Normalizing data using Map/Reduce components - 7.1

Processing (Integration)

Version
7.1
Language
English (United States)
Product
Talend Big Data
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Module
Talend Studio
Content
Data Governance > Third-party systems > Processing components (Integration)
Data Quality and Preparation > Third-party systems > Processing components (Integration)
Design and Development > Third-party systems > Processing components (Integration)

This scenario applies only to subscription-based Talend products with Big Data.

For more technologies supported by Talend, see Talend components.

You can produce the Map/Reduce version of the Job described earlier using Map/Reduce components. This Talend Map/Reduce Job generates Map/Reduce code and is run natively in Hadoop.

Note that the Talend Map/Reduce components are available to subscription-based Big Data users only and this scenario can be replicated only with Map/Reduce components.

The sample data used in this scenario is the same as in the scenario explained earlier.

ldap,
  db2, jdbc driver,
grid computing,  talend architecture  ,
content, environment,,
tmap,,
eclipse,
database,java,postgresql,
tmap,
database,java,sybase,
deployment,,
repository,
database,informix,java

Since Talend Studio allows you to convert a Job between its Map/Reduce and Standard (Non Map/Reduce) versions, you can convert the scenario explained earlier to create this Map/Reduce Job. This way, many components used can keep their original settings so as to reduce your workload in designing this Job.

Before starting to replicate this scenario, ensure that you have appropriate rights and permissions to access the Hadoop distribution to be used. Then proceed as follows: