ueshin commented on code in PR #43611:
URL: https://github.com/apache/spark/pull/43611#discussion_r1398012807
##########
python/pyspark/sql/worker/analyze_udtf.py:
##########
@@ -116,12 +118,94 @@ def main(infile: IO, outfile: IO) -> None:
handler = read_udtf(infile)
args, kwargs = read_arguments(infile)
+ error_prefix = f"Failed to evaluate the user-defined table function
'{handler.__name__}'"
+
+ def format_error(msg: str) -> str:
+ return dedent(msg).replace("\n", " ")
+
+ # Check that the arguments provided to the UDTF call match the
expected parameters defined
+ # in the static 'analyze' method signature.
+ try:
+ inspect.signature(handler.analyze).bind(*args, **kwargs)
+ except TypeError as e:
+ # The UDTF call's arguments did not match the expected signature.
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the function arguments did not
match the expected
+ signature of the static 'analyze' method ({e}). Please
update the query so that
+ this table function call provides arguments matching the
expected signature, or
+ else update the table function so that its static
'analyze' method accepts the
+ provided arguments, and then try the query again."""
+ )
+ )
+
+ # Invoke the UDTF's 'analyze' method.
result = handler.analyze(*args, **kwargs) # type: ignore[attr-defined]
+ # Check invariants about the 'analyze' method after running it.
if not isinstance(result, AnalyzeResult):
raise PySparkValueError(
- "Output of `analyze` static method of Python UDTFs expects "
- f"a pyspark.sql.udtf.AnalyzeResult but got: {type(result)}"
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method expects
a result of type
+ pyspark.sql.udtf.AnalyzeResult, but instead this method
returned a value of
+ type: {type(result)}"""
+ )
+ )
+ elif not isinstance(result.schema, StructType):
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method expects
a result of type
+ pyspark.sql.udtf.AnalyzeResult with a 'schema' field
comprising a StructType,
+ but the 'schema' field had the wrong type:
{type(result.schema)}"""
+ )
+ )
+ has_table_arg = (
+ len([arg for arg in args if arg.isTable])
+ + len([arg for arg in kwargs.items() if arg[-1].isTable])
+ ) > 0
Review Comment:
```suggestion
has_table_arg = any(arg.isTable for arg in args) or any(arg.isTable
for arg in kwargs.values())
```
Please reformat it as I'm not sure it follows the format rule.
##########
python/pyspark/sql/worker/analyze_udtf.py:
##########
@@ -116,12 +118,94 @@ def main(infile: IO, outfile: IO) -> None:
handler = read_udtf(infile)
args, kwargs = read_arguments(infile)
+ error_prefix = f"Failed to evaluate the user-defined table function
'{handler.__name__}'"
+
+ def format_error(msg: str) -> str:
+ return dedent(msg).replace("\n", " ")
+
+ # Check that the arguments provided to the UDTF call match the
expected parameters defined
+ # in the static 'analyze' method signature.
+ try:
+ inspect.signature(handler.analyze).bind(*args, **kwargs)
+ except TypeError as e:
+ # The UDTF call's arguments did not match the expected signature.
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the function arguments did not
match the expected
+ signature of the static 'analyze' method ({e}). Please
update the query so that
+ this table function call provides arguments matching the
expected signature, or
+ else update the table function so that its static
'analyze' method accepts the
+ provided arguments, and then try the query again."""
+ )
+ )
+
+ # Invoke the UDTF's 'analyze' method.
result = handler.analyze(*args, **kwargs) # type: ignore[attr-defined]
+ # Check invariants about the 'analyze' method after running it.
if not isinstance(result, AnalyzeResult):
raise PySparkValueError(
- "Output of `analyze` static method of Python UDTFs expects "
- f"a pyspark.sql.udtf.AnalyzeResult but got: {type(result)}"
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method expects
a result of type
+ pyspark.sql.udtf.AnalyzeResult, but instead this method
returned a value of
+ type: {type(result)}"""
+ )
+ )
+ elif not isinstance(result.schema, StructType):
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method expects
a result of type
+ pyspark.sql.udtf.AnalyzeResult with a 'schema' field
comprising a StructType,
+ but the 'schema' field had the wrong type:
{type(result.schema)}"""
+ )
+ )
+ has_table_arg = (
+ len([arg for arg in args if arg.isTable])
+ + len([arg for arg in kwargs.items() if arg[-1].isTable])
+ ) > 0
+ if not has_table_arg and result.withSinglePartition:
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method
returned an
+ 'AnalyzeResult' object with the 'withSinglePartition'
field set to 'true', but
+ the function call did not provide any table argument.
Please update the query so
+ that it provides a table argument, or else update the
table function so that its
+ 'analyze' method returns an 'AnalyzeResult' object with the
+ 'withSinglePartition' field set to 'false', and then try
the query again."""
+ )
+ )
+ elif not has_table_arg and len(result.partitionBy) > 0:
+ raise PySparkValueError(
+ format_error(
+ f"""
+ {error_prefix} because the static 'analyze' method
returned an
+ 'AnalyzeResult' object with the 'partitionBy' list set to
non-empty, but the
+ function call did not provide any table argument. Please
update the query so
+ that it provides a table argument, or else update the
table function so that its
+ 'analyze' method returns an 'AnalyzeResult' object with
the 'partitionBy' list
+ set to empty, and then try the query again."""
+ )
+ )
+ elif (
+ hasattr(result, "partitionBy")
Review Comment:
Do we need to check this? `AnalyzeResult` should always have this attribute?
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