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[GitHub] [carbondata] ajantha-bhat opened a new pull request #3538: [WIP] Separate Insert and load to later optimize insert.

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

GitBox

[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376351144

##########
File path: integration/spark2/src/main/scala/org/apache/spark/sql/execution/command/management/CarbonInsertIntoCommand.scala
##########
@@ -17,85 +17,518 @@

package org.apache.spark.sql.execution.command.management

-import org.apache.spark.sql.{CarbonDatasourceHadoopRelation, Dataset, Row, SparkSession}
-import org.apache.spark.sql.catalyst.plans.logical.{GlobalLimit, LogicalPlan}
-import org.apache.spark.sql.execution.command.{AtomicRunnableCommand, DataCommand}
-import org.apache.spark.storage.StorageLevel
-
-import org.apache.carbondata.common.logging.{LogService, LogServiceFactory}
-import org.apache.carbondata.core.constants.CarbonCommonConstants
-import org.apache.carbondata.core.util.{CarbonProperties, ThreadLocalSessionInfo}
-
-case class CarbonInsertIntoCommand(
- relation: CarbonDatasourceHadoopRelation,
- child: LogicalPlan,
- overwrite: Boolean,
- partition: Map[String, Option[String]])
+import java.text.SimpleDateFormat
+import java.util
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{AnalysisException, CarbonEnv, DataFrame, Dataset, Row, SparkSession}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.catalog.HiveTableRelation
+import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeReference, Literal, NamedExpression}
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project}
+import org.apache.spark.sql.execution.command.{AtomicRunnableCommand, DataLoadTableFileMapping}
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.types.{StructField, StructType}
+import org.apache.spark.util.CausedBy
+
+import org.apache.carbondata.common.logging.LogServiceFactory
+import org.apache.carbondata.converter.SparkDataTypeConverterImpl
+import org.apache.carbondata.core.datastore.impl.FileFactory
+import org.apache.carbondata.core.indexstore.PartitionSpec
+import org.apache.carbondata.core.metadata.schema.SchemaEvolutionEntry
+import org.apache.carbondata.core.metadata.schema.table.{CarbonTable, TableInfo, TableSchema}
+import org.apache.carbondata.core.metadata.schema.table.column.ColumnSchema
+import org.apache.carbondata.core.statusmanager.{LoadMetadataDetails, SegmentStatus, SegmentStatusManager}
+import org.apache.carbondata.core.util.{CarbonProperties, DataTypeUtil, ThreadLocalSessionInfo}
+import org.apache.carbondata.core.util.path.CarbonTablePath
+import org.apache.carbondata.events.exception.PreEventException
+import org.apache.carbondata.events.OperationContext
+import org.apache.carbondata.processing.loading.TableProcessingOperations
+import org.apache.carbondata.processing.loading.exception.NoRetryException
+import org.apache.carbondata.processing.loading.model.CarbonLoadModel
+import org.apache.carbondata.processing.util.CarbonLoaderUtil
+import org.apache.carbondata.spark.rdd.CarbonDataRDDFactory
+import org.apache.carbondata.spark.util.CarbonScalaUtil
+
+/*
+* insert into without df, by just using logical plan
+*
+*/
+case class CarbonInsertIntoCommand(databaseNameOp: Option[String],
+ tableName: String,
+ options: Map[String, String],
+ isOverwriteTable: Boolean,
+ var logicalPlan: LogicalPlan,
+ var dimFilesPath: Seq[DataLoadTableFileMapping] = Seq(),
+ var inputSqlString: String = null,
+ var tableInfoOp: Option[TableInfo] = None,
+ var internalOptions: Map[String, String] = Map.empty,
+ var partition: Map[String, Option[String]] = Map.empty,
+ var operationContext: OperationContext = new OperationContext)
extends AtomicRunnableCommand {

- var loadCommand: CarbonLoadDataCommand = _
+ var table: CarbonTable = _
+
+ var logicalPartitionRelation: LogicalRelation = _
+
+ var sizeInBytes: Long = _
+
+ var currPartitions: util.List[PartitionSpec] = _
+
+ var parentTablePath: String = _
+
+ val LOGGER = LogServiceFactory.getLogService(this.getClass.getName)
+
+ var scanResultRdd: RDD[InternalRow] = _
+
+ var timeStampFormat: SimpleDateFormat = _
+
+ var dateFormat: SimpleDateFormat = _
+
+ var finalPartition: Map[String, Option[String]] = Map.empty
+
+ var isInsertIntoWithConverterFlow: Boolean = false
+
+ var dataFrame: DataFrame = _

override def processMetadata(sparkSession: SparkSession): Seq[Row] = {
- setAuditTable(relation.carbonTable.getDatabaseName, relation.carbonTable.getTableName)
- val LOGGER = LogServiceFactory.getLogService(this.getClass.getName)
- def containsLimit(plan: LogicalPlan): Boolean = {
- plan find {
- case limit: GlobalLimit => true
- case other => false
- } isDefined
+ if (!tableInfoOp.isDefined) {
+ throw new RuntimeException(" table info must be present when logical relation exist")
}
-
+ // If logical plan is unresolved, need to convert it to resolved.
+ dataFrame = Dataset.ofRows(sparkSession, logicalPlan)
+ logicalPlan = dataFrame.queryExecution.analyzed
+ var isInsertFromTable = false
+ logicalPlan.collect {
+ case _: LogicalRelation =>
+ isInsertFromTable = true
+ }
+ // Currently projection re-ordering is based on schema ordinal,
+ // for some scenarios in alter table scenario, schema ordinal logic cannot be applied.
+ // So, sending it to old flow
+ // TODO: Handle this in future, this must use new flow.
+ if (!isInsertFromTable || isAlteredSchema(tableInfoOp.get.getFactTable)) {
+ isInsertIntoWithConverterFlow = true
+ }
+ if (isInsertIntoWithConverterFlow) {
+ return Seq.empty
+ }
+ setAuditTable(CarbonEnv.getDatabaseName(databaseNameOp)(sparkSession), tableName)
ThreadLocalSessionInfo
.setConfigurationToCurrentThread(sparkSession.sessionState.newHadoopConf())
- val isPersistEnabledUserValue = CarbonProperties.getInstance
- .getProperty(CarbonCommonConstants.CARBON_INSERT_PERSIST_ENABLED,
- CarbonCommonConstants.CARBON_INSERT_PERSIST_ENABLED_DEFAULT)
- val isPersistRequired =
- isPersistEnabledUserValue.equalsIgnoreCase("true") || containsLimit(child)
- val df =
- if (isPersistRequired) {
- LOGGER.info("Persist enabled for Insert operation")
- Dataset.ofRows(sparkSession, child).persist(
- StorageLevel.fromString(
- CarbonProperties.getInstance.getInsertIntoDatasetStorageLevel))
+ val (sizeInBytes, table, dbName, logicalPartitionRelation, finalPartition) = CommonLoadUtils
+ .processMetadataCommon(
+ sparkSession,
+ databaseNameOp,
+ tableName,
+ tableInfoOp,
+ partition)
+ this.sizeInBytes = sizeInBytes
+ this.table = table
+ this.logicalPartitionRelation = logicalPartitionRelation
+ this.finalPartition = finalPartition
+ setAuditTable(dbName, tableName)
+ Seq.empty
+ }
+
+ override def processData(sparkSession: SparkSession): Seq[Row] = {
+ if (isInsertIntoWithConverterFlow) {
+ return CarbonInsertIntoWithDf(
+ databaseNameOp,
+ tableName,
+ options,
+ isOverwriteTable,
+ dimFilesPath,
+ dataFrame,
+ inputSqlString,
+ None,
+ tableInfoOp,
+ internalOptions,
+ partition).process(sparkSession)
+ }
+ val carbonProperty: CarbonProperties = CarbonProperties.getInstance()
+ val dbName = CarbonEnv.getDatabaseName(databaseNameOp)(sparkSession)
+ val hadoopConf = sparkSession.sessionState.newHadoopConf()
+ carbonProperty.addProperty("zookeeper.enable.lock", "false")
+ val factPath = ""
+ currPartitions = CommonLoadUtils.getCurrentParitions(sparkSession, table)
+ CommonLoadUtils.setNumberOfCoresWhileLoading(sparkSession, carbonProperty)
+ val optionsFinal: util.Map[String, String] =
+ CommonLoadUtils.getFinalLoadOptions(
+ carbonProperty, table, options)
+ val carbonLoadModel: CarbonLoadModel = CommonLoadUtils.prepareLoadModel(
+ hadoopConf,
+ factPath,
+ optionsFinal, parentTablePath, table, isDataFrame = true, internalOptions, partition, options)
+
+ val (tf, df) = CommonLoadUtils.getTimeAndDateFormatFromLoadModel(
+ carbonLoadModel)
+ timeStampFormat = tf
+ dateFormat = df
+
+ var complexChildCount: Int = 0
+ var reArrangedIndex: Seq[Int] = Seq()
+ var selectedColumnSchema: Seq[ColumnSchema] = Seq()
+ var partitionIndex: Seq[Int] = Seq()
+
+ val columnSchema = tableInfoOp.get.getFactTable.getListOfColumns.asScala
+ val partitionInfo = tableInfoOp.get.getFactTable.getPartitionInfo
+ val partitionColumnSchema =
+ if (partitionInfo != null && partitionInfo.getColumnSchemaList.size() != 0) {
+ partitionInfo.getColumnSchemaList.asScala
+ } else {
+ null
+ }
+ val convertedStaticPartition = mutable.Map[String, AnyRef]()
+ // Remove the thread local entries of previous configurations.
+ DataTypeUtil.setDataTypeConverter(new SparkDataTypeConverterImpl)
+ if (partition.nonEmpty) {
+ for (col <- partitionColumnSchema) {
+ if (partition(col.getColumnName.toLowerCase).isDefined) {
+ convertedStaticPartition(col.getColumnName.toLowerCase) =
+ CarbonScalaUtil.convertStaticPartitionToValues(partition(col.getColumnName.toLowerCase)
+ .get,
+ SparkDataTypeConverterImpl.convertCarbonToSparkDataType(col.getDataType),
+ timeStampFormat,
+ dateFormat)
+ }
+ }
+ }
+ val partitionColumnNames = if (partitionColumnSchema != null) {
+ partitionColumnSchema.map(x => x.getColumnName).toSet
+ } else {
+ null
+ }
+ // get invisible column indexes, alter table scenarios can have it before or after new column
+ // dummy measure will have ordinal -1 and it is invisible, ignore that column.
+ // alter table old columns are just invisible columns with proper ordinal
+ val invisibleIndex = columnSchema.filter(col => col.isInvisible && col.getSchemaOrdinal != -1)
+ .map(col => col.getSchemaOrdinal)
+ columnSchema.filterNot(col => col.isInvisible).foreach {
+ col =>
+ var skipPartitionColumn = false
+ if (col.getColumnName.contains(".")) {
+ // If the schema ordinal is -1,
+ // no need to consider it during shifting columns to derive new shifted ordinal
+ if (col.getSchemaOrdinal != -1) {
+ complexChildCount = complexChildCount + 1
+ }
+ } else {
+ // get number of invisible index count before this column
+ val invisibleIndexCount = invisibleIndex.count(index => index < col.getSchemaOrdinal)
+ if (col.getDataType.isComplexType) {
+ // Calculate re-arrange index by ignoring the complex child count.
+ // As projection will have only parent columns
+ reArrangedIndex = reArrangedIndex :+
+ (col.getSchemaOrdinal - complexChildCount - invisibleIndexCount)
+ } else {
+ if (partitionColumnNames != null && partitionColumnNames.contains(col.getColumnName)) {
+ partitionIndex = partitionIndex :+ (col.getSchemaOrdinal - invisibleIndexCount)
+ skipPartitionColumn = true
+ } else {
+ reArrangedIndex = reArrangedIndex :+ (col.getSchemaOrdinal - invisibleIndexCount)
+ }
+ }
+ if (!skipPartitionColumn) {
+ selectedColumnSchema = selectedColumnSchema :+ col
+ }
+ }
+ }
+ if (partitionColumnSchema != null) {
+ // keep partition columns in the end
+ selectedColumnSchema = selectedColumnSchema ++ partitionColumnSchema
+ }
+ if (partitionIndex.nonEmpty) {
+ // keep partition columns in the end and in the original create order
+ reArrangedIndex = reArrangedIndex ++ partitionIndex.sortBy(x => x)
+ }
+ var processedProject: Boolean = false
+ // check first node is the projection or not
+ logicalPlan match {
+ case _: Project =>
+ // project is already present as first node
+ case _ =>
+ // If project is not present, add the projection to re-arrange it
+ logicalPlan = Project(logicalPlan.output, logicalPlan)
+ }
+ // Re-arrange the project as per columnSchema
+ val newLogicalPlan = logicalPlan.transformDown {
+ // case logicalRelation: LogicalRelation =>
+ // getReArrangedSchemaLogicalRelation(reArrangedIndex, logicalRelation)
+ // case hiveRelation: HiveTableRelation =>
+ // getReArrangedSchemaHiveRelation(reArrangedIndex, hiveRelation)
+ case p: Project =>
+ var oldProjectionList = p.projectList
+ if (!processedProject) {
+ if (partition.nonEmpty) {
+ // partition keyword is present in insert and
+ // select query partition projections may not be same as create order.
+ // So, bring to create table order
+ val dynamicPartition = partition.filterNot(entry => entry._2.isDefined)
+ var index = 0
+ val map = mutable.Map[String, Int]()
+ for (part <- dynamicPartition) {
+ map(part._1) = index
+ index = index + 1
+ }
+ var tempList = oldProjectionList.take(oldProjectionList.size - dynamicPartition.size)
+ val partitionList = oldProjectionList.takeRight(dynamicPartition.size)
+ val partitionSchema = table.getPartitionInfo.getColumnSchemaList.asScala
+ for (partitionCol <- partitionSchema) {
+ if (map.get(partitionCol.getColumnName).isDefined) {
+ tempList = tempList :+ partitionList(map(partitionCol.getColumnName))
+ }
+ }
+ oldProjectionList = tempList
+ }
+ if (reArrangedIndex.size != oldProjectionList.size) {
+ // for non-partition table columns must match
+ if (partition.isEmpty) {
+ throw new AnalysisException(
+ s"Cannot insert into table $tableName because the number of columns are " +
+ s"different: " +
+ s"need ${ reArrangedIndex.size } columns, " +
+ s"but query has ${ oldProjectionList.size } columns.")
+ } else {
+ if (reArrangedIndex.size - oldProjectionList.size != convertedStaticPartition.size) {
+ throw new AnalysisException(
+ s"Cannot insert into table $tableName because the number of columns are " +
+ s"different: need ${ reArrangedIndex.size } columns, " +
+ s"but query has ${ oldProjectionList.size } columns.")
+ } else {
+ // TODO: For partition case, remaining projections need to validate ?
+ }
+ }
+ }
+ var newProjectionList: Seq[NamedExpression] = Seq.empty
+ var i = 0
+ while (i < reArrangedIndex.size) {
+ // column schema is already has sortColumns-dimensions-measures. Collect the ordinal &
+ // re-arrange the projection in the same order
+ if (partition.nonEmpty &&
+ convertedStaticPartition.contains(selectedColumnSchema(i).getColumnName
+ .toLowerCase())) {
+ // If column schema present in partitionSchema means it is a static partition,
+ // then add a value literal expression in the project.
+ val value = convertedStaticPartition(selectedColumnSchema(i).getColumnName
+ .toLowerCase())
+ newProjectionList = newProjectionList :+
+ Alias(new Literal(value,
+ SparkDataTypeConverterImpl.convertCarbonToSparkDataType(
+ selectedColumnSchema(i).getDataType)), value.toString)(
+ NamedExpression.newExprId,
+ None,
+ None).asInstanceOf[NamedExpression]
+ } else {
+ // If column schema NOT present in partition column,
+ // get projection column mapping its ordinal.
+ if (partition.contains(selectedColumnSchema(i).getColumnName.toLowerCase())) {
+ // static partition + dynamic partition case,
+ // here dynamic partition ordinal will be more than projection size
+ newProjectionList = newProjectionList :+
+ oldProjectionList(
+ reArrangedIndex(i) - convertedStaticPartition.size)
+ } else {
+ newProjectionList = newProjectionList :+
+ oldProjectionList(reArrangedIndex(i))
+ }
+ }
+ i = i + 1
+ }
+ processedProject = true
+ Project(newProjectionList, p.child)
+ } else {
+ p
+ }
+ }
+ scanResultRdd = sparkSession.sessionState.executePlan(newLogicalPlan).toRdd
+ if (logicalPartitionRelation != null) {
+ logicalPartitionRelation =
+ getReArrangedSchemaLogicalRelation(reArrangedIndex, logicalPartitionRelation)
+ }
+ // Delete stale segment folders that are not in table status but are physically present in
+ // the Fact folder
+ LOGGER.info(s"Deleting stale folders if present for table $dbName.$tableName")
+ TableProcessingOperations.deletePartialLoadDataIfExist(table, false)
+ var isUpdateTableStatusRequired = false
+ val uuid = ""
+ try {
+ val (tableDataMaps, dataMapOperationContext) =
+ CommonLoadUtils.firePreLoadEvents(sparkSession,
+ carbonLoadModel,
+ uuid,
+ table,
+ isOverwriteTable,
+ operationContext)
+ // First system has to partition the data first and then call the load data
+ LOGGER.info(s"Initiating Direct Load for the Table : ($dbName.$tableName)")
+ // Clean up the old invalid segment data before creating a new entry for new load.
+ SegmentStatusManager.deleteLoadsAndUpdateMetadata(table, false, currPartitions)
+ // add the start entry for the new load in the table status file
+ if (!table.isHivePartitionTable) {
+ CarbonLoaderUtil.readAndUpdateLoadProgressInTableMeta(
+ carbonLoadModel,
+ isOverwriteTable)
+ isUpdateTableStatusRequired = true
+ }
+ if (isOverwriteTable) {
+ LOGGER.info(s"Overwrite of carbon table with $dbName.$tableName is in progress")
+ }
+ // Create table and metadata folders if not exist
+ if (carbonLoadModel.isCarbonTransactionalTable) {
+ val metadataDirectoryPath = CarbonTablePath.getMetadataPath(table.getTablePath)
+ if (!FileFactory.isFileExist(metadataDirectoryPath)) {
+ FileFactory.mkdirs(metadataDirectoryPath)
+ }
} else {
- Dataset.ofRows(sparkSession, child)
+ carbonLoadModel.setSegmentId(System.nanoTime().toString)
}
- val header = relation.tableSchema.get.fields.map(_.name).mkString(",")
- loadCommand = CarbonLoadDataCommand(
- databaseNameOp = Some(relation.carbonRelation.databaseName),
- tableName = relation.carbonRelation.tableName,
- factPathFromUser = null,
- dimFilesPath = Seq(),
- options = scala.collection.immutable.Map("fileheader" -> header),
- isOverwriteTable = overwrite,
- inputSqlString = null,
- dataFrame = Some(df),
- updateModel = None,
- tableInfoOp = None,
- internalOptions = Map.empty,
- partition = partition)
- val load = loadCommand.processMetadata(sparkSession)
- if (isPersistRequired) {
- df.unpersist()
- }
- load
+ val partitionStatus = SegmentStatus.SUCCESS
+
+ val loadParams = CarbonLoadParams(sparkSession,
+ tableName,
+ sizeInBytes,
+ isOverwriteTable,
+ carbonLoadModel,
+ hadoopConf,
+ logicalPartitionRelation,
+ dateFormat,
+ timeStampFormat,
+ options,
+ finalPartition,
+ currPartitions,
+ partitionStatus,
+ None,
+ Some(scanResultRdd),
+ None,
+ operationContext)
+
+ LOGGER.info("Sort Scope : " + carbonLoadModel.getSortScope)
+ val (rows, loadResult) = insertData(loadParams)
+ val info = CommonLoadUtils.makeAuditInfo(loadResult)
+ setAuditInfo(info)
+ CommonLoadUtils.firePostLoadEvents(sparkSession,
+ carbonLoadModel,
+ tableDataMaps,
+ dataMapOperationContext,
+ table,
+ operationContext)
+ } catch {
+ case CausedBy(ex: NoRetryException) =>
+ // update the load entry in table status file for changing the status to marked for delete
+ if (isUpdateTableStatusRequired) {
+ CarbonLoaderUtil.updateTableStatusForFailure(carbonLoadModel, uuid)
+ }
+ LOGGER.error(s"Dataload failure for $dbName.$tableName", ex)
+ throw new RuntimeException(s"Dataload failure for $dbName.$tableName, ${ex.getMessage}")
+ // In case of event related exception
+ case preEventEx: PreEventException =>
+ LOGGER.error(s"Dataload failure for $dbName.$tableName", preEventEx)
+ throw new AnalysisException(preEventEx.getMessage)
+ case ex: Exception =>
+ LOGGER.error(ex)
+ // update the load entry in table status file for changing the status to marked for delete
+ if (isUpdateTableStatusRequired) {
+ CarbonLoaderUtil.updateTableStatusForFailure(carbonLoadModel, uuid)
+ }
+ throw ex
+ }
+ Seq.empty
}
- override def processData(sparkSession: SparkSession): Seq[Row] = {
- if (null != loadCommand) {
- val rows = loadCommand.processData(sparkSession)
- setAuditInfo(loadCommand.auditInfo)
- rows
+
+ def getReArrangedSchemaLogicalRelation(reArrangedIndex: Seq[Int],

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GitBox

[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376351172

##########
File path: integration/spark2/src/main/scala/org/apache/spark/sql/execution/command/management/CarbonInsertIntoCommand.scala
##########
@@ -17,85 +17,518 @@

package org.apache.spark.sql.execution.command.management

-import org.apache.spark.sql.{CarbonDatasourceHadoopRelation, Dataset, Row, SparkSession}
-import org.apache.spark.sql.catalyst.plans.logical.{GlobalLimit, LogicalPlan}
-import org.apache.spark.sql.execution.command.{AtomicRunnableCommand, DataCommand}
-import org.apache.spark.storage.StorageLevel
-
-import org.apache.carbondata.common.logging.{LogService, LogServiceFactory}
-import org.apache.carbondata.core.constants.CarbonCommonConstants
-import org.apache.carbondata.core.util.{CarbonProperties, ThreadLocalSessionInfo}
-
-case class CarbonInsertIntoCommand(
- relation: CarbonDatasourceHadoopRelation,
- child: LogicalPlan,
- overwrite: Boolean,
- partition: Map[String, Option[String]])
+import java.text.SimpleDateFormat
+import java.util
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{AnalysisException, CarbonEnv, DataFrame, Dataset, Row, SparkSession}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.catalog.HiveTableRelation
+import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeReference, Literal, NamedExpression}
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project}
+import org.apache.spark.sql.execution.command.{AtomicRunnableCommand, DataLoadTableFileMapping}
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.types.{StructField, StructType}
+import org.apache.spark.util.CausedBy
+
+import org.apache.carbondata.common.logging.LogServiceFactory
+import org.apache.carbondata.converter.SparkDataTypeConverterImpl
+import org.apache.carbondata.core.datastore.impl.FileFactory
+import org.apache.carbondata.core.indexstore.PartitionSpec
+import org.apache.carbondata.core.metadata.schema.SchemaEvolutionEntry
+import org.apache.carbondata.core.metadata.schema.table.{CarbonTable, TableInfo, TableSchema}
+import org.apache.carbondata.core.metadata.schema.table.column.ColumnSchema
+import org.apache.carbondata.core.statusmanager.{LoadMetadataDetails, SegmentStatus, SegmentStatusManager}
+import org.apache.carbondata.core.util.{CarbonProperties, DataTypeUtil, ThreadLocalSessionInfo}
+import org.apache.carbondata.core.util.path.CarbonTablePath
+import org.apache.carbondata.events.exception.PreEventException
+import org.apache.carbondata.events.OperationContext
+import org.apache.carbondata.processing.loading.TableProcessingOperations
+import org.apache.carbondata.processing.loading.exception.NoRetryException
+import org.apache.carbondata.processing.loading.model.CarbonLoadModel
+import org.apache.carbondata.processing.util.CarbonLoaderUtil
+import org.apache.carbondata.spark.rdd.CarbonDataRDDFactory
+import org.apache.carbondata.spark.util.CarbonScalaUtil
+
+/*
+* insert into without df, by just using logical plan
+*
+*/
+case class CarbonInsertIntoCommand(databaseNameOp: Option[String],
+ tableName: String,
+ options: Map[String, String],
+ isOverwriteTable: Boolean,
+ var logicalPlan: LogicalPlan,
+ var dimFilesPath: Seq[DataLoadTableFileMapping] = Seq(),
+ var inputSqlString: String = null,
+ var tableInfoOp: Option[TableInfo] = None,
+ var internalOptions: Map[String, String] = Map.empty,
+ var partition: Map[String, Option[String]] = Map.empty,
+ var operationContext: OperationContext = new OperationContext)
extends AtomicRunnableCommand {

- var loadCommand: CarbonLoadDataCommand = _
+ var table: CarbonTable = _
+
+ var logicalPartitionRelation: LogicalRelation = _
+
+ var sizeInBytes: Long = _
+
+ var currPartitions: util.List[PartitionSpec] = _
+
+ var parentTablePath: String = _
+
+ val LOGGER = LogServiceFactory.getLogService(this.getClass.getName)
+
+ var scanResultRdd: RDD[InternalRow] = _
+
+ var timeStampFormat: SimpleDateFormat = _
+
+ var dateFormat: SimpleDateFormat = _
+
+ var finalPartition: Map[String, Option[String]] = Map.empty
+
+ var isInsertIntoWithConverterFlow: Boolean = false
+
+ var dataFrame: DataFrame = _

override def processMetadata(sparkSession: SparkSession): Seq[Row] = {
- setAuditTable(relation.carbonTable.getDatabaseName, relation.carbonTable.getTableName)
- val LOGGER = LogServiceFactory.getLogService(this.getClass.getName)
- def containsLimit(plan: LogicalPlan): Boolean = {
- plan find {
- case limit: GlobalLimit => true
- case other => false
- } isDefined
+ if (!tableInfoOp.isDefined) {
+ throw new RuntimeException(" table info must be present when logical relation exist")
}
-
+ // If logical plan is unresolved, need to convert it to resolved.
+ dataFrame = Dataset.ofRows(sparkSession, logicalPlan)
+ logicalPlan = dataFrame.queryExecution.analyzed
+ var isInsertFromTable = false
+ logicalPlan.collect {
+ case _: LogicalRelation =>
+ isInsertFromTable = true
+ }
+ // Currently projection re-ordering is based on schema ordinal,
+ // for some scenarios in alter table scenario, schema ordinal logic cannot be applied.
+ // So, sending it to old flow
+ // TODO: Handle this in future, this must use new flow.
+ if (!isInsertFromTable || isAlteredSchema(tableInfoOp.get.getFactTable)) {
+ isInsertIntoWithConverterFlow = true
+ }
+ if (isInsertIntoWithConverterFlow) {
+ return Seq.empty
+ }
+ setAuditTable(CarbonEnv.getDatabaseName(databaseNameOp)(sparkSession), tableName)
ThreadLocalSessionInfo
.setConfigurationToCurrentThread(sparkSession.sessionState.newHadoopConf())
- val isPersistEnabledUserValue = CarbonProperties.getInstance
- .getProperty(CarbonCommonConstants.CARBON_INSERT_PERSIST_ENABLED,
- CarbonCommonConstants.CARBON_INSERT_PERSIST_ENABLED_DEFAULT)
- val isPersistRequired =
- isPersistEnabledUserValue.equalsIgnoreCase("true") || containsLimit(child)
- val df =
- if (isPersistRequired) {
- LOGGER.info("Persist enabled for Insert operation")
- Dataset.ofRows(sparkSession, child).persist(
- StorageLevel.fromString(
- CarbonProperties.getInstance.getInsertIntoDatasetStorageLevel))
+ val (sizeInBytes, table, dbName, logicalPartitionRelation, finalPartition) = CommonLoadUtils
+ .processMetadataCommon(
+ sparkSession,
+ databaseNameOp,
+ tableName,
+ tableInfoOp,
+ partition)
+ this.sizeInBytes = sizeInBytes
+ this.table = table
+ this.logicalPartitionRelation = logicalPartitionRelation
+ this.finalPartition = finalPartition
+ setAuditTable(dbName, tableName)
+ Seq.empty
+ }
+
+ override def processData(sparkSession: SparkSession): Seq[Row] = {
+ if (isInsertIntoWithConverterFlow) {
+ return CarbonInsertIntoWithDf(
+ databaseNameOp,
+ tableName,
+ options,
+ isOverwriteTable,
+ dimFilesPath,
+ dataFrame,
+ inputSqlString,
+ None,
+ tableInfoOp,
+ internalOptions,
+ partition).process(sparkSession)
+ }
+ val carbonProperty: CarbonProperties = CarbonProperties.getInstance()
+ val dbName = CarbonEnv.getDatabaseName(databaseNameOp)(sparkSession)
+ val hadoopConf = sparkSession.sessionState.newHadoopConf()
+ carbonProperty.addProperty("zookeeper.enable.lock", "false")
+ val factPath = ""
+ currPartitions = CommonLoadUtils.getCurrentParitions(sparkSession, table)
+ CommonLoadUtils.setNumberOfCoresWhileLoading(sparkSession, carbonProperty)
+ val optionsFinal: util.Map[String, String] =
+ CommonLoadUtils.getFinalLoadOptions(
+ carbonProperty, table, options)
+ val carbonLoadModel: CarbonLoadModel = CommonLoadUtils.prepareLoadModel(
+ hadoopConf,
+ factPath,
+ optionsFinal, parentTablePath, table, isDataFrame = true, internalOptions, partition, options)
+
+ val (tf, df) = CommonLoadUtils.getTimeAndDateFormatFromLoadModel(
+ carbonLoadModel)
+ timeStampFormat = tf
+ dateFormat = df
+
+ var complexChildCount: Int = 0
+ var reArrangedIndex: Seq[Int] = Seq()
+ var selectedColumnSchema: Seq[ColumnSchema] = Seq()
+ var partitionIndex: Seq[Int] = Seq()
+
+ val columnSchema = tableInfoOp.get.getFactTable.getListOfColumns.asScala
+ val partitionInfo = tableInfoOp.get.getFactTable.getPartitionInfo
+ val partitionColumnSchema =
+ if (partitionInfo != null && partitionInfo.getColumnSchemaList.size() != 0) {
+ partitionInfo.getColumnSchemaList.asScala
+ } else {
+ null
+ }
+ val convertedStaticPartition = mutable.Map[String, AnyRef]()
+ // Remove the thread local entries of previous configurations.
+ DataTypeUtil.setDataTypeConverter(new SparkDataTypeConverterImpl)
+ if (partition.nonEmpty) {
+ for (col <- partitionColumnSchema) {
+ if (partition(col.getColumnName.toLowerCase).isDefined) {
+ convertedStaticPartition(col.getColumnName.toLowerCase) =
+ CarbonScalaUtil.convertStaticPartitionToValues(partition(col.getColumnName.toLowerCase)
+ .get,
+ SparkDataTypeConverterImpl.convertCarbonToSparkDataType(col.getDataType),
+ timeStampFormat,
+ dateFormat)
+ }
+ }
+ }
+ val partitionColumnNames = if (partitionColumnSchema != null) {
+ partitionColumnSchema.map(x => x.getColumnName).toSet
+ } else {
+ null
+ }
+ // get invisible column indexes, alter table scenarios can have it before or after new column
+ // dummy measure will have ordinal -1 and it is invisible, ignore that column.
+ // alter table old columns are just invisible columns with proper ordinal
+ val invisibleIndex = columnSchema.filter(col => col.isInvisible && col.getSchemaOrdinal != -1)
+ .map(col => col.getSchemaOrdinal)
+ columnSchema.filterNot(col => col.isInvisible).foreach {
+ col =>
+ var skipPartitionColumn = false
+ if (col.getColumnName.contains(".")) {
+ // If the schema ordinal is -1,
+ // no need to consider it during shifting columns to derive new shifted ordinal
+ if (col.getSchemaOrdinal != -1) {
+ complexChildCount = complexChildCount + 1
+ }
+ } else {
+ // get number of invisible index count before this column
+ val invisibleIndexCount = invisibleIndex.count(index => index < col.getSchemaOrdinal)
+ if (col.getDataType.isComplexType) {
+ // Calculate re-arrange index by ignoring the complex child count.
+ // As projection will have only parent columns
+ reArrangedIndex = reArrangedIndex :+
+ (col.getSchemaOrdinal - complexChildCount - invisibleIndexCount)
+ } else {
+ if (partitionColumnNames != null && partitionColumnNames.contains(col.getColumnName)) {
+ partitionIndex = partitionIndex :+ (col.getSchemaOrdinal - invisibleIndexCount)
+ skipPartitionColumn = true
+ } else {
+ reArrangedIndex = reArrangedIndex :+ (col.getSchemaOrdinal - invisibleIndexCount)
+ }
+ }
+ if (!skipPartitionColumn) {
+ selectedColumnSchema = selectedColumnSchema :+ col
+ }
+ }
+ }
+ if (partitionColumnSchema != null) {
+ // keep partition columns in the end
+ selectedColumnSchema = selectedColumnSchema ++ partitionColumnSchema
+ }
+ if (partitionIndex.nonEmpty) {
+ // keep partition columns in the end and in the original create order
+ reArrangedIndex = reArrangedIndex ++ partitionIndex.sortBy(x => x)
+ }
+ var processedProject: Boolean = false
+ // check first node is the projection or not
+ logicalPlan match {
+ case _: Project =>
+ // project is already present as first node
+ case _ =>
+ // If project is not present, add the projection to re-arrange it
+ logicalPlan = Project(logicalPlan.output, logicalPlan)
+ }
+ // Re-arrange the project as per columnSchema
+ val newLogicalPlan = logicalPlan.transformDown {
+ // case logicalRelation: LogicalRelation =>
+ // getReArrangedSchemaLogicalRelation(reArrangedIndex, logicalRelation)
+ // case hiveRelation: HiveTableRelation =>
+ // getReArrangedSchemaHiveRelation(reArrangedIndex, hiveRelation)
+ case p: Project =>
+ var oldProjectionList = p.projectList
+ if (!processedProject) {
+ if (partition.nonEmpty) {
+ // partition keyword is present in insert and
+ // select query partition projections may not be same as create order.
+ // So, bring to create table order
+ val dynamicPartition = partition.filterNot(entry => entry._2.isDefined)
+ var index = 0
+ val map = mutable.Map[String, Int]()
+ for (part <- dynamicPartition) {
+ map(part._1) = index
+ index = index + 1
+ }
+ var tempList = oldProjectionList.take(oldProjectionList.size - dynamicPartition.size)
+ val partitionList = oldProjectionList.takeRight(dynamicPartition.size)
+ val partitionSchema = table.getPartitionInfo.getColumnSchemaList.asScala
+ for (partitionCol <- partitionSchema) {
+ if (map.get(partitionCol.getColumnName).isDefined) {
+ tempList = tempList :+ partitionList(map(partitionCol.getColumnName))
+ }
+ }
+ oldProjectionList = tempList
+ }
+ if (reArrangedIndex.size != oldProjectionList.size) {
+ // for non-partition table columns must match
+ if (partition.isEmpty) {
+ throw new AnalysisException(
+ s"Cannot insert into table $tableName because the number of columns are " +
+ s"different: " +
+ s"need ${ reArrangedIndex.size } columns, " +
+ s"but query has ${ oldProjectionList.size } columns.")
+ } else {
+ if (reArrangedIndex.size - oldProjectionList.size != convertedStaticPartition.size) {
+ throw new AnalysisException(
+ s"Cannot insert into table $tableName because the number of columns are " +
+ s"different: need ${ reArrangedIndex.size } columns, " +
+ s"but query has ${ oldProjectionList.size } columns.")
+ } else {
+ // TODO: For partition case, remaining projections need to validate ?
+ }
+ }
+ }
+ var newProjectionList: Seq[NamedExpression] = Seq.empty
+ var i = 0
+ while (i < reArrangedIndex.size) {
+ // column schema is already has sortColumns-dimensions-measures. Collect the ordinal &
+ // re-arrange the projection in the same order
+ if (partition.nonEmpty &&
+ convertedStaticPartition.contains(selectedColumnSchema(i).getColumnName
+ .toLowerCase())) {
+ // If column schema present in partitionSchema means it is a static partition,
+ // then add a value literal expression in the project.
+ val value = convertedStaticPartition(selectedColumnSchema(i).getColumnName
+ .toLowerCase())
+ newProjectionList = newProjectionList :+
+ Alias(new Literal(value,
+ SparkDataTypeConverterImpl.convertCarbonToSparkDataType(
+ selectedColumnSchema(i).getDataType)), value.toString)(
+ NamedExpression.newExprId,
+ None,
+ None).asInstanceOf[NamedExpression]
+ } else {
+ // If column schema NOT present in partition column,
+ // get projection column mapping its ordinal.
+ if (partition.contains(selectedColumnSchema(i).getColumnName.toLowerCase())) {
+ // static partition + dynamic partition case,
+ // here dynamic partition ordinal will be more than projection size
+ newProjectionList = newProjectionList :+
+ oldProjectionList(
+ reArrangedIndex(i) - convertedStaticPartition.size)
+ } else {
+ newProjectionList = newProjectionList :+
+ oldProjectionList(reArrangedIndex(i))
+ }
+ }
+ i = i + 1
+ }
+ processedProject = true
+ Project(newProjectionList, p.child)
+ } else {
+ p
+ }
+ }
+ scanResultRdd = sparkSession.sessionState.executePlan(newLogicalPlan).toRdd
+ if (logicalPartitionRelation != null) {
+ logicalPartitionRelation =
+ getReArrangedSchemaLogicalRelation(reArrangedIndex, logicalPartitionRelation)
+ }
+ // Delete stale segment folders that are not in table status but are physically present in
+ // the Fact folder
+ LOGGER.info(s"Deleting stale folders if present for table $dbName.$tableName")
+ TableProcessingOperations.deletePartialLoadDataIfExist(table, false)
+ var isUpdateTableStatusRequired = false
+ val uuid = ""
+ try {
+ val (tableDataMaps, dataMapOperationContext) =
+ CommonLoadUtils.firePreLoadEvents(sparkSession,
+ carbonLoadModel,
+ uuid,
+ table,
+ isOverwriteTable,
+ operationContext)
+ // First system has to partition the data first and then call the load data
+ LOGGER.info(s"Initiating Direct Load for the Table : ($dbName.$tableName)")
+ // Clean up the old invalid segment data before creating a new entry for new load.
+ SegmentStatusManager.deleteLoadsAndUpdateMetadata(table, false, currPartitions)
+ // add the start entry for the new load in the table status file
+ if (!table.isHivePartitionTable) {
+ CarbonLoaderUtil.readAndUpdateLoadProgressInTableMeta(
+ carbonLoadModel,
+ isOverwriteTable)
+ isUpdateTableStatusRequired = true
+ }
+ if (isOverwriteTable) {
+ LOGGER.info(s"Overwrite of carbon table with $dbName.$tableName is in progress")
+ }
+ // Create table and metadata folders if not exist
+ if (carbonLoadModel.isCarbonTransactionalTable) {
+ val metadataDirectoryPath = CarbonTablePath.getMetadataPath(table.getTablePath)
+ if (!FileFactory.isFileExist(metadataDirectoryPath)) {
+ FileFactory.mkdirs(metadataDirectoryPath)
+ }
} else {
- Dataset.ofRows(sparkSession, child)
+ carbonLoadModel.setSegmentId(System.nanoTime().toString)
}
- val header = relation.tableSchema.get.fields.map(_.name).mkString(",")
- loadCommand = CarbonLoadDataCommand(
- databaseNameOp = Some(relation.carbonRelation.databaseName),
- tableName = relation.carbonRelation.tableName,
- factPathFromUser = null,
- dimFilesPath = Seq(),
- options = scala.collection.immutable.Map("fileheader" -> header),
- isOverwriteTable = overwrite,
- inputSqlString = null,
- dataFrame = Some(df),
- updateModel = None,
- tableInfoOp = None,
- internalOptions = Map.empty,
- partition = partition)
- val load = loadCommand.processMetadata(sparkSession)
- if (isPersistRequired) {
- df.unpersist()
- }
- load
+ val partitionStatus = SegmentStatus.SUCCESS
+
+ val loadParams = CarbonLoadParams(sparkSession,
+ tableName,
+ sizeInBytes,
+ isOverwriteTable,
+ carbonLoadModel,
+ hadoopConf,
+ logicalPartitionRelation,
+ dateFormat,
+ timeStampFormat,
+ options,
+ finalPartition,
+ currPartitions,
+ partitionStatus,
+ None,
+ Some(scanResultRdd),
+ None,
+ operationContext)
+
+ LOGGER.info("Sort Scope : " + carbonLoadModel.getSortScope)
+ val (rows, loadResult) = insertData(loadParams)
+ val info = CommonLoadUtils.makeAuditInfo(loadResult)
+ setAuditInfo(info)
+ CommonLoadUtils.firePostLoadEvents(sparkSession,
+ carbonLoadModel,
+ tableDataMaps,
+ dataMapOperationContext,
+ table,
+ operationContext)
+ } catch {
+ case CausedBy(ex: NoRetryException) =>
+ // update the load entry in table status file for changing the status to marked for delete
+ if (isUpdateTableStatusRequired) {
+ CarbonLoaderUtil.updateTableStatusForFailure(carbonLoadModel, uuid)
+ }
+ LOGGER.error(s"Dataload failure for $dbName.$tableName", ex)
+ throw new RuntimeException(s"Dataload failure for $dbName.$tableName, ${ex.getMessage}")
+ // In case of event related exception
+ case preEventEx: PreEventException =>
+ LOGGER.error(s"Dataload failure for $dbName.$tableName", preEventEx)
+ throw new AnalysisException(preEventEx.getMessage)
+ case ex: Exception =>
+ LOGGER.error(ex)
+ // update the load entry in table status file for changing the status to marked for delete
+ if (isUpdateTableStatusRequired) {
+ CarbonLoaderUtil.updateTableStatusForFailure(carbonLoadModel, uuid)
+ }
+ throw ex
+ }
+ Seq.empty
}
- override def processData(sparkSession: SparkSession): Seq[Row] = {
- if (null != loadCommand) {
- val rows = loadCommand.processData(sparkSession)
- setAuditInfo(loadCommand.auditInfo)
- rows
+
+ def getReArrangedSchemaLogicalRelation(reArrangedIndex: Seq[Int],
+ logicalRelation: LogicalRelation): LogicalRelation = {
+ if (reArrangedIndex.size != logicalRelation.schema.size) {
+ throw new AnalysisException(
+ s"Cannot insert into table $tableName because the number of columns are different: " +
+ s"need ${ reArrangedIndex.size } columns, " +
+ s"but query has ${ logicalRelation.schema.size } columns.")
+ }
+ val reArrangedFields = new Array[StructField](logicalRelation.schema.size)
+ val reArrangedAttributes = new Array[AttributeReference](logicalRelation.schema.size)
+ val fields = logicalRelation.schema.fields
+ val output = logicalRelation.output
+ var i = 0
+ for (index <- reArrangedIndex) {
+ reArrangedFields(i) = fields(index)
+ reArrangedAttributes(i) = output(index)
+ i = i + 1
+ }
+ val catalogTable = logicalRelation.catalogTable
+ .get
+ .copy(schema = new StructType(reArrangedFields))
+ logicalRelation.copy(logicalRelation.relation,
+ reArrangedAttributes,
+ Some(catalogTable))
+ }
+
+ def getReArrangedSchemaHiveRelation(reArrangedIndex: Seq[Int],

Review comment:
ok

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

GitBox

[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

GitBox

[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

In reply to this post by GitBox

GitBox

[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376357574

##########
File path: processing/src/main/java/org/apache/carbondata/processing/datatypes/GenericDataType.java
##########
@@ -32,7 +33,7 @@
* Generic DataType interface which will be used while data loading for complex types like Array &
* Struct
*/
-public interface GenericDataType<T> {
+public interface GenericDataType<T> extends Serializable {

Review comment:
ok done

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376357834

##########
File path: processing/src/main/java/org/apache/carbondata/processing/loading/DataLoadProcessBuilder.java
##########
@@ -110,10 +113,10 @@ private AbstractDataLoadProcessorStep buildInternalForNoSort(CarbonIterator[] in
*/
private AbstractDataLoadProcessorStep buildInternalWithNoConverter(
CarbonIterator[] inputIterators, CarbonDataLoadConfiguration configuration,
- SortScopeOptions.SortScope sortScope) {
+ SortScopeOptions.SortScope sortScope, boolean withoutReArrange) {

Review comment:
That is more change, may be refactor in another PR

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376361675

##########
File path: processing/src/main/java/org/apache/carbondata/processing/datatypes/GenericDataType.java
##########
@@ -32,7 +33,7 @@
* Generic DataType interface which will be used while data loading for complex types like Array &
* Struct
*/
-public interface GenericDataType<T> {
+public interface GenericDataType<T> extends Serializable {

Review comment:
Primitive type logger was not user, removed the field itself

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[GitHub] [carbondata] CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow

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CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#issuecomment-583398606

Build Failed with Spark 2.4.4, Please check CI http://121.244.95.60:12545/job/ApacheCarbon_PR_Builder_2.4.4/179/

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[GitHub] [carbondata] CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow

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CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#issuecomment-583440865

Build Success with Spark 2.3.4, Please check CI http://121.244.95.60:12545/job/ApacheCarbonPRBuilder2.3/1882/

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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[GitHub] [carbondata] CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow

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CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#issuecomment-584011058

Build Failed with Spark 2.4.4, Please check CI http://121.244.95.60:12545/job/ApacheCarbon_PR_Builder_2.4.4/207/

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[GitHub] [carbondata] CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow

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CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#issuecomment-584037967

Build Success with Spark 2.3.4, Please check CI http://121.244.95.60:12545/job/ApacheCarbonPRBuilder2.3/1909/

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[GitHub] [carbondata] CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow

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CarbonDataQA1 commented on issue #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#issuecomment-584060297

Build Failed with Spark 2.4.4, Please check CI http://121.244.95.60:12545/job/ApacheCarbon_PR_Builder_2.4.4/210/

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[GitHub] [carbondata] ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow

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ajantha-bhat commented on a change in pull request #3538: [CARBONDATA-3637] Optimize insert into flow
URL: https://github.com/apache/carbondata/pull/3538#discussion_r376361675

##########
File path: processing/src/main/java/org/apache/carbondata/processing/datatypes/GenericDataType.java
##########
@@ -32,7 +33,7 @@
* Generic DataType interface which will be used while data loading for complex types like Array &
* Struct
*/
-public interface GenericDataType<T> {
+public interface GenericDataType<T> extends Serializable {

Review comment:
Primitive type logger was not used, removed the field itself

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