SELECT

Description

Spark supports a SELECT statement and conforms to the ANSI SQL standard. Queries are used to retrieve result sets from one or more tables. The following section describes the overall query syntax and the sub-sections cover different constructs of a query along with examples.

Syntax

[ 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 | regex_column_names ] [ , ... ] }
    FROM { from_item [ , ... ] }
    [ PIVOT clause ]
    [ LATERAL VIEW clause ] [ ... ] 
    [ WHERE boolean_expression ]
    [ GROUP BY expression [ , ... ] ]
    [ HAVING boolean_expression ]

Parameters

• with_query

  Specifies the common table expressions (CTEs) before the main query block. These table expressions are allowed to 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 can be specified to help spark optimizer make better planning decisions. Currently spark supports hints that influence selection of join strategies and repartitioning of the data.

• ALL

  Select all matching rows from the relation and is enabled by default.

• DISTINCT

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

• named_expression

  An expression with an assigned name. In general, it denotes a column expression.

  Syntax: expression [AS] [alias]

• from_item

  Specifies a source of input for the query. It can be one of the following:

  • Table relation
  • Join relation
  • Table-value function
  • Inline table
  • Subquery
  • File

• PIVOT

  The PIVOT clause is used for data perspective; We can get the aggregated values based on specific column value.

• LATERAL VIEW

  The LATERAL VIEW clause is used in conjunction with generator functions such as EXPLODE, which will generate a virtual table containing one or more rows. LATERAL VIEW will apply the rows to each original output row.

• WHERE

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

• GROUP BY

  Specifies the expressions that are used to group the rows. This is used in conjunction with aggregate functions (MIN, MAX, COUNT, SUM, AVG, etc.) 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.

• HAVING

  Specifies 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 HAVING is specified without GROUP BY, it indicates a GROUP BY without grouping expressions (global aggregate).

• ORDER BY

  Specifies 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 can not be specified together.

• SORT BY

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

• CLUSTER BY

  Specifies 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.

• DISTRIBUTE BY

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

• LIMIT

  Specifies 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

  Specifies any expression that evaluates to a result type boolean. Two or more expressions may be combined together using the logical operators ( AND, OR ).

• expression

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

• named_window

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

• regex_column_names

  When spark.sql.parser.quotedRegexColumnNames is true, quoted identifiers (using backticks) in SELECT statement are interpreted as regular expressions and SELECT statement can take regex-based column specification. For example, below SQL will only take column c:

     SELECT `(a|b)?+.+` FROM (
       SELECT 1 as a, 2 as b, 3 as c
     )
  

Related Statements

• WHERE Clause
• GROUP BY Clause
• HAVING Clause
• ORDER BY Clause
• SORT BY Clause
• CLUSTER BY Clause
• DISTRIBUTE BY Clause
• LIMIT Clause
• Common Table Expression
• Hints
• Inline Table
• File
• JOIN
• LIKE Predicate
• Set Operators
• TABLESAMPLE
• Table-valued Function
• Window Function
• CASE Clause
• PIVOT Clause
• LATERAL VIEW Clause