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)