Select
Important
This documentation has been retired and might not be updated. The products, services, or technologies mentioned in this content are no longer supported. See SELECT.
SELECT [hints, ...] [ALL|DISTINCT] named_expression[, named_expression, ...]
FROM relation[, relation, ...]
[lateral_view[, lateral_view, ...]]
[WHERE boolean_expression]
[aggregation [HAVING boolean_expression]]
[ORDER BY sort_expressions]
[CLUSTER BY expressions]
[DISTRIBUTE BY expressions]
[SORT BY sort_expressions]
[WINDOW named_window[, WINDOW named_window, ...]]
[LIMIT num_rows]
named_expression:
: expression [AS alias]
relation:
| join_relation
| (table_name|query|relation) [sample] [AS alias]
: VALUES (expressions)[, (expressions), ...]
[AS (column_name[, column_name, ...])]
expressions:
: expression[, expression, ...]
sort_expressions:
: expression [ASC|DESC][, expression [ASC|DESC], ...]
Output data from one or more relations.
A relation refers to any source of input data. It could be the contents of an existing table (or view), the joined result of two existing tables, or a subquery (the result of another SELECT
statement).
ALL
Select all matching rows from the relation. Enabled by default.
DISTINCT
Select all matching rows from the relation then remove duplicate results.
WHERE
Filter rows by predicate.
HAVING
Filter grouped result by predicate.
ORDER BY
Impose total ordering on a set of expressions. Default sort direction is ascending. You cannot use this with SORT BY
, CLUSTER BY
, or DISTRIBUTE BY
.
DISTRIBUTE BY
Repartition rows in the relation based on a set of expressions. Rows with the same expression values will be hashed to the same worker. You cannot use this with ORDER BY
or CLUSTER BY
.
SORT BY
Impose ordering on a set of expressions within each partition. Default sort direction is ascending. You cannot use this with ORDER BY
or CLUSTER BY
.
CLUSTER BY
Repartition rows in the relation based on a set of expressions and sort the rows in ascending order based on the expressions. In other words, this is a shorthand for DISTRIBUTE BY
and SORT BY
where all expressions are sorted in ascending order. You cannot use this with ORDER BY
, DISTRIBUTE BY
, or SORT BY
.
WINDOW
Assign an identifier to a window specification. See Window functions.
LIMIT
Limit the number of rows returned.
VALUES
Explicitly specify values instead of reading them from a relation.
Examples
SELECT * FROM boxes
SELECT width, length FROM boxes WHERE height=3
SELECT DISTINCT width, length FROM boxes WHERE height=3 LIMIT 2
SELECT * FROM VALUES (1, 2, 3) AS (width, length, height)
SELECT * FROM VALUES (1, 2, 3), (2, 3, 4) AS (width, length, height)
SELECT * FROM boxes ORDER BY width
SELECT * FROM boxes DISTRIBUTE BY width SORT BY width
SELECT * FROM boxes CLUSTER BY length
Delta tables
You can specify a table as
delta.<path-to-table>
or<table-name>
.You can specify a time travel version after the table identifier using
TIMESTAMP AS OF
,VERSION AS OF
, or@
syntax. See Work with Delta Lake table history for details.
Table sample
sample:
| TABLESAMPLE ([integer_expression | decimal_expression] PERCENT)
: TABLESAMPLE (integer_expression ROWS)
Sample the input data. Express in terms of either a percentage (must be between 0 and 100) or a fixed number of input rows.
Join
join_relation:
| relation join_type JOIN relation [ON boolean_expression | USING (column_name, column_name) ]
: relation NATURAL join_type JOIN relation
join_type:
| INNER
| [LEFT | RIGHT] SEMI
| [LEFT | RIGHT | FULL] [OUTER]
: [LEFT] ANTI
INNER JOIN
Select all rows from both relations where there is match.
OUTER JOIN
Select all rows from both relations, filling with null values on the side that does not have a match.
SEMI JOIN
Select only rows from the side of the
SEMI JOIN
where there is a match. If one row matches multiple rows, only the first match is returned.LEFT ANTI JOIN
Select only rows from the left side that match no rows on the right side.
Lateral view
lateral_view:
: LATERAL VIEW [OUTER] function_name (expressions)
table_name [AS (column_name[, column_name, ...])]
Generate zero or more output rows for each input row using a table-generating function. The most common built-in function used with LATERAL VIEW
is explode
.
LATERAL VIEW OUTER
Generate a row with null values even when the function returned zero rows.
Group by
aggregation:
: GROUP BY expressions [WITH ROLLUP | WITH CUBE | GROUPING SETS (expressions)]
Group by a set of expressions using one or more aggregate functions. Common built-in aggregate functions include count, avg, min, max, and sum.
ROLLUP
Create a grouping set at each hierarchical level of the specified expressions. For instance, For instance, GROUP BY a, b, c WITH ROLLUP
is equivalent to GROUP BY a, b, c GROUPING SETS ((a, b, c), (a, b), (a), ())
. The total number of grouping sets will be N + 1
, where N
is the number of group expressions.
CUBE
Create a grouping set for each possible combination of set of the specified expressions. For instance, GROUP BY a, b, c WITH CUBE
is equivalent to GROUP BY a, b, c GROUPING SETS ((a, b, c), (a, b), (b, c), (a, c), (a), (b), (c), ())
. The total number of grouping sets will be 2^N
, where N
is the number of group expressions.
GROUPING SETS
Perform a group by for each subset of the group expressions specified in the grouping sets. For instance, GROUP BY x, y GROUPING SETS (x, y)
is equivalent to the result of GROUP BY x
unioned with that of GROUP BY y
.
Examples
SELECT height, COUNT(*) AS num_rows FROM boxes GROUP BY height
SELECT width, AVG(length) AS average_length FROM boxes GROUP BY width
SELECT width, length, height FROM boxes GROUP BY width, length, height WITH ROLLUP
SELECT width, length, avg(height) FROM boxes GROUP BY width, length GROUPING SETS (width, length)
Window functions
window_expression:
: expression OVER window_spec
named_window:
: window_identifier AS window_spec
window_spec:
| window_identifier
: ( [PARTITION | DISTRIBUTE] BY expressions
[[ORDER | SORT] BY sort_expressions] [window_frame])
window_frame:
| [RANGE | ROWS] frame_bound
: [RANGE | ROWS] BETWEEN frame_bound AND frame_bound
frame_bound:
| CURRENT ROW
| UNBOUNDED [PRECEDING | FOLLOWING]
: expression [PRECEDING | FOLLOWING]
Compute a result over a range of input rows. A windowed expression is specified using the OVER
keyword, which is followed by either an identifier to the window (defined using the WINDOW
keyword) or the specification of a window.
PARTITION BY
Specify which rows will be in the same partition, aliased by DISTRIBUTE BY
.
ORDER BY
Specify how rows within a window partition are ordered, aliased by SORT BY
.
RANGE bound
Express the size of the window in terms of a value range for the expression.
ROWS bound
Express the size of the window in terms of the number of rows before and/or after the current row.
CURRENT ROW
Use the current row as a bound.
UNBOUNDED
Use negative infinity as the lower bound or infinity as the upper bound.
PRECEDING
If used with a RANGE
bound, this defines the lower bound of the value range. If used with a ROWS
bound, this determines the number of rows before the current row to keep in the window.
FOLLOWING
If used with a RANGE
bound, this defines the upper bound of the value range. If used with a ROWS
bound, this determines the number of rows after the current row to keep in the window.
Hints
hints:
: /*+ hint[, hint, ...] */
hint:
: hintName [(expression[, expression, ...])]
You use hints improve the performance of a query. For example, you can hint that a table is small enough to be broadcast, which would speed up joins.
You add one or more hints to a SELECT
statement inside /*+ ... */
comment blocks. You can specify multiple hints inside the same comment block, in which case the hints are separated by commas, and there can be multiple such comment blocks. A hint has a name (for example, BROADCAST
) and accepts 0 or more parameters.
Examples
SELECT /*+ BROADCAST(customers) */ * FROM customers, orders WHERE o_custId = c_custId
SELECT /*+ SKEW('orders') */ * FROM customers, orders WHERE o_custId = c_custId
SELECT /*+ SKEW('orders'), BROADCAST(demographic) */ * FROM orders, customers, demographic WHERE o_custId = c_custId AND c_demoId = d_demoId
Delta Lake on Databricks See Skew join optimization for more information about the SKEW
hint.