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[GitHub] [spark] gengliangwang opened a new pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

gengliangwang opened a new pull request #33516:
URL: https://github.com/apache/spark/pull/33516


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   Add documentation for the ANSI implicit cast rules which are introduced from https://github.com/apache/spark/pull/31349
   
   ### Why are the changes needed?
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   Better documentation.
   
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[GitHub] [spark] SparkQA commented on pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

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URL: https://github.com/apache/spark/pull/33516#issuecomment-886895476


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    * This patch passes all tests.
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[GitHub] [spark] gengliangwang commented on pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
gengliangwang commented on pull request #33516:
URL: https://github.com/apache/spark/pull/33516#issuecomment-886454997


   @srielau Thanks for summary the rules. He should be the first author on merging this PR.


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[GitHub] [spark] cloud-fan closed pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
cloud-fan closed pull request #33516:
URL: https://github.com/apache/spark/pull/33516


   


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[GitHub] [spark] cloud-fan commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r677403082



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -66,11 +66,9 @@ SELECT abs(-2147483648);
 +----------------+
 ```
 
-### Type Conversion
+### Cast
 
-Spark SQL has three kinds of type conversions: explicit casting, type coercion, and store assignment casting.
 When `spark.sql.ansi.enabled` is set to `true`, explicit casting by `CAST` syntax throws a runtime exception for illegal cast patterns defined in the standard, e.g. casts from a string to an integer.
-On the other hand, `INSERT INTO` syntax throws an analysis exception when the ANSI mode enabled via `spark.sql.storeAssignmentPolicy=ANSI`.
 
 The type conversion of Spark ANSI mode follows the syntax rules of section 6.13 "cast specification" in [ISO/IEC 9075-2:2011 Information technology — Database languages - SQL — Part 2: Foundation (SQL/Foundation)](https://www.iso.org/standard/53682.html), except it specially allows the following

Review comment:
       `The type conversion` -> `Explicit cast`

##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -66,11 +66,9 @@ SELECT abs(-2147483648);
 +----------------+
 ```
 
-### Type Conversion
+### Cast
 
-Spark SQL has three kinds of type conversions: explicit casting, type coercion, and store assignment casting.
 When `spark.sql.ansi.enabled` is set to `true`, explicit casting by `CAST` syntax throws a runtime exception for illegal cast patterns defined in the standard, e.g. casts from a string to an integer.
-On the other hand, `INSERT INTO` syntax throws an analysis exception when the ANSI mode enabled via `spark.sql.storeAssignmentPolicy=ANSI`.
 
 The type conversion of Spark ANSI mode follows the syntax rules of section 6.13 "cast specification" in [ISO/IEC 9075-2:2011 Information technology — Database languages - SQL — Part 2: Foundation (SQL/Foundation)](https://www.iso.org/standard/53682.html), except it specially allows the following

Review comment:
       `The type conversion` -> `The explicit cast`




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[GitHub] [spark] gengliangwang commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r676771410



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |

Review comment:
       Done




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[GitHub] [spark] gengliangwang commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r676771658



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |
+| Timestamp | Timestamp                                                        |
+| String    | String                                                           |
+| Binary    | Binary                                                           |
+| Boolean   | Boolean                                                          |
+| Interval  | Interval                                                         |
+| Map       | Map**                                                            |
+| Array     | Array**                                                          |
+| Struct    | Struct**                                                         |
+
+\* For least common type resolution float is skipped to avoid loss of precision.
+
+\*\* For a complex type, the precedence rule applies recursively to its component elements.
+
+Special rules apply for string literals and untyped NULL.
+A NULL can be promoted to any other type, while a string literal can be promoted to any simple data type.
+
+This is a graphical depiction of the precedence list as a directed tree:
+<img src="img/type-precedence-list.png" width="80%" title="Type Precedence List" alt="Type Precedence List">
+
+#### Least Common Type Resolution
+The least common type from a set of types is the narrowest type reachable from the precedence list by all elements of the set of types.
+
+The least common type resolution is used to:
+- Decide whether a function expecting a parameter of a type can be invoked using an argument of a narrower type.
+- Derive the argument  type for functions which expect a shared argument type for multiple parameters, such as coalesce, least, or greatest.

Review comment:
       Done(BTW the extra space will be omitted in web page anyway)




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[GitHub] [spark] cloud-fan commented on pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #33516:
URL: https://github.com/apache/spark/pull/33516#issuecomment-887483184


   thanks, merging to master/3.2!


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[GitHub] [spark] cloud-fan commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r677403890



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -66,11 +66,9 @@ SELECT abs(-2147483648);
 +----------------+
 ```
 
-### Type Conversion
+### Cast

Review comment:
       In this section, it says `In future releases, the behaviour of type coercion might change along with the other two type conversion rules.`
   
   We should update it.




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[GitHub] [spark] MaxGekk commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
MaxGekk commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r676646906



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |

Review comment:
       `Date->  Timestamp` -> `Date -> Timestamp`

##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |
+| Timestamp | Timestamp                                                        |
+| String    | String                                                           |
+| Binary    | Binary                                                           |
+| Boolean   | Boolean                                                          |
+| Interval  | Interval                                                         |
+| Map       | Map**                                                            |
+| Array     | Array**                                                          |
+| Struct    | Struct**                                                         |
+
+\* For least common type resolution float is skipped to avoid loss of precision.
+
+\*\* For a complex type, the precedence rule applies recursively to its component elements.
+
+Special rules apply for string literals and untyped NULL.
+A NULL can be promoted to any other type, while a string literal can be promoted to any simple data type.
+
+This is a graphical depiction of the precedence list as a directed tree:
+<img src="img/type-precedence-list.png" width="80%" title="Type Precedence List" alt="Type Precedence List">
+
+#### Least Common Type Resolution
+The least common type from a set of types is the narrowest type reachable from the precedence list by all elements of the set of types.
+
+The least common type resolution is used to:
+- Decide whether a function expecting a parameter of a type can be invoked using an argument of a narrower type.
+- Derive the argument  type for functions which expect a shared argument type for multiple parameters, such as coalesce, least, or greatest.

Review comment:
       Remove a space in `argument  type` -> `argument type`

##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |
+| Timestamp | Timestamp                                                        |
+| String    | String                                                           |
+| Binary    | Binary                                                           |
+| Boolean   | Boolean                                                          |
+| Interval  | Interval                                                         |

Review comment:
       Should we distinguish year-month and day-time interval types? 




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[GitHub] [spark] gengliangwang commented on a change in pull request #33516: [SPARK-34249][DOCS] Add documentation for ANSI implicit cast rules

Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #33516:
URL: https://github.com/apache/spark/pull/33516#discussion_r676772010



##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -160,6 +160,81 @@ SELECT * FROM t;
 +---+
 ```
 
+### Type coercion
+#### Type Promotion and Precedence
+When `spark.sql.ansi.enabled` is set to `true`, Spark SQL uses several rules that govern how conflicts between data types are resolved.
+At the heart of this conflict resolution is the Type Precedence List which defines whether values of a given data type can be promoted to another data type implicitly.
+
+| Data type | precedence list(from narrowest to widest)                        |
+|-----------|------------------------------------------------------------------|
+| Byte      | Byte -> Short -> Int -> Long -> Decimal -> Float* -> Double      |
+| Short     | Short -> Int -> Long -> Decimal-> Float* -> Double               |
+| Int       | Int -> Long -> Decimal -> Float* -> Double                       |
+| Long      | Long -> Decimal -> Float* -> Double                              |
+| Decimal   | Decimal -> Float* -> Double                                      |
+| Float     | Float -> Double                                                  |
+| Double    | Double                                                           |
+| Date      | Date->  Timestamp                                                |
+| Timestamp | Timestamp                                                        |
+| String    | String                                                           |
+| Binary    | Binary                                                           |
+| Boolean   | Boolean                                                          |
+| Interval  | Interval                                                         |

Review comment:
       Let's keep it simple in this section




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