[ 
https://issues.apache.org/jira/browse/SPARK-61080?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-61080:
---------------------------------
    Description: 
In PySpark Connect, the data types have the attributes of their parameters, 
{{typeName}} is a classmethod, and the types without parameters are singletons:
* {{StringType("UTF8_LCASE").collation}}, {{CharType(3).length}}, 
{{VarcharType(4).length}}, {{TimeType(3).precision}}, the {{startField}} and 
{{endField}} of {{DayTimeIntervalType}} and {{YearMonthIntervalType}}, and 
{{DecimalType(10, 2).hasPrecisionInfo}}
* {{IntegerType.typeName()}} is "integer", of the name of the class 
({{cls.__name__[:-4].lower()}}), also for subclasses of {{DataType}}, and 
"void", "timestamp_ntz" and "interval" for {{NullType}}, {{TimestampNTZType}} 
and {{CalendarIntervalType}}
* {{StructField.typeName()}} raises the {{PySparkTypeError}} 
{{INVALID_TYPENAME_CALL}}
* {{IntegerType() is IntegerType()}}, as for the other types of 
{{DataTypeSingleton}}: {{NullType}}, the integral types, {{FloatType}}, 
{{DoubleType}}, {{BinaryType}}, {{BooleanType}}, {{DateType}}, 
{{TimestampType}}, {{TimestampNTZType}} and {{CalendarIntervalType}}

The Rust-backed Python client lacks these attributes ({{AttributeError}}). Its 
{{typeName}} is an instance method, so {{IntegerType.typeName()}} raises a 
{{TypeError}}, and {{CalendarIntervalType().typeName()}} is "calendarinterval". 
{{StructField.typeName()}} raises a plain {{TypeError}}, and every call of a 
type class returns a new object. Add them as PySpark does.

  was:
In PySpark Connect, the data types have the attributes of their parameters, and 
{{typeName}} is a classmethod:
* {{StringType("UTF8_LCASE").collation}}, {{CharType(3).length}}, 
{{VarcharType(4).length}}, {{TimeType(3).precision}}, the {{startField}} and 
{{endField}} of {{DayTimeIntervalType}} and {{YearMonthIntervalType}}, and 
{{DecimalType(10, 2).hasPrecisionInfo}}
* {{IntegerType.typeName()}} is "integer", of the name of the class 
({{cls.__name__[:-4].lower()}}), also for subclasses, and "void", 
"timestamp_ntz" and "interval" for {{NullType}}, {{TimestampNTZType}} and 
{{CalendarIntervalType}}
* {{StructField.typeName()}} raises the {{PySparkTypeError}} 
{{INVALID_TYPENAME_CALL}}

The Rust-backed Python client lacks these attributes ({{AttributeError}}), 
{{typeName}} is an instance method, so {{IntegerType.typeName()}} raises a 
{{TypeError}}, and {{StructField.typeName()}} raises a plain {{TypeError}}. Add 
them as PySpark does.


        Summary: Expose the attributes of the data types, typeName as a 
classmethod, and the singleton types in the Python client as PySpark does  
(was: Expose the attributes of the data types, and typeName as a classmethod, 
in the Python client as PySpark does)

> Expose the attributes of the data types, typeName as a classmethod, and the 
> singleton types in the Python client as PySpark does
> --------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-61080
>                 URL: https://issues.apache.org/jira/browse/SPARK-61080
>             Project: Spark
>          Issue Type: Bug
>          Components: Connect
>    Affects Versions: connect-rust-4.3.0
>            Reporter: Hyukjin Kwon
>            Priority: Major
>             Fix For: connect-rust-4.3.0
>
>
> In PySpark Connect, the data types have the attributes of their parameters, 
> {{typeName}} is a classmethod, and the types without parameters are 
> singletons:
> * {{StringType("UTF8_LCASE").collation}}, {{CharType(3).length}}, 
> {{VarcharType(4).length}}, {{TimeType(3).precision}}, the {{startField}} and 
> {{endField}} of {{DayTimeIntervalType}} and {{YearMonthIntervalType}}, and 
> {{DecimalType(10, 2).hasPrecisionInfo}}
> * {{IntegerType.typeName()}} is "integer", of the name of the class 
> ({{cls.__name__[:-4].lower()}}), also for subclasses of {{DataType}}, and 
> "void", "timestamp_ntz" and "interval" for {{NullType}}, {{TimestampNTZType}} 
> and {{CalendarIntervalType}}
> * {{StructField.typeName()}} raises the {{PySparkTypeError}} 
> {{INVALID_TYPENAME_CALL}}
> * {{IntegerType() is IntegerType()}}, as for the other types of 
> {{DataTypeSingleton}}: {{NullType}}, the integral types, {{FloatType}}, 
> {{DoubleType}}, {{BinaryType}}, {{BooleanType}}, {{DateType}}, 
> {{TimestampType}}, {{TimestampNTZType}} and {{CalendarIntervalType}}
> The Rust-backed Python client lacks these attributes ({{AttributeError}}). 
> Its {{typeName}} is an instance method, so {{IntegerType.typeName()}} raises 
> a {{TypeError}}, and {{CalendarIntervalType().typeName()}} is 
> "calendarinterval". {{StructField.typeName()}} raises a plain {{TypeError}}, 
> and every call of a type class returns a new object. Add them as PySpark does.



--
This message was sent by Atlassian Jira
(v10.3.26#10030026)

---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to