tOracleOutput properties for Apache Spark Batch
These properties are used to configure tOracleOutput running in the Spark Batch Job framework.
The Spark Batch tOracleOutput component belongs to the Databases family.
This component can also be used to write data to a RDS Oracle database.
The component in this framework is available in all subscription-based Talend products with Big Data and Talend Data Fabric.
Basic settings
Property type |
Either Built-in or Repository . |
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Built-in: No property data stored centrally. |
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Repository: Select the repository file in which the properties are stored. The fields that follow are completed automatically using the data retrieved. |
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. |
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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. |
Connection type |
The available drivers are:
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DB Version |
Select the Oracle version in use. |
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. |
Oracle schema |
Oracle schema name. |
Table |
Name of the table to be written. Note that only one table can be written at a time. |
Action on table |
On the table defined, you can perform one of the following operations: Default: No operation is carried out. Drop and create table: The table is removed and created again. Create table: The table does not exist and gets created. Create table if not exists: The table is created if it does not exist. Drop table if exists and create: The table is removed if it already exists and created again. Clear table: The table content is deleted. Truncate table: The table content is deleted. You do not have the possibility to rollback the operation. Truncate table with reuse storage: The table content is deleted. You do not have the possibility to rollback the operation. However, it is allowed to reuse the existing storage allocated to the table though the storage is considered empty. Information noteWarning:
If you select the Use an existing connection check box and select an option other than Default from the Action on table list, a commit statement will be generated automatically before the data insert/update/delete operation. |
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:
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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 Retrieving table schemas. |
Die on error |
This check box is selected by default. Clear the check box to skip the row on error and complete the process for error-free rows. If needed, you can retrieve the rows on error via a Row > Rejects link. |
Advanced settings
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. |
Use Batch |
Select this check box to activate the batch mode for data processing. |
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 tOracleConfiguration component present in the same Job to connect to Oracle. You need to select the Use an existing connection check box and then select the tOracleConfiguration 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. |