Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime

Repartitions the data based on the input expressions and then sorts the data within each partition. This is semantically equivalent to performing a DISTRIBUTE BY followed by a SORT BY. This clause only ensures that the resultant rows are sorted within each partition and does not guarantee a total order of output.


CLUSTER BY expression [, ...]


  • expression

    Specifies combination of one or more values, operators and SQL functions that results in a value.


> CREATE TEMP VIEW person (name, age)
    AS VALUES ('Zen Hui', 25),
              ('Anil B', 18),
              ('Shone S', 16),
              ('Mike A', 25),
              ('John A', 18),
              ('Jack N', 16);

-- Reduce the number of shuffle partitions to 2 to illustrate the behavior of `CLUSTER BY`.
-- It's easier to see the clustering and sorting behavior with less number of partitions.
> SET spark.sql.shuffle.partitions = 2;

-- Select the rows with no ordering. Please note that without any sort directive, the results
-- of the query is not deterministic. It's included here to show the difference in behavior
-- of a query when `CLUSTER BY` is not used vs when it's used. The query below produces rows
-- where age column is not sorted.
> SELECT age, name FROM person;
  16 Shone S
  25 Zen Hui
  16  Jack N
  25  Mike A
  18  John A
  18  Anil B

-- Produces rows clustered by age. Persons with same age are clustered together.
-- In the query below, persons with age 18 and 25 are in first partition and the
-- persons with age 16 are in the second partition. The rows are sorted based
-- on age within each partition.
> SELECT age, name FROM person CLUSTER BY age;
  18  John A
  18  Anil B
  25 Zen Hui
  25  Mike A
  16 Shone S
  16  Jack N