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[SPARK-12558][SQL][WIP] AnalysisException when multiple functions applied in GROUP BY clause #10520

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[SPARK-12558][SQL][WIP] AnalysisException when multiple functions applied in GROUP BY clause #10520

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[SPARK-12558] AnalysisException when multiple functions applied in GR…
dilipbiswal Dec 30, 2015
de81c21
review comments
dilipbiswal Dec 30, 2015
7dae8e1
override equals
dilipbiswal Jan 5, 2016
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Yin's comment
dilipbiswal Jan 10, 2016
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Yin's comments
dilipbiswal Jan 12, 2016
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style fix
dilipbiswal Jan 12, 2016
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23 changes: 23 additions & 0 deletions sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -26,11 +26,13 @@ import scala.reflect.ClassTag

import com.esotericsoftware.kryo.Kryo
import com.esotericsoftware.kryo.io.{Input, Output}
import com.google.common.base.Objects
import org.apache.avro.Schema
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path
import org.apache.hadoop.hive.ql.exec.{UDF, Utilities}
import org.apache.hadoop.hive.ql.plan.{FileSinkDesc, TableDesc}
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFMacro
import org.apache.hadoop.hive.serde2.ColumnProjectionUtils
import org.apache.hadoop.hive.serde2.avro.{AvroGenericRecordWritable, AvroSerdeUtils}
import org.apache.hadoop.hive.serde2.objectinspector.primitive.HiveDecimalObjectInspector
Expand All @@ -45,6 +47,7 @@ private[hive] object HiveShim {
// scale Hive 0.13 infers for BigDecimals from sources that don't specify them (e.g. UDFs)
val UNLIMITED_DECIMAL_PRECISION = 38
val UNLIMITED_DECIMAL_SCALE = 18
val HIVE_GENERIC_UDF_MACRO_CLS = "org.apache.hadoop.hive.ql.udf.generic.GenericUDFMacro"

/*
* This function in hive-0.13 become private, but we have to do this to walkaround hive bug
Expand Down Expand Up @@ -123,6 +126,26 @@ private[hive] object HiveShim {
// for Serialization
def this() = this(null)

override def hashCode(): Int = {
if (functionClassName == HIVE_GENERIC_UDF_MACRO_CLS) {
Objects.hashCode(functionClassName, instance.asInstanceOf[GenericUDFMacro].getBody())
} else {
functionClassName.hashCode()
}
}

override def equals(other: Any): Boolean = other match {
case a: HiveFunctionWrapper if functionClassName == a.functionClassName =>
// In case of udf macro, check to make sure they point to the same underlying UDF
if (functionClassName == HIVE_GENERIC_UDF_MACRO_CLS) {
a.instance.asInstanceOf[GenericUDFMacro].getBody() ==
instance.asInstanceOf[GenericUDFMacro].getBody()
} else {
true
}
case _ => false
}

@transient
def deserializeObjectByKryo[T: ClassTag](
kryo: Kryo,
Expand Down
7 changes: 7 additions & 0 deletions sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala
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Expand Up @@ -350,6 +350,13 @@ class HiveUDFSuite extends QueryTest with TestHiveSingleton with SQLTestUtils {
sqlContext.dropTempTable("testUDF")
}

test("Hive UDF in group by") {
Seq(Tuple1(1451400761)).toDF("test_date").registerTempTable("tab1")
val count = sql("select date(cast(test_date as timestamp))" +
" from tab1 group by date(cast(test_date as timestamp))").count()
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Actually it will be good to use withTempTable, which will automatically drop the temp table. Also, it will be more robust if we create a temp function based on hive's org.apache.hadoop.hive.ql.udf.generic.GenericUDFToDate. So, even if we later have a native function called date, we can still test the hive udf. We can do the test change in a follow-up pr (the pr can re-use the jira number).

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I just realize it after I merge the PR. Let's have a pr to improve the test. Thanks!

assert(count == 1)
}

test("SPARK-11522 select input_file_name from non-parquet table"){

withTempDir { tempDir =>
Expand Down