tSparkSample – Docs for ESB 5.x

Component family

Big Data / Spark

Function

tSparkSample generates a sample
dataset from the incoming flow.

Purpose

tSparkSample returns a sample
subset of the Spark’s Resilient Distributed Dataset (RDD) being
processed.

Basic settings

Schema and Edit
Schema

A schema is a row description. It defines the number of fields to be processed and passed on
to the next component. The schema is either Built-In or
stored remotely in the Repository.

Click Edit schema to make changes to the schema. If the
current schema is of the Repository type, three options are
available:

Is with replacement

Select this check box to proceed the sampling with replacement to
make each sampling result independent from each other. If you keep
this check box clear, the sampling goes without replacement.

Fraction

Enter the sample size ratio to the RDD being processed. For
example, enter 0.1, then the
ratio of the sampled RDD to the total RDD being processed is
10%.

Seed

Enter a positive seed number (the starting number for a random
sequence of generated numbers) so that the same sample is
reproducible.

Advanced settings

tStatCatcher Statistics

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

Global Variables

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see Talend Studio
User Guide.

Usage

This component is an intermediate component that passes sampled
datasets to the Spark component that follows.

Note that the knowledge of statistics and sampling is
required.

Limitations

It is strongly recommended to use this component in a Spark-only Job, that is to say, to
design and run a Spark Job separately from the non Spark components or Jobs. For example, it
is not recommended to use the tRunJob component to
coordinate a Spark Job and a non Spark Job, or to use the tHDFSPut component along with the Spark components in the same Job.