jackylk commented on a change in pull request #4148:
URL: https://github.com/apache/carbondata/pull/4148#discussion_r670181749



##########
File path: 
integration/spark/src/main/scala/org/apache/spark/sql/execution/command/mutation/merge/CarbonMergeDataSetUtil.scala
##########
@@ -0,0 +1,206 @@
+/*
+ * 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.command.mutation.merge
+
+import java.util
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.optimizer.CarbonFilters
+
+import org.apache.carbondata.core.indexstore.PartitionSpec
+import org.apache.carbondata.core.metadata.datatype.DataTypes
+import org.apache.carbondata.core.metadata.schema.table.CarbonTable
+import org.apache.carbondata.core.metadata.schema.table.column.CarbonColumn
+import org.apache.carbondata.core.mutate.FilePathMinMaxVO
+import org.apache.carbondata.core.util.{ByteUtil, CarbonUtil, DataTypeUtil}
+import org.apache.carbondata.core.util.comparator.SerializableComparator
+
+/**
+ * The utility class for Merge operations
+ */
+object CarbonMergeDataSetUtil {
+
+  /**
+   * This method reads the splits and make (blockPath, (min, max)) tuple to to 
min max pruning of
+   * the src dataset
+   *
+   * @param colTosplitsFilePathAndMinMaxMap   CarbonInputSplit whose min max 
cached in driver or
+   *                                          the index server
+   * @param fileMinMaxMapListOfAllJoinColumns collection to hold the filepath 
and min max of all the
+   *                                          join columns involved
+   */
+  def addFilePathAndMinMaxTuples(
+      colTosplitsFilePathAndMinMaxMap: mutable.Map[String, 
util.List[FilePathMinMaxVO]],
+      carbonTable: CarbonTable,
+      joinColumnsToComparatorMap: mutable.LinkedHashMap[CarbonColumn, 
SerializableComparator],
+      fileMinMaxMapListOfAllJoinColumns: 
mutable.ArrayBuffer[(mutable.Map[String, (AnyRef, AnyRef)],
+        CarbonColumn)]): Unit = {
+    joinColumnsToComparatorMap.foreach { case (joinColumn, comparator) =>
+      val fileMinMaxMap: mutable.Map[String, (AnyRef, AnyRef)] =
+        collection.mutable.Map.empty[String, (AnyRef, AnyRef)]
+      val joinDataType = joinColumn.getDataType
+      val isDimension = joinColumn.isDimension
+      val isPrimitiveAndNotDate = DataTypeUtil.isPrimitiveColumn(joinDataType) 
&&
+                                  (joinDataType != DataTypes.DATE)
+      colTosplitsFilePathAndMinMaxMap(joinColumn.getColName).asScala.foreach {
+        filePathMinMiax =>
+          val filePath = filePathMinMiax.getFilePath
+          val minBytes = filePathMinMiax.getMin
+          val maxBytes = filePathMinMiax.getMax
+          val uniqBlockPath = if (carbonTable.isHivePartitionTable) {
+            // While data loading to SI created on Partition table, on
+            // partition directory, '/' will be
+            // replaced with '#', to support multi level partitioning. For 
example, BlockId will be
+            // look like `part1=1#part2=2/xxxxxxxxx`. During query also, 
blockId should be
+            // replaced by '#' in place of '/', to match and prune data on SI 
table.
+            CarbonUtil.getBlockId(carbonTable.getAbsoluteTableIdentifier,
+              filePath,
+              "",
+              true,
+              false,
+              true)
+          } else {
+            filePath.substring(filePath.lastIndexOf("/Part") + 1)
+          }
+          if (isDimension) {
+            if (isPrimitiveAndNotDate) {
+              val minValue = 
DataTypeUtil.getDataBasedOnDataTypeForNoDictionaryColumn(minBytes,
+                joinDataType)
+              val maxValue = 
DataTypeUtil.getDataBasedOnDataTypeForNoDictionaryColumn(maxBytes,
+                joinDataType)
+              // check here if present in map, if it is, compare and update 
min and amx
+              if (fileMinMaxMap.contains(uniqBlockPath)) {
+                val isMinLessThanMin =
+                  comparator.compare(fileMinMaxMap(uniqBlockPath)._1, 
minValue) > 0
+                val isMaxMoreThanMax =
+                  comparator.compare(maxValue, 
fileMinMaxMap(uniqBlockPath)._2) > 0
+                updateMapIfRequiredBasedOnMinMax(fileMinMaxMap,
+                  minValue,
+                  maxValue,
+                  uniqBlockPath,
+                  isMinLessThanMin,
+                  isMaxMoreThanMax)
+              } else {
+                fileMinMaxMap += (uniqBlockPath -> (minValue, maxValue))
+              }
+            } else {
+              if (fileMinMaxMap.contains(uniqBlockPath)) {
+                val isMinLessThanMin = ByteUtil.UnsafeComparer.INSTANCE
+                                         
.compareTo(fileMinMaxMap(uniqBlockPath)._1
+                                           .asInstanceOf[String].getBytes(), 
minBytes) > 0
+                val isMaxMoreThanMax = ByteUtil.UnsafeComparer.INSTANCE
+                                         .compareTo(maxBytes, 
fileMinMaxMap(uniqBlockPath)._2
+                                           .asInstanceOf[String].getBytes()) > 0
+                updateMapIfRequiredBasedOnMinMax(fileMinMaxMap,
+                  new String(minBytes),
+                  new String(maxBytes),
+                  uniqBlockPath,
+                  isMinLessThanMin,
+                  isMaxMoreThanMax)
+              } else {
+                fileMinMaxMap += (uniqBlockPath -> (new String(minBytes), new 
String(maxBytes)))
+              }
+            }
+          } else {
+            val maxValue = DataTypeUtil.getMeasureObjectFromDataType(maxBytes, 
joinDataType)
+            val minValue = DataTypeUtil.getMeasureObjectFromDataType(minBytes, 
joinDataType)
+            if (fileMinMaxMap.contains(uniqBlockPath)) {
+              val isMinLessThanMin =
+                comparator.compare(fileMinMaxMap(uniqBlockPath)._1, minValue) 
> 0
+              val isMaxMoreThanMin =
+                comparator.compare(maxValue, fileMinMaxMap(uniqBlockPath)._2) 
> 0
+              updateMapIfRequiredBasedOnMinMax(fileMinMaxMap,
+                minValue,
+                maxValue,
+                uniqBlockPath,
+                isMinLessThanMin,
+                isMaxMoreThanMin)
+            } else {
+              fileMinMaxMap += (uniqBlockPath -> (minValue, maxValue))
+            }
+          }
+      }
+      fileMinMaxMapListOfAllJoinColumns += ((fileMinMaxMap, joinColumn))
+    }
+  }
+
+  /**
+   * This method updates the min max map of the block if the value is less 
than min or more
+   * than max
+   */
+  private def updateMapIfRequiredBasedOnMinMax(fileMinMaxMap: 
mutable.Map[String, (AnyRef, AnyRef)],
+      minValue: AnyRef,
+      maxValue: AnyRef,
+      uniqBlockPath: String,
+      isMinLessThanMin: Boolean,
+      isMaxMoreThanMin: Boolean): Unit = {
+    (isMinLessThanMin, isMaxMoreThanMin) match {
+      case (true, true) => fileMinMaxMap(uniqBlockPath) = (minValue, maxValue)
+      case (true, false) => fileMinMaxMap(uniqBlockPath) = (minValue,
+        fileMinMaxMap(uniqBlockPath)._2)
+      case (false, true) => fileMinMaxMap(uniqBlockPath) = 
(fileMinMaxMap(uniqBlockPath)._1,
+        maxValue)
+      case _ =>
+    }
+  }
+
+  /**
+   * This method returns the partitions required to scan in the target table 
based on the
+   * partitions present in the src table or dataset
+   */
+  def getPartitionSpecToConsiderForPruning(sparkSession: SparkSession,

Review comment:
       move param to next line, please follow the coding convension




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