tReservoirSampling properties - 6.1

Talend Components Reference Guide

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Component family

Data Quality



tReservoirSampling enables you to extract a random sample data from a big data set.


tReservoirSampling extracts a sample from the input data set in such a way that profiling results on the sample data are uniform and homogeneous with the profiling results on the full data set.

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. The schema is either Built-In or stored remotely in the Repository.

Since version 5.6, both the Built-In mode and the Repository mode are available in any of the Talend solutions.

Click Sync columns to retrieve the schema from the previous component in the Job.



Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.



Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.


Sample Size

Set how many rows to sample from the input flow.

Advanced settings

Seed for random generator

Set a random number if you want to extract the same sample in different executions of the Job.

Repeating the execution with a different value for the seed will result in a different data samples being extracted.

Keep this field empty if you want to extract a different data sample each time you execute the Job.


tStat Catcher Statistics

Select this check box to collect log data at the component level.


This component helps you to test profiling analyses on a sample data and have results similar to the results on the full data set.

tReservoirSampling can not be used in Map/Reduce Jobs for the time being.