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tHashOutput Standard properties

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

The Standard tHashOutput component belongs to the Technical 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 to be processed and passed on to the next component. The schema is either built-in or remotely stored 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:

  • 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 Dynamic schema.

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: The schema is created and stored locally for this component only. For more information about a component schema in its Basic settings tab, see Basic settings tab.

 

Repository: The schema already exists and is stored in the Repository, hence can be reused. For more information about a component schema in its Basic settings tab, see Basic settings tab.

Link with a tHashOutput

Select this check box to connect to a tHashOutput component.

Information noteNote:

If multiple tHashOutput components are linked in this way, the data loaded to the cache by all of them can be read by a tHashInput component that is linked with any of them.

Component list

Drop-down list of available tHashOutput components.

Data write model

Drop-down list of available data write modes.

Keys management

Drop-down list of available keys management modes.

  • Keep all: writes all the data received to the cache memory.

  • Keep first: writes only the first record to the cache memory if multiple records received have the same key value.

Append

Selected by default, this option is designed to append data to the memory in case an iterator exists in the same subJob. If it is unchecked, tHashOutput will clear the memory before loading data to it.

Information noteNote:

If Link with a tHashOutput is selected, this check box will be hidden but is always enabled.

Advanced settings

tStatCatcher Statistics

Select this check box to collect log data at the 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.

NB_LINE: the number of rows processed. This is an After variable and it returns an integer.

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 more information about variables, see Using contexts and variables.

Usage

Usage rule

This component writes data to the cache memory and is closely related to tHashInput. Together, these twin components offer high-speed data access to facilitate transactions involving a massive amount of data.

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