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:
Returns the number of rows matching the query criteria.
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 XML 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 CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM NorthwindOData
Search data:
SELECT * FROM NorthwindOData WHERE Email = '[email protected]'
Return the number of items matching the query criteria:
SELECT COUNT(*) AS MyCount FROM NorthwindOData
Return the number of unique items matching the query criteria:
SELECT COUNT(DISTINCT Username) FROM NorthwindOData
Return the unique items matching the query criteria:
SELECT DISTINCT Username FROM NorthwindOData
Summarize data:
SELECT Username, MAX(AnnualRevenue) FROM NorthwindOData GROUP BY Username
See Aggregate Functions below for details.
Retrieve data from multiple tables.
SELECT [people].[personal.age] AS age, [people].[personal.gender] AS gender, [people].[personal.name.first] AS first_name, [people].[personal.name.last] AS last_name, [vehicles].[model],FROM [people], [vehicles]WHERE [people].[_id] = [vehicles].[people_id]
See JOIN Queries below for details.
Sort a result set in ascending order:
SELECT Email, Username FROM NorthwindOData ORDER BY Username ASC
Restrict a result set to the specified number of rows:
SELECT Email, Username FROM NorthwindOData LIMIT 10
Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
SELECT * FROM NorthwindOData WHERE Email = @param
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
} [ { AND | OR } ... ]
SELECT * FROM NorthwindOData
SELECT [Username] AS MY_Username FROM NorthwindOData
SELECT COUNT(*) FROM NorthwindOData WHERE Email = '[email protected]'
SELECT COUNT(DISTINCT Email) AS DistinctValues FROM NorthwindOData WHERE Email = '[email protected]'
SELECT Username, AVG(AnnualRevenue) FROM NorthwindOData WHERE Email = '[email protected]' GROUP BY Username
SELECT MIN(AnnualRevenue), Username FROM NorthwindOData WHERE Email = '[email protected]' GROUP BY Username
SELECT Username, MAX(AnnualRevenue) FROM NorthwindOData WHERE Email = '[email protected]' GROUP BY Username
SELECT SUM(AnnualRevenue) FROM NorthwindOData WHERE Email = '[email protected]'
SELECT [people].[personal.age] AS age, [people].[personal.gender] AS gender, [people].[personal.name.first] AS first_name, [people].[personal.name.last] AS last_name, [vehicles].[model],FROM [people], [vehicles]WHERE [people].[_id] = [vehicles].[people_id]
SELECT [people].[personal.age] AS age, [people].[personal.gender] AS gender, [people].[personal.name.first] AS first_name, [people].[personal.name.last] AS last_name, [vehicles].[model],FROM [people]LEFT OUTER JOIN [vehicles]ON [people].[_id] = [vehicles].[people_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)
| BETWEEN} [ <expression> ]