The document discusses Java Batch (JSR-352), which specifies an application programming model for batch processing. It provides common requirements like logging, checkpointing, and transaction management. JSR-352 defines a job specification language and Java programming model. It describes batch job, step, and application concepts. The specification targets Java SE and EE platforms and requires Java 6 or higher. It works with dependency injection containers.
Functional Programming for OO Programmers (part 1)Calvin Cheng
The Why and Benefits of Functional Programming paradigm. Part 2 with source code can be found here: http://www.slideshare.net/calvinchengx/functional-programming-for-oo-programmers-part-2
Related source code https://github.com/calvinchengx/learnhaskell
Funambol Automated Tests for SyncML ClientsFunambol
The presentation shows how an automated test for native SyncML clients works and how to develop it. You'll learn how to get the logs from the devices, assembly the test, run it and check that Funambol server and synclets do not break between a release and another, or after committing a piece of code. Watch this presentation if you want to improve the automated tests for SyncML devices
This presentation shows introduction to performance testing open source tool Gatling.
I am working on this tool from more than a year now and loved it's load testing features.
It uncovered many performance issues in our web based software service application.
I made and presented these slides to 20 QA people audience in our organization to show basics of Gatling tool. It also covers main facilities of Gatling for effective performance testing.
Thanks,
er.viral.jain@gmail.com
Functional Programming for OO Programmers (part 1)Calvin Cheng
The Why and Benefits of Functional Programming paradigm. Part 2 with source code can be found here: http://www.slideshare.net/calvinchengx/functional-programming-for-oo-programmers-part-2
Related source code https://github.com/calvinchengx/learnhaskell
Funambol Automated Tests for SyncML ClientsFunambol
The presentation shows how an automated test for native SyncML clients works and how to develop it. You'll learn how to get the logs from the devices, assembly the test, run it and check that Funambol server and synclets do not break between a release and another, or after committing a piece of code. Watch this presentation if you want to improve the automated tests for SyncML devices
This presentation shows introduction to performance testing open source tool Gatling.
I am working on this tool from more than a year now and loved it's load testing features.
It uncovered many performance issues in our web based software service application.
I made and presented these slides to 20 QA people audience in our organization to show basics of Gatling tool. It also covers main facilities of Gatling for effective performance testing.
Thanks,
er.viral.jain@gmail.com
Why should a Java programmer shifts towards Functional Programming ParadigmTech Triveni
Functional programming, a buzz word these days. Everyone is trying to learn it. A few functional programming languages are getting attraction and are getting used in the production too such as Scala, Haskell, Clojure and so on. And Even Java has already introduced a few concepts to support functional programming which are Lambdas, Functional Interfaces, Streams, etc. Now the question comes, why should a Java programmer needs to shift towards functional programming.
Java has a very big community and using imperative programming from the last 2 decades. It needs a very solid reason to shift towards the functional programming paradigm. The functional programming paradigm focuses on some key concepts like immutability, higher-order functions and so on and it has a moderate learning curve, but if we can get benefit out of it, then there is no harm in learning functional.
In this talk we will see, what are the benefits we get when we follow the functional programming paradigm in Java, how it makes the developer life easy. We will discuss the comparison between the imperative code vs functional code with some examples.
We will discuss the transition from imperative coding to functional coding with some code examples. This talk will be good for the people who really want to switch to functional programming and want to know how to use that in Java.
Performance Testing is a type of testing to ensure software applications will perform well under their expected workload.
It evaluates the quality or capability of a product. Take your Performance Tests to next level with Gatling!
Zen and the Art of REST API documentation - MuCon London 2015Steve Judd
Struggling to document your APIs? Still using a wiki page to do it? Watch this presentation and learn the secrets of documenting REST APIs!
One of the secrets to a successful Microservices application is the quality of its APIs - so using a decent tool to help develop them is essential; without the right tool, producing APIs can become as tedious as reading through a dump file. This presentation introduces a selection of opensource tools intended to help with not just documenting APIs but designing and testing them as well. Tools covered will include: Swagger, RAML, Spring RestDocs and Apiary.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight dsl written in scala by which you can treat your performance test as a production code means you can easily write a readable code to test the performance of an application it s a framework based on Scala, Akka and Netty.
Flink Forward Berlin 2018: Thomas Weise & Aljoscha Krettek - "Python Streamin...Flink Forward
Python is popular amongst data scientists and engineers for data processing tasks. The big data ecosystem has traditionally been rather JVM centric. Often Java (or Scala) are the only viable option to implement data processing pipelines. That sometimes poses an adoption barrier for organizations that have already invested in other language ecosystems. The Apache Beam project provides a unified programming model for data processing and its ongoing portability effort aims to enable multiple language SDKs (currently Java, Python and Go) on a common set of runners. The combination of Python streaming on the Apache Flink runner is one example. Let’s take a look how the Flink runner translates the Beam model into the native DataStream (or DataSet) API, how the runner is changing to support portable pipelines, how Python user code execution is coordinated with gRPC based services and how a sample pipeline runs on Flink.
Agile has democratized software architecture, taking it out of the hands of the few and putting it into the hands of the many. But architecture is a complex thing, and there are lots of mines in the meadow. This presentation provides some key things to keep in mind as you contribute to the evolution of your Rails application.
JDK.IO 2016 (http://jdk.io)
Java EE 7 introduced a new batch processing API. This session will go over how to use the batch processing API introduced with Java EE 7. This API is makes it easy to implement long running data/compute intensive jobs which need to be scheduled or initiated on-demand. Basics of the API will be demonstrated via code samples. The API will also be compared to Spring Batching and Hadoop to provide context and guidance on when these technologies are appropriate.
Why should a Java programmer shifts towards Functional Programming ParadigmTech Triveni
Functional programming, a buzz word these days. Everyone is trying to learn it. A few functional programming languages are getting attraction and are getting used in the production too such as Scala, Haskell, Clojure and so on. And Even Java has already introduced a few concepts to support functional programming which are Lambdas, Functional Interfaces, Streams, etc. Now the question comes, why should a Java programmer needs to shift towards functional programming.
Java has a very big community and using imperative programming from the last 2 decades. It needs a very solid reason to shift towards the functional programming paradigm. The functional programming paradigm focuses on some key concepts like immutability, higher-order functions and so on and it has a moderate learning curve, but if we can get benefit out of it, then there is no harm in learning functional.
In this talk we will see, what are the benefits we get when we follow the functional programming paradigm in Java, how it makes the developer life easy. We will discuss the comparison between the imperative code vs functional code with some examples.
We will discuss the transition from imperative coding to functional coding with some code examples. This talk will be good for the people who really want to switch to functional programming and want to know how to use that in Java.
Performance Testing is a type of testing to ensure software applications will perform well under their expected workload.
It evaluates the quality or capability of a product. Take your Performance Tests to next level with Gatling!
Zen and the Art of REST API documentation - MuCon London 2015Steve Judd
Struggling to document your APIs? Still using a wiki page to do it? Watch this presentation and learn the secrets of documenting REST APIs!
One of the secrets to a successful Microservices application is the quality of its APIs - so using a decent tool to help develop them is essential; without the right tool, producing APIs can become as tedious as reading through a dump file. This presentation introduces a selection of opensource tools intended to help with not just documenting APIs but designing and testing them as well. Tools covered will include: Swagger, RAML, Spring RestDocs and Apiary.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight dsl written in scala by which you can treat your performance test as a production code means you can easily write a readable code to test the performance of an application it s a framework based on Scala, Akka and Netty.
Flink Forward Berlin 2018: Thomas Weise & Aljoscha Krettek - "Python Streamin...Flink Forward
Python is popular amongst data scientists and engineers for data processing tasks. The big data ecosystem has traditionally been rather JVM centric. Often Java (or Scala) are the only viable option to implement data processing pipelines. That sometimes poses an adoption barrier for organizations that have already invested in other language ecosystems. The Apache Beam project provides a unified programming model for data processing and its ongoing portability effort aims to enable multiple language SDKs (currently Java, Python and Go) on a common set of runners. The combination of Python streaming on the Apache Flink runner is one example. Let’s take a look how the Flink runner translates the Beam model into the native DataStream (or DataSet) API, how the runner is changing to support portable pipelines, how Python user code execution is coordinated with gRPC based services and how a sample pipeline runs on Flink.
Agile has democratized software architecture, taking it out of the hands of the few and putting it into the hands of the many. But architecture is a complex thing, and there are lots of mines in the meadow. This presentation provides some key things to keep in mind as you contribute to the evolution of your Rails application.
JDK.IO 2016 (http://jdk.io)
Java EE 7 introduced a new batch processing API. This session will go over how to use the batch processing API introduced with Java EE 7. This API is makes it easy to implement long running data/compute intensive jobs which need to be scheduled or initiated on-demand. Basics of the API will be demonstrated via code samples. The API will also be compared to Spring Batching and Hadoop to provide context and guidance on when these technologies are appropriate.
one of the most interesting project I have ever worked on was a migration project that needed to be handled as a batch process, in this slides we will have an overview of the challenge we had, the choices, why we chosed Spring batch, and have an overview of Spring Batch capabilities, in less than 15 minutes.
This presentation explains the architecture of classic mapreduce or MapReduce 1 in Hadoop, Most of the sides are animated. So please download and read it.
Informatica Power Center - Workflow ManagerZaranTech LLC
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Training Highlights
Focus on Hands on training
30-35 hours of Assignments, Live Case Studies
Video Recordings of sessions provided
Demonstration of Concepts using different tools
One Problem Statement discussed across the Whole training program
Informatica Certification Guidance
Resume prep, Interview Questions provided
Introduction to Data Warehousing, Infomatica Designer
Understand the Transformation, Mapping and Qualifier
Informatica Advanced Features
Spring Day | Spring and Scala | Eberhard WolffJAX London
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Spring is widely used in the Java world - but does it make any sense to combine it with Scala? This talk gives an answer and shows how and why Spring is useful in the Scala world. All areas of Spring such as Dependency Injection, Aspect-Oriented Programming and the Portable Service Abstraction as well as Spring MVC are covered.
Building Continuous Application with Structured Streaming and Real-Time Data ...Databricks
One of the biggest challenges in data science is to build a continuous data application which delivers results rapidly and reliably. Spark Streaming offers a powerful solution for real-time data processing. However, the challenge remains in how to connect them with various continuous and real-time data sources, guaranteeing the responsiveness and reliability of data applications.
In this talk, Nan and Arijit will summarize their experiences learned from serving the real-time Spark-based data analytic solutions on Azure HDInsight. Their solution seamlessly integrates Spark and Azure EventHubs which is a hyper-scale telemetry ingestion service enabling users to ingress massive amounts of telemetry into the cloud and read the data from multiple applications using publish-subscribe semantics.
They’ll will cover three topics: bridging the gap of data communication model in Spark and data source, accommodating Spark to rate control and message addressing of data source, and the co-design of fault tolerance Mechanisms. This talk will share the insights on how to build continuous data applications with Spark and boost more availabilities of connectors for Spark and different real-time data sources.
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Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
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A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
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Venez le découvrir lors de cette session ignite
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
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Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
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Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
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In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
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6. JSR-352[Final Release]
Describes
Job Specification Language
Java Programming Model
Runtime environment of Batch Applications
Targets both Java SE and Java EE platforms.
Requires Java 6 or higher.
Works with dependency Injection(DI)
containers
12. Step
Each step may be either a chunk type step or
batchlet type step
Chunk
Periodically Checkpointed
ItemBased
Batchlet
Task-oriented
13. Chunk
Must have only one ItemReader and ItemWriter
ItemProcessor is optional but only a single
processor element may be specified.
Each Chunk is processed in a separate transaction
ItemWriter is called once per chunk
BatchRuntime writes checkpointinfo to
JobRepository
18. Transition Elements
Transition Elements
next - directs execution flow to the next execution
element.
fail - causes a job to end with FAILED batch status.
end - causes a job to end with COMPLETED batch
status.
stop - causes a job to end with STOPPED batch
status.
22. Batch and Exit Status
Batch Status : Runtime Status Value
STARTING
STARTED
STOPPING
STOPPED
FAILED
COMPLETED
ABANDONED
Exit Status: User-defined
Any String
23. Job XML Substituion
Job XML supports attribute value substitution
Substitutions expressions may include a default
value using the "?:" operator
Value is substituted with
• Any resolvable Job Properties
• Job Parameters
• Partition Plan
• System Properties
25. Batch Programming Model
Described by interfaces, abstract classes, and
field annotations.
Javax.batch package and subpackages
26. Batch Property
Must be used with the standard @Inject
annotation (javax.inject.Inject).
Used to assign batch artifact property values
from Job XML to the batch artifact itself
27. Batch Contexts
StepContext and JobContext are accessible via
@Injection
Batch Runtime must ensure the correct
context object is injected according to the job
or step currently executing.
28. Job Metrics
Chunk-type step metrics are avaliable through
the StepExecution runtime object.
READ_COUNT,
WRITE_COUNT,
COMMIT_COUNT,
ROLLBACK_COUNT,
READ_SKIP_COUNT,
PROCESS_SKIP_COUNT,
FILTER_COUNT,
WRITE_SKIP_COUNT
34. IBM Extensions
Built on Liberty Profile as the Java Runtime Server
Liberty Profile 8.5.5.6 and above
Extensions:
Rest interface to JobOperator
Command line client for job submission
Multi-JVM support: Jobs or partitions can be
executed in a distributed topology