This document discusses various programming paradigms and concurrency concepts in Java. It covers single process and multi-process programming, as well as multi-core and multi-threaded programming. Key concepts discussed include processes, threads, synchronization, deadlocks, and high-level concurrency objects like locks, executors, and concurrent collections. The document provides examples of implementing threads using subclasses and interfaces, and communicating between threads using interrupts, joins, and guarded blocks.
This session discusses about the basic building blocks of Concurrent Programming in Java, which include:
synchronisation part 2, synchronized methods, intrinsic locks, atomic access, liveness, deadlock, starvation, livelock, guarded blocks, immutable objects, synchronized class example, strategy for defining immutable objects
Concurrency Programming in Java - 05 - Processes and Threads, Thread Objects,...Sachintha Gunasena
This session discusses about the basic building blocks of Concurrent Programming in Java, which include:
processes, threads, how to define a thread, how to start a thread, how to sleep a thread, thread interrupt, interrupt status flag, joins, simple thread example, synchronization part 1, thread interference, memory consistency errors
Threads And Synchronization in C#
Concept about Threads And Synchronization in C#
it will help you about this concept
feel free
Download free programming applications on
http://www.androidapplications.xyz
This session discusses about the basic building blocks of Concurrent Programming in Java, which include:
synchronisation part 2, synchronized methods, intrinsic locks, atomic access, liveness, deadlock, starvation, livelock, guarded blocks, immutable objects, synchronized class example, strategy for defining immutable objects
Concurrency Programming in Java - 05 - Processes and Threads, Thread Objects,...Sachintha Gunasena
This session discusses about the basic building blocks of Concurrent Programming in Java, which include:
processes, threads, how to define a thread, how to start a thread, how to sleep a thread, thread interrupt, interrupt status flag, joins, simple thread example, synchronization part 1, thread interference, memory consistency errors
Threads And Synchronization in C#
Concept about Threads And Synchronization in C#
it will help you about this concept
feel free
Download free programming applications on
http://www.androidapplications.xyz
Lecture 10 from the IAG0040 Java course in TTÜ.
See the accompanying source code written during the lectures: https://github.com/angryziber/java-course
Advanced Introduction to Java Multi-Threading - Full (chok)choksheak
Designed for the beginning Java developer to grasp advanced Java multi-threading concepts quickly. Talks mainly about the Java Memory Model and the Concurrent Utilities. This presentation is Java-specific and we intentionally omit general non-Java-specific details, such as hardware architecture, OS, native threads, algorithms, and general software design principles etc.
This presentation is about advanced multithreading and concurrency in Java. I have tried my best to explain the concepts with code. Feel free to reach me if you have any questions or concerns.
Java has a solid Memory Model, and there are a couple of excellent libraries for concurrency. When you start working with threads however, pitfalls start appearing - especially if the program is supposed to be fast and correct. This session shows proven solutions for some typical problems, showing how to view program code from a concurrency perspective: Which threads share which data, and how? How to reduce the impact of locks? How to avoid them altogether - and when is that worth it?
Concurrency Programming in Java - 01 - Introduction to Concurrency ProgrammingSachintha Gunasena
This session discusses a basic high-level introduction to concurrency programming with Java which include:
programming basics, OOP concepts, concurrency, concurrent programming, parallel computing, concurrent vs parallel, why concurrency, real world example, terms, Moore's Law, Amdahl's Law, types of parallel computation, MIMD Variants, shared memory model, distributed memory model, client server model, scoop mechanism, scoop preview - a sequential program, in a concurrent setting - using scoop, programming then & now, sequential programming, concurrent programming,
Slide deck from my presentation on multi-threading with .NET. The presentation covers from beginner onwards and looks at current technologies (i.e. pre .NET 4.0) specifically.
What makes this extra special is the entire process of how I prepared for it, from finding content to slide deck layout to presentation prep is documented at: http://www.sadev.co.za/content/how-i-build-presentations-series-index
Multithreading in java is a process of executing multiple threads simultaneously. The thread is basically a lightweight sub-process, the smallest unit of processing. Multiprocessing and multithreading, both are used to achieve multitasking.
Lecture 10 from the IAG0040 Java course in TTÜ.
See the accompanying source code written during the lectures: https://github.com/angryziber/java-course
Advanced Introduction to Java Multi-Threading - Full (chok)choksheak
Designed for the beginning Java developer to grasp advanced Java multi-threading concepts quickly. Talks mainly about the Java Memory Model and the Concurrent Utilities. This presentation is Java-specific and we intentionally omit general non-Java-specific details, such as hardware architecture, OS, native threads, algorithms, and general software design principles etc.
This presentation is about advanced multithreading and concurrency in Java. I have tried my best to explain the concepts with code. Feel free to reach me if you have any questions or concerns.
Java has a solid Memory Model, and there are a couple of excellent libraries for concurrency. When you start working with threads however, pitfalls start appearing - especially if the program is supposed to be fast and correct. This session shows proven solutions for some typical problems, showing how to view program code from a concurrency perspective: Which threads share which data, and how? How to reduce the impact of locks? How to avoid them altogether - and when is that worth it?
Concurrency Programming in Java - 01 - Introduction to Concurrency ProgrammingSachintha Gunasena
This session discusses a basic high-level introduction to concurrency programming with Java which include:
programming basics, OOP concepts, concurrency, concurrent programming, parallel computing, concurrent vs parallel, why concurrency, real world example, terms, Moore's Law, Amdahl's Law, types of parallel computation, MIMD Variants, shared memory model, distributed memory model, client server model, scoop mechanism, scoop preview - a sequential program, in a concurrent setting - using scoop, programming then & now, sequential programming, concurrent programming,
Slide deck from my presentation on multi-threading with .NET. The presentation covers from beginner onwards and looks at current technologies (i.e. pre .NET 4.0) specifically.
What makes this extra special is the entire process of how I prepared for it, from finding content to slide deck layout to presentation prep is documented at: http://www.sadev.co.za/content/how-i-build-presentations-series-index
Multithreading in java is a process of executing multiple threads simultaneously. The thread is basically a lightweight sub-process, the smallest unit of processing. Multiprocessing and multithreading, both are used to achieve multitasking.
Thread vs Process
scheduling
synchronization
The thread begins execution with the C/C run-time library startup code.
The startup code calls your main or WinMain and execution continues until the main function returns and the C/C library code calls ExitProcess.
Reflection is the ability of a managed code to read its own metadata for the purpose of finding assemblies, modules and type information at runtime. The classes that give access to the metadata of a running program are in System.Reflection.
System.Reflection namespace defines the following types to analyze the module's metadata of an assembly:
Assembly, Module, Enum, ParameterInfo, MemberInfo, Type, MethodInfo, ConstructorInfo, FieldInfo, EventInfo, and PropertyInfo
In 1965, Dijkstra proposed a new and very significant technique for managing concurrent processes by using the value of a simple integer variable to synchronize the progress of interacting processes.
This integer variable is called semaphore. So it is basically a synchronizing tool and is accessed only through two low standard atomic operations, wait and signal designated by P() and V() respectively.
The classical definition of wait and signal are :
Wait : decrement the value of its argument S as soon as it would become non-negative.
Signal : increment the value of its argument, S as an individual operation.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
3. Process
• Process
A process runs independently and isolated of
other processes. It cannot directly access
shared data in other processes. The resources
of the process are allocated to it via the
operating system, e.g. memory and CPU time.
4. Java Process
Objects
• ADTs, aggregate components, JavaBeans, monitors,
business objects, remote RMI objects, subsystems, ...
• May be grouped according to structure, role, ...
• Usable across multiple activities — focus on SAFETY
Activities
• Messages, call chains, threads, sessions, scenarios,
scripts, workflows, use cases, transactions, data flows,
mobile computations
5. Thread
• Threads are so called lightweight processes
which have their own call stack but an access
shared data. Every thread has its own memory
cache. If a thread reads shared data it stores
this data in its own memory cache. A thread
can re-read the shared data
6. What is The Gain
• Amdahl's Law
• It states that a small portion of the program which
cannot be parallelized will limit the overall speed-up
available from parallelization.
• A program solving a large mathematical or engineering
problem will typically consist of several parallelizable
parts and several non-parallelizable (sequential) parts.
If p is the fraction of running time a sequential program
spends on non-parallelizable parts, then
• S = 1/p
7. How much is the speed up
• If the sequential portion of a program accounts
for 10% of the runtime, we can get no more than
a 10× speed-up, regardless of how many
processors are added. This puts an upper limit on
the usefulness of adding more parallel execution
units. "When a task cannot be partitioned
because of sequential constraints, the application
of more effort has no effect on the schedule. The
bearing of a child takes nine months, no matter
how many women are assigned
8. How does Java help to Parallel
Programming
• Has Threads since its inception
• Threads have their own stack. But uses heap
of the JVM
• Has many constructs to control the
concurrency
• Programmer knowledge is very critical
10. Thread Class
Constructors
• Thread(Runnable r) constructs so run() calls r.run()
• — Other versions allow names, ThreadGroup placement
Principal methods
• start() activates run() then returns to caller
• isAlive() returns true if started but not stopped
• join() waits for termination (optional timeout)
• interrupt() breaks out of wait, sleep, or join
• isInterrupted() returns interruption state
• getPriority() returns current scheduling priority
• setPriority(int priorityFromONEtoTEN) sets it
11. How to Implement a Thread
• Subclass Thread. The Thread class itself
implements Runnable, though its run method
does nothing. An application can subclass
Thread, providing its own implementation of
run
12. Thread Subclass
public class HelloThread extends Thread {
public void run() {
System.out.println("Hello from a thread!");
}
public static void main(String args[]) {
(new HelloThread()).start();
}
}
13. Implement Runnable Interface
public class HelloRunnable implements Runnable
{
public void run() {
System.out.println("Hello from a thread!"); }
public static void main(String args[]) {
(new HelloRunnable()).start();
}
}
14. Pausing while executing
• Thread.sleep causes the current thread to
suspend execution for a specified period.
• This is an efficient means of making processor
time available to the other threads of an
application or other applications that might be
running on a computer system. The sleep
method can also be used for pacing
15. Thread Management
• To directly control thread creation and
management, simply instantiate Thread each
time the application needs to initiate an
asynchronous task.
• To abstract thread management from the rest
of your application, pass the application's
tasks to an executor.
16. Sleep Example
• main declares that it throws
InterruptedException. This is an exception that
sleep throws when another thread interrupts
the current thread while sleep is active. Since
this application has not defined another
thread to cause the interrupt, it doesn't
bother to catch InterruptedException.
17. Communicating with Thread
• Interrupts
• An interrupt is an indication to a thread that it
should stop what it is doing and do something
else. It's up to the programmer to decide
exactly how a thread responds to an interrupt,
but it is very common for the thread to
terminate. This is the usage emphasized in this
lesson.
18. Interrupt requirement
• A thread sends an interrupt by invoking
interrupt on the Thread object for the thread
to be interrupted. For the interrupt
mechanism to work correctly, the interrupted
thread must support its own interruption.
19. Interrupt Status
• The interrupt mechanism is implemented
using an internal flag known as the interrupt
status. Invoking Thread.interrupt sets this flag.
When a thread checks for an interrupt by
invoking the static method
Thread.interrupted, interrupt status is cleared.
The non-static isInterrupted method, which is
used by one thread to query the interrupt
status of another, does not change the
interrupt status flag.
20. Interrupted Exception and Status
• By convention, any method that exits by
throwing an InterruptedException clears
interrupt status when it does so. However, it's
always possible that interrupt status will
immediately be set again, by another thread
invoking interrupt.
21. Thread Collaboration
• The join method allows one thread to wait for the
completion of another. If t is a Thread object whose
thread is currently executing,
• t.join();
• causes the current thread to pause execution until t's
thread terminates. Overloads of join allow the
programmer to specify a waiting period. However, as
with sleep, join is dependent on the OS for timing, so
you should not assume that join will wait exactly as
long as you specify.
• Like sleep, join responds to an interrupt by exiting with
an InterruptedException.
23. Synchronization
• Threads communicate primarily by sharing
access to fields and the objects reference
fields refer to. This form of communication is
extremely efficient, but makes two kinds of
errors possible: thread interference and
memory consistency errors. The tool needed
to prevent these errors is synchronization.
24. Synchronization Mechanisms
• Thread Interference describes how errors are introduced
when multiple threads access shared data.
• Memory Consistency Errors describes errors that result
from inconsistent views of shared memory.
• Synchronized Methods describes a simple idiom that can
effectively prevent thread interference and memory
consistency errors.
• Implicit Locks and Synchronization describes a more
general synchronization idiom, and describes how
synchronization is based on implicit locks.
• Atomic Access talks about the general idea of operations
that can't be interfered with by other threads.
25. Synchronization Libraries
Semaphores
Maintain count of the number of threads allowed to pass
Latches
Boolean conditions that are set once, ever
Barriers
Counters that cause all threads to wait until all have
finished
Reentrant Locks
Java-style locks allowing multiple acquisition by same
thread, but that may be acquired and released as needed
Mutexes
Non-reentrant locks
Read/Write Locks
Pairs of conditions in which the readLock may be shared,
but the writeLock is exclusive
26. Semaphores
Conceptually serve as permit holders
• Construct with an initial number of permits (usually 0)
• require waits for a permit to be available, then takes one
• release adds a permit But in normal implementations, no actual
permits change hands.
• The semaphore just maintains the current count.
• Enables very efficient implementation
Applications
• Isolating wait sets in buffers, resource controllers
• Designs that would otherwise encounter missed signals
— Where one thread signals before the other has even
started waiting
— Semaphores ‘remember’ how many times they were signalled
27. Counter Using Semaphores
class BoundedCounterUsingSemaphores {
long count_ = MIN;
Sync decPermits_= new Semaphore(0);
Sync incPermits_= new Semaphore(MAX-MIN);
synchronized long value() { return count_; }
void inc() throws InterruptedException {
incPermits_.acquire();
synchronized(this) { ++count_; }
decPermits_.release();
}
void dec() throws InterruptedException {
decPermits_.acquire();
synchronized(this) { --count_; }
incPermits_.release();
}
}
28. Using Latches
• Conditions starting out false, but once set
true, remain true forever
• Initialization flags
• End-of-stream conditions
• Thread termination
• Event occurrence
29. Using Barrier Conditions
Count-based latches
• Initialize with a fixed count
• Each release monotonically decrements count
• All acquires pass when count reaches zero
30. Liveness
• A concurrent application's ability to execute in
a timely manner is known as its liveness. This
section describes the most common kind of
liveness problem, deadlock, and goes on to
briefly describe two other liveness problems,
starvation and livelock.
31. Deadlock
• Deadlock describes a situation where two or
more threads are blocked forever, waiting for
each other. Here's an example.
• Alphonse and Gaston are friends, and great
believers in courtesy. A strict rule of courtesy is
that when you bow to a friend, you must remain
bowed until your friend has a chance to return
the bow. Unfortunately, this rule does not
account for the possibility that two friends might
bow to each other at the same time.
32. Starvation and Livelock
• Starvation describes a situation where a thread is
unable to gain regular access to shared resources
and is unable to make progress. This happens
when shared resources are made unavailable for
long periods by "greedy" threads.
• A thread often acts in response to the action of
another thread. If the other thread's action is also
a response to the action of another thread, then
livelock may result.
33. Guarded Blocks
• Threads often have to coordinate their
actions. The most common coordination idiom
is the guarded block. Such a block begins by
polling a condition that must be true before
the block can proceed. There are a number of
steps to follow in order to do this correctly.
34. Guarded Block (cont..)
• Constant polling for Condition
• Use wait/notify method
• Immutable Objects
• Producer Consumer Example
• A Synchronized Class Example
35. Immutable Object
1. Don't provide "setter" methods — methods that modify fields or
objects referred to by fields.
2. Make all fields final and private.
3. Don't allow subclasses to override methods. The simplest way to
do this is to declare the class as final. A more sophisticated
approach is to make the constructor private and construct
instances in factory methods.
4. If the instance fields include references to mutable objects, don't
allow those objects to be changed:
– Don't provide methods that modify the mutable objects.
– Don't share references to the mutable objects. Never store
references to external, mutable objects passed to the constructor; if
necessary, create copies, and store references to the copies.
Similarly, create copies of your internal mutable objects when
necessary to avoid returning the originals in your methods.
36. High Level Concurrency Objects
• Lock objects support locking idioms that simplify many
concurrent applications.
• Executors define a high-level API for launching and
managing threads. Executor implementations provided by
java.util.concurrent provide thread pool management
suitable for large-scale applications.
• Concurrent collections make it easier to manage large
collections of data, and can greatly reduce the need for
synchronization.
• Atomic variables have features that minimize
synchronization and help avoid memory consistency errors.
• ThreadLocalRandom (in JDK 7) provides efficient generation
of pseudorandom numbers from multiple threads.
37. Lock Objects
• Only one thread can own a implicit Lock object at a
time. Lock objects also support a wait/notify
mechanism, through their associated Condition
objects.
• The biggest advantage of Lock objects over implicit
locks is their ability to back out of an attempt to
acquire a lock. The tryLock method backs out if the
lock is not available immediately or before a timeout
expires (if specified). The lockInterruptibly method
backs out if another thread sends an interrupt before
the lock is acquired.
39. Executors
• In large-scale applications, it makes sense to
separate thread management and creation from
the rest of the application. Objects that
encapsulate these functions are known as
executors.
• Executor Interfaces define the three executor
object types.
• Thread Pools are the most common kind of
executor implementation.
• Fork/Join is a framework (new in JDK 7) for taking
advantage of multiple processors.
40. Executor Interfaces
• The java.util.concurrent package defines three
executor interfaces:
• Executor, a simple interface that supports
launching new tasks.
• ExecutorService, a subinterface of Executor,
which adds features that help manage the
lifecycle, both of the individual tasks and of the
executor itself.
• ScheduledExecutorService, a subinterface of
ExecutorService, supports future and/or periodic
execution of tasks.
41. The Executor Interface
• The Executor interface provides a single
method, execute, designed to be a drop-in
replacement for a common thread-creation
idiom. If r is a Runnable object, and e is an
Executor object you can replace
• (new Thread(r)).start();
• with
• e.execute(r);
42. The ExecutorService Interface
• The ExecutorService interface supplements execute with
a similar, but more versatile submit method. Like
execute, submit accepts Runnable objects, but also
accepts Callable objects, which allow the task to return a
value. The submit method returns a Future object, which
is used to retrieve the Callable return value and to
manage the status of both Callable and Runnable tasks.
• ExecutorService also provides methods for submitting
large collections of Callable objects. Finally,
ExecutorService provides a number of methods for
managing the shutdown of the executor. To support
immediate shutdown, tasks should handle interrupts
correctly.
43. The ScheduledExecutorService
Interface
• The ScheduledExecutorService interface
supplements the methods of its parent
ExecutorService with schedule, which
executes a Runnable or Callable task after a
specified delay. In addition, the interface
defines scheduleAtFixedRate and
scheduleWithFixedDelay, which executes
specified tasks repeatedly, at defined intervals.
44. Thread Pools
• Using worker threads minimizes the overhead
due to thread creation. Thread objects use a
significant amount of memory, and in a large-
scale application, allocating and deallocating
many thread objects creates a significant
memory management overhead.
• Tasks are submitted to the pool via an internal
queue, which holds extra tasks whenever
there are more active tasks than threads.
45. Thread Pools
• newFixedThreadPool
• newCachedThreadPool
• newSingleThreadExecutor
• For customized needs one can construct
• java.util.concurrent.ThreadPoolExecutor or
java.util.concurrent.ScheduledThreadPoolExec
utor
46. Fork/Join
• The fork/join framework is an implementation
of the ExecutorService interface that helps you
take advantage of multiple processors. It is
designed for work that can be broken into
smaller pieces recursively. The goal is to use all
the available processing power to enhance the
performance of your application.
47. Basic Use
• if (my portion of the work is small enough)
– do the work directly
• else
– split my work into two pieces
– invoke the two pieces and wait for the results
• After your ForkJoinTask is ready, create one that
represents all the work to be done and pass it to
the invoke() method of a ForkJoinPool instance.
48. Concurrent Collections
• The java.util.concurrent package includes a
number of additions to the Java Collections
Framework
• BlockingQueue
• ConcurrentMap
• ConcurrentSkipList
• All of these collections help avoid Memory
Consistency Errors by defining a happens-before
relationship between an operation that adds an
object to the collection with subsequent
operations that access or remove that object.
49. Atomic Variables
• The java.util.concurrent.atomic package
defines classes that support atomic operations
on single variables. All classes have get and set
methods that work like reads and writes on
volatile variables.
50. Concurrent Random Numbers
• In JDK 7, java.util.concurrent includes a
convenience class, ThreadLocalRandom, for
applications that expect to use random
numbers from multiple threads or
ForkJoinTasks.
• int r = ThreadLocalRandom.current()
.nextInt(4, 77);
51. Designing Objects for
Concurrency
Patterns for safely representing and managing state
Immutability
• Avoiding interference by avoiding change
Locking
• Guaranteeing exclusive access
State dependence
• What to do when you can’t do anything
Containment
• Hiding internal objects
Splitting
• Separating independent aspects of objects and locks