245 lines
11 KiB
Plaintext
245 lines
11 KiB
Plaintext
[role="xpack"]
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[testenv="basic"]
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[[sql-limitations]]
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== SQL Limitations
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[float]
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[[large-parsing-trees]]
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=== Large queries may throw `ParsingExpection`
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Extremely large queries can consume too much memory during the parsing phase, in which case the {es-sql} engine will
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abort parsing and throw an error. In such cases, consider reducing the query to a smaller size by potentially
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simplifying it or splitting it into smaller queries.
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[float]
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[[sys-columns-describe-table-nested-fields]]
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=== Nested fields in `SYS COLUMNS` and `DESCRIBE TABLE`
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{es} has a special type of relationship fields called `nested` fields. In {es-sql} they can be used by referencing their inner
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sub-fields. Even though `SYS COLUMNS` in non-driver mode (in the CLI and in REST calls) and `DESCRIBE TABLE` will still display
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them as having the type `NESTED`, they cannot be used in a query. One can only reference its sub-fields in the form:
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[source, sql]
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--------------------------------------------------
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[nested_field_name].[sub_field_name]
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--------------------------------------------------
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For example:
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[source, sql]
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--------------------------------------------------
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SELECT dep.dep_name.keyword FROM test_emp GROUP BY languages;
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--------------------------------------------------
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[float]
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=== Scalar functions on nested fields are not allowed in `WHERE` and `ORDER BY` clauses
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{es-sql} doesn't support the usage of scalar functions on top of nested fields in `WHERE`
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and `ORDER BY` clauses with the exception of comparison and logical operators.
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For example:
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[source, sql]
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--------------------------------------------------
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SELECT * FROM test_emp WHERE LENGTH(dep.dep_name.keyword) > 5;
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--------------------------------------------------
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and
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[source, sql]
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--------------------------------------------------
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SELECT * FROM test_emp ORDER BY YEAR(dep.start_date);
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--------------------------------------------------
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are not supported but:
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[source, sql]
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--------------------------------------------------
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SELECT * FROM test_emp WHERE dep.start_date >= CAST('2020-01-01' AS DATE) OR dep.dep_end_date IS NULL;
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--------------------------------------------------
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is supported.
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[float]
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=== Multi-nested fields
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{es-sql} doesn't support multi-nested documents, so a query cannot reference more than one nested field in an index.
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This applies to multi-level nested fields, but also multiple nested fields defined on the same level. For example, for this index:
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[source, sql]
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----------------------------------------------------
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column | type | mapping
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----------------------+---------------+-------------
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nested_A |STRUCT |NESTED
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nested_A.nested_X |STRUCT |NESTED
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nested_A.nested_X.text|VARCHAR |KEYWORD
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nested_A.text |VARCHAR |KEYWORD
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nested_B |STRUCT |NESTED
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nested_B.text |VARCHAR |KEYWORD
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----------------------------------------------------
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`nested_A` and `nested_B` cannot be used at the same time, nor `nested_A`/`nested_B` and `nested_A.nested_X` combination.
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For such situations, {es-sql} will display an error message.
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[float]
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=== Paginating nested inner hits
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When SELECTing a nested field, pagination will not work as expected, {es-sql} will return __at least__ the page size records.
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This is because of the way nested queries work in {es}: the root nested field will be returned and it's matching inner nested fields as well,
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pagination taking place on the **root nested document and not on its inner hits**.
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[float]
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[[normalized-keyword-fields]]
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=== Normalized `keyword` fields
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`keyword` fields in {es} can be normalized by defining a `normalizer`. Such fields are not supported in {es-sql}.
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[float]
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=== Array type of fields
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Array fields are not supported due to the "invisible" way in which {es} handles an array of values: the mapping doesn't indicate whether
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a field is an array (has multiple values) or not, so without reading all the data, {es-sql} cannot know whether a field is a single or multi value.
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When multiple values are returned for a field, by default, {es-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
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`field.multi.value.leniency` in drivers (enabled by default).
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[float]
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=== Sorting by aggregation
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When doing aggregations (`GROUP BY`) {es-sql} relies on {es}'s `composite` aggregation for its support for paginating results.
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However this type of aggregation does come with a limitation: sorting can only be applied on the key used for the aggregation's buckets.
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{es-sql} overcomes this limitation by doing client-side sorting however as a safety measure, allows only up to *512* rows.
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It is recommended to use `LIMIT` for queries that use sorting by aggregation, essentially indicating the top N results that are desired:
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[source, sql]
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--------------------------------------------------
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SELECT * FROM test GROUP BY age ORDER BY COUNT(*) LIMIT 100;
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--------------------------------------------------
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It is possible to run the same queries without a `LIMIT` however in that case if the maximum size (*10000*) is passed,
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an exception will be returned as {es-sql} is unable to track (and sort) all the results returned.
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Moreover, the aggregation(s) used in the `ORDER BY` must be only plain aggregate functions. No scalar
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functions or operators can be used, and therefore no complex columns that combine two ore more aggregate
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functions can be used for ordering. Here are some examples of queries that are *not allowed*:
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[source, sql]
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--------------------------------------------------
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SELECT age, ROUND(AVG(salary)) AS avg FROM test GROUP BY age ORDER BY avg;
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SELECT age, MAX(salary) - MIN(salary) AS diff FROM test GROUP BY age ORDER BY diff;
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--------------------------------------------------
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[float]
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=== Using aggregation functions on top of scalar functions
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Aggregation functions like <<sql-functions-aggs-min,`MIN`>>, <<sql-functions-aggs-max,`MAX`>>, etc. can only be used
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directly on fields, and so queries like `SELECT MAX(abs(age)) FROM test` are not possible.
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[float]
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=== Using a sub-select
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Using sub-selects (`SELECT X FROM (SELECT Y)`) is **supported to a small degree**: any sub-select that can be "flattened" into a single
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`SELECT` is possible with {es-sql}. For example:
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["source","sql",subs="attributes,macros"]
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--------------------------------------------------
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include-tagged::{sql-specs}/docs/docs.csv-spec[limitationSubSelect]
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--------------------------------------------------
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The query above is possible because it is equivalent with:
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["source","sql",subs="attributes,macros"]
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--------------------------------------------------
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include-tagged::{sql-specs}/docs/docs.csv-spec[limitationSubSelectRewritten]
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--------------------------------------------------
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But, if the sub-select would include a `GROUP BY` or `HAVING` or the enclosing `SELECT` would be more complex than `SELECT X
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FROM (SELECT ...) WHERE [simple_condition]`, this is currently **un-supported**.
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[float]
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[[first-last-agg-functions-having-clause]]
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=== Using <<sql-functions-aggs-first, `FIRST`>>/<<sql-functions-aggs-last,`LAST`>> aggregation functions in `HAVING` clause
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Using `FIRST` and `LAST` in the `HAVING` clause is not supported. The same applies to
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<<sql-functions-aggs-min,`MIN`>> and <<sql-functions-aggs-max,`MAX`>> when their target column
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is of type <<keyword, `keyword`>> as they are internally translated to `FIRST` and `LAST`.
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[float]
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[[group-by-time]]
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=== Using TIME data type in GROUP BY or <<sql-functions-grouping-histogram>>
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Using `TIME` data type as a grouping key is currently not supported. For example:
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[source, sql]
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-------------------------------------------------------------
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SELECT count(*) FROM test GROUP BY CAST(date_created AS TIME);
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-------------------------------------------------------------
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On the other hand, it can still be used if it's wrapped with a scalar function that returns another data type,
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for example:
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[source, sql]
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-------------------------------------------------------------
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SELECT count(*) FROM test GROUP BY MINUTE((CAST(date_created AS TIME));
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-------------------------------------------------------------
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`TIME` data type is also currently not supported in histogram grouping function. For example:
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[source, sql]
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-------------------------------------------------------------
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SELECT HISTOGRAM(CAST(birth_date AS TIME), INTERVAL '10' MINUTES) as h, COUNT(*) FROM t GROUP BY h
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-------------------------------------------------------------
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[float]
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[[geo-sql-limitations]]
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=== Geo-related functions
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Since `geo_shape` fields don't have doc values these fields cannot be used for filtering, grouping or sorting.
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By default,`geo_points` fields are indexed and have doc values. However only latitude and longitude are stored and
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indexed with some loss of precision from the original values (4.190951585769653E-8 for the latitude and
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8.381903171539307E-8 for longitude). The altitude component is accepted but not stored in doc values nor indexed.
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Therefore calling `ST_Z` function in the filtering, grouping or sorting will return `null`.
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[float]
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[[fields-from-source]]
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=== Retrieving from `_source`
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Most of {es-sql}'s columns are retrieved from the document's `_source` and there is no attempt to get the columns content from
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`docvalue_fields` not even in the case <<mapping-source-field,`_source`>> field is disabled in the mapping explicitly.
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If a column, for which there is no source stored, is asked for in a query, {es-sql} will not return it. Field types that don't follow
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this restriction are: `keyword`, `date`, `scaled_float`, `geo_point`, `geo_shape` since they are NOT returned from `_source` but
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from `docvalue_fields`.
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[float]
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[[fields-from-docvalues]]
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=== Retrieving from `docvalue_fields`
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When the number of columns retrievable from `docvalue_fields` is greater than the configured <<dynamic-index-settings,`index.max_docvalue_fields_search` setting>>
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the query will fail with `IllegalArgumentException: Trying to retrieve too many docvalue_fields` error. Either the mentioned {es}
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setting needs to be adjusted or fewer columns retrievable from `docvalue_fields` need to be selected.
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[float]
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[[aggs-in-pivot]]
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=== Aggregations in the <<sql-syntax-pivot, `PIVOT`>> clause
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The aggregation expression in <<sql-syntax-pivot, `PIVOT`>> will currently accept only one aggregation. It is thus not possible to obtain multiple aggregations for any one pivoted column.
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[float]
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[[subquery-in-pivot]]
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=== Using a subquery in <<sql-syntax-pivot, `PIVOT`>>'s `IN`-subclause
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The values that the <<sql-syntax-pivot, `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:
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[source, sql]
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-------------------------------------------------------------
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SELECT * FROM test_emp PIVOT (SUM(salary) FOR languages IN (1, 2))
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-------------------------------------------------------------
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the `languages` of interest must be listed explicitly: `IN (1, 2)`. On the other hand, this example would **not work**:
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[source, sql]
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-------------------------------------------------------------
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SELECT * FROM test_emp PIVOT (SUM(salary) FOR languages IN (SELECT languages FROM test_emp WHERE languages <=2 GROUP BY languages))
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-------------------------------------------------------------
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