tTeradataLookupInput
Executes a database query with a strictly defined order which must correspond to
the schema definition.
It passes on the extracted data to tMap in order to
provide the lookup data to the main flow. It must be directly connected to a tMap component and requires this tMap to use Reload at each row or Reload at each row (cache) for the lookup flow.
tTeradataLookupInput properties for Apache Spark Streaming
These properties are used to configure tTeradataLookupInput running in the Spark Streaming Job framework.
The Spark Streaming
tTeradataLookupInput component belongs to the Databases family.
The streaming version of this component is available in Talend Real Time Big Data Platform and in
Talend Data Fabric.
Basic settings
Property type |
Either Built-in or |
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Built-in: No property data stored |
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Repository: Select the repository |
Use an existing configuration |
Select this check box and in the Component List click the relevant connection component to |
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Click this icon to open a database connection wizard and store the For more information about setting up and storing database |
Host |
Database server IP address |
Database |
Name of the database |
Username and |
DB user authentication data. To enter the password, click the […] button next to the |
Table |
Name of the table to be used. |
Schema and Edit |
A schema is a row description. It defines the number of fields |
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Built-In: You create and store the schema locally for this component |
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Repository: You have already created the schema and stored it in the When the schema to be reused has default values that are You can find more details about how to |
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Click Edit
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Query type and Query |
Enter your DB query paying particularly attention to properly sequence The result of the query must contain only records that match join key you need to use in This approach ensures that no redundant records are loaded into memory and outputted to |
Advanced settings
Additional JDBC parameters |
Specify additional connection properties in the existing DB |
Trim all the String/Char columns |
Select this check box to remove leading and trailing whitespace from |
Trim column |
Remove leading and trailing whitespace from defined columns. |
Connection pool |
In this area, you configure, for each Spark executor, the connection pool used to control
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Evict connections |
Select this check box to define criteria to destroy connections in the connection pool. The
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Usage
Usage rule |
This component is used as a start component and requires an output link. This component should use a tTeradataConfiguration This component, along with the Spark Streaming component Palette it belongs to, appears Note that in this documentation, unless otherwise explicitly stated, a scenario presents |
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. |
Limitation |
Due to license incompatibility, one or more JARs required to use |
Related scenarios
For a scenario about how to use the same type of component in a Spark Streaming Job, see
Reading and writing data in MongoDB using a Spark Streaming Job.