August 15, 2023

Scenario: Matching data through multiple passes using Map/Reduce components – Docs for ESB 6.x

Scenario: Matching data through multiple passes using Map/Reduce components

This scenario applies only to a subscription-based Talend Platform solution with Big data or Talend Data Fabric.

Note that
Talend
Map/Reduce components are available only to users
who subscribed to Big Data.

This scenario shows how to create a
Talend
Map/Reduce Job to match data by
using Map/Reduce components. It generates Map/Reduce code and runs right in
Hadoop.

use_case-mr_tmatchgroup.png

The Job in this scenario, groups similar customer records by running through two
subsequent matching passes (tMatchGroup components) and
outputs the calculated matches in groups. Each pass provides its matches to the pass
that follows in order for the latter to add more matches identified with new rules and
blocking keys.

This Job is a duplication of the Standard data
integration Job described in Scenario 2: Matching customer data through multiple passes where standard components are replaced with Map/Reduce components.

You can use
Talend Studio
to automatically
convert the standard Job in the previous section to a Map/Reduce Job. This way, you do
not need to redefine the settings of the components in the Job.

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


Document get from Talend https://help.talend.com
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