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[SPARK-32243][SQL]HiveSessionCatalog call super.makeFunctionExpression should throw earlier when got Spark UDAF Invalid arguments number error #29054

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[SPARK-32243][SQL]HiveSessionCatalog call super.makeFunctionExpression should throw earlier when got Spark UDAF Invalid arguments number error #29054

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AngersZhuuuu Jul 10, 2020
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Update HiveUDAFSuite.scala
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Update HiveSessionCatalog.scala
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Update HiveUDAFSuite.scala
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Update HiveSessionCatalog.scala
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Update HiveUDAFSuite.scala
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92 changes: 50 additions & 42 deletions sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveSessionCatalog.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -69,49 +69,57 @@ private[sql] class HiveSessionCatalog(
// Current thread context classloader may not be the one loaded the class. Need to switch
// context classloader to initialize instance properly.
Utils.withContextClassLoader(clazz.getClassLoader) {
Try(super.makeFunctionExpression(name, clazz, input)).getOrElse {

@HyukjinKwon HyukjinKwon Aug 19, 2020

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@AngersZhuuuu, can you get rid of this unrelated diffs?

@AngersZhuuuu AngersZhuuuu Aug 21, 2020 •
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@AngersZhuuuu, can you get rid of this unrelated diffs?

How about current change, it won't change indentation. cc @maropu

var udfExpr: Option[Expression] = None
try {
// When we instantiate hive UDF wrapper class, we may throw exception if the input
// expressions don't satisfy the hive UDF, such as type mismatch, input number
// mismatch, etc. Here we catch the exception and throw AnalysisException instead.
if (classOf[UDF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveSimpleUDF(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[GenericUDF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveGenericUDF(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[AbstractGenericUDAFResolver].isAssignableFrom(clazz)) {
udfExpr = Some(HiveUDAFFunction(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[UDAF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveUDAFFunction(
name,
new HiveFunctionWrapper(clazz.getName),
input,
isUDAFBridgeRequired = true))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveGenericUDTF(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.asInstanceOf[HiveGenericUDTF].elementSchema // Force it to check data types.
try {
super.makeFunctionExpression(name, clazz, input)
} catch {
case NonFatal(exception) =>
val superError =
s"Make Expression failed in SessionCatalog for function name = ${name}:" +
s" ${exception.getMessage}"
var udfExpr: Option[Expression] = None

@cloud-fan cloud-fan Sep 29, 2020

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We can move the code below to a new method.

@AngersZhuuuu AngersZhuuuu Sep 29, 2020

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We can move the code below to a new method.

Done

try {
// When we instantiate hive UDF wrapper class, we may throw exception if the input
// expressions don't satisfy the hive UDF, such as type mismatch, input number
// mismatch, etc. Here we catch the exception and throw AnalysisException instead.
if (classOf[UDF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveSimpleUDF(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[GenericUDF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveGenericUDF(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[AbstractGenericUDAFResolver].isAssignableFrom(clazz)) {
udfExpr = Some(HiveUDAFFunction(name, new HiveFunctionWrapper(clazz.getName), input))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[UDAF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveUDAFFunction(
name,
new HiveFunctionWrapper(clazz.getName),
input,
isUDAFBridgeRequired = true))
udfExpr.get.dataType // Force it to check input data types.
} else if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
udfExpr = Some(HiveGenericUDTF(name, new HiveFunctionWrapper(clazz.getName), input))
// Force it to check data types.
udfExpr.get.asInstanceOf[HiveGenericUDTF].elementSchema
}
} catch {
case NonFatal(e) =>
val noHandlerMsg = s"No handler for UDF/UDAF/UDTF '${clazz.getCanonicalName}': $e"
val errorMsg =
if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
s"$noHandlerMsg\nPlease make sure your function overrides " +
"`public StructObjectInspector initialize(ObjectInspector[] args)`."
} else {
noHandlerMsg
}
val analysisException = new AnalysisException(s"1. $superError\n2. $errorMsg")
analysisException.setStackTrace(e.getStackTrace)
throw analysisException
}
udfExpr.getOrElse {
throw new AnalysisException(
s"1. $superError\n2. No handler for UDF/UDAF/UDTF '${clazz.getCanonicalName}'")
}
} catch {
case NonFatal(e) =>
val noHandlerMsg = s"No handler for UDF/UDAF/UDTF '${clazz.getCanonicalName}': $e"
val errorMsg =
if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
s"$noHandlerMsg\nPlease make sure your function overrides " +
"`public StructObjectInspector initialize(ObjectInspector[] args)`."
} else {
noHandlerMsg
}
val analysisException = new AnalysisException(errorMsg)
analysisException.setStackTrace(e.getStackTrace)
throw analysisException
}
udfExpr.getOrElse {
throw new AnalysisException(s"No handler for UDF/UDAF/UDTF '${clazz.getCanonicalName}'")
}
}
}
}
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15 changes: 15 additions & 0 deletions sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDAFSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -161,6 +161,21 @@ class HiveUDAFSuite extends QueryTest
checkAnswer(sql("select histogram_numeric(a,2) from abc where a=3"), Row(null))
}
}

test("Hive mode use spark udaf should show error") {

@HyukjinKwon HyukjinKwon Jul 10, 2020

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Let's add a JIRA prefix.

@AngersZhuuuu AngersZhuuuu Jul 10, 2020

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Let's add a JIRA prefix.

Done

val functionName = "longProductSum"
val functionClass = "org.apache.spark.sql.hive.execution.LongProductSum"
withUserDefinedFunction(functionName -> true) {
sql(s"CREATE TEMPORARY FUNCTION $functionName AS '$functionClass'")
val e = intercept[AnalysisException] {
sql(s"SELECT $functionName(100)")
}.getMessage
assert(
Seq(s"Invalid number of arguments for function $functionName. Expected: 2; Found: 1;",
"No handler for UDF/UDAF/UDTF 'org.apache.spark.sql.hive.execution.LongProductSum';")
.forall(e.contains))
}
}
}

/**
Expand Down