itholic commented on code in PR #45377:
URL: https://github.com/apache/spark/pull/45377#discussion_r1548983997
##########
python/pyspark/sql/tests/test_dataframe.py:
##########
@@ -825,6 +828,172 @@ def test_duplicate_field_names(self):
self.assertEqual(df.schema, schema)
self.assertEqual(df.collect(), data)
+ def test_dataframe_error_context(self):
+ # SPARK-47274: Add more useful contexts for PySpark DataFrame API
errors.
+ with self.sql_conf({"spark.sql.ansi.enabled": True}):
+ df = self.spark.range(10)
+
+ # DataFrameQueryContext with pysparkCallSite - divide
+ with self.assertRaises(ArithmeticException) as pe:
+ df.withColumn("div_zero", df.id / 0).collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="DIVIDE_BY_ZERO",
+ message_parameters={"config": '"spark.sql.ansi.enabled"'},
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="divide",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - plus
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("plus_invalid_type", df.id + "string").collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="plus",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - minus
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("minus_invalid_type", df.id - "string").collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="minus",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - multiply
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("multiply_invalid_type", df.id *
"string").collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="multiply",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - chained (`divide`
is problematic)
+ with self.assertRaises(ArithmeticException) as pe:
+ df.withColumn("multiply_ten", df.id * 10).withColumn(
+ "divide_zero", df.id / 0
+ ).withColumn("plus_ten", df.id + 10).withColumn("minus_ten",
df.id - 10).collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="DIVIDE_BY_ZERO",
+ message_parameters={"config": '"spark.sql.ansi.enabled"'},
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="divide",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - chained (`plus` is
problematic)
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("multiply_ten", df.id * 10).withColumn(
+ "divide_ten", df.id / 10
+ ).withColumn("plus_string", df.id + "string").withColumn(
+ "minus_ten", df.id - 10
+ ).collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="plus",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - chained (`minus` is
problematic)
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("multiply_ten", df.id * 10).withColumn(
+ "divide_ten", df.id / 10
+ ).withColumn("plus_ten", df.id + 10).withColumn(
+ "minus_string", df.id - "string"
+ ).collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="minus",
+ )
+
+ # DataFrameQueryContext with pysparkCallSite - chained (`multiply`
is problematic)
+ with self.assertRaises(NumberFormatException) as pe:
+ df.withColumn("multiply_string", df.id * "string").withColumn(
+ "divide_ten", df.id / 10
+ ).withColumn("plus_ten", df.id + 10).withColumn("minus_ten",
df.id - 10).collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="CAST_INVALID_INPUT",
+ message_parameters={
+ "expression": "'string'",
+ "sourceType": '"STRING"',
+ "targetType": '"BIGINT"',
+ "ansiConfig": '"spark.sql.ansi.enabled"',
+ },
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="multiply",
+ )
+
+ # DataFrameQueryContext without pysparkCallSite
+ with self.assertRaises(AnalysisException) as pe:
+ df.select("non-existing-column")
+ self.check_error(
+ exception=pe.exception,
+ error_class="UNRESOLVED_COLUMN.WITH_SUGGESTION",
+ message_parameters={"objectName": "`non-existing-column`",
"proposal": "`id`"},
+ query_context_type=QueryContextType.DataFrame,
+ pyspark_fragment="",
+ )
+
+ # SQLQueryContext
+ with self.assertRaises(ArithmeticException) as pe:
+ self.spark.sql("select 10/0").collect()
+ self.check_error(
+ exception=pe.exception,
+ error_class="DIVIDE_BY_ZERO",
+ message_parameters={"config": '"spark.sql.ansi.enabled"'},
+ query_context_type=QueryContextType.SQL,
+ )
+
+ # No QueryContext
+ with self.assertRaises(AnalysisException) as pe:
+ self.spark.sql("select * from non-existing-table")
+ self.check_error(
+ exception=pe.exception,
+ error_class="INVALID_IDENTIFIER",
+ message_parameters={"ident": "non-existing-table"},
+ query_context_type=None,
Review Comment:
FYI: `None` is default, so we don't need to specify like this when
`QueryContext` not existing, but I made this test for explicit example.
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