Odoo
Last updated
Last updated
A SELECT statement can consist of the following basic clauses.
SELECT
INTO
FROM
JOIN
WHERE
GROUP BY
HAVING
UNION
ORDER BY
LIMIT
The following syntax diagram outlines the syntax supported by the SQL engine of the provider:
Return all columns:
Rename a column:
Cast a column's data as a different data type:
Search data:
Return the number of items matching the query criteria:
Return the number of unique items matching the query criteria:
Return the unique items matching the query criteria:
Summarize data:
See Aggregate Functions below for details.
Retrieve data from multiple tables.
See JOIN Queries below for details.
Sort a result set in ascending order:
Restrict a result set to the specified number of rows:
Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
Returns the number of rows matching the query criteria.
COUNT(DISTINCT)
Returns the number of distinct, non-null field values matching the query criteria.
Returns the average of the column values.
Returns the minimum column value.
Returns the maximum column value.
Returns the total sum of the column values.
The Provider for Odoo supports standard SQL joins like the following examples.
An inner join selects only rows from both tables that match the join condition:
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
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.
The current day.
The previous day.
The following day.
Every day in the preceding week.
Every day in the current week.
Every day in the following week.
Also available:
L_LAST/L_THIS/L_NEXT MONTH
L_LAST/L_THIS/L_NEXT QUARTER
L_LAST/L_THIS/L_NEXT YEAR
The previous n days, excluding the current day.
The following n days, including the current day.
Also available:
L_LAST/L_NEXT_90_DAYS
Every day in every week, starting n weeks before current week, and ending in the previous week.
Every day in every week, starting the following week, and ending n weeks in the future.
Also available:
L_LAST/L_NEXT_N_MONTHS(n)
L_LAST/L_NEXT_N_QUARTERS(n)
L_LAST/L_NEXT_N_YEARS(n)
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 } ... ]
SELECT * FROM res_users
SELECT [email] AS MY_email FROM res_users
SELECT CAST(meeting_count AS VARCHAR) AS Str_meeting_count FROM res_users
SELECT * FROM res_users WHERE company_name = 'Company Inc.'
SELECT COUNT(*) AS MyCount FROM res_users
SELECT COUNT(DISTINCT email) FROM res_users
SELECT DISTINCT email FROM res_users
SELECT email, MAX(meeting_count) FROM res_users GROUP BY email
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
SELECT name, email FROM res_users ORDER BY email ASC
SELECT name, email FROM res_users LIMIT 10
SELECT * FROM res_users WHERE company_name = @param
SELECT COUNT(*) FROM res_users WHERE company_name = 'Company Inc.'
SELECT COUNT(DISTINCT name) AS DistinctValues FROM res_users WHERE company_name = 'Company Inc.'
SELECT email, AVG(meeting_count) FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email
SELECT MIN(meeting_count), email FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email
SELECT email, MAX(meeting_count) FROM res_users WHERE company_name = 'Company Inc.' GROUP BY email
SELECT SUM(meeting_count) FROM res_users WHERE company_name = 'Company Inc.'
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
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
SELECT * FROM MyTable WHERE MyDateField = L_TODAY()
SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()
SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()
SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()
SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()
SELECT * FROM MyTable WHERE MyDateField = L_NEXT_WEEK()
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)
SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_DAYS(3)
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_WEEKS(3)
SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_WEEKS(3)