Odoo

SELECT Statements

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 provider:

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 below 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 below 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

Aggregate Functions

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM res_users WHERE company_name = 'Company Inc.'

COUNT(DISTINCT)

Returns the number of distinct, non-null field values matching the query criteria.

SELECT COUNT(DISTINCT name) AS DistinctValues FROM res_users WHERE company_name = 'Company Inc.'

AVG

Returns the average of the column values.

SELECT email, AVG(meeting_count) FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email

MIN

Returns the minimum column value.

SELECT MIN(meeting_count), email FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email

MAX

Returns the maximum column value.

SELECT email, MAX(meeting_count) FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email

SUM

Returns the total sum of the column values.

SELECT SUM(meeting_count) FROM res_users WHERE company_name = 'Company Inc.'

JOIN Queries

The Provider for Odoo supports standard SQL joins like the following examples.

Inner Join

An inner join selects only rows from both tables that match the join condition:

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

Left Join

A left join selects all rows in the FROM table and only matching rows in the JOIN table:

SELECT res_partner.name AS contact, res_users.login AS username FROM res_partner LEFT JOIN res_users ON res_partner.id = res_users.partner_id

Date Literal Functions

The following date literal functions can be used to filter date fields using relative intervals. Note that while the <, >, and = operators are supported for these functions, <= and >= are not.

L_TODAY()

The current day.

SELECT * FROM MyTable WHERE MyDateField = L_TODAY()

L_YESTERDAY()

The previous day.

SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()

L_TOMORROW()

The following day.

SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()

L_LAST_WEEK()

Every day in the preceding week.

SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()

L_THIS_WEEK()

Every day in the current week.

SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()

L_NEXT_WEEK()

Every day in the following week.

SELECT * FROM MyTable WHERE MyDateField = L_NEXT_WEEK()

Also available:

• L_LAST/L_THIS/L_NEXT MONTH

• L_LAST/L_THIS/L_NEXT QUARTER

• L_LAST/L_THIS/L_NEXT YEAR

L_LAST_N_DAYS(n)

The previous n days, excluding the current day.

SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)

L_NEXT_N_DAYS(n)

The following n days, including the current day.

SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_DAYS(3)

Also available:

• L_LAST/L_NEXT_90_DAYS

L_LAST_N_WEEKS(n)

Every day in every week, starting n weeks before current week, and ending in the previous week.

SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_WEEKS(3)

L_NEXT_N_WEEKS(n)

Every day in every week, starting the following week, and ending n weeks in the future.

SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_WEEKS(3)

Also available:

• L_LAST/L_NEXT_N_MONTHS(n)

• L_LAST/L_NEXT_N_QUARTERS(n)

• L_LAST/L_NEXT_N_YEARS(n)