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new bbcc438e5b3 [SPARK-43915][SQL] Assign names to the error class
_LEGACY_ERROR_TEMP_[2438-2445]
bbcc438e5b3 is described below
commit bbcc438e5b3aef67bf430b6bb6e4f893d8e66d13
Author: Jiaan Geng <belie...@163.com>
AuthorDate: Wed Jun 21 21:20:01 2023 +0300
[SPARK-43915][SQL] Assign names to the error class
_LEGACY_ERROR_TEMP_[2438-2445]
### What changes were proposed in this pull request?
The pr aims to assign names to the error class
_LEGACY_ERROR_TEMP_[2438-2445].
### Why are the changes needed?
Improve the error framework.
### Does this PR introduce _any_ user-facing change?
'No'.
### How was this patch tested?
Exists test cases updated.
Closes #41553 from beliefer/SPARK-43915.
Authored-by: Jiaan Geng <belie...@163.com>
Signed-off-by: Max Gekk <max.g...@gmail.com>
---
core/src/main/resources/error/error-classes.json | 47 +++++++++-------------
python/pyspark/sql/tests/test_udtf.py | 8 +++-
.../spark/sql/catalyst/analysis/Analyzer.scala | 4 +-
.../sql/catalyst/analysis/CheckAnalysis.scala | 23 +++++------
.../sql/catalyst/analysis/AnalysisSuite.scala | 28 ++++++++-----
.../analyzer-results/group-analytics.sql.out | 2 +-
.../analyzer-results/join-lateral.sql.out | 4 +-
.../udf/udf-group-analytics.sql.out | 2 +-
.../sql-tests/results/group-analytics.sql.out | 2 +-
.../sql-tests/results/join-lateral.sql.out | 4 +-
.../results/udf/udf-group-analytics.sql.out | 2 +-
.../spark/sql/DataFrameSetOperationsSuite.scala | 44 ++++++++++++++------
.../sql/connector/DataSourceV2FunctionSuite.scala | 13 +++++-
.../sql/connector/DeleteFromTableSuiteBase.scala | 15 +------
.../connector/DeltaBasedDeleteFromTableSuite.scala | 20 +++++++++
.../sql/connector/DeltaBasedUpdateTableSuite.scala | 21 ++++++++++
.../connector/GroupBasedDeleteFromTableSuite.scala | 22 +++++++++-
.../sql/connector/GroupBasedUpdateTableSuite.scala | 23 ++++++++++-
.../spark/sql/connector/UpdateTableSuiteBase.scala | 15 +------
19 files changed, 195 insertions(+), 104 deletions(-)
diff --git a/core/src/main/resources/error/error-classes.json
b/core/src/main/resources/error/error-classes.json
index 1d2f25b72f3..264d9b7c3a0 100644
--- a/core/src/main/resources/error/error-classes.json
+++ b/core/src/main/resources/error/error-classes.json
@@ -643,6 +643,11 @@
],
"sqlState" : "23505"
},
+ "DUPLICATED_METRICS_NAME" : {
+ "message" : [
+ "The metric name is not unique: <metricName>. The same name cannot be
used for metrics with different results. However multiple instances of metrics
with with same result and name are allowed (e.g. self-joins)."
+ ]
+ },
"DUPLICATE_CLAUSES" : {
"message" : [
"Found duplicate clauses: <clauseName>. Please, remove one of them."
@@ -1237,6 +1242,11 @@
}
}
},
+ "INVALID_NON_DETERMINISTIC_EXPRESSIONS" : {
+ "message" : [
+ "The operator expects a deterministic expression, but the actual
expression is <sqlExprs>."
+ ]
+ },
"INVALID_NUMERIC_LITERAL_RANGE" : {
"message" : [
"Numeric literal <rawStrippedQualifier> is outside the valid range for
<typeName> with minimum value of <minValue> and maximum value of <maxValue>.
Please adjust the value accordingly."
@@ -1512,6 +1522,11 @@
],
"sqlState" : "42604"
},
+ "INVALID_UDF_IMPLEMENTATION" : {
+ "message" : [
+ "Function <funcName> does not implement ScalarFunction or
AggregateFunction."
+ ]
+ },
"INVALID_URL" : {
"message" : [
"The url is invalid: <url>. If necessary set <ansiConfig> to \"false\"
to bypass this error."
@@ -2458,6 +2473,11 @@
"<property> is a reserved namespace property, <msg>."
]
},
+ "SET_OPERATION_ON_MAP_TYPE" : {
+ "message" : [
+ "Cannot have MAP type columns in DataFrame which calls set
operations (INTERSECT, EXCEPT, etc.), but the type of column <colName> is
<dataType>."
+ ]
+ },
"SET_PROPERTIES_AND_DBPROPERTIES" : {
"message" : [
"set PROPERTIES and DBPROPERTIES at the same time."
@@ -5659,33 +5679,6 @@
"Conflicting attributes: <conflictingAttributes>."
]
},
- "_LEGACY_ERROR_TEMP_2438" : {
- "message" : [
- "Cannot have map type columns in DataFrame which calls set
operations(intersect, except, etc.), but the type of column <colName> is
<dataType>."
- ]
- },
- "_LEGACY_ERROR_TEMP_2439" : {
- "message" : [
- "nondeterministic expressions are only allowed in Project, Filter,
Aggregate or Window, found:",
- "<sqlExprs>",
- "in operator <operator>."
- ]
- },
- "_LEGACY_ERROR_TEMP_2443" : {
- "message" : [
- "Multiple definitions of observed metrics named '<name>': <plan>."
- ]
- },
- "_LEGACY_ERROR_TEMP_2444" : {
- "message" : [
- "Function '<funcName>' does not implement ScalarFunction or
AggregateFunction."
- ]
- },
- "_LEGACY_ERROR_TEMP_2445" : {
- "message" : [
- "grouping() can only be used with GroupingSets/Cube/Rollup."
- ]
- },
"_LEGACY_ERROR_TEMP_2446" : {
"message" : [
"Operation not allowed: <cmd> only works on table with location
provided: <tableIdentWithDB>"
diff --git a/python/pyspark/sql/tests/test_udtf.py
b/python/pyspark/sql/tests/test_udtf.py
index 628f2696b84..ccf271ceec2 100644
--- a/python/pyspark/sql/tests/test_udtf.py
+++ b/python/pyspark/sql/tests/test_udtf.py
@@ -350,7 +350,9 @@ class UDTFTestsMixin(ReusedSQLTestCase):
random_udtf = udtf(RandomUDTF, returnType="x:
int").asNondeterministic()
# TODO(SPARK-43966): support non-deterministic UDTFs
- with self.assertRaisesRegex(AnalysisException, "nondeterministic
expressions"):
+ with self.assertRaisesRegex(
+ AnalysisException, "The operator expects a deterministic
expression"
+ ):
random_udtf(lit(1)).collect()
def test_udtf_with_nondeterministic_input(self):
@@ -362,7 +364,9 @@ class UDTFTestsMixin(ReusedSQLTestCase):
yield a + 1,
# TODO(SPARK-43966): support non-deterministic UDTFs
- with self.assertRaisesRegex(AnalysisException, "nondeterministic
expressions"):
+ with self.assertRaisesRegex(
+ AnalysisException, " The operator expects a deterministic
expression"
+ ):
TestUDTF(rand(0) * 100).collect()
def test_udtf_no_eval(self):
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 3f07f0f5032..8a192a4c132 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -2326,8 +2326,8 @@ class Analyzer(override val catalogManager:
CatalogManager) extends RuleExecutor
processV2AggregateFunction(aggFunc, arguments, u)
case _ =>
failAnalysis(
- errorClass = "_LEGACY_ERROR_TEMP_2444",
- messageParameters = Map("funcName" -> bound.name()))
+ errorClass = "INVALID_UDF_IMPLEMENTATION",
+ messageParameters = Map("funcName" -> toSQLId(bound.name())))
}
}
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
index e47966f1e27..649140e466a 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
@@ -302,7 +302,8 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog with QueryErrorsB
"\nReplacement is unresolved: " + e.replacement)
case g: Grouping =>
- g.failAnalysis(errorClass = "_LEGACY_ERROR_TEMP_2445",
messageParameters = Map.empty)
+ g.failAnalysis(
+ errorClass = "UNSUPPORTED_GROUPING_EXPRESSION",
messageParameters = Map.empty)
case g: GroupingID =>
g.failAnalysis(
errorClass = "UNSUPPORTED_GROUPING_EXPRESSION",
messageParameters = Map.empty)
@@ -721,10 +722,10 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog with QueryErrorsB
case o if mapColumnInSetOperation(o).isDefined =>
val mapCol = mapColumnInSetOperation(o).get
o.failAnalysis(
- errorClass = "_LEGACY_ERROR_TEMP_2438",
+ errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE",
messageParameters = Map(
- "colName" -> mapCol.name,
- "dataType" -> mapCol.dataType.catalogString))
+ "colName" -> toSQLId(mapCol.name),
+ "dataType" -> toSQLType(mapCol.dataType)))
case o if o.expressions.exists(!_.deterministic) &&
!o.isInstanceOf[Project] && !o.isInstanceOf[Filter] &&
@@ -734,10 +735,9 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog with QueryErrorsB
!o.isInstanceOf[LateralJoin] =>
// The rule above is used to check Aggregate operator.
o.failAnalysis(
- errorClass = "_LEGACY_ERROR_TEMP_2439",
- messageParameters = Map(
- "sqlExprs" -> o.expressions.map(_.sql).mkString(","),
- "operator" ->
operator.simpleString(SQLConf.get.maxToStringFields)))
+ errorClass = "INVALID_NON_DETERMINISTIC_EXPRESSIONS",
+ messageParameters = Map("sqlExprs" ->
o.expressions.map(toSQLExpr(_)).mkString(", "))
+ )
case _: UnresolvedHint => throw new IllegalStateException(
"Logical hint operator should be removed during analysis.")
@@ -868,6 +868,7 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog with QueryErrorsB
private def scrubOutIds(string: String): String =
string.replaceAll("#\\d+", "#x")
.replaceAll("operator id = \\d+", "operator id = #x")
+ .replaceAll("rand\\(-?\\d+\\)", "rand(number)")
private def planToString(plan: LogicalPlan): String = {
if (Utils.isTesting) scrubOutIds(plan.toString) else plan.toString
@@ -1056,10 +1057,8 @@ trait CheckAnalysis extends PredicateHelper with
LookupCatalog with QueryErrorsB
// of a CTE that is used multiple times or a self join.
if (!simplifiedMetrics.sameResult(simplifiedOther)) {
failAnalysis(
- errorClass = "_LEGACY_ERROR_TEMP_2443",
- messageParameters = Map(
- "name" -> name,
- "plan" -> plan.toString))
+ errorClass = "DUPLICATED_METRICS_NAME",
+ messageParameters = Map("metricName" -> name))
}
case None =>
metricsMap.put(name, metrics)
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
index 105753ab3d1..1e844e22bec 100644
---
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
+++
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
@@ -821,25 +821,35 @@ class AnalysisSuite extends AnalysisTest with Matchers {
CollectMetrics("evt1", count :: Nil, testRelation) :: Nil))
// Same children, structurally different metrics - fail
- assertAnalysisError(Union(
- CollectMetrics("evt1", count :: Nil, testRelation) ::
- CollectMetrics("evt1", sum :: Nil, testRelation) :: Nil),
- "Multiple definitions of observed metrics" :: "evt1" :: Nil)
+ assertAnalysisErrorClass(
+ Union(
+ CollectMetrics("evt1", count :: Nil, testRelation) ::
+ CollectMetrics("evt1", sum :: Nil, testRelation) :: Nil),
+ expectedErrorClass = "DUPLICATED_METRICS_NAME",
+ expectedMessageParameters = Map("metricName" -> "evt1")
+ )
// Different children, same metrics - fail
val b = $"b".string
val tblB = LocalRelation(b)
- assertAnalysisError(Union(
- CollectMetrics("evt1", count :: Nil, testRelation) ::
- CollectMetrics("evt1", count :: Nil, tblB) :: Nil),
- "Multiple definitions of observed metrics" :: "evt1" :: Nil)
+ assertAnalysisErrorClass(
+ Union(
+ CollectMetrics("evt1", count :: Nil, testRelation) ::
+ CollectMetrics("evt1", count :: Nil, tblB) :: Nil),
+ expectedErrorClass = "DUPLICATED_METRICS_NAME",
+ expectedMessageParameters = Map("metricName" -> "evt1")
+ )
// Subquery different tree - fail
val subquery = Aggregate(Nil, sum :: Nil, CollectMetrics("evt1", count ::
Nil, testRelation))
val query = Project(
b :: ScalarSubquery(subquery, Nil).as("sum") :: Nil,
CollectMetrics("evt1", count :: Nil, tblB))
- assertAnalysisError(query, "Multiple definitions of observed metrics" ::
"evt1" :: Nil)
+ assertAnalysisErrorClass(
+ query,
+ expectedErrorClass = "DUPLICATED_METRICS_NAME",
+ expectedMessageParameters = Map("metricName" -> "evt1")
+ )
// Aggregate with filter predicate - fail
val sumWithFilter = sum.transform {
diff --git
a/sql/core/src/test/resources/sql-tests/analyzer-results/group-analytics.sql.out
b/sql/core/src/test/resources/sql-tests/analyzer-results/group-analytics.sql.out
index 773965d76b9..327caef217a 100644
---
a/sql/core/src/test/resources/sql-tests/analyzer-results/group-analytics.sql.out
+++
b/sql/core/src/test/resources/sql-tests/analyzer-results/group-analytics.sql.out
@@ -332,7 +332,7 @@ SELECT course, year, GROUPING(course) FROM courseSales
GROUP BY course, year
-- !query analysis
org.apache.spark.sql.AnalysisException
{
- "errorClass" : "_LEGACY_ERROR_TEMP_2445",
+ "errorClass" : "UNSUPPORTED_GROUPING_EXPRESSION",
"queryContext" : [ {
"objectType" : "",
"objectName" : "",
diff --git
a/sql/core/src/test/resources/sql-tests/analyzer-results/join-lateral.sql.out
b/sql/core/src/test/resources/sql-tests/analyzer-results/join-lateral.sql.out
index 74c25e11bd9..a9bfbc69cf2 100644
---
a/sql/core/src/test/resources/sql-tests/analyzer-results/join-lateral.sql.out
+++
b/sql/core/src/test/resources/sql-tests/analyzer-results/join-lateral.sql.out
@@ -480,7 +480,7 @@ org.apache.spark.sql.AnalysisException
"errorClass" :
"UNSUPPORTED_SUBQUERY_EXPRESSION_CATEGORY.NON_DETERMINISTIC_LATERAL_SUBQUERIES",
"sqlState" : "0A000",
"messageParameters" : {
- "treeNode" : "LateralJoin lateral-subquery#x [c1#x && c2#x], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project
[(cast((outer(c1#x) + outer(c2#x)) as double) + rand(0)) AS c3#x]\n: +-
OneRowRelation\n+- SubqueryAlias spark_catalog.default.t1\n +- View
(`spark_catalog`.`default`.`t1`, [c1#x,c2#x])\n +- Project [cast(col1#x as
int) AS c1#x, cast(col2#x as int) AS c2#x]\n +- LocalRelation [col1#x,
col2#x]\n"
+ "treeNode" : "LateralJoin lateral-subquery#x [c1#x && c2#x], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project
[(cast((outer(c1#x) + outer(c2#x)) as double) + rand(number)) AS c3#x]\n:
+- OneRowRelation\n+- SubqueryAlias spark_catalog.default.t1\n +- View
(`spark_catalog`.`default`.`t1`, [c1#x,c2#x])\n +- Project [cast(col1#x as
int) AS c1#x, cast(col2#x as int) AS c2#x]\n +- LocalRelation [col1#x,
col2#x]\n"
},
"queryContext" : [ {
"objectType" : "",
@@ -500,7 +500,7 @@ org.apache.spark.sql.AnalysisException
"errorClass" :
"UNSUPPORTED_SUBQUERY_EXPRESSION_CATEGORY.NON_DETERMINISTIC_LATERAL_SUBQUERIES",
"sqlState" : "0A000",
"messageParameters" : {
- "treeNode" : "LateralJoin lateral-subquery#x [], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project [rand(0) AS
rand(0)#x]\n: +- SubqueryAlias spark_catalog.default.t2\n: +-
View (`spark_catalog`.`default`.`t2`, [c1#x,c2#x])\n: +- Project
[cast(col1#x as int) AS c1#x, cast(col2#x as int) AS c2#x]\n:
+- LocalRelation [col1#x, col2#x]\n+- SubqueryAlias spark_catalog.default.t1\n
+- View (`spark_catalog`.`default`. [...]
+ "treeNode" : "LateralJoin lateral-subquery#x [], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project [rand(number) AS
rand(number)#x]\n: +- SubqueryAlias spark_catalog.default.t2\n:
+- View (`spark_catalog`.`default`.`t2`, [c1#x,c2#x])\n: +-
Project [cast(col1#x as int) AS c1#x, cast(col2#x as int) AS c2#x]\n:
+- LocalRelation [col1#x, col2#x]\n+- SubqueryAlias
spark_catalog.default.t1\n +- View (`spark_catalog`. [...]
},
"queryContext" : [ {
"objectType" : "",
diff --git
a/sql/core/src/test/resources/sql-tests/analyzer-results/udf/udf-group-analytics.sql.out
b/sql/core/src/test/resources/sql-tests/analyzer-results/udf/udf-group-analytics.sql.out
index d8ed67d3002..8a9c142bb87 100644
---
a/sql/core/src/test/resources/sql-tests/analyzer-results/udf/udf-group-analytics.sql.out
+++
b/sql/core/src/test/resources/sql-tests/analyzer-results/udf/udf-group-analytics.sql.out
@@ -205,7 +205,7 @@ SELECT course, udf(year), GROUPING(course) FROM courseSales
GROUP BY course, udf
-- !query analysis
org.apache.spark.sql.AnalysisException
{
- "errorClass" : "_LEGACY_ERROR_TEMP_2445",
+ "errorClass" : "UNSUPPORTED_GROUPING_EXPRESSION",
"queryContext" : [ {
"objectType" : "",
"objectName" : "",
diff --git
a/sql/core/src/test/resources/sql-tests/results/group-analytics.sql.out
b/sql/core/src/test/resources/sql-tests/results/group-analytics.sql.out
index accc141d811..d9e1a25b574 100644
--- a/sql/core/src/test/resources/sql-tests/results/group-analytics.sql.out
+++ b/sql/core/src/test/resources/sql-tests/results/group-analytics.sql.out
@@ -466,7 +466,7 @@ struct<>
-- !query output
org.apache.spark.sql.AnalysisException
{
- "errorClass" : "_LEGACY_ERROR_TEMP_2445",
+ "errorClass" : "UNSUPPORTED_GROUPING_EXPRESSION",
"queryContext" : [ {
"objectType" : "",
"objectName" : "",
diff --git a/sql/core/src/test/resources/sql-tests/results/join-lateral.sql.out
b/sql/core/src/test/resources/sql-tests/results/join-lateral.sql.out
index cc7b44ca8e8..ddee595372b 100644
--- a/sql/core/src/test/resources/sql-tests/results/join-lateral.sql.out
+++ b/sql/core/src/test/resources/sql-tests/results/join-lateral.sql.out
@@ -360,7 +360,7 @@ org.apache.spark.sql.AnalysisException
"errorClass" :
"UNSUPPORTED_SUBQUERY_EXPRESSION_CATEGORY.NON_DETERMINISTIC_LATERAL_SUBQUERIES",
"sqlState" : "0A000",
"messageParameters" : {
- "treeNode" : "LateralJoin lateral-subquery#x [c1#x && c2#x], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project
[(cast((outer(c1#x) + outer(c2#x)) as double) + rand(0)) AS c3#x]\n: +-
OneRowRelation\n+- SubqueryAlias spark_catalog.default.t1\n +- View
(`spark_catalog`.`default`.`t1`, [c1#x,c2#x])\n +- Project [cast(col1#x as
int) AS c1#x, cast(col2#x as int) AS c2#x]\n +- LocalRelation [col1#x,
col2#x]\n"
+ "treeNode" : "LateralJoin lateral-subquery#x [c1#x && c2#x], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project
[(cast((outer(c1#x) + outer(c2#x)) as double) + rand(number)) AS c3#x]\n:
+- OneRowRelation\n+- SubqueryAlias spark_catalog.default.t1\n +- View
(`spark_catalog`.`default`.`t1`, [c1#x,c2#x])\n +- Project [cast(col1#x as
int) AS c1#x, cast(col2#x as int) AS c2#x]\n +- LocalRelation [col1#x,
col2#x]\n"
},
"queryContext" : [ {
"objectType" : "",
@@ -382,7 +382,7 @@ org.apache.spark.sql.AnalysisException
"errorClass" :
"UNSUPPORTED_SUBQUERY_EXPRESSION_CATEGORY.NON_DETERMINISTIC_LATERAL_SUBQUERIES",
"sqlState" : "0A000",
"messageParameters" : {
- "treeNode" : "LateralJoin lateral-subquery#x [], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project [rand(0) AS
rand(0)#x]\n: +- SubqueryAlias spark_catalog.default.t2\n: +-
View (`spark_catalog`.`default`.`t2`, [c1#x,c2#x])\n: +- Project
[cast(col1#x as int) AS c1#x, cast(col2#x as int) AS c2#x]\n:
+- LocalRelation [col1#x, col2#x]\n+- SubqueryAlias spark_catalog.default.t1\n
+- View (`spark_catalog`.`default`. [...]
+ "treeNode" : "LateralJoin lateral-subquery#x [], Inner\n: +-
SubqueryAlias __auto_generated_subquery_name\n: +- Project [rand(number) AS
rand(number)#x]\n: +- SubqueryAlias spark_catalog.default.t2\n:
+- View (`spark_catalog`.`default`.`t2`, [c1#x,c2#x])\n: +-
Project [cast(col1#x as int) AS c1#x, cast(col2#x as int) AS c2#x]\n:
+- LocalRelation [col1#x, col2#x]\n+- SubqueryAlias
spark_catalog.default.t1\n +- View (`spark_catalog`. [...]
},
"queryContext" : [ {
"objectType" : "",
diff --git
a/sql/core/src/test/resources/sql-tests/results/udf/udf-group-analytics.sql.out
b/sql/core/src/test/resources/sql-tests/results/udf/udf-group-analytics.sql.out
index 1d1b54fc707..f927bf03663 100644
---
a/sql/core/src/test/resources/sql-tests/results/udf/udf-group-analytics.sql.out
+++
b/sql/core/src/test/resources/sql-tests/results/udf/udf-group-analytics.sql.out
@@ -208,7 +208,7 @@ struct<>
-- !query output
org.apache.spark.sql.AnalysisException
{
- "errorClass" : "_LEGACY_ERROR_TEMP_2445",
+ "errorClass" : "UNSUPPORTED_GROUPING_EXPRESSION",
"queryContext" : [ {
"objectType" : "",
"objectName" : "",
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
index 61724a39dfa..7e04053957b 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
@@ -352,20 +352,40 @@ class DataFrameSetOperationsSuite extends QueryTest with
SharedSparkSession {
test("SPARK-19893: cannot run set operations with map type") {
val df = spark.range(1).select(map(lit("key"), $"id").as("m"))
- val e = intercept[AnalysisException](df.intersect(df))
- assert(e.message.contains(
- "Cannot have map type columns in DataFrame which calls set operations"))
- val e2 = intercept[AnalysisException](df.except(df))
- assert(e2.message.contains(
- "Cannot have map type columns in DataFrame which calls set operations"))
- val e3 = intercept[AnalysisException](df.distinct())
- assert(e3.message.contains(
- "Cannot have map type columns in DataFrame which calls set operations"))
+ checkError(
+ exception = intercept[AnalysisException](df.intersect(df)),
+ errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE",
+ parameters = Map(
+ "colName" -> "`m`",
+ "dataType" -> "\"MAP<STRING, BIGINT>\"")
+ )
+ checkError(
+ exception = intercept[AnalysisException](df.except(df)),
+ errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE",
+ parameters = Map(
+ "colName" -> "`m`",
+ "dataType" -> "\"MAP<STRING, BIGINT>\"")
+ )
+ checkError(
+ exception = intercept[AnalysisException](df.distinct()),
+ errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE",
+ parameters = Map(
+ "colName" -> "`m`",
+ "dataType" -> "\"MAP<STRING, BIGINT>\"")
+ )
withTempView("v") {
df.createOrReplaceTempView("v")
- val e4 = intercept[AnalysisException](sql("SELECT DISTINCT m FROM v"))
- assert(e4.message.contains(
- "Cannot have map type columns in DataFrame which calls set
operations"))
+ checkError(
+ exception = intercept[AnalysisException](sql("SELECT DISTINCT m FROM
v")),
+ errorClass = "UNSUPPORTED_FEATURE.SET_OPERATION_ON_MAP_TYPE",
+ parameters = Map(
+ "colName" -> "`m`",
+ "dataType" -> "\"MAP<STRING, BIGINT>\""),
+ context = ExpectedContext(
+ fragment = "SELECT DISTINCT m FROM v",
+ start = 0,
+ stop = 23)
+ )
}
}
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2FunctionSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2FunctionSuite.scala
index 9a31948889c..eea2eebf849 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2FunctionSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2FunctionSuite.scala
@@ -446,8 +446,17 @@ class DataSourceV2FunctionSuite extends
DatasourceV2SQLBase {
catalog("testcat").asInstanceOf[SupportsNamespaces].createNamespace(Array("ns"),
emptyProps)
addFunction(Identifier.of(Array("ns"), "strlen"), StrLen(BadBoundFunction))
- assert(intercept[AnalysisException](sql("SELECT testcat.ns.strlen('abc')"))
- .getMessage.contains("does not implement ScalarFunction or
AggregateFunction"))
+ checkError(
+ exception = intercept[AnalysisException](
+ sql("SELECT testcat.ns.strlen('abc')")),
+ errorClass = "INVALID_UDF_IMPLEMENTATION",
+ parameters = Map(
+ "funcName" -> "`bad_bound_func`"),
+ context = ExpectedContext(
+ fragment = "testcat.ns.strlen('abc')",
+ start = 7,
+ stop = 30)
+ )
}
test("aggregate function: lookup int average") {
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTableSuiteBase.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTableSuiteBase.scala
index 11e22a744f3..94109681b8e 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTableSuiteBase.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTableSuiteBase.scala
@@ -17,7 +17,7 @@
package org.apache.spark.sql.connector
-import org.apache.spark.sql.{AnalysisException, Row}
+import org.apache.spark.sql.Row
import org.apache.spark.sql.execution.datasources.v2.{DeleteFromTableExec,
ReplaceDataExec, WriteDeltaExec}
abstract class DeleteFromTableSuiteBase extends RowLevelOperationSuiteBase {
@@ -449,19 +449,6 @@ abstract class DeleteFromTableSuiteBase extends
RowLevelOperationSuiteBase {
}
}
- test("delete with nondeterministic conditions") {
- createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
- """{ "pk": 1, "id": 1, "dep": "hr" }
- |{ "pk": 2, "id": 2, "dep": "software" }
- |{ "pk": 3, "id": 3, "dep": "hr" }
- |""".stripMargin)
-
- val e = intercept[AnalysisException] {
- sql(s"DELETE FROM $tableNameAsString WHERE id <= 1 AND rand() > 0.5")
- }
- assert(e.message.contains("nondeterministic expressions are only allowed"))
- }
-
test("delete without condition executed as delete with filters") {
createAndInitTable("pk INT NOT NULL, id INT, dep INT",
"""{ "pk": 1, "id": 1, "dep": 100 }
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedDeleteFromTableSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedDeleteFromTableSuite.scala
index fd7a04ea926..4da85a5ce05 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedDeleteFromTableSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedDeleteFromTableSuite.scala
@@ -27,6 +27,26 @@ class DeltaBasedDeleteFromTableSuite extends
DeleteFromTableSuiteBase {
props
}
+ test("delete with nondeterministic conditions") {
+ createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
+ """{ "pk": 1, "id": 1, "dep": "hr" }
+ |{ "pk": 2, "id": 2, "dep": "software" }
+ |{ "pk": 3, "id": 3, "dep": "hr" }
+ |""".stripMargin)
+
+ checkError(
+ exception = intercept[AnalysisException](
+ sql(s"DELETE FROM $tableNameAsString WHERE id <= 1 AND rand() > 0.5")),
+ errorClass = "INVALID_NON_DETERMINISTIC_EXPRESSIONS",
+ parameters = Map(
+ "sqlExprs" -> "\"((id <= 1) AND (rand() > 0.5))\""),
+ context = ExpectedContext(
+ fragment = "DELETE FROM cat.ns1.test_table WHERE id <= 1 AND rand() >
0.5",
+ start = 0,
+ stop = 60)
+ )
+ }
+
test("nullable row ID attrs") {
createAndInitTable("pk INT, salary INT, dep STRING",
"""{ "pk": 1, "salary": 300, "dep": 'hr' }
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedUpdateTableSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedUpdateTableSuite.scala
index af78b2884f5..73b6ec22a72 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedUpdateTableSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeltaBasedUpdateTableSuite.scala
@@ -53,4 +53,25 @@ class DeltaBasedUpdateTableSuite extends
UpdateTableSuiteBase {
sql(s"SELECT * FROM $tableNameAsString"),
Row(10, 1, "hr") :: Row(2, 2, "software") :: Row(3, 3, "hr") :: Nil)
}
+
+ test("update with nondeterministic conditions") {
+ createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
+ """{ "pk": 1, "id": 1, "dep": "hr" }
+ |{ "pk": 2, "id": 2, "dep": "software" }
+ |{ "pk": 3, "id": 3, "dep": "hr" }
+ |""".stripMargin)
+
+ checkError(
+ exception = intercept[AnalysisException] {
+ sql(s"UPDATE $tableNameAsString SET dep = 'invalid' WHERE id <= 1 AND
rand() > 0.5")
+ },
+ errorClass = "INVALID_NON_DETERMINISTIC_EXPRESSIONS",
+ parameters = Map(
+ "sqlExprs" -> "\"((id <= 1) AND (rand() > 0.5))\""),
+ context = ExpectedContext(
+ fragment = "UPDATE cat.ns1.test_table SET dep = 'invalid' WHERE id <=
1 AND rand() > 0.5",
+ start = 0,
+ stop = 75)
+ )
+ }
}
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedDeleteFromTableSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedDeleteFromTableSuite.scala
index 6c80d46b0ef..0aeab95f58a 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedDeleteFromTableSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedDeleteFromTableSuite.scala
@@ -17,13 +17,33 @@
package org.apache.spark.sql.connector
-import org.apache.spark.sql.Row
+import org.apache.spark.sql.{AnalysisException, Row}
import org.apache.spark.sql.internal.SQLConf
class GroupBasedDeleteFromTableSuite extends DeleteFromTableSuiteBase {
import testImplicits._
+ test("delete with nondeterministic conditions") {
+ createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
+ """{ "pk": 1, "id": 1, "dep": "hr" }
+ |{ "pk": 2, "id": 2, "dep": "software" }
+ |{ "pk": 3, "id": 3, "dep": "hr" }
+ |""".stripMargin)
+
+ checkError(
+ exception = intercept[AnalysisException](
+ sql(s"DELETE FROM $tableNameAsString WHERE id <= 1 AND rand() > 0.5")),
+ errorClass = "INVALID_NON_DETERMINISTIC_EXPRESSIONS",
+ parameters = Map(
+ "sqlExprs" -> "\"((id <= 1) AND (rand() > 0.5))\", \"((id <= 1) AND
(rand() > 0.5))\""),
+ context = ExpectedContext(
+ fragment = "DELETE FROM cat.ns1.test_table WHERE id <= 1 AND rand() >
0.5",
+ start = 0,
+ stop = 60)
+ )
+ }
+
test("delete with IN predicate and runtime group filtering") {
createAndInitTable("id INT, salary INT, dep STRING",
"""{ "id": 1, "salary": 300, "dep": 'hr' }
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedUpdateTableSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedUpdateTableSuite.scala
index e2f73e51de0..3e736421a31 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedUpdateTableSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/GroupBasedUpdateTableSuite.scala
@@ -17,7 +17,7 @@
package org.apache.spark.sql.connector
-import org.apache.spark.sql.Row
+import org.apache.spark.sql.{AnalysisException, Row}
import org.apache.spark.sql.catalyst.expressions.DynamicPruningExpression
import org.apache.spark.sql.execution.{InSubqueryExec, ReusedSubqueryExec}
import org.apache.spark.sql.execution.datasources.v2.BatchScanExec
@@ -110,4 +110,25 @@ class GroupBasedUpdateTableSuite extends
UpdateTableSuiteBase {
}
}
}
+
+ test("update with nondeterministic conditions") {
+ createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
+ """{ "pk": 1, "id": 1, "dep": "hr" }
+ |{ "pk": 2, "id": 2, "dep": "software" }
+ |{ "pk": 3, "id": 3, "dep": "hr" }
+ |""".stripMargin)
+
+ checkError(
+ exception = intercept[AnalysisException] {
+ sql(s"UPDATE $tableNameAsString SET dep = 'invalid' WHERE id <= 1 AND
rand() > 0.5")
+ },
+ errorClass = "INVALID_NON_DETERMINISTIC_EXPRESSIONS",
+ parameters = Map(
+ "sqlExprs" -> "\"((id <= 1) AND (rand() > 0.5))\", \"((id <= 1) AND
(rand() > 0.5))\""),
+ context = ExpectedContext(
+ fragment = "UPDATE cat.ns1.test_table SET dep = 'invalid' WHERE id <=
1 AND rand() > 0.5",
+ start = 0,
+ stop = 75)
+ )
+ }
}
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/UpdateTableSuiteBase.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/UpdateTableSuiteBase.scala
index 346390efa94..b43101c2e02 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/UpdateTableSuiteBase.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/UpdateTableSuiteBase.scala
@@ -18,7 +18,7 @@
package org.apache.spark.sql.connector
import org.apache.spark.SparkException
-import org.apache.spark.sql.{AnalysisException, Row}
+import org.apache.spark.sql.Row
import org.apache.spark.sql.connector.catalog.{Column, ColumnDefaultValue}
import org.apache.spark.sql.connector.expressions.LiteralValue
import org.apache.spark.sql.types.{IntegerType, StringType}
@@ -528,19 +528,6 @@ abstract class UpdateTableSuiteBase extends
RowLevelOperationSuiteBase {
Row(2) :: Nil)
}
- test("update with nondeterministic conditions") {
- createAndInitTable("pk INT NOT NULL, id INT, dep STRING",
- """{ "pk": 1, "id": 1, "dep": "hr" }
- |{ "pk": 2, "id": 2, "dep": "software" }
- |{ "pk": 3, "id": 3, "dep": "hr" }
- |""".stripMargin)
-
- val e = intercept[AnalysisException] {
- sql(s"UPDATE $tableNameAsString SET dep = 'invalid' WHERE id <= 1 AND
rand() > 0.5")
- }
- assert(e.message.contains("nondeterministic expressions are only allowed"))
- }
-
test("update with default values") {
val idDefault = new ColumnDefaultValue("42", LiteralValue(42, IntegerType))
val columns = Array(
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