These properties are used to configure tDataShuffling running in the Standard Job framework.
The Standard tDataShuffling component belongs to the Data Quality family.
The component in this framework is available in Talend Data Management Platform, Talend Big Data Platform, Talend Real Time Big Data Platform, Talend Data Services Platform, Talend MDM Platform and in Talend Data Fabric.
Basic settings
Schema and Edit Schema |
A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. When you create a Spark Job, avoid the reserved word line when naming the fields. Click Sync columns to retrieve the schema from the previous component connected in the Job. Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:
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Built-In: You create and store the schema locally for this component only. |
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Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. |
Shuffling columns |
Define the groups of columns to be shuffled:
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Advanced settings
Seed for random generator |
Set a random number if you want to shuffle the data in the same order in each execution of the Job. This field is set to 12345678 by default. Repeating the execution with a different value for this field will shuffle the data in a different order. Keep this field empty if you want the data to be shuffled in random order each time you execute the Job. |
Buffer size |
Type in the size of physical memory, in number of rows, you want to allocate to processed data. |
Partitioning columns |
Add the columns used for partitioning the data. The selected columns separate the shuffling process into small partitions. Only the rows within a partition can be shuffled together. |
tStat Catcher Statistics |
Select this check box to gather the Job processing metadata at the Job level as well as at each component level. |
Usage
Usage rule |
This component is usually used as an intermediate component, and it requires an input component and an output component. |