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 Builds

2. Rename a column:
   

   SELECT [BuildNumber] AS MY_BuildNumber FROM Builds

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

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Builds

4. Search data:
   

   SELECT * FROM Builds WHERE Reason = 'Manual'

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

   SELECT COUNT(*) AS MyCount FROM Builds 

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

   SELECT COUNT(DISTINCT BuildNumber) FROM Builds 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT BuildNumber FROM Builds 

8. Summarize data:
   

   SELECT BuildNumber, MAX(AnnualRevenue) FROM Builds GROUP BY BuildNumber

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

   SELECT Builds.BuildNumber FROM Builds INNER JOIN BuildDefinitions ON BuildDefinitions.Id = Builds.DefinitionId

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

    SELECT Id, BuildNumber FROM Builds  ORDER BY BuildNumber ASC

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

    SELECT Id, BuildNumber FROM Builds 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 Builds WHERE Reason = @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 Azure DevOps.

    SELECT * FROM Builds WHERE Pseudo = '@Pseudo'