Elasticsearch коннектор#
Примечание
Ниже приведена оригинальная документация Trino. Скоро мы ее переведем на русский язык и дополним полезными примерами.
The Elasticsearch connector allows access to Elasticsearch data from Trino. This document describes how to configure a catalog with the Elasticsearch connector to run SQL queries against Elasticsearch.
Requirements#
Elasticsearch 7.x or 8.x
Network access from the Trino coordinator and workers to the Elasticsearch nodes.
Configuration#
To configure the Elasticsearch connector, create a catalog properties file
etc/catalog/example.properties
with the following contents, replacing the
properties as appropriate for your setup:
connector.name=elasticsearch
elasticsearch.host=localhost
elasticsearch.port=9200
elasticsearch.default-schema-name=default
The following table details all general configuration properties:
Property name |
Description |
Default |
---|---|---|
|
The comma-separated list of host names for the Elasticsearch node to connect to. This property is required. |
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Port to use to connecto to Elasticsearch. |
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The schema that contains all tables defined without a qualifying schema name. |
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Sets the maximum number of hits that can be returned with each Elasticsearch scroll request. |
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Duration for Elasticsearch to keep the search context alive for scroll requests. |
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Timeout duration for all Elasticsearch requests. |
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Timeout duration for all Elasticsearch connection attempts. |
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The minimum duration between backpressure retry attempts for a single request to Elasticsearch. Setting it too low can overwhelm an already struggling cluster. |
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The maximum duration between backpressure retry attempts for a single request to Elasticsearch. |
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The maximum duration across all retry attempts for a single request to Elasticsearch. |
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Duration between requests to refresh the list of available Elasticsearch nodes. |
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Disable using the address published by the Elasticsearch API to connect for queries. Some deployments map Elasticsearch ports to a random public port and enabling this property can help in these cases. |
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Authentication#
The connection to Elasticsearch can use AWS or password authentication.
To enable AWS authentication and authorization using IAM policies, the
elasticsearch.security
option must be set to AWS
. Additionally, the
following options must be configured:
Property name |
Description |
---|---|
|
AWS region of the Elasticsearch endpoint. This option is required. |
|
AWS access key to use to connect to the Elasticsearch domain. If not set, the default AWS credentials provider chain is used. |
|
AWS secret key to use to connect to the Elasticsearch domain. If not set, the default AWS credentials provider chain is used. |
|
Optional ARN of an IAM role to assume to connect to Elasticsearch. Note that the configured IAM user must be able to assume this role. |
|
Optional external ID to pass while assuming an AWS IAM role. |
To enable password authentication, the elasticsearch.security
option must be set
to PASSWORD
. Additionally the following options must be configured:
Property name |
Description |
---|---|
|
User name to use to connect to Elasticsearch. |
|
Password to use to connect to Elasticsearch. |
Connection security with TLS#
The connector provides additional security options to connect to Elasticsearch clusters with TLS enabled.
If your cluster has globally-trusted certificates, you should only need to enable TLS. If you require custom configuration for certificates, the connector supports key stores and trust stores in PEM or Java Key Store (JKS) format.
The available configuration values are listed in the following table:
Property name |
Description |
---|---|
|
Enables TLS security. |
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|
The key password for the key store specified by
|
|
The key password for the trust store specified by
|
|
Flag to determine if the hostnames in the certificates must be verified. Defaults
to |
Type mapping#
Because Trino and Elasticsearch each support types that the other does not, this connector maps some types when reading data.
Elasticsearch type to Trino type mapping#
The connector maps Elasticsearch types to the corresponding Trino types according to the following table:
Elasticsearch type |
Trino type |
Notes |
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For more information, see Date types. |
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No other types are supported.
Array types#
Fields in Elasticsearch can contain zero or more values, but there is no dedicated array type. To indicate a field contains an array, it can be annotated in a Trino-specific structure in the _meta section of the index mapping.
For example, you can have an Elasticsearch index that contains documents with the following structure:
{
"array_string_field": ["trino","the","lean","machine-ohs"],
"long_field": 314159265359,
"id_field": "564e6982-88ee-4498-aa98-df9e3f6b6109",
"timestamp_field": "1987-09-17T06:22:48.000Z",
"object_field": {
"array_int_field": [86,75,309],
"int_field": 2
}
}
The array fields of this structure can be defined by using the following command to add the field
property definition to the _meta.trino
property of the target index mapping with Elasticsearch available at search.example.com:9200
:
curl --request PUT \
--url search.example.com:9200/doc/_mapping \
--header 'content-type: application/json' \
--data '
{
"_meta": {
"trino":{
"array_string_field":{
"isArray":true
},
"object_field":{
"array_int_field":{
"isArray":true
}
},
}
}
}'
Примечание
It is not allowed to use asRawJson
and isArray
flags simultaneously for the same column.
Date types#
The Elasticsearch connector supports only the default date
type. All other
date formats including built-in date formats and custom date formats are
not supported. Dates with the format property are ignored.
Raw JSON transform#
Documents in Elasticsearch can include more complex structures that are not
represented in the mapping. For example, a single keyword
field can have
widely different content including a single keyword
value, an array, or a
multidimensional keyword
array with any level of nesting.
The following command configures array_string_field
mapping with Elasticsearch
available at search.example.com:9200
:
curl --request PUT \
--url search.example.com:9200/doc/_mapping \
--header 'content-type: application/json' \
--data '
{
"properties": {
"array_string_field":{
"type": "keyword"
}
}
}'
All the following documents are legal for Elasticsearch with
array_string_field
mapping:
[
{
"array_string_field": "trino"
},
{
"array_string_field": ["trino","is","the","best"]
},
{
"array_string_field": ["trino",["is","the","best"]]
},
{
"array_string_field": ["trino",["is",["the","best"]]]
}
]
See the Elasticsearch array documentation for more details.
Further, Elasticsearch supports types, such as
dense_vector,
that are not supported in Trino. These and other types can cause parsing
exceptions for users that use of these types in Elasticsearch. To manage all of
these scenarios, you can transform fields to raw JSON by annotating it in a
Trino-specific structure in the
_meta
section of the index mapping. This indicates to Trino that the field, and all
nested fields beneath, need to be cast to a VARCHAR
field that contains the
raw JSON content. These fields can be defined by using the following command to
add the field property definition to the _meta.trino
property of the target
index mapping.
curl --request PUT \
--url search.example.com:9200/doc/_mapping \
--header 'content-type: application/json' \
--data '
{
"_meta": {
"trino":{
"array_string_field":{
"asRawJson":true
}
}
}
}'
This preceding configuration causes Trino to return the array_string_field
field as a VARCHAR
containing raw JSON. You can parse these fields with the
built-in JSON functions.
Примечание
It is not allowed to use asRawJson
and isArray
flags simultaneously for the same column.
Special columns#
The following hidden columns are available:
Column |
Description |
---|---|
|
The Elasticsearch document ID. |
|
The document score returned by the Elasticsearch query. |
|
The source of the original document. |
Full text queries#
Trino SQL queries can be combined with Elasticsearch queries by providing the full text query as part of the table name, separated by a colon. For example:
SELECT * FROM "tweets: +trino SQL^2"
SQL support#
The connector provides globally available and read operation statements to access data and metadata in the Elasticsearch catalog.
Table functions#
The connector provides specific table functions to access Elasticsearch.
raw_query(varchar) -> table
#
The raw_query
function allows you to query the underlying database directly.
This function requires Elastic Query
DSL
syntax. The full DSL query is pushed down and processed in Elasticsearch. This
can be useful for accessing native features which are not available in Trino or
for improving query performance in situations where running a query natively may
be faster.
Предупреждение
Нативный запрос, переданный в источник, должен возвращать набор записей (result set). CedrusData не осуществляет проверку доступа текущего пользователя к объектам источника, задействованным в нативном запросе. Используйте нативные запросы только для чтения данных.
The raw_query
function requires three parameters:
schema
: The schema in the catalog that the query is to be executed on.index
: The index in Elasticsearch to be searched.query
: The query to execute, written in Elastic Query DSL.
Once executed, the query returns a single row containing the resulting JSON payload returned by Elasticsearch.
For example, query the example
catalog and use the raw_query
table function
to search for documents in the orders
index where the country name is
ALGERIA
as defined as a JSON-formatted query matcher and passed to the
raw_query
table function in the query
parameter:
SELECT
*
FROM
TABLE(
example.system.raw_query(
schema => 'sales',
index => 'orders',
query => '{
"query": {
"match": {
"name": "ALGERIA"
}
}
}'
)
);
Примечание
Полиморфные табличные функции не сохраняют оригинальный порядок записей в результате запроса. Есть переданный
запрос содержит запрос выражение ORDER BY
, функция может вернуть записи в ином порядке. Для восстановления
требуемого порядка используйте ORDER BY
в запросе CedrusData.
Performance#
The connector includes a number of performance improvements, detailed in the following sections.
Parallel data access#
The connector requests data from multiple nodes of the Elasticsearch cluster for query processing in parallel.
Predicate push down#
The connector supports predicate push down for the following data types:
Elasticsearch |
Trino |
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No other data types are supported for predicate push down.