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Subject [GitHub] [carbondata] ravipesala commented on a change in pull request #3483: [CARBONDATA-3597] Support Merge for SCD and CCD scenarios
Date Mon, 30 Dec 2019 04:34:08 GMT
ravipesala commented on a change in pull request #3483: [CARBONDATA-3597] Support Merge for
SCD and CCD scenarios
URL: https://github.com/apache/carbondata/pull/3483#discussion_r361897551
 
 

 ##########
 File path: integration/spark2/src/main/scala/org/apache/spark/sql/execution/command/mutation/merge/CarbonMergeDataSetCommand.scala
 ##########
 @@ -0,0 +1,520 @@
+/*
+ * 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.UUID
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.hadoop.io.NullWritable
+import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType}
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+import org.apache.spark.sql.{AnalysisException, CarbonDatasourceHadoopRelation, Column, DataFrame,
Dataset, Row, SparkSession}
+import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, GenericRowWithSchema}
+import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
+import org.apache.spark.sql.execution.command.{DataCommand, ExecutionErrors}
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.hive.DistributionUtil
+import org.apache.spark.sql.types.{IntegerType, StringType, StructField}
+import org.apache.spark.sql.util.SparkSQLUtil
+import org.apache.spark.util.{AccumulatorContext, AccumulatorMetadata, LongAccumulator}
+
+import org.apache.carbondata.common.logging.LogServiceFactory
+import org.apache.carbondata.core.constants.CarbonCommonConstants
+import org.apache.carbondata.core.datamap.Segment
+import org.apache.carbondata.core.metadata.SegmentFileStore
+import org.apache.carbondata.core.metadata.schema.table.CarbonTable
+import org.apache.carbondata.core.mutate.CarbonUpdateUtil
+import org.apache.carbondata.core.statusmanager.{LoadMetadataDetails, SegmentStatus}
+import org.apache.carbondata.core.util.path.CarbonTablePath
+import org.apache.carbondata.hadoop.api.CarbonTableOutputFormat
+import org.apache.carbondata.hadoop.internal.ObjectArrayWritable
+import org.apache.carbondata.processing.loading.FailureCauses
+import org.apache.carbondata.processing.loading.model.{CarbonLoadModel, CarbonLoadModelBuilder}
+import org.apache.carbondata.processing.util.CarbonLoaderUtil
+
+/**
+ * This command will merge the data of source dataset to target dataset backed by carbon
table.
+ * @param targetDsOri Target dataset to merge the data. This dataset should be backed by
carbontable
+ * @param srcDS  Source dataset, it can be any data.
+ * @param mergeMatches It contains the join condition and list match conditions to apply.
+ */
+case class CarbonMergeDataSetCommand(targetDsOri: Dataset[Row],
+    srcDS: Dataset[Row],
+    var mergeMatches: MergeDataSetMatches)
+  extends DataCommand {
+
+  val LOGGER = LogServiceFactory.getLogService(this.getClass.getName)
+
+  override def processData(sparkSession: SparkSession): Seq[Row] = {
+    val rltn = collectCarbonRelation(targetDsOri.logicalPlan)
+    // Target dataset must be backed by carbondata table.
+    if (rltn.length != 1) {
+      throw new UnsupportedOperationException(
+        "Carbon table supposed to be present in merge dataset")
+    }
+    // validate the merge matches and actions.
+    validateMergeActions(mergeMatches, targetDsOri, sparkSession)
+    val carbonTable = rltn.head.carbonRelation.carbonTable
+    val hasDelAction = mergeMatches.matchList
+      .exists(_.getActions.exists(_.isInstanceOf[DeleteAction]))
+    val hasUpdateAction = mergeMatches.matchList
+      .exists(_.getActions.exists(_.isInstanceOf[UpdateAction]))
+    val (insertHistOfUpdate, insertHistOfDelete) = getInsertHistoryStatus(mergeMatches)
+    // Get all the required columns of targetDS by going through all match conditions and
actions.
+    val columns = getSelectExpressionsOnExistingDF(targetDsOri, mergeMatches, sparkSession)
+    // select only the required columns, it can avoid lot of and shuffling.
+    val targetDs = targetDsOri.select(columns: _*)
+    // Update the update mapping with unfilled columns.From here on system assumes all mappings
+    // are existed.
+    mergeMatches = updateMappingIfNotExists(mergeMatches, targetDs)
+    // Lets generate all conditions combinations as one column and add them as 'status'.
+    val condition = generateStatusColumnWithAllCombinations(mergeMatches)
+
+    // Add the tupleid udf to get the tupleid to generate delete delta.
+    val frame = targetDs.withColumn(CarbonCommonConstants.CARBON_IMPLICIT_COLUMN_TUPLEID,
+      expr("getTupleId()")).withColumn("exist_on_target", lit(1)).join(
+      srcDS.withColumn("exist_on_src", lit(1)),
+      // Do the full outer join to get the data from both sides without missing anything.
+      // TODO As per the match conditions choose the join, sometimes it might be possible
to use
+      // left_outer join.
+      mergeMatches.joinExpr, "full_outer").withColumn("status", condition)
+    if (LOGGER.isDebugEnabled) {
+      frame.explain()
+    }
+    val tableCols =
+      carbonTable.getTableInfo.getFactTable.getListOfColumns.asScala.map(_.getColumnName).
+        filterNot(_.equalsIgnoreCase(CarbonCommonConstants.DEFAULT_INVISIBLE_DUMMY_MEASURE))
+    val builder = new CarbonLoadModelBuilder(carbonTable)
+    val options = Seq(("fileheader", tableCols.mkString(","))).toMap
+    val model = builder.build(options.asJava, CarbonUpdateUtil.readCurrentTime, "1")
+    model.setLoadWithoutConverterStep(true)
+    val newLoadMetaEntry = new LoadMetadataDetails
+    CarbonLoaderUtil.populateNewLoadMetaEntry(newLoadMetaEntry,
+      SegmentStatus.INSERT_IN_PROGRESS,
+      model.getFactTimeStamp,
+      false)
+    CarbonLoaderUtil.recordNewLoadMetadata(newLoadMetaEntry, model, true, false)
+
+    model.setCsvHeader(tableCols.mkString(","))
+
+    val projections: Seq[Seq[MergeProjection]] = mergeMatches.matchList.map { m =>
+      m.getActions.map {
+        case u: UpdateAction => MergeProjection(tableCols, frame, rltn.head, sparkSession,
u)
+        case i: InsertAction => MergeProjection(tableCols, frame, rltn.head, sparkSession,
i)
+        case d: DeleteAction => MergeProjection(tableCols, frame, rltn.head, sparkSession,
d)
+        case _ => null
+      }.filter(_ != null)
+    }
+
+    val st = System.currentTimeMillis()
+    // Create accumulators to log the stats
+    val stats = Stats(createLongAccumalator("insertedRows"),
+      createLongAccumalator("updatedRows"),
+      createLongAccumalator("deletedRows"))
+    val processedRDD = processIUD(sparkSession, frame, carbonTable, model, projections, stats)
+
+    val executorErrors = ExecutionErrors(FailureCauses.NONE, "")
+    val trxMgr = TranxManager(model.getFactTimeStamp)
+
+    val mutationAction = MutationActionFactory.getMutationAction(sparkSession,
+      carbonTable, hasDelAction, hasUpdateAction,
+      insertHistOfUpdate, insertHistOfDelete)
+
+    val tuple = mutationAction.handleAction(processedRDD, executorErrors, trxMgr)
+
+    // In case user only has insert action.
+    if (!(hasDelAction || hasUpdateAction)) {
+      processedRDD.count()
+    }
+    LOGGER.info(s"Total inserted rows: ${stats.insertedRows.sum}")
+    LOGGER.info(s"Total updated rows: ${stats.updatedRows.sum}")
+    LOGGER.info(s"Total deleted rows: ${stats.deletedRows.sum}")
+    LOGGER.info(
+      " Time taken to merge data  : " + tuple + " :: " + (System.currentTimeMillis() - st))
+
+    val segment = new Segment(model.getSegmentId,
+      SegmentFileStore.genSegmentFileName(
+        model.getSegmentId,
+        System.nanoTime().toString) + CarbonTablePath.SEGMENT_EXT,
+      CarbonTablePath.getSegmentPath(carbonTable.getTablePath,
+        model.getSegmentId), Map.empty[String, String].asJava)
+    val writeSegment =
+      SegmentFileStore.writeSegmentFile(carbonTable, segment)
+
+    if (writeSegment) {
+      SegmentFileStore.updateTableStatusFile(
+        carbonTable,
+        model.getSegmentId,
+        segment.getSegmentFileName,
+        carbonTable.getCarbonTableIdentifier.getTableId,
+        new SegmentFileStore(carbonTable.getTablePath, segment.getSegmentFileName),
+        SegmentStatus.SUCCESS)
+    } else {
+      CarbonLoaderUtil.updateTableStatusForFailure(model)
+    }
+
+    if (hasDelAction || hasUpdateAction) {
+      if (CarbonUpdateUtil.updateSegmentStatus(tuple._1, carbonTable,
+        trxMgr.getLatestTrx.toString, false) &&
+          CarbonUpdateUtil
+            .updateTableMetadataStatus(
+              model.getLoadMetadataDetails.asScala.map(l =>
+                new Segment(l.getMergedLoadName,
+                  l.getSegmentFile)).toSet.asJava,
+              carbonTable,
+              trxMgr.getLatestTrx.toString,
+              true,
+              tuple._2.asJava)) {
+        LOGGER.info(s"Merge data operation is successful for " +
+                    s"${ carbonTable.getDatabaseName }.${ carbonTable.getTableName }")
+      } else {
+        throw new CarbonMergeDataSetException("Saving update status or table status failed")
+      }
+    }
+    // Load the history table if the inserthistorytable action is added by user.
+    HistoryTableLoadHelper.loadHistoryTable(sparkSession, rltn.head, carbonTable,
+      trxMgr, mutationAction, mergeMatches)
+    Seq.empty
+  }
+
+  private def processIUD(sparkSession: SparkSession,
+      frame: DataFrame,
+      carbonTable: CarbonTable,
+      model: CarbonLoadModel,
+      projections: Seq[Seq[MergeProjection]],
+      stats: Stats) = {
+    val conf = SparkSQLUtil.sessionState(sparkSession).newHadoopConf()
 
 Review comment:
   ok

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