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:
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 } ... ]
Return all columns:
SELECT * FROM Groups
Rename a column:
SELECT [ContentDetails_ItemType] AS MY_ContentDetails_ItemType FROM Groups
Cast a column's data as a different data type:
SELECT CAST(Additive_Tax AS VARCHAR) AS Str_Additive_Tax FROM Groups
Search data:
SELECT * FROM Groups WHERE Id = 'S'
The YouTube Analytics APIs support the following operators in the WHERE clause: =, AND.
SELECT * FROM Groups WHERE Id = 'S';
Return the number of items matching the query criteria:
SELECT COUNT(*) AS MyCount FROM Groups
Return the number of unique items matching the query criteria:
SELECT COUNT(DISTINCT ContentDetails_ItemType) FROM Groups
Return the unique items matching the query criteria:
SELECT DISTINCT ContentDetails_ItemType FROM Groups
Summarize data:
SELECT ContentDetails_ItemType, MAX(Additive_Tax) FROM Groups GROUP BY ContentDetails_ItemType
See Aggregate Functions below for details.
Retrieve data from multiple tables.
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
See JOIN Queries below for details.
Sort a result set in ascending order:
SELECT Snippet_Title, ContentDetails_ItemType FROM Groups ORDER BY ContentDetails_ItemType ASC
Restrict a result set to the specified number of rows:
SELECT Snippet_Title, ContentDetails_ItemType FROM Groups 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 Groups WHERE Id = @param
Below are several examples of SQL aggregate functions. You can use these with a GROUP BY clause to aggregate rows based on the specified GROUP BY criterion. This can be a reporting tool.
Returns the number of rows matching the query criteria.
SELECT COUNT(*) FROM Groups WHERE Id = 'S'
Returns the number of distinct, non-null field values matching the query criteria.
SELECT COUNT(DISTINCT Snippet_Title) AS DistinctValues FROM Groups WHERE Id = 'S'
Returns the number of rows matching the query criteria.
SELECT COUNT(*) FROM Groups WHERE Id = 'S'
Returns the number of distinct, non-null field values matching the query criteria.
SELECT COUNT(DISTINCT Snippet_Title) AS DistinctValues FROM Groups WHERE Id = 'S'
Returns the average of the column values.
SELECT ContentDetails_ItemType, AVG(Additive_Tax) FROM Groups WHERE Id = 'S' GROUP BY ContentDetails_ItemType
Returns the minimum column value.
SELECT MIN(Additive_Tax), ContentDetails_ItemType FROM Groups WHERE Id = 'S' GROUP BY ContentDetails_ItemType
Returns the maximum column value.
SELECT ContentDetails_ItemType, MAX(Additive_Tax) FROM Groups WHERE Id = 'S' GROUP BY ContentDetails_ItemType
Returns the total sum of the column values.
SELECT SUM(Additive_Tax) FROM Groups WHERE Id = 'S'
The Provider for YouTube Analytics supports standard SQL joins like the following examples.
An inner join selects only rows from both tables that match the join condition:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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.
SELECT * FROM MyTable WHERE MyDateField = L_TODAY()
The previous day.
SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()
The following day.
SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()
Every day in the preceding week.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()
Every day in the current week.
SELECT * FROM MyTable WHERE MyDateField = L_THIS_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
The previous n days, excluding the current day.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)
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
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)
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)
SAS Data Sets
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:
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 } ... ]
Return all columns:
SELECT * FROM Account
Rename a column:
SELECT [Name] AS MY_Name FROM Account
Cast a column's data as a different data type:
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Account
Search data:
SELECT * FROM Account WHERE Industry = 'Floppy Disks'
Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
SELECT * FROM Account WHERE Industry = @param
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:
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 } ... ]
Return all columns:
SELECT * FROM SampleTable_1
Rename a column:
SELECT [Column1] AS MY_Column1 FROM SampleTable_1
Cast a column's data as a different data type:
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM SampleTable_1
Search data:
SELECT * FROM SampleTable_1 WHERE Column2 = 'Bob'
Return the number of items matching the query criteria:
SELECT COUNT(*) AS MyCount FROM SampleTable_1
Return the number of unique items matching the query criteria:
SELECT COUNT(DISTINCT Column1) FROM SampleTable_1
Return the unique items matching the query criteria:
SELECT DISTINCT Column1 FROM SampleTable_1
Summarize data:
SELECT Column1, MAX(AnnualRevenue) FROM SampleTable_1 GROUP BY Column1
See Aggregate Functions below for details.
Retrieve data from multiple tables.
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2
See JOIN Queries below for details.
Sort a result set in ascending order:
SELECT Id, Column1 FROM SampleTable_1 ORDER BY Column1 ASC
Restrict a result set to the specified number of rows:
SELECT Id, Column1 FROM SampleTable_1 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 SampleTable_1 WHERE Column2 = @param
Returns the number of rows matching the query criteria.
SELECT COUNT(*) FROM SampleTable_1 WHERE Column2 = 'Bob'
Returns the number of distinct, non-null field values matching the query criteria.
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM SampleTable_1 WHERE Column2 = 'Bob'
Returns the average of the column values.
SELECT Column1, AVG(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
Returns the minimum column value.
SELECT MIN(AnnualRevenue), Column1 FROM SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
Returns the maximum column value.
SELECT Column1, MAX(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
Returns the total sum of the column values.
SELECT SUM(AnnualRevenue) FROM SampleTable_1 WHERE Column2 = 'Bob'
The Provider for Adobe Analytics supports standard SQL joins like the following examples.
An inner join selects only rows from both tables that match the join condition:
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c LEFT JOIN SampleTable_2 o ON c.Id = o.Id2
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.
SELECT * FROM MyTable WHERE MyDateField = L_TODAY()
The previous day.
SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()
The following day.
SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()
Every day in the preceding week.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()
Every day in the current week.
SELECT * FROM MyTable WHERE MyDateField = L_THIS_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
The previous n days, excluding the current day.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)
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
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)
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)
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:
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 } ... ]
Return all columns:
SELECT Country, Education FROM [adventureworks].[Model].Customer
Rename a column:
SELECT [Education] AS MY_Education FROM [adventureworks].[Model].Customer
Cast a column's data as a different data type:
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM [adventureworks].[Model].Customer
Search data:
SELECT Country, Education FROM [adventureworks].[Model].Customer WHERE Country = 'Australia'
Return the number of items matching the query criteria:
SELECT COUNT(*) AS MyCount FROM [adventureworks].[Model].Customer
Return the number of unique items matching the query criteria:
SELECT COUNT(DISTINCT Education) FROM [adventureworks].[Model].Customer
Return the unique items matching the query criteria:
SELECT DISTINCT Education FROM [adventureworks].[Model].Customer
Summarize data:
SELECT Education, MAX(AnnualRevenue) FROM [adventureworks].[Model].Customer GROUP BY Education
See Aggregate Functions below for details.
Retrieve data from multiple tables.
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
See JOIN Queries below for details.
Sort a result set in ascending order:
SELECT Country, Education FROM [adventureworks].[Model].Customer ORDER BY Education ASC
Restrict a result set to the specified number of rows:
SELECT Country, Education FROM [adventureworks].[Model].Customer 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 Country, Education FROM [adventureworks].[Model].Customer WHERE Country = @param
Returns the number of rows matching the query criteria.
SELECT COUNT(*) FROM [adventureworks].[Model].Customer WHERE Country = 'Australia'
Returns the number of distinct, non-null field values matching the query criteria.
SELECT COUNT(DISTINCT Country) AS DistinctValues FROM [adventureworks].[Model].Customer WHERE Country = 'Australia'
Returns the average of the column values.
SELECT Education, AVG(AnnualRevenue) FROM [adventureworks].[Model].Customer WHERE Country = 'Australia' GROUP BY Education
Returns the minimum column value.
SELECT MIN(AnnualRevenue), Education FROM [adventureworks].[Model].Customer WHERE Country = 'Australia' GROUP BY Education
Returns the maximum column value.
SELECT Education, MAX(AnnualRevenue) FROM [adventureworks].[Model].Customer WHERE Country = 'Australia' GROUP BY Education
Returns the total sum of the column values.
SELECT SUM(AnnualRevenue) FROM [adventureworks].[Model].Customer WHERE Country = 'Australia'
The Provider for Azure Analysis Services supports standard SQL joins like the following examples.
An inner join selects only rows from both tables that match the join condition:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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.
SELECT * FROM MyTable WHERE MyDateField = L_TODAY()
The previous day.
SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()
The following day.
SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()
Every day in the preceding week.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()
Every day in the current week.
SELECT * FROM MyTable WHERE MyDateField = L_THIS_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
The previous n days, excluding the current day.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)
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
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)
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)
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:
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 } ... ]
Return all columns:
SELECT * FROM Traffic
Rename a column:
SELECT [DeviceCategory] AS MY_DeviceCategory FROM Traffic
Cast a column's data as a different data type:
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Traffic
Search data:
SELECT * FROM Traffic WHERE Transactions > '0'
Return the number of items matching the query criteria:
SELECT COUNT(*) AS MyCount FROM Traffic
Return the number of unique items matching the query criteria:
SELECT COUNT(DISTINCT DeviceCategory) FROM Traffic
Return the unique items matching the query criteria:
SELECT DISTINCT DeviceCategory FROM Traffic
Summarize data:
SELECT DeviceCategory, MAX(AnnualRevenue) FROM Traffic GROUP BY DeviceCategory
See Aggregate Functions below for details.
Retrieve data from multiple tables.
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
See JOIN Queries below for details.
Sort a result set in ascending order:
SELECT Browser, DeviceCategory FROM Traffic ORDER BY DeviceCategory ASC
Restrict a result set to the specified number of rows:
SELECT Browser, DeviceCategory FROM Traffic 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 Traffic WHERE Transactions = @param
Returns the number of rows matching the query criteria.
SELECT COUNT(*) FROM Traffic WHERE Transactions = '0'
Returns the number of distinct, non-null field values matching the query criteria.
SELECT COUNT(DISTINCT Browser) AS DistinctValues FROM Traffic WHERE Transactions > '0'
Returns the average of the column values.
SELECT DeviceCategory, AVG(AnnualRevenue) FROM Traffic WHERE Transactions > '0' GROUP BY DeviceCategory
Returns the minimum column value.
SELECT MIN(AnnualRevenue), DeviceCategory FROM Traffic WHERE Transactions > '0' GROUP BY DeviceCategory
Returns the maximum column value.
SELECT DeviceCategory, MAX(AnnualRevenue) FROM Traffic WHERE Transactions > '0' GROUP BY DeviceCategory
Returns the total sum of the column values.
SELECT SUM(AnnualRevenue) FROM Traffic WHERE Transactions = '0'
The Provider for Google Analytics supports standard SQL joins like the following examples.
An inner join selects only rows from both tables that match the join condition:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers, Orders WHERE Customers.CustomerId=Orders.CustomerId
A left join selects all rows in the FROM table and only matching rows in the JOIN table:
SELECT Customers.ContactName, Orders.OrderDate FROM Customers LEFT OUTER JOIN Orders ON Customers.CustomerId=Orders.CustomerId
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.
SELECT * FROM MyTable WHERE MyDateField = L_TODAY()
The previous day.
SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()
The following day.
SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()
Every day in the preceding week.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()
Every day in the current week.
SELECT * FROM MyTable WHERE MyDateField = L_THIS_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
The previous n days, excluding the current day.
SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)
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
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)
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)