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.

Examples 

SELECT * FROM delta.`/mnt/delta/events` TIMESTAMP AS OF '2019-10-18T22:15:12.013Z'
SELECT * FROM events VERSION AS OF 5

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.

Examples 

SELECT * FROM boxes TABLESAMPLE (3 ROWS)
SELECT * FROM boxes TABLESAMPLE (25 PERCENT)

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.

Examples 

SELECT * FROM boxes INNER JOIN rectangles ON boxes.width = rectangles.width
SELECT * FROM boxes FULL OUTER JOIN rectangles USING (width, length)
SELECT * FROM boxes NATURAL JOIN rectangles

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.

Examples 

SELECT * FROM boxes LATERAL VIEW explode(Array(1, 2, 3)) my_view
SELECT name, my_view.grade FROM students LATERAL VIEW OUTER explode(grades) my_view AS grade

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.