Using parallelization to optimize Job performance - 6.5

Talend Big Data Studio User Guide

EnrichVersion
6.5
EnrichProdName
Talend Big Data
task
Design and Development
EnrichPlatform
Talend Studio

Parallelization in terms of Talend Jobs means to accomplish technical processes through parallel executions. When properly designed, a parallelization-enabled technical process can be completed within a shorter time frame.

Talend Studio allows you to implement different types of parallelization depending on ranging circumstances. These circumstances could be:

  1. Parallel executions of multiple subJobs. For further information, see How to execute multiple subJobs in parallel.

  2. Parallel iterations for reading data. For further information, see How to launch parallel iterations to read data.

  3. Orchestrating executions of subJobs. For further information, see How to orchestrate parallel executions of subJobs.

  4. Speeding-up data writing into a database. For further information, see How to write data in parallel.

  5. Speeding-up processing of a data flow. For further information, see How to enable parallelization of data flows.

Parallelization is an advanced feature and requires basic knowledge about a Talend Job such as how to design and execute a Job or a subJob, how to use components and how to use the different types of connections that link components or Jobs. If you feel that you need to acquire this kind of knowledge, see Designing a Job.