HyukjinKwon commented on a change in pull request #27406:
[SPARK-30681][PYSPARK][SQL] Add higher order functions API to PySpark
URL: https://github.com/apache/spark/pull/27406#discussion_r373896752
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File path: python/pyspark/sql/column.py
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@@ -129,6 +129,103 @@ def _(self, other):
return _
+def _unresolved_named_lambda_variable(*name_parts):
+ """
+ Create o.a.s.sql.expressions.UnresolvedNamedLambdaVariable and
+ convert it to o.s.sql.Column
+
+ :param name_parts: str
+ """
+ sc = SparkContext._active_spark_context
+ name_parts_seq = _to_seq(sc, name_parts)
+ expressions = sc._jvm.org.apache.spark.sql.catalyst.expressions
+ return Column(
+ sc._jvm.Column(
+ expressions.UnresolvedNamedLambdaVariable(name_parts_seq)
+ )
+ )
+
+
+def _get_lambda_parameters(f):
+ import inspect
+
+ signature = inspect.signature(f)
+ parameters = signature.parameters.values()
+
+ # We should exclude functions that use
+ # variable args and keyword argnames
+ # as well as keyword only args
+ supported_parmeter_types = {
+ inspect.Parameter.POSITIONAL_OR_KEYWORD,
+ inspect.Parameter.POSITIONAL_ONLY,
+ }
+
+ # Validate that
+ # function arity is between 1 and 3
+ if not (1 <= len(parameters) <= 3):
Review comment:
I am not sure if this is a good way to duplicately handle error cases. I
mean, for simple cechking, I am good with that but if it needs some
considerable codes like the current, I am not sure yet.
I fully understand the concern about JVM stracktrace being exposed to Python
users; however, I don't think we should add such checking to every API in
PySpark. It will end up with duplicating whole
[CheckAnalysis.scala](https://github.com/apache/spark/blob/290a528bff7bcb449714c1c6f1885bd0f804358d/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala)
and
[TypeCoercion.scala](https://github.com/apache/spark/blob/297f406425d410e5c450a9fbe24679b49f00a553/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala).
I admit that I don't have a good idea except just fixing
[utils.py#L76-L92](https://github.com/apache/spark/blob/0a95eb08003a115f59495b30aacaaa832940e977/python/pyspark/sql/utils.py#L76-L92)
somehow better.
Hope we can discuss separately in a separate PR.
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