Large queries may throw
Extremely 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
Elasticsearch 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:
SELECT dep.dep_name.keyword FROM test_emp GROUP BY languages;
Elasticsearch 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_B cannot be used at the same time, nor
For such situations, Elasticsearch SQL will display an error message.
Paginating nested inner hitsedit
When 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.
keyword fields in Elasticsearch can be normalized by defining a
normalizer. Such fields are not supported in Elasticsearch SQL.
Array type of fieldsedit
Array 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 aggregationedit
When 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 512 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.
Using aggregation functions on top of scalar functionsedit
Using a sub-selectedit
Using 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
FROM (SELECT ...) WHERE [simple_condition], this is currently un-supported.
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_shape fields don’t have doc values these fields cannot be used for filtering, grouping or sorting.
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.
ST_Z function in the filtering, grouping or sorting will return
Most 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:
geo_shape since they are NOT returned from
When the number of columns retrievable from
docvalue_fields is greater than the configured
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))
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))