tMysqlInput properties for Apache Spark Batch

Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

Repository: Select the repository file where the properties are stored.

Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view.

For more information about setting up and storing database connection parameters, see Centralizing database metadata.

Use an existing connection

Select this check box and in the Component List drop-down list, select the desired connection component to reuse the connection details you already defined.

DB version

Select the version of the database to be used.

When the database to be used is RDS Aurora, you need to select Mysql 5.

Host

Database server IP address.

Port

Listening port number of DB server.

Database

Name of the database.

Username and Password

DB user authentication data.

To enter the password, click the [...] button next to the password field, enter the password in double quotes in the pop-up dialog box, and click OK to save the 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.

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.

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.

Table Name

Type in the name of the table from which you need to read data.

This field is only available when you select Table from the Read from drop-down list.

Read from

Query type and Query

Specify the database query statement paying particularly attention to the properly sequence of the fields which must correspond to the schema definition.

If you are using Spark V2.0 onwards, the Spark SQL does not recognize the prefix of a database table anymore. This means that you must enter only the table name without adding any prefix that indicates for example the schema this table belongs to.

For example, if you need to perform a query in a table system.mytable, in which the system prefix indicates the schema that the mytable table belongs to, in the query, you must enter mytable only.

These fields are only available when you select Query from the Read from drop-down list.

Additional JDBC parameters

Specify additional connection properties for the database connection you are creating. The properties are separated by semicolon and each property is a key-value pair, for example, encryption=1;clientname=Talend.

This field is not available if the Use an existing connection check box is selected.

Spark SQL JDBC parameters

Add the JDBC properties supported by Spark SQL to this table. For a list of the user configurable properties, see JDBC to other database.

This component automatically set the url, dbtable and driver properties by using the configuration from the Basic settings tab.

Trim all the String/Char columns

Select this check box to remove leading and trailing whitespace from all the String/Char columns.

Trim column

Remove leading and trailing whitespace from defined columns.

Enable partitioning

Select this check box to read data in partitions.

For example, to partition 1000 rows into 4 partitions, if you enter 0 for the lower bound and 1000 for the upper bound, each partition will contain 250 rows and so the partitioning is even. If you enter 250 for the lower bound and 750 for the upper bound, the second and the third partition will each contain 125 rows and the first and the last partitions each 375 rows. With this configuration, the partitioning is skewed.

Usage rule

This component is used as a start component and requires an output link.

This component should use a tMysqlConfiguration component present in the same Job to connect to MySQL. You need to select the Use an existing connection check box and then select the tMysqlConfiguration component to be used.

This component, along with the Spark Batch component Palette it belongs to, appears only when you are creating a Spark Batch Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.

Spark Connection

This connection is effective on a per-Job basis.