tSparkAggregate – Docs for ESB 5.x

Component family

Big Data / Spark

Function

tSparkAggregate receives data
from its preceding Spark component and aggregates the dataset
elements on the basis of the operations you define.

Purpose

tSparkAggregate performs
aggregating operations on the datasets incoming from its preceding
Spark component.

Basic settings

Spark connection

Select the Spark connection component to be used from the drop-down list in order to reuse
the connection created by that component.

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:

Group by

Define the aggregation sets, the values of which will be used for
calculations.

Operations

Complete this table to select the operations to be performed on
each column of the input dataset elements:

Additional Output Column: select
the column from the output schema to receive the aggregated input
data.

Function: select the function to be
used to aggregate the input data.

Input Column: select the column
from the input schema to provide the input data to be
aggregated.

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 of a Spark
process.

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.