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Application Platforms

Alfresco Platform

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:

  1. 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.

  2. HAVING can only be applied to aggregation functions.

  3. LIKE, JOIN, and UNION are unsupported.

  4. Sub-queries are not supported.

  5. 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 = '*'.

  6. The CMIS Query Language functions IN_TREE, IN_FOLDER, SCORE, and CONTAINS are unsupported.

Kintone Platform

SELECT Statements

A SELECT statement can consist of the following basic clauses.

  • SELECT

  • INTO

  • FROM

  • JOIN

  • WHERE

  • GROUP BY

  • HAVING

  • UNION

  • ORDER BY

  • LIMIT

SELECT Syntax

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 } ... ]

Examples

  1. Return all columns:

    SELECT * FROM Comments

  2. Rename a column:

    SELECT [Text] AS MY_Text FROM Comments

  3. Cast a column's data as a different data type:

    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Comments

  4. Search data:

    SELECT * FROM Comments WHERE AppId = '1354841'

  5. Return the number of items matching the query criteria:

    SELECT COUNT(*) AS MyCount FROM Comments

  6. Return the number of unique items matching the query criteria:

    SELECT COUNT(DISTINCT Text) FROM Comments

  7. Return the unique items matching the query criteria:

    SELECT DISTINCT Text FROM Comments

  8. Summarize data:

    SELECT Text, MAX(AnnualRevenue) FROM Comments GROUP BY Text

    See Aggregate Functions below for details.

  9. Retrieve data from multiple tables.

    SELECT Apps.Name, Comments.Text FROM Apps INNER JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1

    See JOIN Queries below for details.

  10. Sort a result set in ascending order:

    SELECT CreatorName, Text FROM Comments ORDER BY Text ASC

  11. Restrict a result set to the specified number of rows:

    SELECT CreatorName, Text FROM Comments LIMIT 10

  12. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.

    SELECT * FROM Comments WHERE AppId = @param

Aggregate Functions

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM Comments WHERE AppId = '1354841'

COUNT(DISTINCT)

Returns the number of distinct, non-null field values matching the query criteria.

SELECT COUNT(DISTINCT CreatorName) AS DistinctValues FROM Comments WHERE AppId = '1354841'

AVG

Returns the average of the column values.

SELECT Text, AVG(AnnualRevenue) FROM Comments WHERE AppId = '1354841' GROUP BY Text

MIN

Returns the minimum column value.

SELECT MIN(AnnualRevenue), Text FROM Comments WHERE AppId = '1354841' GROUP BY Text

MAX

Returns the maximum column value.

SELECT Text, MAX(AnnualRevenue) FROM Comments WHERE AppId = '1354841' GROUP BY Text

SUM

Returns the total sum of the column values.

SELECT SUM(AnnualRevenue) FROM Comments WHERE AppId = '1354841'

JOIN Queries

The Provider for Kintone supports standard SQL joins like the following examples.

Inner Join

An inner join selects only rows from both tables that match the join condition:

SELECT Apps.Name, Comments.Text FROM Apps INNER JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1

Left Join

A left join selects all rows in the FROM table and only matching rows in the JOIN table:

SELECT Apps.Name, Comments.Text FROM Apps LEFT JOIN Comments ON Apps.AppId = Comments.AppId WHERE Comments.Appid=5 AND Comments.RecordId=1

Date Literal Functions

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.

L_TODAY()

The current day.

SELECT * FROM MyTable WHERE MyDateField = L_TODAY()

L_YESTERDAY()

The previous day.

SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()

L_TOMORROW()

The following day.

SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()

L_LAST_WEEK()

Every day in the preceding week.

SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()

L_THIS_WEEK()

Every day in the current week.

SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()

L_NEXT_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

L_LAST_N_DAYS(n)

The previous n days, excluding the current day.

SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)

L_NEXT_N_DAYS(n)

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

L_LAST_N_WEEKS(n)

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)

L_NEXT_N_WEEKS(n)

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)

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