Elasticsearch catalog

StarRocks supports Elasticsearch catalogs from v3.1 onwards.

StarRocks and Elasticsearch are both popular analytical systems with distinct strengths. StarRocks excels in large-scale distributed computing and supports querying data from Elasticsearch through external tables. Elasticsearch is known for its full-text search capabilities. The combination of StarRocks and Elasticsearch provides a more comprehensive OLAP solution. With Elasticsearch catalogs, you can directly analyze all indexed data in your Elasticsearch cluster by using SQL statements on StarRocks without the need for data migration.

Unlike catalogs for other data sources, an Elasticsearch catalog has only one database named default in it upon creation. Each Elasticsearch index is automatically mapped to a data table and mounted to the default database.

Create an Elasticsearch catalog

Syntax

CREATE EXTERNAL CATALOG <catalog_name>
[COMMENT <comment>]
PROPERTIES ("key"="value", ...)

Parameters

catalog_name

The name of the Elasticsearch catalog. The naming conventions are as follows:

• The name can contain letters, digits (0-9), and underscores (_). It must start with a letter.
• The name is case-sensitive and cannot exceed 1023 characters in length.

comment

The description of the Elasticsearch catalog. This parameter is optional.

PROPERTIES

The properties of the Elasticsearch catalog. The following table describes the properties supported for Elasticsearch catalogs.

Parameter	Required	Default value	Description
hosts	Yes	None	The connection address of the Elasticsearch cluster. You can specify one or more addresses. StarRocks can parse the Elasticsearch version and index shard allocation from this address. StarRocks communicates with your Elasticsearch cluster based on the address returned by the GET /_nodes/http API operation. Therefore, the value of the hosts parameter must be the same as the address returned by the GET /_nodes/http API operation. Otherwise, BEs or CNs may not be able to communicate with your Elasticsearch cluster.
type	Yes	None	The type of the data source. Set this parameter to es when you create an Elasticsearch catalog.
user	No	Empty	The username that is used to log in to the Elasticsearch cluster with HTTP basic authentication enabled. Make sure that you have permissions to access paths such as /cluster/state/ nodes/http and have permissions to read the index.
password	No	Empty	The password that is used to log in to the Elasticsearch cluster.
es.type	No	_doc	The type of the index. If you want to query data in Elasticsearch 8 and later versions, you do not need to configure this parameter because the mapping types have been removed in Elasticsearch 8 and later versions.
es.nodes.wan.only	No	FALSE	Specifies whether StarRocks only uses the addresses specified by hosts to access the Elasticsearch cluster and fetch data. true: StarRocks only uses the addresses specified by hosts to access the Elasticsearch cluster and fetch data and does not sniff data nodes on which the shards of the Elasticsearch index reside. If StarRocks cannot access the addresses of the data nodes inside the Elasticsearch cluster, you need to set this parameter to true. false: StarRocks uses the addresses specified by hosts to sniff data nodes on which the shards of the Elasticsearch cluster indexes reside. After StarRocks generates a query execution plan, BEs or CNs directly access the data nodes inside the Elasticsearch cluster to fetch data from the shards of indexes. If StarRocks can access the addresses of the data nodes inside the Elasticsearch cluster, we recommend that you retain the default value false.
es.net.ssl	No	FALSE	Specifies whether the HTTPS protocol can be used to access the Elasticsearch cluster. Only StarRocks v2.4 and later support configuring this parameter. true: Both the HTTPS and HTTP protocols can be used to access your Elasticsearch cluster. false: Only the HTTP protocol can be used to access your Elasticsearch cluster.
enable_docvalue_scan	No	TRUE	Specifies whether to obtain the values of the target fields from Elasticsearch columnar storage. In most cases, reading data from columnar storage outperforms reading data from row storage.
enable_keyword_sniff	No	TRUE	Specifies whether to sniff TEXT-type fields in Elasticsearch based on KEYWORD-type fields. If this parameter is set to false, StarRocks performs matching after tokenization.

Examples

The following example creates an Elasticsearch catalog named es_test:

CREATE EXTERNAL CATALOG es_test
COMMENT 'test123'
PROPERTIES
(
    "type" = "es",
    "es.type" = "_doc",
    "hosts" = "https://xxx:9200",
    "es.net.ssl" = "true",
    "user" = "admin",
    "password" = "xxx",
    "es.nodes.wan.only" = "true"
);

Predicate pushdown

StarRocks supports pushing the predicates specified in queries against Elasticsearch tables down to Elasticsearch for execution. This minimizes the distance between the query engine and the storage source and improves query performance. The following table lists the operators that can be pushed down to Elasticsearch.

SQL syntax	Elasticsearch syntax
=	term query
in	terms query
>=, <=, >, <	range
and	bool.filter
or	bool.should
not	bool.must_not
not in	bool.must_not + terms
esquery	ES Query DSL

Query examples

The esquery() function can be used to push Elasticsearch queries, such as match and geoshape queries, that cannot be expressed in SQL down to Elasticsearch for filtering and processing. In the esquery() function, the first parameter that specifies a column name is used to associate with the index, and the second parameter is an Elasticsearch query's Elasticsearch Query DSL-based JSON representation enclosed in curly braces ({}). The JSON representation can and must have only one root key, such as match, geo_shape, or bool.

• Match query

  SELECT * FROM es_table WHERE esquery(k4, '{
     "match": {
        "k4": "StarRocks on elasticsearch"
     }
  }');

• Geoshape query

  SELECT * FROM es_table WHERE esquery(k4, '{
  "geo_shape": {
     "location": {
        "shape": {
           "type": "envelope",
           "coordinates": [
              [
                 13,
                 53
              ],
              [
                 14,
                 52
              ]
           ]
        },
        "relation": "within"
     }
  }
  }');

• Boolean query

  SELECT * FROM es_table WHERE esquery(k4, ' {
     "bool": {
        "must": [
           {
              "terms": {
                 "k1": [
                    11,
                    12
                 ]
              }
           },
           {
              "terms": {
                 "k2": [
                    100
                 ]
              }
           }
        ]
     }
  }');

Usage notes

• From v5.x onwards, Elasticsearch adopts a different data scanning method. StarRocks only supports querying data from Elasticsearch v5.x and later.
• StarRocks only supports querying data from Elasticsearch clusters that have HTTP basic authentication enabled.
• Some queries, such as count()-involved queries, run much slower on StarRocks than on Elasticsearch, because Elasticsearch can directly read the metadata related to the specified number of documents that meet the query conditions without the need to filter the requested data.