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Elasticsearch SQL Connector

Sink: Batch Sink: Streaming Append & Upsert Mode

The Elasticsearch connector allows for writing into an index of the Elasticsearch engine. This document describes how to setup the Elasticsearch Connector to run SQL queries against Elasticsearch.

The connector can operate in upsert mode for exchanging UPDATE/DELETE messages with the external system using the primary key defined on the DDL.

If no primary key is defined on the DDL, the connector can only operate in append mode for exchanging INSERT only messages with external system.


In order to use the Elasticsearch connector the following dependencies are required for both projects using a build automation tool (such as Maven or SBT) and SQL Client with SQL JAR bundles.

Elasticsearch version Maven dependency SQL Client JAR
6.x <dependency>
7.x and later versions <dependency>

Attention Elasticsearch connector works with JSON format which defines how to encode documents for the external system, therefore, it must be added as a dependency.

How to create an Elasticsearch table

The example below shows how to create an Elasticsearch sink table:

CREATE TABLE myUserTable (
  user_id STRING,
  user_name STRING
  uv BIGINT,
  pv BIGINT,
) WITH (
  'connector' = 'elasticsearch-7',
  'hosts' = 'http://localhost:9200',
  'index' = 'users'

Connector Options

Option Required Default Type Description
required (none) String Specify what connector to use, valid values are:
  • elasticsearch-6: connect to Elasticsearch 6.x cluster
  • elasticsearch-7: connect to Elasticsearch 7.x and later versions cluster
required (none) String One or more Elasticsearch hosts to connect to, e.g. 'http://host_name:9092;http://host_name:9093'.
required (none) String Elasticsearch index for every record. Can be a static index (e.g. 'myIndex') or a dynamic index (e.g. 'index-{log_ts|yyyy-MM-dd}'). See the following Dynamic Index section for more details.
required in 6.x (none) String Elasticsearch document type. Not necessary anymore in elasticsearch-7.
optional _ String Delimiter for composite keys ("_" by default), e.g., "$" would result in IDs "KEY1$KEY2$KEY3"."
optional (none) String Username used to connect to Elasticsearch instance. Please notice that Elasticsearch doesn't pre-bundled security feature, but you can enable it by following the guideline to secure an Elasticsearch cluster.
optional (none) String Password used to connect to Elasticsearch instance. If username is configured, this option must be configured with non-empty string as well.
optional fail String Failure handling strategy in case a request to Elasticsearch fails. Valid strategies are:
  • fail: throws an exception if a request fails and thus causes a job failure.
  • ignore: ignores failures and drops the request.
  • retry_rejected: re-adds requests that have failed due to queue capacity saturation.
  • custom class name: for failure handling with a ActionRequestFailureHandler subclass.
optional true Boolean Flush on checkpoint or not. When disabled, a sink will not wait for all pending action requests to be acknowledged by Elasticsearch on checkpoints. Thus, a sink does NOT provide any strong guarantees for at-least-once delivery of action requests.
optional 1000 Integer Maximum number of buffered actions per bulk request. Can be set to '0' to disable it.
optional 2mb MemorySize Maximum size in memory of buffered actions per bulk request. Must be in MB granularity. Can be set to '0' to disable it.
optional 1s Duration The interval to flush buffered actions. Can be set to '0' to disable it. Note, both 'sink.bulk-flush.max-size' and 'sink.bulk-flush.max-actions' can be set to '0' with the flush interval set allowing for complete async processing of buffered actions.
optional DISABLED String Specify how to perform retries if any flush actions failed due to a temporary request error. Valid strategies are:
  • DISABLED: no retry performed, i.e. fail after the first request error.
  • CONSTANT: wait for backoff delay between retries.
  • EXPONENTIAL: initially wait for backoff delay and increase exponentially between retries.
optional 8 Integer Maximum number of backoff retries.
optional 50ms Duration Delay between each backoff attempt. For CONSTANT backoff, this is simply the delay between each retry. For EXPONENTIAL backoff, this is the initial base delay.
optional (none) Duration Maximum timeout between retries.
optional (none) String Prefix string to be added to every REST communication, e.g., '/v1'
optional json String Elasticsearch connector supports to specify a format. The format must produce a valid json document. By default uses built-in 'json' format. Please refer to JSON Format page for more details.


Key Handling

Elasticsearch sink can work in either upsert mode or append mode, it depends on whether primary key is defined. If primary key is defined, Elasticsearch sink works in upsert mode which can consume queries containing UPDATE/DELETE messages. If primary key is not defined, Elasticsearch sink works in append mode which can only consume queries containing INSERT only messages.

In Elasticsearch connector, the primary key is used to calculate the Elasticsearch document id, which is a string of up to 512 bytes. It cannot have whitespaces. The Elasticsearch connector generates a document ID string for every row by concatenating all primary key fields in the order defined in the DDL using a key delimiter specified by document-id.key-delimiter. Certain types are not allowed as primary key field as they do not have a good string representation, e.g. BYTES, ROW, ARRAY, MAP, etc. If no primary key is specified, Elasticsearch will generate a document id automatically.

See CREATE TABLE DDL for more details about PRIMARY KEY syntax.

Dynamic Index

Elasticsearch sink supports both static index and dynamic index.

If you want to have a static index, the index option value should be a plain string, e.g. 'myusers', all the records will be consistently written into “myusers” index.

If you want to have a dynamic index, you can use {field_name} to reference a field value in the record to dynamically generate a target index. You can also use '{field_name|date_format_string}' to convert a field value of TIMESTAMP/DATE/TIME type into the format specified by the date_format_string. The date_format_string is compatible with Java’s DateTimeFormatter. For example, if the option value is 'myusers-{log_ts|yyyy-MM-dd}', then a record with log_ts field value 2020-03-27 12:25:55 will be written into “myusers-2020-03-27” index.

Data Type Mapping

Elasticsearch stores document in a JSON string. So the data type mapping is between Flink data type and JSON data type. Flink uses built-in 'json' format for Elasticsearch connector. Please refer to JSON Format page for more type mapping details.

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