tSortRow

Helps creating metrics and
classification table.

tSortRow sorts input data based on one or several
columns, by sort type and order.

Depending on the Talend
product you are using, this component can be used in one, some or all of the following
Job frameworks:

Standard: see tSortRow Standard properties.

The component in this framework is available in all Talend
products.
MapReduce: see tSortRow MapReduce properties (deprecated).

The component in this framework is available in all subscription-based Talend products with Big Data
and Talend Data Fabric.
Spark Batch:
see tSortRow properties for Apache Spark Batch.

The component in this framework is available in all subscription-based Talend products with Big Data
and Talend Data Fabric.
Spark Streaming:
see tSortRow properties for Apache Spark Streaming.

This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.

tSortRow Standard properties

These properties are used to configure tSortRow running in the Standard Job framework.

The Standard
tSortRow component belongs to the Processing family.

The component in this framework is available in all Talend
products.

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. Click Sync columns to retrieve the schema from the previous component connected in the Job. This component offers the advantage of the dynamic schema feature. This allows you to retrieve unknown columns from source files or to copy batches of columns from a source without mapping each column individually. For further information about dynamic schemas, see Talend Studio User Guide. This dynamic schema feature is designed for the purpose of retrieving unknown columns of a table and is recommended to be used for this purpose only; it is not recommended for the use of creating tables.
	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.
Criteria	Click + to add as many lines as required for the sort to be complete. By default the first column defined in your schema is selected.
	Schema column: Select the column label from your schema, which the sort will be based on. Note that the order is essential as it determines the sorting priority.
	Sort type: Numerical and Alphabetical order are proposed. More sorting types to come.
	Order: Ascending or descending order.

Advanced settings

Sort on disk	Customize the memory used to temporarily store output data. Temp data directory path: Set the location where the temporary files should be stored. Create temp data directory if not exists: Select this check box to create the directory if it does not exist. Buffer size of external sort: Type in the size of physical memory you want to allocate to sort processing.
tStatCatcher Statistics	Select this check box to gather the Job processing metadata at the Job level as well as at each component level.

Sort on disk

Customize the memory used to temporarily store output data.

Temp data directory path: Set the
location where the temporary files should be stored.

Create temp data directory if not
exists: Select this check box to create the directory
if it does not exist.

Buffer size of external sort: Type
in the size of physical memory you want to allocate to sort
processing.

tStatCatcher Statistics

Select this check box to gather the Job processing metadata at the Job level as well as
at each component level.

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.

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	This component handles flow of data therefore it requires input and output, hence is defined as an intermediary step.

Sorting entries

This scenario describes a three-component Job. A tRowGenerator is used to create random entries which are directly sent
to a tSortRow to be ordered following a defined value
entry. In this scenario, we suppose the input flow contains names of salespersons along
with their respective sales and their years of presence in the company. The result of
the sorting operation is displayed on the Run
console.

Drop the three components required for this use case: tRowGenerator, tSortRow and
tLogRow from the Palette to the design workspace.
Connect them together using Row
main links.
On the tRowGenerator editor, define the
values to be randomly used in the Sort component. For more information regarding
the use of this particular component, see tRowGenerator

In this scenario, we want to rank each salesperson according to its
Sales value and to its number of years in the
company.
Double-click tSortRow to display the
Basic settings tab panel. Set the sort
priority on the Sales value and as secondary criteria, set the number of years
in the company.

Use the plus button to add the number of rows required. Set the type of
sorting, in this case, both criteria being integer, the sort is numerical. At
last, given that the output wanted is a rank classification, set the order as
descending.
Display the Advanced Settings tab and select
the Sort on disk check box to modify the
temporary memory parameters. In the Temp data directory
path field, type the path to the directory where you want to
store the temporary data. In the Buffer size of external
sort field, set the maximum buffer value you want to allocate to
the processing.

Warning:

The default buffer value is 1000000 but the more rows and/or columns you
process, the higher the value needs to be to prevent the Job from automatically
stopping. In that event, an “out of memory” error message displays.

Make sure you connected this flow to the output component, tLogRow, to display the result in the Job
console.
Press F6 to run the Job. The ranking is based
first on the Sales value and then on the number of years of experience.

Sorting entries based on dynamic schema

This scenario applies only to subscription-based Talend products.

In this scenario we will sort entries in an input file based on a dynamic schema,
display the sorting result on the Run console, and save
the sorting result in an output file. For more information about the dynamic schema
feature, see
Talend Studio User
Guide.

Drop the components required for this use case: tFileInputDelimited, tSortRow,
tLogRow and tFileOutputDelimited from the Palette to the design workspace.
Connect these components together using Row
> Main links.
Double-click the tFileInputDelimited
component to display its Basic settings view.

Warning:

The dynamic schema feature is only supported in Built-In mode and requires the input file to have a
header row.

Select Built-In from the Property Type list.
Click the […] button next to the File Name field to browse to your input file. In this
use case, the input file cars.csv has five columns:
ID_Owner, Registration,
Make, Color, and
ID_Reseller.
Specify the header row in Header field. In
this use case the first row is the header row.
Select Built-In from the Schema list, and click Edit
schema to set the input schema.

Warning:

The dynamic column must be defined in the last row of the
schema.

In the schema editor, add two columns and name them
ID_Owner and Other respectively.
Set the data type of the Other column to Dynamic to retrieve all the columns undefined in the
schema.
Click OK to propagate the schema and close
the schema editor.
Double-click tSortRow to display the
Basic settings view.

Add a row in the Criteria table by clicking
the plus button, select Other under Schema column, select alpha as the sorting
type, and select the ascending or
descending order for data output.

Warning:

Dynamic column sorting works only when the sorting type is
set to alpha.

To view the output in the form of a table on the Run console, double-click the tLogRow component and select the Table option in the Basic
settings view.
Double-click the tFileOutputDelimited
component to display its Basic Settings
view.

Click the […] button next to the File Name field to browse to the directory where you
want to save the output file, and then enter a name for the file.
Select the Include Header check box to
retrieve the column names as well as the sorted data.
Save your Job and press F6 to run it.

The sorting result is displayed on the Run
console and written into the output file.