# tAggregateRow MapReduce properties (deprecated) Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. These properties are used to configure tAggregateRow running in the MapReduce Job framework. The MapReduce tAggregateRow component belongs to the Processing family. The component in this framework is available in all Talend products with Big Data and Talend Data Fabric. Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. The MapReduce framework is deprecated from Talend 7.3 onwards. Use Talend Jobs for Apache Spark to accomplish your integration tasks. ## 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 Edit
schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

View schema: choose this option to view the schema only.
Change to built-in property: choose this option to change the schema to Built-in for local changes.
Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the Repository Content window.

| | --- | --- | | | Built-In: You create and store the schema locally for this component
only. | | | Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs. | | Group by | Define the aggregation sets, the values of which will be used for
calculations. | | | Output Column: Select the column
label in the list offered based on the schema structure you defined.
You can add as many output columns as you wish to make more precise
aggregations.

Ex: Select Country to calculate an average of values for each
country of a list or select Country and Region if you want to
compare one country's regions with another country' regions. | | | Input Column: Match the input
column label with your output columns, in case the output label of
the aggregation set needs to be different. | | Operations | Select the type of operation along with the value to use for the
calculation and the output field. | | | Output Column: Select the
destination field in the list. | | | Function: Select the operator among:

count: calculates the number of rows
min: selects the minimum value
max: selects the maximum value
avg: calculates the average
sum: calculates the sum
list: lists values of an aggregation by multiple keys.
list (object): lists Java values of an aggregation by multiple keys
count (distinct): counts the number of the distinct rows
standard deviation: calculates the variability of a set of value.
union (geometry): makes the union of a set of Geometry objects

Some functions that are available in a traditional ETL Job, such as first or last, are not available in MapReduce Jobs because these functions does not make sense in a distributed environment. | | | Input column: Select the input
column from which the values are taken to be aggregated. | | | Ignore null values: Select the
check boxes corresponding to the names of the columns for which you
want the NULL value to be ignored. | ## Advanced settings | Delimiter(only for list operation) | Enter the delimiter you want to use to separate the different
operations. | | --- | --- | | Use financial precision, this is the max precision for
"sum" and "avg" operations, checked option heaps more memory and
slower than unchecked. | Select this check box to use a financial precision. This is a max
precision but consumes more memory and slows the processing.

Information noteWarning:

*We advise you to use the BigDecimal type for the
output in order to obtain precise results.* | | Check type overflow (slower) | Checks the type of data to ensure that the Job doesn't
crash. | | Check ULP (Unit in the Last Place), ensure that a value
will be incremented or decremented correctly, only float and
double types. (slower) | Select this check box to ensure the most precise results possible
for the Float and Double types. | ## Global Variables | 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 | **Usage rule** | In a
Talend
Map/Reduce Job, this component is used as an intermediate
step and other components used along with it must be Map/Reduce components, too. They
generate native Map/Reduce code that can be executed directly in Hadoop.

For further information about a
Talend
Map/Reduce Job, see the sections
describing how to create, convert and configure a
Talend
Map/Reduce Job of the
**Talend Big Data Getting Started Guide**.

Note that in this documentation, unless otherwise
explicitly stated, a scenario presents only Standard Jobs,
that is to say traditional
Talend
data integration Jobs, and non Map/Reduce Jobs. | | --- | --- |