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 Tasks

2. Rename a column:
   

   SELECT [startDateTime] AS MY_startDateTime FROM Tasks

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

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Tasks

4. Search data:
   

   SELECT * FROM Tasks WHERE TaskId  = 'BCrvyMoiLEafem-3RxIESmUAHbLK'

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

   SELECT COUNT(*) AS MyCount FROM Tasks 

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

   SELECT COUNT(DISTINCT startDateTime) FROM Tasks 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT startDateTime FROM Tasks 

8. Summarize data:
   

   SELECT startDateTime, MAX(AnnualRevenue) FROM Tasks GROUP BY startDateTime

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

   SELECT Tasks.Title, Buckets.Name FROM Tasks INNER JOIN Buckets ON Tasks.BucketId = Buckets.BucketId

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

    SELECT TaskId, startDateTime FROM Tasks  ORDER BY startDateTime ASC

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

    SELECT TaskId, startDateTime FROM Tasks 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 Tasks WHERE TaskId  = @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 Microsoft Planner.

    SELECT * FROM Tasks WHERE Query = 'percentComplete > 60'