The document discusses batch job processing in Mule. It describes a use case where a batch job queries a database to retrieve approved users and generates a CSV file with the user account attributes. Batch processing in Mule allows splitting messages into records, performing actions on each record, and reporting results. It is useful for integrating or synchronizing data sets, ETL processes, and handling large amounts of incoming data.

1. Batch Job Processing

2. • THE APPLICATION ILLUSTRATES A USE CASE OF A BATCH
JOB THAT QUERIES A DATABASE TO GET ALL USERS WITH
A STATUS "APPROVED" AND IF ANY EXIST GETS EACH
USER ACCOUNT RECORD AND GENERATES A CSV FILE
USING THE ACCOUNT ATTRIBUTES. THE RESULTING CSV
FILE WILL BE SAVED FOR LATER USE OR IT MAY BE SENT
VIA EMAIL OR SENT TO AN FTP SERVER.
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Batch Processing in Mule
Batch is a Mule construct that provides the ability to process messages in batches.
Within an application, you can initiate a batch job which is a block of code that splits
messages into individual records, performs actions upon each record, then reports
on the results and potentially pushes the processed output to other systems or
queues.

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Batch processing is particularly useful when working with the following scenarios:
Integrating data sets, small or large, streaming or not, to parallel process records
Synchronising data sets between business applications, such as syncing contacts
between Netsuite and Salesforce, effecting “near real-time”data integration
Extracting, transforming and loading (ETL) information into a target system, such as
uploading data from a flat file (CSV) to Hadoop
Handling large quantities of incoming data from an API into a legacy system

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Learn Batch Fundamentals
Mule’s December 2013 release shipped with a major leap forward feature that will
massively change and simplify Mule’s user experience for both SaaS and On-
Premise users. Yes, we are talking about the new Batch jobs. If you need to handle
massive amounts of data, or you’re longing for record based reporting and error
handling, or even if you are all about resilience and reliability with parallel
processing, then this post is for you!

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What's new in Batch
We received great feedback about it and we even have some CloudHub users
happily using it in production! However, we know that the journey of Batch has just
begun and for the Early Access release of Mule 3.5 we added a bunch of
improvements.
Let’s have a look!
https://www.mulesoft.com/exchange#!/batch-process-mule?filters=Business
%20Process%20Administration

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Error handling in Batch
Fact: Batch Jobs are tricky to handle when exceptions raise. The problem is the
huge amounts of data that these jobs are designed to take. If you’re processing 1
million records you simply can’t log everything. Logs would become huge and
unreadable. Not to mention the performance toll it would take. On the other hand, if
you log too little then it’s impossible to know what went wrong, and if 30 thousand
records failed, not knowing what’s wrong with them can be a royal pain. This is a
trade-off not simple to overcome.

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Near real time sync with Batch
Learn how to do Real time sync with Mule ESB. We’ll use several of the newest
features that Mule has to offer – like the improved Poll component with
watermarking and the Batch Module. Finally we’ll use one of our Anypoint
Templates as an example application to illustrate the concepts.

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Near real time sync with Batch
Learn how to do Real time sync with Mule ESB. We’ll use several of the newest
features that Mule has to offer – like the improved Poll component with
watermarking and the Batch Module. Finally we’ll use one of our Anypoint
Templates as an example application to illustrate the concepts.