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 projects

2. Rename a column:
   

   SELECT [WorkspaceId] AS MY_WorkspaceId FROM projects

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

   SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM projects

4. Search data:
   

   SELECT * FROM projects WHERE Archived = 'true'

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

   SELECT COUNT(*) AS MyCount FROM projects 

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

   SELECT COUNT(DISTINCT WorkspaceId) FROM projects 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT WorkspaceId FROM projects 

8. Summarize data:
   

   SELECT WorkspaceId, MAX(AnnualRevenue) FROM projects GROUP BY WorkspaceId

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

   SELECT P.Id,P.Name,P.color,PS.Id,PS.Title FROM Projects P INNER JOIN ProjectStatuses PS ON P.Id=PS.ProjectId

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

    SELECT Id, WorkspaceId FROM projects  ORDER BY WorkspaceId ASC

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

    SELECT Id, WorkspaceId FROM projects 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 projects WHERE Archived = @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 Asana.

    SELECT * FROM projects WHERE Query = 'Column3 > 100'