Retrieves result sets from one or more tables.


[ WITH with_query [ , ... ] ]
select_statement [ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] select_statement, ... ]
  [ ORDER BY { expression [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ , ... ] } ]
  [ SORT BY { expression [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ , ... ] } ]
  [ CLUSTER BY { expression [ , ... ] } ]
  [ DISTRIBUTE BY { expression [, ... ] } ]
  [ WINDOW { named_window [ , WINDOW named_window, ... ] } ]
  [ LIMIT { ALL | expression } ]

While select_statement is defined as

SELECT [ hints , ... ] [ ALL | DISTINCT ] { named_expression [ , ... ] }
  FROM { from_item [ , ... ] }
  [ PIVOT clause ]
  [ LATERAL VIEW clause ] [ ... ]
  [ WHERE boolean_expression ]
  [ GROUP BY expression [ , ... ] ]
  [ HAVING boolean_expression ]


  • with_query

    One or more common table expressions before the main query block.These table expressions can be referenced later in the FROM clause. This is useful to abstract out repeated subquery blocks in the FROM clause and improves readability of the query.

  • hints

    Hints help the Spark optimizer make better planning decisions. Spark supports hints that influence selection of join strategies and repartitioning of the data.

  • ALL

    Select all matching rows from the relation. Enabled by default.


    Select all matching rows from the relation after removing duplicates in results.

  • named_expression

    An expression with an assigned name. Denotes a column expression.

    Syntax: expression [AS] [alias]

  • from_item

    A source of input for the query. One of the following:


    Used for data perspective; you can get the aggregated values based on specific column value.


    Used in conjunction with generator functions such as EXPLODE, which generates a virtual table containing one or more rows. LATERAL VIEW applies the rows to each original output row.


    Filters the result of the FROM clause based on the supplied predicates.


    The expressions that are used to group the rows. This is used in conjunction with aggregate functions (MIN, MAX, COUNT, SUM, AVG) to group rows based on the grouping expressions and aggregate values in each group. When a FILTER clause is attached to an aggregate function, only the matching rows are passed to that function.


    The predicates by which the rows produced by GROUP BY are filtered. The HAVING clause is used to filter rows after the grouping is performed. If you specify HAVING without GROUP BY, it indicates a GROUP BY without grouping expressions (global aggregate).


    An ordering of the rows of the complete result set of the query. The output rows are ordered across the partitions. This parameter is mutually exclusive with SORT BY, CLUSTER BY, and DISTRIBUTE BY and cannot be specified together.


    An ordering by which the rows are ordered within each partition. This parameter is mutually exclusive with ORDER BY and CLUSTER BY and cannot be specified together.


    A set of expressions that is used to repartition and sort the rows. Using this clause has the same effect of using DISTRIBUTE BY and SORT BY together.


    A set of expressions by which the result rows are repartitioned. This parameter is mutually exclusive with ORDER BY and CLUSTER BY and cannot be specified together.


    The maximum number of rows that can be returned by a statement or subquery. This clause is mostly used in the conjunction with ORDER BY to produce a deterministic result.

  • boolean_expression

    Any expression that evaluates to a result type Boolean. You can combine two or more expressions together using the logical operators ( AND, OR ).

  • expression

    A combination of one or more values, operators, and SQL functions that evaluates to a value.

  • named_window

    Aliases for one or more source window specifications. The source window specifications can be referenced in the window definitions in the query.

Select on Delta table

In addition to the standard SELECT options, Delta tables support the time travel options described in this section. For details, see Query an older snapshot of a table (time travel).

AS OF syntax

SELECT * FROM table_identifier TIMESTAMP AS OF timestamp_expression
SELECT * FROM table_identifier VERSION AS OF version


  • timestamp_expression can be any one of:
    • '2018-10-18T22:15:12.013Z', that is, a string that can be cast to a timestamp
    • cast('2018-10-18 13:36:32 CEST' as timestamp)
    • '2018-10-18', that is, a date string
    • In Databricks Runtime 6.6 and above:
      • current_timestamp() - interval 12 hours
      • date_sub(current_date(), 1)
      • Any other expression that is or can be cast to a timestamp
  • version is a long value that can be obtained from the output of DESCRIBE HISTORY table_spec.

Neither timestamp_expression nor version can be subqueries.


SELECT * FROM events TIMESTAMP AS OF '2018-10-18T22:15:12.013Z'
SELECT * FROM delta.`/mnt/delta/events` VERSION AS OF 123

@ syntax

Use the @ syntax to specify the timestamp or version. The timestamp must be in yyyyMMddHHmmssSSS format. You can specify a version after @ by prepending a v to the version. For example, to query version 123 for the table events, specify events@v123.


SELECT * FROM events@20190101000000000
SELECT * FROM events@v123