The Alfresco driver exposes the alfresco table in order to pass queries to the Alfresco Search SQL API. The driver supports translating most SQL-92 queries into the SQL syntax required by the Alfresco Search SQL API. However, syntax limitations and incompatibilities do exist. A full overview of the capabilities and restrictions of the Search SQL API syntax is maintained in Alfresco documentation, but important syntax requirements and limitations for the API and driver are documented below:
The aggregation functions COUNT(*), SUM(numeric_field), AVG(numeric_field), MAX(numeric_field), and MIN(numeric_field) are supported. The COUNT(specific_field) or COUNT(DISTINCT specific_field) aggregations are unsupported.
HAVING can only be applied to aggregation functions.
LIKE, JOIN, and UNION are unsupported.
Sub-queries are not supported.
The following should be used in place of an IS NULL filter: where cm_content != '*'. The following should be used in place of an IS NOT NULL filter: where cm_content = '*'.
The CMIS Query Language functions IN_TREE, IN_FOLDER, SCORE, and CONTAINS are unsupported.
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 Veeva Vault 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 Quickbase 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 Kintone 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>
]
]
}
<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 Documents
SELECT [Name] AS MY_Name FROM Documents
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Documents
SELECT * FROM Documents WHERE Name = 'Test'
SELECT COUNT(*) AS MyCount FROM Documents
SELECT COUNT(DISTINCT Name) FROM Documents
SELECT DISTINCT Name FROM Documents
SELECT Name, MAX(AnnualRevenue) FROM Documents GROUP BY Name
SELECT c.Id, c.Name, o.Id, o.Name FROM Documents c INNER JOIN Products o ON c.Id = o.DocumentId
SELECT Id, Name FROM Documents ORDER BY Name ASC
SELECT Id, Name FROM Documents LIMIT 10
SELECT * FROM Documents WHERE Name = @param
SELECT COUNT(*) FROM Documents WHERE Name = 'Test'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Documents WHERE Name = 'Test'
SELECT Name, AVG(AnnualRevenue) FROM Documents WHERE Name = 'Test' GROUP BY Name
SELECT MIN(AnnualRevenue), Name FROM Documents WHERE Name = 'Test' GROUP BY Name
SELECT Name, MAX(AnnualRevenue) FROM Documents WHERE Name = 'Test' GROUP BY Name
SELECT SUM(AnnualRevenue) FROM Documents WHERE Name = 'Test'
SELECT c.Id, c.Name, o.Id, o.Name FROM Documents c INNER JOIN Products o ON c.Id = o.DocumentId
SELECT c.Id, c.Name, o.Id, o.Name FROM Documents c LEFT JOIN Products o ON c.Id = o.DocumentId
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 [CData].[QuickBase].SampleTable_1
SELECT [Column1] AS MY_Column1 FROM [CData].[QuickBase].SampleTable_1
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM [CData].[QuickBase].SampleTable_1
SELECT * FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob'
SELECT COUNT(*) AS MyCount FROM [CData].[QuickBase].SampleTable_1
SELECT COUNT(DISTINCT Column1) FROM [CData].[QuickBase].SampleTable_1
SELECT DISTINCT Column1 FROM [CData].[QuickBase].SampleTable_1
SELECT Column1, MAX(AnnualRevenue) FROM [CData].[QuickBase].SampleTable_1 GROUP BY Column1
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2
SELECT Id, Column1 FROM [CData].[QuickBase].SampleTable_1 ORDER BY Column1 ASC
SELECT Id, Column1 FROM [CData].[QuickBase].SampleTable_1 LIMIT 10
SELECT * FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = @param
SELECT COUNT(*) FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob'
SELECT COUNT(DISTINCT Id) AS DistinctValues FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob'
SELECT Column1, AVG(AnnualRevenue) FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
SELECT MIN(AnnualRevenue), Column1 FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
SELECT Column1, MAX(AnnualRevenue) FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob' GROUP BY Column1
SELECT SUM(AnnualRevenue) FROM [CData].[QuickBase].SampleTable_1 WHERE Column2 = 'Bob'
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c INNER JOIN SampleTable_2 o ON c.Id = o.Id2
SELECT c.SampleCol1, o.SampleCol2, o.SampleCol3, o.SampleCol4 FROM SampleTable_1 c LEFT JOIN SampleTable_2 o ON c.Id = o.Id2
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 Comments
SELECT [Text] AS MY_Text FROM Comments
SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Comments
SELECT * FROM Comments WHERE AppId = '1354841'
SELECT COUNT(*) AS MyCount FROM Comments
SELECT COUNT(DISTINCT Text) FROM Comments
SELECT DISTINCT Text FROM Comments
SELECT Text, MAX(AnnualRevenue) FROM Comments GROUP BY Text
SELECT Apps.Name, Comments.Text FROM Apps INNER JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1
SELECT CreatorName, Text FROM Comments ORDER BY Text ASC
SELECT CreatorName, Text FROM Comments LIMIT 10
SELECT * FROM Comments WHERE AppId = @param
SELECT COUNT(*) FROM Comments WHERE AppId = '1354841'
SELECT COUNT(DISTINCT CreatorName) AS DistinctValues FROM Comments WHERE AppId = '1354841'
SELECT Text, AVG(AnnualRevenue) FROM Comments WHERE AppId = '1354841' GROUP BY Text
SELECT MIN(AnnualRevenue), Text FROM Comments WHERE AppId = '1354841' GROUP BY Text
SELECT Text, MAX(AnnualRevenue) FROM Comments WHERE AppId = '1354841' GROUP BY Text
SELECT SUM(AnnualRevenue) FROM Comments WHERE AppId = '1354841'
SELECT Apps.Name, Comments.Text FROM Apps INNER JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1
SELECT Apps.Name, Comments.Text FROM Apps LEFT JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1
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)