    • Optimistic Non-Exclusive Read (no lock)
    • Writing with a StampedLock
    • Optimistic reading with a StampedLock
• 14 Building Custom Synchronizers
  • 14.1 Managing state dependence
    • Single-threaded vs multi-threaded
    • Structure of blocking state-dependent actions
    • Example using bounded queues
    • Introducing condition queues
      • With monitor locks
  • 14.2 Using condition queues
    • Condition predicate
    • Lock
    • Condition queue
    • Waking up too soon
    • Missed signals
      • InterruptedException
    • notify() vs notifyAll()
    • Encapsulating condition queues
    • How wait() works for Virtual Threads
  • 14.3 Explicit condition objects
    • Condition interface
    • Benefits of explicit condition queues
    • Timed conditions
  • 14.4 AbstractQueuedSynchronizer (AQS)
    • Basis for other synchronizers
  • 14.4 ManagedBlocker
    • Desired parallelism in ForkJoinPool
    • ManagedUnboundedQueue
    • Where ManagedBlocker is used in JDK
• 15 Atomic Variables and Nonblocking Synchronization
  • 15.1 Disadvantages of locking
    • Elimination of uncontended intrinsic locks
    • Volatile vs locking performance
    • Priority inversion
    • Volatile flushing
  • 15.2 Hardware support for concurrency
    • Optimistic locking
    • Compare-and-Swap (CAS)
    • Compare-and-Set
    • CAS support in the JVM
    • Managing conflicts with CAS
    • Using "Unsafe" to access memory directly
    • Java 9 VarHandles Instead of Unsafe
    • Shared cache lines
    • Performance advantage of padding
  • 15.3 Atomic variable classes
    • Optimistic locking classes
    • Very fast when not too much contention
    • Types of atomic classes
    • How do atomics work?
    • Atomic array classes
  • 15.4 Nonblocking algorithms
    • Definition of lock-free and wait-free
    • Nonblocking stack
    • Doing speculative work
    • accumulateAndGet()
    • Position with AtomicReference
    • Atomic field updaters
    • Updating with VarHandles
    • compareAndExchange
  • 15.5 Striped64
    • How it works
    • Memory Usage
    • LongAdder
      • Performance
    • LongAccumulator
    • BitUtils for Fast Positions
• 16 Conclusion
  • Tips on where to learn more
  • Thank you!