tAvroOutput properties for Apache Spark Streaming
These properties are used to configure tAvroOutput running in the Spark Streaming Job framework.
The Spark Streaming tAvroOutput component belongs to the File family.
This component is available in Talend Real-Time Big Data Platform and Talend Data Fabric.
Basic settings
Define a storage configuration component |
Select the configuration component to be used to provide the configuration information for the connection to the target file system such as HDFS. If you leave this check box clear, the target file system is the local system. The configuration component to be used must be present in the same Job. For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write the result in a given HDFS system. |
Property type |
Either Built-In or Repository. |
Built-In: No property data stored centrally. |
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Repository: Select the repository file where the properties are stored. The properties are stored centrally under the Hadoop Cluster node of the Repository tree. The fields that come after are pre-filled in using the fetched data. For further information about the Hadoop Cluster node, see Managing Hadoop connection metadata. |
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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. |
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Folder |
Browse to, or enter the path pointing to the data to be used in the file system. This path must point to a folder rather than a file. The button for browsing does not work with the Spark Local mode; if you are using the other Spark Yarn modes that Talend Studio supports with your distribution, ensure that you have properly configured the connection in a configuration component in the same Job. Use the configuration component depending on the filesystem to be used. |
Action |
Select an operation for writing data: Create: Creates a file and write data in it. Overwrite: Overwrites the file existing in the directory specified in the Folder field. |
Compression |
Select the Compress data blocks check box to compress the output data. Hadoop provides different compression formats that help reduce the space needed for storing files and speed up data transfer. When reading a compressed file, Talend Studio needs to uncompress it before being able to feed it to the input flow. |
Advanced settings
Write empty batches | Select this check box to allow your Spark Job to create an empty batch when the
incoming batch is empty. For further information about when this is desirable behavior, see this discussion. |
Usage
Usage rule |
This component is used as an end component and requires an input link. This component, along with the Spark Streaming component Palette it belongs to, appears only when you are creating a Spark Streaming 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. |