tElasticSearchLookupInput properties for Apache Spark Streaming - 7.1

ElasticSearch

author
Talend Documentation Team
EnrichVersion
7.1
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > ElasticSearch components
Data Quality and Preparation > Third-party systems > ElasticSearch components
Design and Development > Third-party systems > ElasticSearch components
EnrichPlatform
Talend Studio

These properties are used to configure tElasticSearchLookupInput running in the Spark Streaming Job framework.

The Spark Streaming tElasticSearchLookupInput component belongs to the ElasticSearch family.

The component in this framework is available in Talend Real Time Big Data Platform and in Talend Data Fabric.

Basic settings

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.

Use an existing configuration

Select this check box and in the Component List click the relevant connection component to reuse the connection details you already defined.

Transport addresses

Enter the addresses of the ElasticSearch nodes you need the component to connect to.

Different from tElasticSearchOutput which uses ElasticSearch Node Client, tElasticSearchLookupInput uses ElasticSearch Transport Client to connect to the ElasticCluster cluster. This allows tElasticSearchLookupInput to quickly create multiple connections to the cluster.

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.

The Cluster name parameter is mandatory and eventually taken into account only when the ElasticSearch component to be connected to ElasticSearch is tElasticSearchLookupInput.

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.

Index

Enter the name of the index you want to read documents from.

An index is the largest unit of storage in the Elastisearch system.

Type

Enter the name of the type the documents to be read belong to.

For example, blogpost_en and blogpost_fr can be two types that represent given English blog posts and French blog posts, respectively.

You can dynamically uses the values of a given column to be document types. If you need to do so, enter the name of that column into a pair of braces ({}), for example, {blog_author}.

Query

Enter the ElasticSearch query to be performed by this component.

In editing queries, you need to use the syntax required by ElasticSearch along with escape characters required by Java, and put the query within double quotation marks.

For example, in the ElasticSearch documentation, an example query reads as follows:
es.query = { "query" : { "term" : { "user" : "costinl" } } }
In this Query field, you should write the same query in the following way:
"{ \"query\" : { \"term\" : {\"user\" : \"costinl\" } } }"

The result of the query must contain only records that match join key you need to use in tMap. In other words, you must use the schema of the main flow to tMap to construct the SQL statement here in order to load only the matched records into the lookup flow.

This approach ensures that no redundant records are loaded into memory and outputted to the component that follows.

Advanced settings

Scroll time

Enter the time duration (in milliseconds) through which an input batch is progressively loaded from ElasticSearch.

This duration is useful only in case your query is bringing in huge batches. But since tMap in the Streaming mode reloads data at each row, an appropriately written query should avoid producing huge batches.

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.

For further information about tSetKeystore, see tSetKeystore.

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.

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.

  • Max total number of connections: enter the maximum number of connections (idle or active) that are allowed to stay open simultaneously.

    The default number is 8. If you enter -1, you allow unlimited number of open connections at the same time.

  • Max waiting time (ms): enter the maximum amount of time at the end of which the response to a demand for using a connection should be returned by the connection pool. By default, it is -1, that is to say, infinite.

  • Min number of idle connections: enter the minimum number of idle connections (connections not used) maintained in the connection pool.

  • Max number of idle connections: enter the maximum number of idle connections (connections not used) maintained in the connection pool.

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.

  • Time between two eviction runs: enter the time interval (in milliseconds) at the end of which the component checks the status of the connections and destroys the idle ones.

  • Min idle time for a connection to be eligible to eviction: enter the time interval (in milliseconds) at the end of which the idle connections are destroyed.

  • Soft min idle time for a connection to be eligible to eviction: this parameter works the same way as Min idle time for a connection to be eligible to eviction but it keeps the minimum number of idle connections, the number you define in the Min number of idle connections field.

Usage

Usage rule

This component is used as a start component and requires an output link.

This component should use a tElasticSearchConfiguration component present in the same Job to connect to ElasticSearch. You need to select the Use an existing configuration check box and then select the tElasticSearchConfiguration component to be used.

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:
  • Yarn mode (Yarn client or Yarn cluster):
    • When using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab.

    • When using HDInsight, specify the blob to be used for Job deployment in the Windows Azure Storage configuration area in the Spark configuration tab.

    • When using Altus, specify the S3 bucket or the Azure Data Lake Storage for Job deployment in the Spark configuration tab.
    • When using Qubole, add a tS3Configuration to your Job to write your actual business data in the S3 system with Qubole. Without tS3Configuration, this business data is written in the Qubole HDFS system and destroyed once you shut down your cluster.
    • When using on-premise distributions, use the configuration component corresponding to the file system your cluster is using. Typically, this system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the configuration component corresponding to the file system your cluster is using, such as tHDFSConfiguration or tS3Configuration.

    If you are using Databricks without any configuration component present in your Job, your business data is written directly in DBFS (Databricks Filesystem).

This connection is effective on a per-Job basis.