tTeradataOutput properties for Apache Spark Streaming
These properties are used to configure tTeradataOutput running in the Spark Streaming Job framework.
The Spark Streaming tTeradataOutput component belongs to the Databases family.
This component is available in Talend Real Time Big Data Platform 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 where the properties are stored. |
Use an existing configuration |
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. |
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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Host |
Database server IP address |
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. |
Action on table |
On the table defined, you can perform one of the following operations: None: No operation is carried out. Drop and create a table: The table is removed and created again. Create a table: The table does not exist and gets created. Create a table if not exists: The table is created if it does not exist. Drop a table if exists and create: The table is removed if it already exists and created again. Clear a table: The table content is deleted. |
Action on data |
On the data of the table defined, you can perform: Insert: Add new entries to the table. If duplicates are found, the Job stops. Update: Make changes to existing entries. Insert or update: Insert a new record. If the record with the given reference already exists, an update would be made. Update or insert: Update the record with the given reference. If the record does not exist, a new record would be inserted. Delete: Remove entries corresponding to the input flow. |
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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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 DB connection you are creating. This option is not available if you have selected the Use an existing connection check box in the Basic settings. This is intended to allow specific character set support. E.G.: CHARSET=KANJISJIS_OS to get support of Japanese characters. Information noteNote:
You can press Ctrl+Space to access a list of predefined global variables. |
Use batch per partition |
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 tTeradataConfiguration component present in the same Job to connect to Oracle. You need to select the Use an existing configuration check box and then select the tTeradataConfiguration 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. |