Deduplicating entries using Map/Reduce components - 7.3

Processing (Integration)

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7.3
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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)

For more technologies supported by Talend, see Talend components.

This scenario illustrates how to create a Talend Map/Reduce Job to deduplicate entries, that is to say, to use Map/Reduce components to generate Map/Reduce code and run the Job right 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 to be used in this scenario reads as follows:
1;Harry;Ford;68;Albany
2;Franklin;Wilson;79;Juneau
3;Ulysses;Roosevelt;25;Harrisburg
4;Harry;Ford;48;Olympia
5;Martin;Reagan;75;Columbia
6;Woodrow;Roosevelt;63;Harrisburg
7;Grover;McKinley;98;Atlanta
8;John;Taft;93;Montpelier
9;Herbert;Johnson;85;Lincoln
10;Grover;McKinley;33;Lansing

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: