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 ServiceNow 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 incident
SELECT [priority] AS MY_priority FROM incident
SELECT CAST(priority AS VARCHAR) AS Str_priority FROM incident
SELECT * FROM incident WHERE category = 'request'
SELECT COUNT(*) AS MyCount FROM incident
SELECT COUNT(DISTINCT priority) FROM incident
SELECT DISTINCT priority FROM incident
SELECT priority, MAX(priority) FROM incident GROUP BY priority
SELECT incident.close_notes, system_user.name FROM incident INNER JOIN system_user ON incident.caller_id = system_user.system_id
SELECT sys_id, priority FROM incident ORDER BY priority ASC
SELECT sys_id, priority FROM incident LIMIT 10
SELECT * FROM incident WHERE category = @param
SELECT COUNT(*) FROM incident WHERE category = 'request'
SELECT COUNT(DISTINCT sys_id) AS DistinctValues FROM incident WHERE category = 'request'
SELECT priority, AVG(priority) FROM incident WHERE category = 'request'
GROUP BY priority
SELECT MIN(priority), priority FROM incident WHERE category = 'request'
GROUP BY priority
SELECT priority, MAX(priority) FROM incident WHERE category = 'request'
GROUP BY priority
SELECT SUM(priority) FROM incident WHERE category = 'request'
SELECT incident.close_notes, system_user.name FROM incident INNER JOIN system_user ON incident.caller_id = system_user.system_id
SELECT incident.close_notes, system_user.name FROM incident LEFT JOIN system_user ON incident.caller_id = system_user.system_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)
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 Jira 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 Zendesk 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 [Name] AS MY_Name FROM Projects
SELECT CAST(Size AS VARCHAR) AS Str_Size FROM Projects
SELECT * FROM Projects WHERE Id = '10000'
SELECT COUNT(*) AS MyCount FROM Projects
SELECT COUNT(DISTINCT Name) FROM Projects
SELECT DISTINCT Name FROM Projects
SELECT Name, MAX(Size) FROM Projects GROUP BY Name
SELECT Projects.LeadName, Issues.Summary FROM Projects, Issues WHERE Projects.Id=Issues.ProjectId
SELECT Key, Name FROM Projects ORDER BY Name ASC
SELECT Key, Name FROM Projects LIMIT 10
SELECT * FROM Projects WHERE Id = @param
SELECT COUNT(*) FROM Projects WHERE Id = '10000'
SELECT COUNT(DISTINCT Key) AS DistinctValues FROM Projects WHERE Id = '10000'
SELECT Name, AVG(Size) FROM Projects WHERE Id = '10000'
GROUP BY Name
SELECT MIN(Size), Name FROM Projects WHERE Id = '10000'
GROUP BY Name
SELECT Name, MAX(Size) FROM Projects WHERE Id = '10000'
GROUP BY Name
SELECT SUM(Size) FROM Projects WHERE Id = '10000'
SELECT Projects.LeadName, Issues.Summary FROM Projects, Issues WHERE Projects.Id=Issues.ProjectId
SELECT Projects.LeadName, Issues.Summary FROM Projects LEFT OUTER JOIN Issues ON Projects.Id=Issues.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)
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 Tickets
SELECT [Subject] AS MY_Subject FROM Tickets
SELECT CAST(Size AS VARCHAR) AS Str_Size FROM Tickets
SELECT * FROM Tickets WHERE Industry = 'Floppy Disks'
SELECT COUNT(*) AS MyCount FROM Tickets
SELECT COUNT(DISTINCT Subject) FROM Tickets
SELECT DISTINCT Subject FROM Tickets
SELECT Subject, MAX(Size) FROM Tickets GROUP BY Subject
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
SELECT Id, Subject FROM Tickets ORDER BY Subject ASC
SELECT Id, Subject FROM Tickets LIMIT 10
SELECT * FROM Tickets WHERE Industry = @param
SELECT COUNT(*) FROM Tickets WHERE Industry = 'Floppy Disks'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Tickets WHERE Industry = 'Floppy Disks'
SELECT Subject, AVG(Size) FROM Tickets WHERE Industry = 'Floppy Disks'
GROUP BY Subject
SELECT MIN(Size), Subject FROM Tickets WHERE Industry = 'Floppy Disks'
GROUP BY Subject
SELECT Subject, MAX(Size) FROM Tickets WHERE Industry = 'Floppy Disks'
GROUP BY Subject
SELECT SUM(Size) FROM Tickets WHERE Industry = 'Floppy Disks'
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)