Aggregating the extracted information - 7.1

Kafka

author
Talend Documentation Team
EnrichVersion
7.1
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Open Studio for Big Data
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > Messaging components (Integration) > Kafka components
Data Quality and Preparation > Third-party systems > Messaging components (Integration) > Kafka components
Design and Development > Third-party systems > Messaging components (Integration) > Kafka components
EnrichPlatform
Talend Studio

Procedure

  1. Double-click tAggregateRow to open its Component view. This component allows you to find out the most popular activity recorded in the received messages.
  2. Click the [...] button next to Edit schema to open the schema editor.
  3. On the output side (right), click the [+] button three times to add three rows and in the Column column, rename them to activity, gender and popularity, respectively.
  4. In the Type column of the popularity row of the output side, select Double.
  5. Click OK to validate these changes and accept the propagation prompted by the pop-up dialog box.
  6. In the Group by table, add two rows by clicking the [+] button twice and configure these two rows as follows to group the outputted data:

    Column

    Description

    Output column

    Select the columns from the output schema to be used as the conditions to group the outputted data. In this example, they are activity and gender.

    Input column position

    Select the columns from the input schema to send data to the output columns you have selected in the Output column column. In this scenario, they are activity and gender.

  7. In the Operations table, add one row by clicking the [+] button once and configure this row as follows to calculate the popularity of each activity:

    Column

    Description

    Output column

    Select the column from the output schema to carry the calculated results. In this scenario, it is popularity.

    Function

    Select the function to be used to process the incoming data. In this scenario, select count. It counts the frequency of each activity in the received messages.

    Input column position

    Select the column from the input schema to provide the data to be processed. In this scenario, it is activity.