[jira] [Commented] (SPARK-38483) Column name or alias as an attribute of the PySpark Column class
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https://issues.apache.org/jira/browse/SPARK-38483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17514788#comment-17514788
]
Brian Schaefer commented on SPARK-38483:
I've been thinking about this the past few weeks and would like to propose a
minimal version of this suggested feature:
* a property {{Column._name}} that simply returns {{Column._jc.toString()}}
* an instance variable {{Column._alias}} that is set when {{Column.alias()}}
is called.
The combination of these two provides a convenient interface for Python users
without promising too much. A common use case in my own work would be re-using
an alias (mentioned in the ticket description):
{code:python}
>>> def process_values(col):
... new_values = ...
... return new_values.alias(col._alias or col._name)
...
>>> values = F.col("original_values").alias("values")
>>> df.select(process_values(values))
{code}
> Column name or alias as an attribute of the PySpark Column class
>
>
> Key: SPARK-38483
> URL: https://issues.apache.org/jira/browse/SPARK-38483
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
>Affects Versions: 3.2.1
>Reporter: Brian Schaefer
>Priority: Minor
> Labels: starter
>
> Having the name of a column as an attribute of PySpark {{Column}} class
> instances can enable some convenient patterns, for example:
> Applying a function to a column and aliasing with the original name:
> {code:java}
> values = F.col("values")
> # repeating the column name as an alias
> distinct_values = F.array_distinct(values).alias("values")
> # re-using the existing column name
> distinct_values = F.array_distinct(values).alias(values._name){code}
> Checking the column name inside a custom function and applying conditional
> logic on the name:
> {code:java}
> def custom_function(col: Column) -> Column:
> if col._name == "my_column":
> return col.astype("int")
> return col.astype("string"){code}
> The proposal in this issue is to add a property {{Column.\_name}} that
> obtains the name or alias of a column in a similar way as currently done in
> the {{Column.\_\_repr\_\_}} method:
> [https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L1062.]
> The choice of {{_name}} intentionally avoids collision with the existing
> {{Column.name}} method, which is an alias for {{{}Column.alias{}}}.
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[jira] [Commented] (SPARK-38483) Column name or alias as an attribute of the PySpark Column class
[
https://issues.apache.org/jira/browse/SPARK-38483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17504529#comment-17504529
]
Brian Schaefer commented on SPARK-38483:
The column name does differ between the two when selecting a struct field, but
handling that case seems fairly straightforward.
{code:python}
>>> df = spark.createDataFrame([{"struct": {"outer_field": {"inner_field":
>>> 1}}}])
>>> values = F.col("struct.outer_field.inner_field")
>>> print(df.select(values).schema[0].name)
inner_field
>>> print(values._jc.toString())
struct.outer_field.inner_field
>>> print(values._jc.toString().split(".")[-1])
inner_field{code}
> Column name or alias as an attribute of the PySpark Column class
>
>
> Key: SPARK-38483
> URL: https://issues.apache.org/jira/browse/SPARK-38483
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
>Affects Versions: 3.2.1
>Reporter: Brian Schaefer
>Priority: Minor
> Labels: starter
>
> Having the name of a column as an attribute of PySpark {{Column}} class
> instances can enable some convenient patterns, for example:
> Applying a function to a column and aliasing with the original name:
> {code:java}
> values = F.col("values")
> # repeating the column name as an alias
> distinct_values = F.array_distinct(values).alias("values")
> # re-using the existing column name
> distinct_values = F.array_distinct(values).alias(values._name){code}
> Checking the column name inside a custom function and applying conditional
> logic on the name:
> {code:java}
> def custom_function(col: Column) -> Column:
> if col._name == "my_column":
> return col.astype("int")
> return col.astype("string"){code}
> The proposal in this issue is to add a property {{Column.\_name}} that
> obtains the name or alias of a column in a similar way as currently done in
> the {{Column.\_\_repr\_\_}} method:
> [https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L1062.]
> The choice of {{_name}} intentionally avoids collision with the existing
> {{Column.name}} method, which is an alias for {{{}Column.alias{}}}.
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[jira] [Commented] (SPARK-38483) Column name or alias as an attribute of the PySpark Column class
[
https://issues.apache.org/jira/browse/SPARK-38483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17504448#comment-17504448
]
Brian Schaefer commented on SPARK-38483:
Could you provide an example of when the real column names would be different?
At least for basic examples, it looks like the real column names match those
found using {{{}Column._jc.toString(){}}}. With some careful regex it may also
be possible to catch aliases.
{code:python}
>>> df = spark.createDataFrame([{"values": [1,2,3]}])
>>> values = F.col("values")
>>> print(df.select(values).schema[0].name)
values
>>> print(values._jc.toString())
values
>>> import re
>>> aliased_values = F.col("values").alias("aliased")
>>> print(df.select(aliased_values).schema[0].name)
aliased
>>> print(re.match(".*`(.*)`", aliased_values._jc.toString())[1])
aliased
{code}
> Column name or alias as an attribute of the PySpark Column class
>
>
> Key: SPARK-38483
> URL: https://issues.apache.org/jira/browse/SPARK-38483
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
>Affects Versions: 3.2.1
>Reporter: Brian Schaefer
>Priority: Minor
> Labels: starter
>
> Having the name of a column as an attribute of PySpark {{Column}} class
> instances can enable some convenient patterns, for example:
> Applying a function to a column and aliasing with the original name:
> {code:java}
> values = F.col("values")
> # repeating the column name as an alias
> distinct_values = F.array_distinct(values).alias("values")
> # re-using the existing column name
> distinct_values = F.array_distinct(values).alias(values._name){code}
> Checking the column name inside a custom function and applying conditional
> logic on the name:
> {code:java}
> def custom_function(col: Column) -> Column:
> if col._name == "my_column":
> return col.astype("int")
> return col.astype("string"){code}
> The proposal in this issue is to add a property {{Column.\_name}} that
> obtains the name or alias of a column in a similar way as currently done in
> the {{Column.\_\_repr\_\_}} method:
> [https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L1062.]
> The choice of {{_name}} intentionally avoids collision with the existing
> {{Column.name}} method, which is an alias for {{{}Column.alias{}}}.
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[jira] [Commented] (SPARK-38483) Column name or alias as an attribute of the PySpark Column class
[
https://issues.apache.org/jira/browse/SPARK-38483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17503963#comment-17503963
]
Hyukjin Kwon commented on SPARK-38483:
--
The real column names can only be known after resolving it by analyzer. You
would have to do it with, for example:
{code}
values = F.col("values")
df.select(values).schema[0]
{code}
> Column name or alias as an attribute of the PySpark Column class
>
>
> Key: SPARK-38483
> URL: https://issues.apache.org/jira/browse/SPARK-38483
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
>Affects Versions: 3.2.1
>Reporter: Brian Schaefer
>Priority: Minor
> Labels: starter
>
> Having the name of a column as an attribute of PySpark {{Column}} class
> instances can enable some convenient patterns, for example:
> Applying a function to a column and aliasing with the original name:
> {code:java}
> values = F.col("values")
> # repeating the column name as an alias
> distinct_values = F.array_distinct(values).alias("values")
> # re-using the existing column name
> distinct_values = F.array_distinct(values).alias(values._name){code}
> Checking the column name inside a custom function and applying conditional
> logic on the name:
> {code:java}
> def custom_function(col: Column) -> Column:
> if col._name == "my_column":
> return col.astype("int")
> return col.astype("string"){code}
> The proposal in this issue is to add a property {{Column.\_name}} that
> obtains the name or alias of a column in a similar way as currently done in
> the {{Column.\_\_repr\_\_}} method:
> [https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L1062.]
> The choice of {{_name}} intentionally avoids collision with the existing
> {{Column.name}} method, which is an alias for {{{}Column.alias{}}}.
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[jira] [Commented] (SPARK-38483) Column name or alias as an attribute of the PySpark Column class
[
https://issues.apache.org/jira/browse/SPARK-38483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17503782#comment-17503782
]
Brian Schaefer commented on SPARK-38483:
Extracting the column name from the {{Column.__repr__}} method has been
discussed on StackExchange: [https://stackoverflow.com/a/43150264.] However, it
would be useful to have the column name more easily accessible.
> Column name or alias as an attribute of the PySpark Column class
>
>
> Key: SPARK-38483
> URL: https://issues.apache.org/jira/browse/SPARK-38483
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
>Affects Versions: 3.2.1
>Reporter: Brian Schaefer
>Priority: Minor
> Labels: starter
>
> Having the name of a column as an attribute of PySpark {{Column}} class
> instances can enable some convenient patterns, for example:
> Applying a function to a column and aliasing with the original name:
> {code:java}
> values = F.col("values")
> # repeating the column name as an alias
> distinct_values = F.array_distinct(values).alias("values")
> # re-using the existing column name
> distinct_values = F.array_distinct(values).alias(values._name){code}
> Checking the column name inside a custom function and applying conditional
> logic on the name:
> {code:java}
> def custom_function(col: Column) -> Column:
> if col._name == "my_column":
> return col.astype("int")
> return col.astype("string"){code}
> The proposal in this issue is to add a property {{Column.\_name}} that
> obtains the name or alias of a column in a similar way as currently done in
> the {{Column.\_\_repr\_\_}} method:
> [https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L1062.]
> The choice of {{_name}} intentionally avoids collision with the existing
> {{Column.name}} method, which is an alias for {{{}Column.alias{}}}.
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