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new 3cdee78cb7c [SPARK-42192][FOLLOWUP][PYTHON] Refine improper error
class and error type
3cdee78cb7c is described below
commit 3cdee78cb7c113c9f3ba893299ea4b48919fc889
Author: itholic <[email protected]>
AuthorDate: Thu Apr 27 08:55:50 2023 +0800
[SPARK-42192][FOLLOWUP][PYTHON] Refine improper error class and error type
### What changes were proposed in this pull request?
This is follow-up for https://github.com/apache/spark/pull/39785 to address
improper error class and error type.
### Why are the changes needed?
We should use proper error class and error type for PySpark errors.
### Does this PR introduce _any_ user-facing change?
No, it's error correction
### How was this patch tested?
The existing CI should pass
Closes #40965 from itholic/error_frame_followup.
Authored-by: itholic <[email protected]>
Signed-off-by: Ruifeng Zheng <[email protected]>
---
python/pyspark/sql/dataframe.py | 12 +++++++-----
1 file changed, 7 insertions(+), 5 deletions(-)
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 4febdd447c9..39e644731c1 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -4416,9 +4416,11 @@ class DataFrame(PandasMapOpsMixin,
PandasConversionMixin):
and not isinstance(to_replace, dict)
):
raise PySparkTypeError(
- "If to_replace is not a dict, value should be "
- "a bool, float, int, string, list, tuple or None. "
- "Got {0}".format(type(value))
+
error_class="NOT_BOOL_OR_FLOAT_OR_INT_OR_LIST_OR_NONE_OR_STR_OR_TUPLE",
+ message_parameters={
+ "arg_name": "value",
+ "arg_type": type(value).__name__,
+ },
)
if isinstance(to_replace, (list, tuple)) and isinstance(value, (list,
tuple)):
@@ -4611,7 +4613,7 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
},
)
if relativeError < 0:
- raise PySparkTypeError(
+ raise PySparkValueError(
error_class="NEGATIVE_VALUE",
message_parameters={
"arg_name": "relativeError",
@@ -4672,7 +4674,7 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
if not method:
method = "pearson"
if not method == "pearson":
- raise PySparkTypeError(
+ raise PySparkValueError(
error_class="VALUE_NOT_PEARSON",
message_parameters={"arg_name": "method", "arg_value": method},
)
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