asfgit closed pull request #23466: [SPARK-26547][SQL] Remove duplicate 
toHiveString from HiveUtils
URL: https://github.com/apache/spark/pull/23466
 
 
   

This is a PR merged from a forked repository.
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the sake of provenance:

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diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala
index 22d3ca958a210..c90b254a6d121 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala
@@ -56,61 +56,70 @@ object HiveResult {
       result.map(_.zip(types).map(toHiveString)).map(_.mkString("\t"))
   }
 
-  /** Formats a datum (based on the given data type) and returns the string 
representation. */
-  private def toHiveString(a: (Any, DataType)): String = {
-    val primitiveTypes = Seq(StringType, IntegerType, LongType, DoubleType, 
FloatType,
-      BooleanType, ByteType, ShortType, DateType, TimestampType, BinaryType)
-    val timeZone = DateTimeUtils.getTimeZone(SQLConf.get.sessionLocalTimeZone)
-
-    def formatDecimal(d: java.math.BigDecimal): String = {
-      if (d.compareTo(java.math.BigDecimal.ZERO) == 0) {
-        java.math.BigDecimal.ZERO.toPlainString
-      } else {
-        d.stripTrailingZeros().toPlainString
-      }
+  private def formatDecimal(d: java.math.BigDecimal): String = {
+    if (d.compareTo(java.math.BigDecimal.ZERO) == 0) {
+      java.math.BigDecimal.ZERO.toPlainString
+    } else {
+      d.stripTrailingZeros().toPlainString // Hive strips trailing zeros
     }
+  }
 
-    /** Hive outputs fields of structs slightly differently than top level 
attributes. */
-    def toHiveStructString(a: (Any, DataType)): String = a match {
-      case (struct: Row, StructType(fields)) =>
-        struct.toSeq.zip(fields).map {
-          case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
-        }.mkString("{", ",", "}")
-      case (seq: Seq[_], ArrayType(typ, _)) =>
-        seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
-      case (map: Map[_, _], MapType(kType, vType, _)) =>
-        map.map {
-          case (key, value) =>
-            toHiveStructString((key, kType)) + ":" + 
toHiveStructString((value, vType))
-        }.toSeq.sorted.mkString("{", ",", "}")
-      case (null, _) => "null"
-      case (s: String, StringType) => "\"" + s + "\""
-      case (decimal, DecimalType()) => decimal.toString
-      case (interval, CalendarIntervalType) => interval.toString
-      case (other, tpe) if primitiveTypes contains tpe => other.toString
-    }
+  private val primitiveTypes = Seq(
+    StringType,
+    IntegerType,
+    LongType,
+    DoubleType,
+    FloatType,
+    BooleanType,
+    ByteType,
+    ShortType,
+    DateType,
+    TimestampType,
+    BinaryType)
 
-    a match {
-      case (struct: Row, StructType(fields)) =>
-        struct.toSeq.zip(fields).map {
-          case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
-        }.mkString("{", ",", "}")
-      case (seq: Seq[_], ArrayType(typ, _)) =>
-        seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
-      case (map: Map[_, _], MapType(kType, vType, _)) =>
-        map.map {
-          case (key, value) =>
-            toHiveStructString((key, kType)) + ":" + 
toHiveStructString((value, vType))
-        }.toSeq.sorted.mkString("{", ",", "}")
-      case (null, _) => "NULL"
-      case (d: Date, DateType) =>
-        DateTimeUtils.dateToString(DateTimeUtils.fromJavaDate(d))
-      case (t: Timestamp, TimestampType) =>
-        DateTimeUtils.timestampToString(DateTimeUtils.fromJavaTimestamp(t), 
timeZone)
-      case (bin: Array[Byte], BinaryType) => new String(bin, 
StandardCharsets.UTF_8)
-      case (decimal: java.math.BigDecimal, DecimalType()) => 
formatDecimal(decimal)
-      case (interval, CalendarIntervalType) => interval.toString
-      case (other, tpe) if primitiveTypes.contains(tpe) => other.toString
-    }
+  /** Hive outputs fields of structs slightly differently than top level 
attributes. */
+  private def toHiveStructString(a: (Any, DataType)): String = a match {
+    case (struct: Row, StructType(fields)) =>
+      struct.toSeq.zip(fields).map {
+        case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
+      }.mkString("{", ",", "}")
+    case (seq: Seq[_], ArrayType(typ, _)) =>
+      seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
+    case (map: Map[_, _], MapType(kType, vType, _)) =>
+      map.map {
+        case (key, value) =>
+          toHiveStructString((key, kType)) + ":" + toHiveStructString((value, 
vType))
+      }.toSeq.sorted.mkString("{", ",", "}")
+    case (null, _) => "null"
+    case (s: String, StringType) => "\"" + s + "\""
+    case (decimal, DecimalType()) => decimal.toString
+    case (interval, CalendarIntervalType) => interval.toString
+    case (other, tpe) if primitiveTypes contains tpe => other.toString
+  }
+
+  /** Formats a datum (based on the given data type) and returns the string 
representation. */
+  def toHiveString(a: (Any, DataType)): String = a match {
+    case (struct: Row, StructType(fields)) =>
+      struct.toSeq.zip(fields).map {
+        case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
+      }.mkString("{", ",", "}")
+    case (seq: Seq[_], ArrayType(typ, _)) =>
+      seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
+    case (map: Map[_, _], MapType(kType, vType, _)) =>
+      map.map {
+        case (key, value) =>
+          toHiveStructString((key, kType)) + ":" + toHiveStructString((value, 
vType))
+      }.toSeq.sorted.mkString("{", ",", "}")
+    case (null, _) => "NULL"
+    case (d: Date, DateType) =>
+      DateTimeUtils.dateToString(DateTimeUtils.fromJavaDate(d))
+    case (t: Timestamp, TimestampType) =>
+      val timeZone = 
DateTimeUtils.getTimeZone(SQLConf.get.sessionLocalTimeZone)
+      DateTimeUtils.timestampToString(DateTimeUtils.fromJavaTimestamp(t), 
timeZone)
+    case (bin: Array[Byte], BinaryType) => new String(bin, 
StandardCharsets.UTF_8)
+    case (decimal: java.math.BigDecimal, DecimalType()) => 
formatDecimal(decimal)
+    case (interval, CalendarIntervalType) => interval.toString
+    case (other, _ : UserDefinedType[_]) => other.toString
+    case (other, tpe) if primitiveTypes.contains(tpe) => other.toString
   }
 }
diff --git 
a/sql/core/src/test/scala/org/apache/spark/sql/execution/HiveResultSuite.scala 
b/sql/core/src/test/scala/org/apache/spark/sql/execution/HiveResultSuite.scala
new file mode 100644
index 0000000000000..4205b3f79a972
--- /dev/null
+++ 
b/sql/core/src/test/scala/org/apache/spark/sql/execution/HiveResultSuite.scala
@@ -0,0 +1,30 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.test.{ExamplePoint, ExamplePointUDT}
+
+class HiveResultSuite extends SparkFunSuite {
+
+  test("toHiveString correctly handles UDTs") {
+    val point = new ExamplePoint(50.0, 50.0)
+    val tpe = new ExamplePointUDT()
+    assert(HiveResult.toHiveString((point, tpe)) === "(50.0, 50.0)")
+  }
+}
diff --git 
a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
 
b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
index 3cfc81b8a9579..e68c6011c1393 100644
--- 
a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
+++ 
b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
@@ -34,8 +34,8 @@ import org.apache.hive.service.cli.session.HiveSession
 
 import org.apache.spark.internal.Logging
 import org.apache.spark.sql.{DataFrame, Row => SparkRow, SQLContext}
+import org.apache.spark.sql.execution.HiveResult
 import org.apache.spark.sql.execution.command.SetCommand
-import org.apache.spark.sql.hive.HiveUtils
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types._
 import org.apache.spark.util.{Utils => SparkUtils}
@@ -103,7 +103,7 @@ private[hive] class SparkExecuteStatementOperation(
       case BinaryType =>
         to += from.getAs[Array[Byte]](ordinal)
       case _: ArrayType | _: StructType | _: MapType | _: UserDefinedType[_] =>
-        val hiveString = HiveUtils.toHiveString((from.get(ordinal), 
dataTypes(ordinal)))
+        val hiveString = HiveResult.toHiveString((from.get(ordinal), 
dataTypes(ordinal)))
         to += hiveString
     }
   }
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveUtils.scala 
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveUtils.scala
index b60d4c71f5941..597eef129f63e 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveUtils.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveUtils.scala
@@ -444,52 +444,6 @@ private[spark] object HiveUtils extends Logging {
     propMap.toMap
   }
 
-  protected val primitiveTypes =
-    Seq(StringType, IntegerType, LongType, DoubleType, FloatType, BooleanType, 
ByteType,
-      ShortType, DateType, TimestampType, BinaryType)
-
-  protected[sql] def toHiveString(a: (Any, DataType)): String = a match {
-    case (struct: Row, StructType(fields)) =>
-      struct.toSeq.zip(fields).map {
-        case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
-      }.mkString("{", ",", "}")
-    case (seq: Seq[_], ArrayType(typ, _)) =>
-      seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
-    case (map: Map[_, _], MapType(kType, vType, _)) =>
-      map.map {
-        case (key, value) =>
-          toHiveStructString((key, kType)) + ":" + toHiveStructString((value, 
vType))
-      }.toSeq.sorted.mkString("{", ",", "}")
-    case (null, _) => "NULL"
-    case (d: Int, DateType) => new DateWritable(d).toString
-    case (t: Timestamp, TimestampType) => new TimestampWritable(t).toString
-    case (bin: Array[Byte], BinaryType) => new String(bin, 
StandardCharsets.UTF_8)
-    case (decimal: java.math.BigDecimal, DecimalType()) =>
-      // Hive strips trailing zeros so use its toString
-      HiveDecimal.create(decimal).toString
-    case (other, _ : UserDefinedType[_]) => other.toString
-    case (other, tpe) if primitiveTypes contains tpe => other.toString
-  }
-
-  /** Hive outputs fields of structs slightly differently than top level 
attributes. */
-  protected def toHiveStructString(a: (Any, DataType)): String = a match {
-    case (struct: Row, StructType(fields)) =>
-      struct.toSeq.zip(fields).map {
-        case (v, t) => s""""${t.name}":${toHiveStructString((v, 
t.dataType))}"""
-      }.mkString("{", ",", "}")
-    case (seq: Seq[_], ArrayType(typ, _)) =>
-      seq.map(v => (v, typ)).map(toHiveStructString).mkString("[", ",", "]")
-    case (map: Map[_, _], MapType(kType, vType, _)) =>
-      map.map {
-        case (key, value) =>
-          toHiveStructString((key, kType)) + ":" + toHiveStructString((value, 
vType))
-      }.toSeq.sorted.mkString("{", ",", "}")
-    case (null, _) => "null"
-    case (s: String, StringType) => "\"" + s + "\""
-    case (decimal, DecimalType()) => decimal.toString
-    case (other, tpe) if primitiveTypes contains tpe => other.toString
-  }
-
   /**
    * Infers the schema for Hive serde tables and returns the CatalogTable with 
the inferred schema.
    * When the tables are data source tables or the schema already exists, 
returns the original
diff --git 
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUtilsSuite.scala 
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUtilsSuite.scala
index f2b75e4b23f02..303dd70760a1b 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUtilsSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUtilsSuite.scala
@@ -17,16 +17,15 @@
 
 package org.apache.spark.sql.hive
 
-import java.net.URL
-
 import org.apache.hadoop.hive.conf.HiveConf.ConfVars
 
 import org.apache.spark.SparkConf
 import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.sql.QueryTest
+import org.apache.spark.sql.execution.HiveResult
 import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.test.{ExamplePoint, ExamplePointUDT, SQLTestUtils}
-import org.apache.spark.util.{ChildFirstURLClassLoader, MutableURLClassLoader}
+import org.apache.spark.util.ChildFirstURLClassLoader
 
 class HiveUtilsSuite extends QueryTest with SQLTestUtils with 
TestHiveSingleton {
 
@@ -62,10 +61,4 @@ class HiveUtilsSuite extends QueryTest with SQLTestUtils 
with TestHiveSingleton
       Thread.currentThread().setContextClassLoader(contextClassLoader)
     }
   }
-
-  test("toHiveString correctly handles UDTs") {
-    val point = new ExamplePoint(50.0, 50.0)
-    val tpe = new ExamplePointUDT()
-    assert(HiveUtils.toHiveString((point, tpe)) === "(50.0, 50.0)")
-  }
 }


 

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