A SELECT statement can consist of the following basic clauses.

• SELECT
• INTO
• FROM
• JOIN
• WHERE
• GROUP BY
• HAVING
• UNION
• ORDER BY
• LIMIT

SELECT Syntax

The following syntax diagram outlines the syntax supported by the SQL engine of the driver:

SELECT {
  [ TOP <numeric_literal> | DISTINCT ]
  { 
    * 
    | { 
        <expression> [ [ AS ] <column_reference> ] 
        | { <table_name> | <correlation_name> } .* 
      } [ , ... ] 
  }
  [ INTO csv:// [ filename= ] <file_path> [ ;delimiter=tab ] ]
  { 
    FROM <table_reference> [ [ AS ] <identifier> ] 
  } [ , ... ]
  [ [  
      INNER | { { LEFT | RIGHT | FULL } [ OUTER ] } 
    ] JOIN <table_reference> [ ON <search_condition> ] [ [ AS ] <identifier> ] 
  ] [ ... ] 
  [ WHERE <search_condition> ]
  [ GROUP BY <column_reference> [ , ... ]
  [ HAVING <search_condition> ]
  [ UNION [ ALL ] <select_statement> ]
  [ 
    ORDER BY 
    <column_reference> [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]
  ]
  [ 
    LIMIT <expression>
    [ 
      { OFFSET | , }
      <expression> 
    ]
  ] 
} | SCOPE_IDENTITY() 

<expression> ::=
  | <column_reference>
  | @ <parameter> 
  | ?
  | COUNT( * | { [ DISTINCT ] <expression> } )
  | { AVG | MAX | MIN | SUM | COUNT } ( <expression> ) 
  | NULLIF ( <expression> , <expression> ) 
  | COALESCE ( <expression> , ... ) 
  | CASE <expression>
      WHEN { <expression> | <search_condition> } THEN { <expression> | NULL } [ ... ]
    [ ELSE { <expression> | NULL } ]
    END 
  | <literal>
  | <sql_function> 

<search_condition> ::= 
  {
    <expression> { = | > | < | >= | <= | <> | != | LIKE | NOT LIKE | IN | NOT IN | IS NULL | IS NOT NULL | AND | OR | CONTAINS | BETWEEN } [ <expression> ]
  } [ { AND | OR } ... ] 

Examples

1. Return all columns:
   

   SELECT * FROM SampleTable_1

2. Rename a column:
   

   SELECT [Column1] AS MY_Column1 FROM SampleTable_1

3. Cast a column's data as a different data type:
   

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM SampleTable_1

4. Search data:
   

   SELECT * FROM SampleTable_1 WHERE Column2 = 'Bob'

5. Return the number of items matching the query criteria:
   

   SELECT COUNT(*) AS MyCount FROM SampleTable_1 

6. Return the number of unique items matching the query criteria:
   

   SELECT COUNT(DISTINCT Column1) FROM SampleTable_1 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT Column1 FROM SampleTable_1 

8. Summarize data:
   

   SELECT Column1, MAX(AnnualRevenue) FROM SampleTable_1 GROUP BY Column1

   See Aggregate Functions for details.
9. Retrieve data from multiple tables.
   

   SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2

   See JOIN Queries for details.
10. Sort a result set in ascending order:
    

    SELECT Id, Column1 FROM SampleTable_1  ORDER BY Column1 ASC

11. Restrict a result set to the specified number of rows:
    

    SELECT Id, Column1 FROM SampleTable_1 LIMIT 10 

12. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    

    SELECT * FROM SampleTable_1 WHERE Column2 = @param

See Explicitly Caching Data for information on using the SELECT statement in offline mode.

Pseudo Columns

Some input-only fields are available in SELECT statements. These fields, called pseudo columns, do not appear as regular columns in the results, yet may be specified as part of the WHERE clause. You can use pseudo columns to access additional features from Parquet.

    SELECT * FROM SampleTable_1 WHERE Pseudo = '@Pseudo'