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- Dependencies and versions
SELECT
editSELECT
editSynopsis:
SELECT [TOP [ count ] ] select_expr [, ...] [ FROM table_name ] [ WHERE condition ] [ GROUP BY grouping_element [, ...] ] [ HAVING condition] [ ORDER BY expression [ ASC | DESC ] [, ...] ] [ LIMIT [ count ] ] [ PIVOT ( aggregation_expr FOR column IN ( value [ [ AS ] alias ] [, ...] ) ) ]
Description: Retrieves rows from zero or more tables.
The general execution of SELECT
is as follows:
-
All elements in the
FROM
list are computed (each element can be base or alias table). CurrentlyFROM
supports exactly one table. Do note however that the table name can be a pattern (see FROM Clause below). -
If the
WHERE
clause is specified, all rows that do not satisfy the condition are eliminated from the output. (See WHERE Clause below.) -
If the
GROUP BY
clause is specified, or if there are aggregate function calls, the output is combined into groups of rows that match on one or more values, and the results of aggregate functions are computed. If theHAVING
clause is present, it eliminates groups that do not satisfy the given condition. (See GROUP BY Clause and HAVING Clause below.) -
The actual output rows are computed using the
SELECT
output expressions for each selected row or row group. -
If the
ORDER BY
clause is specified, the returned rows are sorted in the specified order. IfORDER BY
is not given, the rows are returned in whatever order the system finds fastest to produce. (See ORDER BY Clause below.) -
If the
LIMIT
orTOP
is specified (cannot use both in the same query), theSELECT
statement only returns a subset of the result rows. (See LIMIT Clause and TOP clause below.)
SELECT
List
editSELECT
list, namely the expressions between SELECT
and FROM
, represent the output rows of the SELECT
statement.
As with a table, every output column of a SELECT
has a name which can be either specified per column through the AS
keyword :
SELECT 1 + 1 AS result; result --------------- 2
Note: AS
is an optional keyword however it helps with the readability and in some case ambiguity of the query
which is why it is recommended to specify it.
assigned by Elasticsearch SQL if no name is given:
SELECT 1 + 1; 1 + 1 -------------- 2
or if it’s a simple column reference, use its name as the column name:
SELECT emp_no FROM emp LIMIT 1; emp_no --------------- 10001
Wildcard
editTo select all the columns in the source, one can use *
:
SELECT * FROM emp LIMIT 1; birth_date | emp_no | first_name | gender | hire_date | languages | last_name | salary --------------------+---------------+---------------+---------------+--------------------+---------------+---------------+--------------- 1953-09-02T00:00:00Z|10001 |Georgi |M |1986-06-26T00:00:00Z|2 |Facello |57305
which essentially returns all(top-level fields, sub-fields, such as multi-fields are ignored] columns found.
TOP
editThe TOP
clause can be used before the SELECT
list or the <<sql-syntax-select-wildcard, wildcard
> to
restrict (limit) the number of rows returned using the format:
SELECT TOP <count> <select list> ...
where
- count
-
is a positive integer or zero indicating the maximum possible number of results being returned (as there might be fewer matches
than the limit). If
0
is specified, no results are returned.
SELECT TOP 2 first_name, last_name, emp_no FROM emp; first_name | last_name | emp_no ---------------+---------------+--------------- Georgi |Facello |10001 Bezalel |Simmel |10002
FROM Clause
editThe FROM
clause specifies one table for the SELECT
and has the following syntax:
FROM table_name [ [ AS ] alias ]
where:
-
table_name
- Represents the name (optionally qualified) of an existing table, either a concrete or base one (actual index) or alias.
If the table name contains special SQL characters (such as .
,-
,*
,etc…) use double quotes to escape them:
SELECT * FROM "emp" LIMIT 1; birth_date | emp_no | first_name | gender | hire_date | languages | last_name | salary --------------------+---------------+---------------+---------------+--------------------+---------------+---------------+--------------- 1953-09-02T00:00:00Z|10001 |Georgi |M |1986-06-26T00:00:00Z|2 |Facello |57305
The name can be a pattern pointing to multiple indices (likely requiring quoting as mentioned above) with the restriction that all resolved concrete tables have exact mapping.
SELECT emp_no FROM "e*p" LIMIT 1; emp_no --------------- 10001
-
alias
-
A substitute name for the
FROM
item containing the alias. An alias is used for brevity or to eliminate ambiguity. When an alias is provided, it completely hides the actual name of the table and must be used in its place.
SELECT e.emp_no FROM emp AS e LIMIT 1; emp_no ------------- 10001
WHERE Clause
editThe optional WHERE
clause is used to filter rows from the query and has the following syntax:
WHERE condition
where:
-
condition
-
Represents an expression that evaluates to a
boolean
. Only the rows that match the condition (totrue
) are returned.
SELECT last_name FROM emp WHERE emp_no = 10001; last_name --------------- Facello
GROUP BY
editThe GROUP BY
clause is used to divide the results into groups of rows on matching values from the designated columns. It has the following syntax:
GROUP BY grouping_element [, ...]
where:
-
grouping_element
- Represents an expression on which rows are being grouped on. It can be a column name, alias or ordinal number of a column or an arbitrary expression of column values.
A common, group by column name:
SELECT gender AS g FROM emp GROUP BY gender; g --------------- null F M
Grouping by output ordinal:
SELECT gender FROM emp GROUP BY 1; gender --------------- null F M
Grouping by alias:
SELECT gender AS g FROM emp GROUP BY g; g --------------- null F M
And grouping by column expression (typically used along-side an alias):
SELECT languages + 1 AS l FROM emp GROUP BY l; l --------------- null 2 3 4 5 6
Or a mixture of the above:
SELECT gender g, languages l, COUNT(*) c FROM "emp" GROUP BY g, l ORDER BY languages ASC, gender DESC; g | l | c ---------------+---------------+--------------- M |null |7 F |null |3 M |1 |9 F |1 |4 null |1 |2 M |2 |11 F |2 |5 null |2 |3 M |3 |11 F |3 |6 M |4 |11 F |4 |6 null |4 |1 M |5 |8 F |5 |9 null |5 |4
When a GROUP BY
clause is used in a SELECT
, all output expressions must be either aggregate functions or expressions used for grouping or derivatives of (otherwise there would be more than one possible value to return for each ungrouped column).
To wit:
SELECT gender AS g, COUNT(*) AS c FROM emp GROUP BY gender; g | c ---------------+--------------- null |10 F |33 M |57
Expressions over aggregates used in output:
SELECT gender AS g, ROUND((MIN(salary) / 100)) AS salary FROM emp GROUP BY gender; g | salary ---------------+--------------- null |253 F |260 M |259
Multiple aggregates used:
SELECT gender AS g, KURTOSIS(salary) AS k, SKEWNESS(salary) AS s FROM emp GROUP BY gender; g | k | s ---------------+------------------+------------------- null |2.2215791166941923|-0.03373126000214023 F |1.7873117044424276|0.05504995122217512 M |2.280646181070106 |0.44302407229580243
Implicit Grouping
editWhen an aggregation is used without an associated GROUP BY
, an implicit grouping is applied, meaning all selected rows are considered to form a single default, or implicit group.
As such, the query emits only a single row (as there is only a single group).
A common example is counting the number of records:
SELECT COUNT(*) AS count FROM emp; count --------------- 100
Of course, multiple aggregations can be applied:
SELECT MIN(salary) AS min, MAX(salary) AS max, AVG(salary) AS avg, COUNT(*) AS count FROM emp; min:i | max:i | avg:d | count:l ---------------+---------------+---------------+--------------- 25324 |74999 |48248.55 |100
HAVING
editThe HAVING
clause can be used only along aggregate functions (and thus GROUP BY
) to filter what groups are kept or not and has the following syntax:
HAVING condition
where:
-
condition
-
Represents an expression that evaluates to a
boolean
. Only groups that match the condition (totrue
) are returned.
Both WHERE
and HAVING
are used for filtering however there are several significant differences between them:
-
WHERE
works on individual rows,HAVING
works on the groups created by ``GROUP BY`` -
WHERE
is evaluated before grouping,HAVING
is evaluated after grouping
SELECT languages AS l, COUNT(*) AS c FROM emp GROUP BY l HAVING c BETWEEN 15 AND 20; l | c ---------------+--------------- 1 |15 2 |19 3 |17 4 |18
Further more, one can use multiple aggregate expressions inside HAVING
even ones that are not used in the output (SELECT
):
SELECT MIN(salary) AS min, MAX(salary) AS max, MAX(salary) - MIN(salary) AS diff FROM emp GROUP BY languages HAVING diff - max % min > 0 AND AVG(salary) > 30000; min | max | diff ---------------+---------------+--------------- 28336 |74999 |46663 25976 |73717 |47741 29175 |73578 |44403 26436 |74970 |48534 27215 |74572 |47357 25324 |66817 |41493
Implicit Grouping
editAs indicated above, it is possible to have a HAVING
clause without a GROUP BY
. In this case, the so-called implicit grouping is applied, meaning all selected rows are considered to form a single group and HAVING
can be applied on any of the aggregate functions specified on this group.
As such, the query emits only a single row (as there is only a single group) and HAVING
condition returns either one row (the group) or zero if the condition fails.
In this example, HAVING
matches:
SELECT MIN(salary) AS min, MAX(salary) AS max FROM emp HAVING min > 25000; min | max ---------------+--------------- 25324 |74999
ORDER BY
editThe ORDER BY
clause is used to sort the results of SELECT
by one or more expressions:
ORDER BY expression [ ASC | DESC ] [, ...]
where:
-
expression
-
Represents an input column, an output column or an ordinal number of the position (starting from one) of an output column. Additionally, ordering can be done based on the results score.
The direction, if not specified, is by default
ASC
(ascending). Regardless of the ordering specified, null values are ordered last (at the end).
When used along-side, GROUP BY
expression can point only to the columns used for grouping or aggregate functions.
For example, the following query sorts by an arbitrary input field (page_count
):
SELECT * FROM library ORDER BY page_count DESC LIMIT 5; author | name | page_count | release_date -----------------+--------------------+---------------+-------------------- Peter F. Hamilton|Pandora's Star |768 |2004-03-02T00:00:00Z Vernor Vinge |A Fire Upon the Deep|613 |1992-06-01T00:00:00Z Frank Herbert |Dune |604 |1965-06-01T00:00:00Z Alastair Reynolds|Revelation Space |585 |2000-03-15T00:00:00Z James S.A. Corey |Leviathan Wakes |561 |2011-06-02T00:00:00Z
Order By and Grouping
editFor queries that perform grouping, ordering can be applied either on the grouping columns (by default ascending) or on aggregate functions.
With GROUP BY
, make sure the ordering targets the resulting group - applying it to individual elements inside the group will have no impact on the results since regardless of the order, values inside the group are aggregated.
For example, to order groups simply indicate the grouping key:
SELECT gender AS g, COUNT(*) AS c FROM emp GROUP BY gender ORDER BY g DESC; g | c ---------------+--------------- M |57 F |33 null |10
Multiple keys can be specified of course:
SELECT gender g, languages l, COUNT(*) c FROM "emp" GROUP BY g, l ORDER BY languages ASC, gender DESC; g | l | c ---------------+---------------+--------------- M |null |7 F |null |3 M |1 |9 F |1 |4 null |1 |2 M |2 |11 F |2 |5 null |2 |3 M |3 |11 F |3 |6 M |4 |11 F |4 |6 null |4 |1 M |5 |8 F |5 |9 null |5 |4
Further more, it is possible to order groups based on aggregations of their values:
SELECT gender AS g, MIN(salary) AS salary FROM emp GROUP BY gender ORDER BY salary DESC; g | salary ---------------+--------------- F |25976 M |25945 null |25324
Order By Score
editWhen doing full-text queries in the WHERE
clause, results can be returned based on their
score or relevance to the given query.
When doing multiple text queries in the WHERE
clause then, their scores will be
combined using the same rules as Elasticsearch’s
bool query.
To sort based on the score
, use the special function SCORE()
:
SELECT SCORE(), * FROM library WHERE MATCH(name, 'dune') ORDER BY SCORE() DESC; SCORE() | author | name | page_count | release_date ---------------+---------------+-------------------+---------------+-------------------- 2.2886353 |Frank Herbert |Dune |604 |1965-06-01T00:00:00Z 1.8893257 |Frank Herbert |Dune Messiah |331 |1969-10-15T00:00:00Z 1.6086556 |Frank Herbert |Children of Dune |408 |1976-04-21T00:00:00Z 1.4005898 |Frank Herbert |God Emperor of Dune|454 |1981-05-28T00:00:00Z
Note that you can return SCORE()
by using a full-text search predicate in the WHERE
clause.
This is possible even if SCORE()
is not used for sorting:
SELECT SCORE(), * FROM library WHERE MATCH(name, 'dune') ORDER BY page_count DESC; SCORE() | author | name | page_count | release_date ---------------+---------------+-------------------+---------------+-------------------- 2.2886353 |Frank Herbert |Dune |604 |1965-06-01T00:00:00Z 1.4005898 |Frank Herbert |God Emperor of Dune|454 |1981-05-28T00:00:00Z 1.6086556 |Frank Herbert |Children of Dune |408 |1976-04-21T00:00:00Z 1.8893257 |Frank Herbert |Dune Messiah |331 |1969-10-15T00:00:00Z
NOTE:
Trying to return score
from a non full-text query will return the same value for all results, as
all are equally relevant.
LIMIT
editThe LIMIT
clause restricts (limits) the number of rows returned using the format:
LIMIT ( <count> | ALL )
where
- count
-
is a positive integer or zero indicating the maximum possible number of results being returned (as there might be fewer matches
than the limit). If
0
is specified, no results are returned. - ALL
- indicates there is no limit and thus all results are being returned.
SELECT first_name, last_name, emp_no FROM emp LIMIT 1; first_name | last_name | emp_no ---------------+---------------+--------------- Georgi |Facello |10001
PIVOT
editThe PIVOT
clause performs a cross tabulation on the results of the query: it aggregates the results and rotates rows into columns. The rotation is done by turning unique values from one column in the expression - the pivoting column - into multiple columns in the output. The column values are aggregations on the remaining columns specified in the expression.
The clause can be broken down in three parts: the aggregation, the FOR
- and the IN
-subclause.
The aggregation_expr
subclause specifies an expression containing an aggregation function to be applied on one of the source columns. Only one aggregation can be provided, currently.
The FOR
-subclause specifies the pivoting column: the distinct values of this column will become the candidate set of values to be rotated.
The IN
-subclause defines a filter: the intersection between the set provided here and the candidate set from the FOR
-subclause will be rotated to become the headers of the columns appended to the end result. The filter can not be a subquery, one must provide here literal values, obtained in advance.
The pivoting operation will perform an implicit GROUP BY on all source columns not specified in the PIVOT
clause, along with the values filtered through the IN
-clause. Consider the following statement:
SELECT * FROM test_emp PIVOT (SUM(salary) FOR languages IN (1, 2)) LIMIT 5; birth_date | emp_no | first_name | gender | hire_date | last_name | 1 | 2 ---------------------+---------------+---------------+---------------+---------------------+---------------+---------------+--------------- null |10041 |Uri |F |1989-11-12 00:00:00.0|Lenart |56415 |null null |10043 |Yishay |M |1990-10-20 00:00:00.0|Tzvieli |34341 |null null |10044 |Mingsen |F |1994-05-21 00:00:00.0|Casley |39728 |null 1952-04-19 00:00:00.0|10009 |Sumant |F |1985-02-18 00:00:00.0|Peac |66174 |null 1953-01-07 00:00:00.0|10067 |Claudi |M |1987-03-04 00:00:00.0|Stavenow |null |52044
The query execution could logically be broken down in the following steps:
-
a GROUP BY on the column in the
FOR
-clause:languages
; -
the resulting values are filtered through the set provided in the
IN
-clause; -
the now filtered column is pivoted to form the headers of the two additional columns appended to the result:
1
and2
; -
a GROUP BY on all columns of the source table
test_emp
, exceptsalary
(part of the aggregation subclause) andlanguages
(part of theFOR
-clause); -
the values in these appended columns are the
SUM
aggregations ofsalary
, grouped by the respective language.
The table-value expression to cross-tabulate can also be the result of a subquery:
SELECT * FROM (SELECT languages, gender, salary FROM test_emp) PIVOT (AVG(salary) FOR gender IN ('F')); languages | 'F' ---------------+------------------ null |62140.666666666664 1 |47073.25 2 |50684.4 3 |53660.0 4 |49291.5 5 |46705.555555555555
The pivoted columns can be aliased (and quoting is required to accommodate white spaces), with or without a supporting AS
token:
SELECT * FROM (SELECT languages, gender, salary FROM test_emp) PIVOT (AVG(salary) FOR gender IN ('M' AS "XY", 'F' "XX")); languages | XY | XX ---------------+-----------------+------------------ null |48396.28571428572|62140.666666666664 1 |49767.22222222222|47073.25 2 |44103.90909090909|50684.4 3 |51741.90909090909|53660.0 4 |47058.90909090909|49291.5 5 |39052.875 |46705.555555555555
The resulting cross tabulation can further have the ORDER BY and LIMIT clauses applied:
SELECT * FROM (SELECT languages, gender, salary FROM test_emp) PIVOT (AVG(salary) FOR gender IN ('F')) ORDER BY languages DESC LIMIT 4; languages | 'F' ---------------+------------------ 5 |46705.555555555555 4 |49291.5 3 |53660.0 2 |50684.4
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