- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.10
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Setting JVM options
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
- HTTP
- Index lifecycle management settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging
- Machine learning settings
- Monitoring settings
- Node
- Network settings
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- Transforms settings
- Transport
- Thread pools
- Watcher settings
- Important Elasticsearch configuration
- Important System Configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Max file size check
- Maximum size virtual memory check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- All permission check
- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
- Full-cluster restart and rolling restart
- Remote clusters
- Set up X-Pack
- Configuring X-Pack Java Clients
- Plugins
- Upgrade Elasticsearch
- Index modules
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Token filter reference
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten graph
- Hunspell
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword marker
- Keyword repeat
- KStem
- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
- Pattern replace
- Phonetic
- Porter stem
- Predicate script
- Remove duplicates
- Reverse
- Shingle
- Snowball
- Stemmer
- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
- Truncate
- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index templates
- Data streams
- Ingest node
- Search your data
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Geo-distance
- Geohash grid
- Geotile grid
- Global
- Histogram
- IP range
- Missing
- Nested
- Parent
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Bucket aggregations
- EQL
- SQL access
- Overview
- Getting Started with SQL
- Conventions and Terminology
- Security
- SQL REST API
- SQL Translate API
- SQL CLI
- SQL JDBC
- SQL ODBC
- SQL Client Applications
- SQL Language
- Functions and Operators
- Comparison Operators
- Logical Operators
- Math Operators
- Cast Operators
- LIKE and RLIKE Operators
- Aggregate Functions
- Grouping Functions
- Date/Time and Interval Functions and Operators
- Full-Text Search Functions
- Mathematical Functions
- String Functions
- Type Conversion Functions
- Geo Functions
- Conditional Functions And Expressions
- System Functions
- Reserved keywords
- SQL Limitations
- Scripting
- Data management
- ILM: Manage the index lifecycle
- Overview
- Concepts
- Automate rollover
- Manage Filebeat time-based indices
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Resolve lifecycle policy execution errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Monitor a cluster
- Frozen indices
- Roll up or transform your data
- Set up a cluster for high availability
- Snapshot and restore
- Secure a cluster
- Overview
- Configuring security
- User authentication
- Built-in users
- Internal users
- Token-based authentication services
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Controlling the user cache
- Configuring SAML single-sign-on on the Elastic Stack
- Configuring single sign-on to the Elastic Stack using OpenID Connect
- User authorization
- Built-in roles
- Defining roles
- Granting access to Stack Management features
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams and index aliases
- Mapping users and groups to roles
- Setting up field and document level security
- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enabling audit logging
- Encrypting communications
- Restricting connections with IP filtering
- Cross cluster search, clients, and integrations
- Tutorial: Getting started with security
- Tutorial: Encrypting communications
- Troubleshooting
- Some settings are not returned via the nodes settings API
- Authorization exceptions
- Users command fails due to extra arguments
- Users are frequently locked out of Active Directory
- Certificate verification fails for curl on Mac
- SSLHandshakeException causes connections to fail
- Common SSL/TLS exceptions
- Common Kerberos exceptions
- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
- Failures due to relocation of the configuration files
- Limitations
- Watch for cluster and index events
- Command line tools
- How To
- Glossary of terms
- REST APIs
- API conventions
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat count
- cat data frame analytics
- cat datafeeds
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat snapshots
- cat task management
- cat templates
- cat thread pool
- cat trained model
- cat transforms
- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Nodes reload secure settings
- Nodes stats
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Cross-cluster replication APIs
- Data stream APIs
- Document APIs
- Enrich APIs
- Graph explore API
- Index APIs
- Add index alias
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Delete index
- Delete index alias
- Delete component template
- Delete index template
- Delete index template (legacy)
- Flush
- Force merge
- Freeze index
- Get component template
- Get field mapping
- Get index
- Get index alias
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Index alias exists
- Index exists
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- Open index
- Put index template
- Put index template (legacy)
- Put component template
- Put mapping
- Refresh
- Rollover index
- Shrink index
- Simulate index
- Simulate template
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index alias
- Update index settings
- Resolve index
- List dangling indices
- Import dangling index
- Delete dangling index
- Index lifecycle management APIs
- Ingest APIs
- Info API
- Licensing APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendars
- Create datafeeds
- Create filters
- Delete calendars
- Delete datafeeds
- Delete events from calendar
- Delete filters
- Delete forecasts
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Estimate model memory
- Find file structure
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Revert model snapshots
- Set upgrade mode
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create trained models
- Update data frame analytics jobs
- Delete data frame analytics jobs
- Delete trained models
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Get trained models
- Get trained models stats
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Search APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 7.10.2
- Elasticsearch version 7.10.1
- Elasticsearch version 7.10.0
- Elasticsearch version 7.9.3
- Elasticsearch version 7.9.2
- Elasticsearch version 7.9.1
- Elasticsearch version 7.9.0
- Elasticsearch version 7.8.1
- Elasticsearch version 7.8.0
- Elasticsearch version 7.7.1
- Elasticsearch version 7.7.0
- Elasticsearch version 7.6.2
- Elasticsearch version 7.6.1
- Elasticsearch version 7.6.0
- Elasticsearch version 7.5.2
- Elasticsearch version 7.5.1
- Elasticsearch version 7.5.0
- Elasticsearch version 7.4.2
- Elasticsearch version 7.4.1
- Elasticsearch version 7.4.0
- Elasticsearch version 7.3.2
- Elasticsearch version 7.3.1
- Elasticsearch version 7.3.0
- Elasticsearch version 7.2.1
- Elasticsearch version 7.2.0
- Elasticsearch version 7.1.1
- Elasticsearch version 7.1.0
- Elasticsearch version 7.0.0
- Elasticsearch version 7.0.0-rc2
- Elasticsearch version 7.0.0-rc1
- Elasticsearch version 7.0.0-beta1
- Elasticsearch version 7.0.0-alpha2
- Elasticsearch version 7.0.0-alpha1
- Dependencies and versions
SQL Limitations
editSQL Limitations
editLarge queries may throw ParsingExpection
editExtremely large queries can consume too much memory during the parsing phase, in which case the Elasticsearch SQL engine will abort parsing and throw an error. In such cases, consider reducing the query to a smaller size by potentially simplifying it or splitting it into smaller queries.
Nested fields in SYS COLUMNS
and DESCRIBE TABLE
editElasticsearch has a special type of relationship fields called nested
fields. In Elasticsearch SQL they can be used by referencing their inner
sub-fields. Even though SYS COLUMNS
in non-driver mode (in the CLI and in REST calls) and DESCRIBE TABLE
will still display
them as having the type NESTED
, they cannot be used in a query. One can only reference its sub-fields in the form:
[nested_field_name].[sub_field_name]
For example:
SELECT dep.dep_name.keyword FROM test_emp GROUP BY languages;
Scalar functions on nested fields are not allowed in WHERE
and ORDER BY
clauses
editElasticsearch SQL doesn’t support the usage of scalar functions on top of nested fields in WHERE
and ORDER BY
clauses with the exception of comparison and logical operators.
For example:
SELECT * FROM test_emp WHERE LENGTH(dep.dep_name.keyword) > 5;
and
SELECT * FROM test_emp ORDER BY YEAR(dep.start_date);
are not supported but:
SELECT * FROM test_emp WHERE dep.start_date >= CAST('2020-01-01' AS DATE) OR dep.dep_end_date IS NULL;
is supported.
Multi-nested fields
editElasticsearch SQL doesn’t support multi-nested documents, so a query cannot reference more than one nested field in an index. This applies to multi-level nested fields, but also multiple nested fields defined on the same level. For example, for this index:
column | type | mapping ----------------------+---------------+------------- nested_A |STRUCT |NESTED nested_A.nested_X |STRUCT |NESTED nested_A.nested_X.text|VARCHAR |KEYWORD nested_A.text |VARCHAR |KEYWORD nested_B |STRUCT |NESTED nested_B.text |VARCHAR |KEYWORD
nested_A
and nested_B
cannot be used at the same time, nor nested_A
/nested_B
and nested_A.nested_X
combination.
For such situations, Elasticsearch SQL will display an error message.
Paginating nested inner hits
editWhen SELECTing a nested field, pagination will not work as expected, Elasticsearch SQL will return at least the page size records. This is because of the way nested queries work in Elasticsearch: the root nested field will be returned and it’s matching inner nested fields as well, pagination taking place on the root nested document and not on its inner hits.
Normalized keyword
fields
editkeyword
fields in Elasticsearch can be normalized by defining a normalizer
. Such fields are not supported in Elasticsearch SQL.
Array type of fields
editArray fields are not supported due to the "invisible" way in which Elasticsearch handles an array of values: the mapping doesn’t indicate whether
a field is an array (has multiple values) or not, so without reading all the data, Elasticsearch SQL cannot know whether a field is a single or multi value.
When multiple values are returned for a field, by default, Elasticsearch SQL will throw an exception. However, it is possible to change this behavior through field_multi_value_leniency
parameter in REST (disabled by default) or
field.multi.value.leniency
in drivers (enabled by default).
Sorting by aggregation
editWhen doing aggregations (GROUP BY
) Elasticsearch SQL relies on Elasticsearch’s composite
aggregation for its support for paginating results.
However this type of aggregation does come with a limitation: sorting can only be applied on the key used for the aggregation’s buckets.
Elasticsearch SQL overcomes this limitation by doing client-side sorting however as a safety measure, allows only up to 65535 rows.
It is recommended to use LIMIT
for queries that use sorting by aggregation, essentially indicating the top N results that are desired:
SELECT * FROM test GROUP BY age ORDER BY COUNT(*) LIMIT 100;
It is possible to run the same queries without a LIMIT
however in that case if the maximum size (10000) is passed,
an exception will be returned as Elasticsearch SQL is unable to track (and sort) all the results returned.
Moreover, the aggregation(s) used in the ORDER BY
must be only plain aggregate functions. No scalar
functions or operators can be used, and therefore no complex columns that combine two ore more aggregate
functions can be used for ordering. Here are some examples of queries that are not allowed:
SELECT age, ROUND(AVG(salary)) AS avg FROM test GROUP BY age ORDER BY avg; SELECT age, MAX(salary) - MIN(salary) AS diff FROM test GROUP BY age ORDER BY diff;
Using a sub-select
editUsing sub-selects (SELECT X FROM (SELECT Y)
) is supported to a small degree: any sub-select that can be "flattened" into a single
SELECT
is possible with Elasticsearch SQL. For example:
SELECT * FROM (SELECT first_name, last_name FROM emp WHERE last_name NOT LIKE '%a%') WHERE first_name LIKE 'A%' ORDER BY 1; first_name | last_name ---------------+--------------- Alejandro |McAlpine Anneke |Preusig Anoosh |Peyn Arumugam |Ossenbruggen
The query above is possible because it is equivalent with:
SELECT first_name, last_name FROM emp WHERE last_name NOT LIKE '%a%' AND first_name LIKE 'A%' ORDER BY 1;
But, if the sub-select would include a GROUP BY
or HAVING
or the enclosing SELECT
would be more complex than SELECT X
FROM (SELECT ...) WHERE [simple_condition]
, this is currently un-supported.
Using FIRST
and LAST
in the HAVING
clause is not supported. The same applies to
MIN
and MAX
when their target column
is of type keyword
as they are internally translated to FIRST
and LAST
.
Using TIME
data type as a grouping key is currently not supported. For example:
SELECT count(*) FROM test GROUP BY CAST(date_created AS TIME);
On the other hand, it can still be used if it’s wrapped with a scalar function that returns another data type, for example:
SELECT count(*) FROM test GROUP BY MINUTE((CAST(date_created AS TIME));
TIME
data type is also currently not supported in histogram grouping function. For example:
SELECT HISTOGRAM(CAST(birth_date AS TIME), INTERVAL '10' MINUTES) as h, COUNT(*) FROM t GROUP BY h
Geo-related functions
editSince geo_shape
fields don’t have doc values these fields cannot be used for filtering, grouping or sorting.
By default,geo_points
fields are indexed and have doc values. However only latitude and longitude are stored and
indexed with some loss of precision from the original values (4.190951585769653E-8 for the latitude and
8.381903171539307E-8 for longitude). The altitude component is accepted but not stored in doc values nor indexed.
Therefore calling ST_Z
function in the filtering, grouping or sorting will return null
.
Retrieving from _source
editMost of Elasticsearch SQL’s columns are retrieved from the document’s _source
and there is no attempt to get the columns content from
docvalue_fields
not even in the case _source
field is disabled in the mapping explicitly.
If a column, for which there is no source stored, is asked for in a query, Elasticsearch SQL will not return it. Field types that don’t follow
this restriction are: keyword
, date
, scaled_float
, geo_point
, geo_shape
since they are NOT returned from _source
but
from docvalue_fields
.
Retrieving from docvalue_fields
editWhen the number of columns retrievable from docvalue_fields
is greater than the configured index.max_docvalue_fields_search
setting
the query will fail with IllegalArgumentException: Trying to retrieve too many docvalue_fields
error. Either the mentioned Elasticsearch
setting needs to be adjusted or fewer columns retrievable from docvalue_fields
need to be selected.
The aggregation expression in PIVOT
will currently accept only one aggregation. It is thus not possible to obtain multiple aggregations for any one pivoted column.
The values that the PIVOT
query could pivot must be provided in the query as a list of literals; providing a subquery instead to build this list is not currently supported. For example, in this query:
SELECT * FROM test_emp PIVOT (SUM(salary) FOR languages IN (1, 2))
the languages
of interest must be listed explicitly: IN (1, 2)
. On the other hand, this example would not work:
SELECT * FROM test_emp PIVOT (SUM(salary) FOR languages IN (SELECT languages FROM test_emp WHERE languages <=2 GROUP BY languages))
On this page
- Large queries may throw
ParsingExpection
- Nested fields in
SYS COLUMNS
andDESCRIBE TABLE
- Scalar functions on nested fields are not allowed in
WHERE
andORDER BY
clauses - Multi-nested fields
- Paginating nested inner hits
- Normalized
keyword
fields - Array type of fields
- Sorting by aggregation
- Using a sub-select
- Using / aggregation functions in
HAVING
clause - Using TIME data type in GROUP BY or
- Geo-related functions
- Retrieving from
_source
- Retrieving from
docvalue_fields
- Aggregations in the clause
- Using a subquery in 's
IN
-subclause