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 res_users

2. Rename a column:
   

   SELECT [email] AS MY_email FROM res_users

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

   SELECT CAST(meeting_count AS VARCHAR) AS Str_meeting_count FROM res_users

4. Search data:
   

   SELECT * FROM res_users WHERE company_name = 'Company Inc.'

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

   SELECT COUNT(*) AS MyCount FROM res_users 

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

   SELECT COUNT(DISTINCT email) FROM res_users 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT email FROM res_users 

8. Summarize data:
   

   SELECT email, MAX(meeting_count) FROM res_users GROUP BY email

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

   SELECT res_users.name AS login, res_partner.name AS contact, res_partner.company_name AS company FROM res_users INNER JOIN res_partner ON res_users.partner_id = res_partner.id

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

    SELECT name, email FROM res_users  ORDER BY email ASC

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

    SELECT name, email FROM res_users 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 res_users WHERE company_name = @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 Odoo.

    SELECT * FROM res_users WHERE Pseudo = '@Pseudo'