tMysqlOutput properties for Apache Spark Batch
These properties are used to configure tMysqlOutput running in the Spark Batch Job framework.
The Spark Batch tMysqlOutput component belongs to the Databases family.
This component can also be used to write data to a RDS Aurora or a RDS MySQL database.
The component in this framework is available in all Talend products with Big Data and Talend Data Fabric.
Basic settings
Property type |
Either Built-In or Repository. Built-In: No property data stored centrally. Repository: Select the repository file where the properties are stored. |
DB Version |
Select the MySQL version you are using. When the database to be used is RDS Aurora, you need to select Mysql 5. |
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 Talend Studio User Guide. |
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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. |
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, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings. |
Table |
Name of the table to be written. Note that only one table can be written at a time |
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. |
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Built-In: You create and store the schema locally for this component only. |
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Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. When the schema to be reused has default values that are integers or functions, ensure that these default values are not enclosed within quotation marks. If they are, you must remove the quotation marks manually. For more information, see the related description of retrieving table schemas in Talend Studio User Guide. |
Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:
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Advanced settings
Additional JDBC parameters |
Specify additional connection properties for the database connection you are creating. |
Use Batch per partition |
Select this check box to activate the batch mode for data processing. Information noteNote:
This check box is available only when you have selected, the Update or the Delete option in the Action on data field. |
Batch Size |
Specify the number of records to be processed in each batch. This field appears only when the Use batch mode check box is selected. |
Connection pool |
In this area, you configure, for each Spark executor, the connection pool used to control the number of connections that stay open simultaneously. The default values given to the following connection pool parameters are good enough for most use cases.
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Evict connections |
Select this check box to define criteria to destroy connections in the connection pool. The following fields are displayed once you have selected it.
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Usage
Usage rule |
This component is used as an end component and requires an input 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 |
In the Spark
Configuration tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:
This connection is effective on a per-Job basis. |