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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.
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 Asana 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 projects
SELECT [WorkspaceId] AS MY_WorkspaceId FROM projects
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM projects
SELECT * FROM projects WHERE Archived = 'true'
SELECT COUNT(*) AS MyCount FROM projects
SELECT COUNT(DISTINCT WorkspaceId) FROM projects
SELECT DISTINCT WorkspaceId FROM projects
SELECT WorkspaceId, MAX(AnnualRevenue) FROM projects GROUP BY WorkspaceId
SELECT P.Id,P.Name,P.color,PS.Id,PS.Title FROM Projects P INNER JOIN ProjectStatuses PS ON P.Id=PS.ProjectId
SELECT Id, WorkspaceId FROM projects ORDER BY WorkspaceId ASC
SELECT Id, WorkspaceId FROM projects LIMIT 10
SELECT * FROM projects WHERE Archived = @param
SELECT COUNT(*) FROM projects WHERE Archived = 'true'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM projects WHERE Archived = 'true'
SELECT WorkspaceId, AVG(AnnualRevenue) FROM projects WHERE Archived = 'true'
GROUP BY WorkspaceId
SELECT MIN(AnnualRevenue), WorkspaceId FROM projects WHERE Archived = 'true'
GROUP BY WorkspaceId
SELECT WorkspaceId, MAX(AnnualRevenue) FROM projects WHERE Archived = 'true'
GROUP BY WorkspaceId
SELECT SUM(AnnualRevenue) FROM projects WHERE Archived = 'true'
SELECT P.Id,P.Name,P.color,PS.Id,PS.Title FROM Projects P INNER JOIN ProjectStatuses PS ON P.Id=PS.ProjectId
SELECT P.Id,P.Name,P.color,PS.Id,PS.Title FROM Projects P LEFT JOIN ProjectStatuses PS ON P.Id=PS.ProjectId
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)
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.
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 Dropbox 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)
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.
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 Box 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)
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.
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 Google Drive 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)
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.
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 Microsoft OneNote 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)
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.
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 Microsoft Office 365 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 Files
SELECT [Name] AS MY_Name FROM Files
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Files
SELECT * FROM Files WHERE ParentPath = '/Test Folder'
SELECT COUNT(*) AS MyCount FROM Files
SELECT COUNT(DISTINCT Name) FROM Files
SELECT DISTINCT Name FROM Files
SELECT Name, MAX(AnnualRevenue) FROM Files GROUP BY Name
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Id, Name FROM Files ORDER BY Name ASC
SELECT Id, Name FROM Files LIMIT 10
SELECT * FROM Files WHERE ParentPath = @param
SELECT COUNT(*) FROM Files WHERE ParentPath = '/Test Folder'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Files WHERE ParentPath = '/Test Folder'
SELECT Name, AVG(AnnualRevenue) FROM Files WHERE ParentPath = '/Test Folder'
GROUP BY Name
SELECT MIN(AnnualRevenue), Name FROM Files WHERE ParentPath = '/Test Folder'
GROUP BY Name
SELECT Name, MAX(AnnualRevenue) FROM Files WHERE ParentPath = '/Test Folder'
GROUP BY Name
SELECT SUM(AnnualRevenue) FROM Files WHERE ParentPath = '/Test Folder'
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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)
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 Files
SELECT [Name] AS MY_Name FROM Files
SELECT CAST(Size AS VARCHAR) AS Str_Size FROM Files
SELECT * FROM Files WHERE Id = '123'
SELECT COUNT(*) AS MyCount FROM Files
SELECT COUNT(DISTINCT Name) FROM Files
SELECT DISTINCT Name FROM Files
SELECT Name, MAX(Size) FROM Files GROUP BY Name
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Id, Name FROM Files ORDER BY Name ASC
SELECT Id, Name FROM Files LIMIT 10
SELECT * FROM Files WHERE Id = @param
SELECT COUNT(*) FROM Files WHERE Id = '123'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Files WHERE Id = '123'
SELECT Name, AVG(Size) FROM Files WHERE Id = '123'
GROUP BY Name
SELECT MIN(Size), Name FROM Files WHERE Id = '123'
GROUP BY Name
SELECT Name, MAX(Size) FROM Files WHERE Id = '123'
GROUP BY Name
SELECT SUM(Size) FROM Files WHERE Id = '123'
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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)
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 Files
SELECT [Name] AS MY_Name FROM Files
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Files
SELECT * FROM Files WHERE Extension = 'png'
SELECT COUNT(*) AS MyCount FROM Files
SELECT COUNT(DISTINCT Name) FROM Files
SELECT DISTINCT Name FROM Files
SELECT Name, MAX(AnnualRevenue) FROM Files GROUP BY Name
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Id, Name FROM Files ORDER BY Name ASC
SELECT Id, Name FROM Files LIMIT 10
SELECT * FROM Files WHERE Extension = @param
SELECT COUNT(*) FROM Files WHERE Extension = 'png'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Files WHERE Extension = 'png'
SELECT Name, AVG(AnnualRevenue) FROM Files WHERE Extension = 'png'
GROUP BY Name
SELECT MIN(AnnualRevenue), Name FROM Files WHERE Extension = 'png'
GROUP BY Name
SELECT Name, MAX(AnnualRevenue) FROM Files WHERE Extension = 'png'
GROUP BY Name
SELECT SUM(AnnualRevenue) FROM Files WHERE Extension = 'png'
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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)
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 } ... ] |
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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 } ... ] |
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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.
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 Microsoft SharePoint 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)
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.
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 Smartsheet 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)
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.
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 Slack 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)
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.
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 Microsoft Exchange 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)
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.
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 Airtable 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)
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.
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 Salesforce Chatter 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 Provider for Salesforce Chatter 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:
LAST/THIS/NEXT MONTH
LAST/THIS/NEXT QUARTER
LAST/THIS/NEXT YEAR
The previous n days, excluding the current day.
The following n days, including the current day.
Also available:
LAST/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:
LAST/NEXT_N_MONTHS(n)
LAST/NEXT_N_QUARTERS(n)
LAST/NEXT_N_YEARS(n)
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.
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 Microsoft OneDrive 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)
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.
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 Microsoft Teams 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 Calendar
SELECT [Location] AS MY_Location FROM Calendar
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Calendar
SELECT * FROM Calendar WHERE Location <> 'Chapel Hill'
SELECT COUNT(*) AS MyCount FROM Calendar
SELECT COUNT(DISTINCT Location) FROM Calendar
SELECT DISTINCT Location FROM Calendar
SELECT Location, MAX(AnnualRevenue) FROM Calendar GROUP BY Location
SELECT d.LinkFileName, u.Name FROM Documents d, Users u WHERE d.CheckOutUser = u.Name
SELECT Id, Location FROM Calendar ORDER BY Location ASC
SELECT Id, Location FROM Calendar LIMIT 10
SELECT * FROM Calendar WHERE Location = @param
SELECT COUNT(*) FROM Calendar WHERE Location = 'Chapel Hill'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Calendar WHERE Location <> 'Chapel Hill'
SELECT Location, AVG(AnnualRevenue) FROM Calendar WHERE Location <> 'Chapel Hill'
GROUP BY Location
SELECT MIN(AnnualRevenue), Location FROM Calendar WHERE Location <> 'Chapel Hill'
GROUP BY Location
SELECT Location, MAX(AnnualRevenue) FROM Calendar WHERE Location <> 'Chapel Hill'
GROUP BY Location
SELECT SUM(AnnualRevenue) FROM Calendar WHERE Location = 'Chapel Hill'
SELECT d.LinkFileName, u.Name FROM Documents d, Users u WHERE d.CheckOutUser = u.Name
SELECT d.LinkFileName, u.Name FROM Users u LEFT JOIN Documents d ON d.CheckOutUser = u.Name
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)
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 Sheet_Test_Sheet
SELECT [Name] AS MY_Name FROM Sheet_Test_Sheet
SELECT CAST(TotalRowCount AS VARCHAR) AS Str_TotalRowCount FROM Sheet_Test_Sheet
SELECT * FROM Sheet_Test_Sheet WHERE Favorite = 'True'
SELECT COUNT(*) AS MyCount FROM Sheet_Test_Sheet
SELECT COUNT(DISTINCT Name) FROM Sheet_Test_Sheet
SELECT DISTINCT Name FROM Sheet_Test_Sheet
SELECT Name, MAX(TotalRowCount) FROM Sheet_Test_Sheet GROUP BY Name
SELECT Sheet_Customers.ContactName, Sheet_Orders.OrderDate FROM Sheet_Customers, Sheet_Orders WHERE Sheet_Customers.CustomerId=Sheet_Orders.CustomerId
SELECT Id, Name FROM Sheet_Test_Sheet ORDER BY Name ASC
SELECT Id, Name FROM Sheet_Test_Sheet LIMIT 10
SELECT * FROM Sheet_Test_Sheet WHERE Favorite = @param
SELECT COUNT(*) FROM Sheet_Test_Sheet WHERE Favorite = 'True'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Sheet_Test_Sheet WHERE Favorite = 'True'
SELECT Name, AVG(TotalRowCount) FROM Sheet_Test_Sheet WHERE Favorite = 'True'
GROUP BY Name
SELECT MIN(TotalRowCount), Name FROM Sheet_Test_Sheet WHERE Favorite = 'True'
GROUP BY Name
SELECT Name, MAX(TotalRowCount) FROM Sheet_Test_Sheet WHERE Favorite = 'True'
GROUP BY Name
SELECT SUM(TotalRowCount) FROM Sheet_Test_Sheet WHERE Favorite = 'True'
SELECT Sheet_Customers.ContactName, Sheet_Orders.OrderDate FROM Sheet_Customers, Sheet_Orders WHERE Sheet_Customers.CustomerId=Sheet_Orders.CustomerId
SELECT Sheet_Customers.ContactName, Sheet_Orders.OrderDate FROM Sheet_Customers LEFT OUTER JOIN Sheet_Orders ON Sheet_Customers.CustomerId=Orders.CustomerId
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)
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 } ... ] |
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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 } ... ] |
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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 } ... ] |
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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 } ... ] |
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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> ] ] }
<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 } ... ] |
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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 } ... ] |
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