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 LinkedIn 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 CompanyStatusUpdates
SELECT [Comment] AS MY_Comment FROM CompanyStatusUpdates
SELECT CAST(Size AS VARCHAR) AS Str_Size FROM CompanyStatusUpdates
SELECT * FROM CompanyStatusUpdates WHERE EntityId = '238'
SELECT COUNT(*) AS MyCount FROM CompanyStatusUpdates
SELECT COUNT(DISTINCT Comment) FROM CompanyStatusUpdates
SELECT DISTINCT Comment FROM CompanyStatusUpdates
SELECT Comment, MAX(Size) FROM CompanyStatusUpdates GROUP BY Comment
SELECT CompanyList.Name, Comments.ContractNumber FROM CompanyList, Comments WHERE CompanyList.Id=Comments.CompanyId
SELECT VisibilityCode, Comment FROM CompanyStatusUpdates ORDER BY Comment ASC
SELECT VisibilityCode, Comment FROM CompanyStatusUpdates LIMIT 10
SELECT * FROM CompanyStatusUpdates WHERE EntityId = @param
SELECT COUNT(*) FROM CompanyStatusUpdates WHERE EntityId = '238'
SELECT COUNT(DISTINCT VisibilityCode) AS DistinctValues FROM CompanyStatusUpdates WHERE EntityId = '238'
SELECT Comment, AVG(Size) FROM CompanyStatusUpdates WHERE EntityId = '238' GROUP BY Comment
SELECT MIN(Size), Comment FROM CompanyStatusUpdates WHERE EntityId = '238' GROUP BY Comment
SELECT Comment, MAX(Size) FROM CompanyStatusUpdates WHERE EntityId = '238' GROUP BY Comment
SELECT SUM(Size) FROM CompanyStatusUpdates WHERE EntityId = '238'
SELECT CompanyList.Name, Comments.ContractNumber FROM CompanyList, Comments WHERE CompanyList.Id=Comments.CompanyId
SELECT CompanyList.Name, Comments.Text FROM CompanyList LEFT OUTER JOIN Comments ON CompanyList.Id=Comments.CompanyId
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)
Coming soon
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 Facebook 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 Twitter 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 Instagram 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 Posts
SELECT [FromName] AS MY_FromName FROM Posts
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Posts
SELECT * FROM Posts WHERE Target = '11111'
SELECT COUNT(*) AS MyCount FROM Posts
SELECT COUNT(DISTINCT FromName) FROM Posts
SELECT DISTINCT FromName FROM Posts
SELECT FromName, MAX(AnnualRevenue) FROM Posts GROUP BY FromName
SELECT u.Name, u.Gender, u.Birthday, p.Type, p.LikesCount, p.SharesCount FROM Users u INNER JOIN Posts p ON u.Id = p.FromId
SELECT ID, FromName FROM Posts ORDER BY FromName ASC
SELECT ID, FromName FROM Posts LIMIT 10
SELECT * FROM Posts WHERE Target = @param
SELECT COUNT(*) FROM Posts WHERE Target = '11111'
SELECT COUNT(DISTINCT ID) AS DistinctValues FROM Posts WHERE Target = '11111'
SELECT FromName, AVG(AnnualRevenue) FROM Posts WHERE Target = '11111' GROUP BY FromName
SELECT MIN(AnnualRevenue), FromName FROM Posts WHERE Target = '11111' GROUP BY FromName
SELECT FromName, MAX(AnnualRevenue) FROM Posts WHERE Target = '11111' GROUP BY FromName
SELECT SUM(AnnualRevenue) FROM Posts WHERE Target = '11111'
SELECT u.Name, u.Gender, u.Birthday, p.Type, p.LikesCount, p.SharesCount FROM Users u INNER JOIN Posts p ON u.Id = p.FromId
SELECT u.Name, u.Gender, u.Birthday, p.Type, p.LikesCount, p.SharesCount FROM Users u LEFT JOIN Posts p ON u.Id = p.FromId
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 Tweets
SELECT [Text] AS MY_Text FROM Tweets
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Tweets
SELECT * FROM Tweets WHERE From_User_Name = 'twitter'
SELECT COUNT(*) AS MyCount FROM Tweets
SELECT COUNT(DISTINCT Text) FROM Tweets
SELECT DISTINCT Text FROM Tweets
SELECT Text, MAX(AnnualRevenue) FROM Tweets GROUP BY Text
SELECT u.Name, u.Friends_Count, u.Followers_Count, m.Favorite_Count, m.Retweet_Count, m.Text FROM Users u INNER JOIN Mentions m ON u.Id = m.User_ID
SELECT From_User_Name, Text FROM Tweets ORDER BY Text ASC
SELECT From_User_Name, Text FROM Tweets LIMIT 10
SELECT * FROM Tweets WHERE From_User_Name = @param
SELECT COUNT(*) FROM Tweets WHERE From_User_Name = 'twitter'
SELECT COUNT(DISTINCT From_User_Name) AS DistinctValues FROM Tweets WHERE From_User_Name = 'twitter'
SELECT Text, AVG(AnnualRevenue) FROM Tweets WHERE From_User_Name = 'twitter' GROUP BY Text
SELECT MIN(AnnualRevenue), Text FROM Tweets WHERE From_User_Name = 'twitter' GROUP BY Text
SELECT Text, MAX(AnnualRevenue) FROM Tweets WHERE From_User_Name = 'twitter' GROUP BY Text
SELECT SUM(AnnualRevenue) FROM Tweets WHERE From_User_Name = 'twitter'
SELECT u.Name, u.Friends_Count, u.Followers_Count, m.Favorite_Count, m.Retweet_Count, m.Text FROM Users u INNER JOIN Mentions m ON u.Id = m.User_ID
SELECT u.Name, u.Friends_Count, u.Followers_Count, m.Favorite_Count, m.Retweet_Count, m.Text FROM Users u LEFT JOIN Mentions m ON u.Id = m.User_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)
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 Users
SELECT [Email] AS MY_Email FROM Users
SELECT CAST(Size AS VARCHAR) AS Str_Size FROM Users
SELECT * FROM Users WHERE UserLogin = 'mojombo'
SELECT COUNT(*) AS MyCount FROM Users
SELECT COUNT(DISTINCT Email) FROM Users
SELECT DISTINCT Email FROM Users
SELECT Email, MAX(Size) FROM Users GROUP BY Email
SELECT Commits.AuthorName, CommitComments.Body FROM Commits, CommitComments WHERE Commits.Sha=CommitComments.CommitSha
SELECT Name, Email FROM Users ORDER BY Email ASC
SELECT Name, Email FROM Users LIMIT 10
SELECT * FROM Users WHERE UserLogin = @param
SELECT COUNT(*) FROM Users WHERE UserLogin = 'mojombo'
SELECT COUNT(DISTINCT Name) AS DistinctValues FROM Users WHERE UserLogin = 'mojombo'
SELECT Email, AVG(Size) FROM Users WHERE UserLogin = 'mojombo' GROUP BY Email
SELECT MIN(Size), Email FROM Users WHERE UserLogin = 'mojombo' GROUP BY Email
SELECT Email, MAX(Size) FROM Users WHERE UserLogin = 'mojombo' GROUP BY Email
SELECT SUM(Size) FROM Users WHERE UserLogin = 'mojombo'
SELECT Commits.AuthorName, CommitComments.Body FROM Commits, CommitComments WHERE Commits.Sha=CommitComments.CommitSha
SELECT Commits.AuthorName, CommitComments.Body FROM Commits LEFT OUTER JOIN CommitComments ON Commits.Sha=CommitComments.CommitSha
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)