tElasticSearchConfiguration properties for Apache Spark Streaming
These properties are used to configure tElasticSearchConfiguration running in the Spark Streaming Job framework.
The Spark Streaming tElasticSearchConfiguration component belongs to the ElasticSearch family.
This component is available in Talend Real-Time Big Data Platform and Talend Data Fabric.
Basic settings
Nodes |
Enter the location of the cluster hosting the Elasticsearch system to be used. The Nodes parameter is mandatory and eventually taken into account only when the Elasticsearch component to be connected to Elasticsearch uses the Elasticsearch Node Client, that is to say, the tElasticSearchInput component and the tElasticSearchOutput component. For further information about the Elasticsearch Node Client and the Elasticsearch Transport Client, see https://www.elastic.co/guide/en/elasticsearch/guide/current/_transport_client_versus_node_client.html. |
Transport addresses |
Enter the addresses of the Elasticsearch nodes you need the component to connect to. This parameter is required when your Elasticsearch Job, exactly speaking, tElasticSearchLookupInput in your Job, to use the Elasticsearch Transport Client to connect to the Elasticsearch cluster to be used. If you do not use Elasticsearch Transport Client, leave empty double quotation marks ("") in this field. For further information about the Elasticsearch Node Client and the Elasticsearch Transport Client, see https://www.elastic.co/guide/en/elasticsearch/guide/current/_transport_client_versus_node_client.html. |
Cluster name |
Enter the name the Elasticsearch cluster to be used. This parameter is required when your Elasticsearch Job, exactly speaking, tElasticSearchLookupInput in your Job, to use the Elasticsearch Transport Client to connect to the Elasticsearch cluster to be used. If you do not use Elasticsearch Transport Client, leave empty double quotation marks ("") in this field. |
Use SSL/TLS |
Select this check box to enable the SSL or TLS encrypted connection. Then you need to use the tSetKeystore component in the same Job to specify the encryption information. |
User authentication |
If the Elasticsearch system to be used requires authentication information, select this check box and enter the credentials. 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. |
Configuration |
Add the parameters accepted by Elasticsearch to perform more customized actions. For example, enter es.mapping.id in the Key column and true in the Value column to make the document field/property name contain the document ID. Note that you must put double quotation marks around the entered information. For a list of the parameters you can use, see https://www.elastic.co/guide/en/elasticsearch/hadoop/master/configuration.html. |
Advanced settings
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 with no need to be connected to other components. Drop tElasticSearchConfiguration along with
the Elasticsearch-related subJob to be run in the same Job so that the configuration is used
by the whole Job at runtime.
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. |