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 connector:

SELECT {
  [ TOP <numeric_literal> | DISTINCT ]
  { 
    * 
    | { 
        <expression> [ [ AS ] <column_reference> ] 
        | { <table_name> | <correlation_name> } .* 
      } [ , ... ] 
  }
  { 
    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> 
    ]
  ] 
}

<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 
  | {RANK() | DENSE_RANK()} OVER ([PARTITION BY <column_reference>] {ORDER BY <column_reference>})
  | <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 [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer

2. Rename a column:
   

   SELECT [Education] AS MY_Education FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer

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

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer

4. Search data:
   

   SELECT * FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer WHERE Country = 'Australia'

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

   SELECT COUNT(*) AS MyCount FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer 

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

   SELECT COUNT(DISTINCT Education) FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT Education FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer 

8. Sort a result set in ascending order:
   

   SELECT Country, Education FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer  ORDER BY Education ASC

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

   SELECT Country, Education FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer LIMIT 10 

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

    SELECT * FROM [AdventureWorksDW2012Multidimensional-SE].[Adventure Works].Customer WHERE Country = @param

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

Aggregate Functions

For SELECT examples using aggregate functions, see Aggregate Functions.

JOIN Queries

See JOIN Queries for SELECT query examples using JOINs.

Date Literal Functions

Date Literal Functions contains SELECT examples with date literal functions.

Window Functions

See Window Functions for SELECT examples containing window functions.

Table-Valued Functions

See Table-Valued Functions for SELECT examples with table-valued functions.