Scenario: Indexing a reference data set in Elasticsearch

Continuous matching

author
Talend Documentation Team
EnrichVersion
6.5
EnrichProdName
Talend Big Data Platform
Talend Data Fabric
Talend Real-Time Big Data Platform
task
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components > Continuous matching components
Design and Development > Third-party systems > Data Quality components > Matching components > Continuous matching components
Data Governance > Third-party systems > Data Quality components > Matching components > Continuous matching components
EnrichPlatform
Talend Studio
Talend Data Stewardship

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

For more technologies supported by Talend, see Talend components.

In this Job, the tMatchIndex component creates an index in Elasticsearch and populates it with a clean and deduplicated data set which contains a list of education centers in Chicago.

After performing all the matching actions on the data set which contains a list of education centers in Chicago, you do not need to restart the matching process from scratch when you get new data records having the same schema. You can index the clean data set in Elasticsearch using tMatchIndex for continuous matching purposes.

Before indexing a reference data set in Elasticsearch: