tElasticSearchInput

Reads documents from a given Elasticsearch system based on a user-defined
query.

tElasticSearchInput reads ElasticSearch documents from the ElasticSearch system based on user-defined queries, translates the documents into RDDs
(Resilient Distributed Datasets) and sends the RDDs to the Job.

Only one query is allowed per tElasticSearchInput.

tElasticSearchInput properties for Apache Spark Batch

These properties are used to configure tElasticSearchInput running in the Spark Batch Job framework.

The Spark Batch
tElasticSearchInput component belongs to the ElasticSearch family.

This component is available in all Talend products with Big Data 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.

The schema of the data outputted by this component is read-only, id_document and json_document. The json_document column contains the body of the documents read
from ElasticSearch. If you need to explore data from this json_document column, you have to use tExtractJSONFields to extract the data to be
used.

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.

Nodes

Enter the location of the cluster hosting the Elasticsearch system to be used.

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" } } }

1	es.query = { "query" : { "term" : { "user" : "costinl" } } }

In this Query field, you should write the same query in
the following
way:

"{ "query" : { "term" : {"user" : "costinl" } } }"

1	"{ "query" : { "term" : {"user" : "costinl" } } }"

Advanced settings

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.
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.

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.

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.

Usage

Usage rule	This component is used as a start component and requires an output link.. Drop a tElasticSearchConfiguration component in the same Job to connect to ElasticSearch. Then you need to select the Use an existing configuration check box and then select the tElasticSearchConfiguration component to be used. Note that the Talend components for Spark Jobs support the Elasticsearch versions up to 6.4.2. 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: 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.

Usage rule

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

Drop a tElasticSearchConfiguration component in the same Job to connect to
ElasticSearch. Then you need to select the Use
an existing configuration check box and then select the tElasticSearchConfiguration component to be used.

Note that the Talend components for Spark Jobs support the
Elasticsearch versions up to 6.4.2.

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:

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.

Related scenarios

No scenario is available for the Spark Batch version of this component
yet.

Document get from Talend https://help.talend.com

Thank you for watching.

Docs 7.x

0 Comments

Inline Feedbacks

View all comments

tElasticSearchInput – Docs for ESB 7.x