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.

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.

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.

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.

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 rule

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

This connection is effective on a per-Job basis.