garyli1019 commented on a change in pull request #1938: URL: https://github.com/apache/hudi/pull/1938#discussion_r480529973
########## File path: hudi-spark/src/main/scala/org/apache/hudi/MergeOnReadIncrementalRelation.scala ########## @@ -0,0 +1,209 @@ +/* + * 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.hudi + +import org.apache.hudi.common.model.{HoodieCommitMetadata, HoodieRecord, HoodieTableType} +import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver} +import org.apache.hudi.exception.HoodieException +import org.apache.hadoop.fs.{FileStatus, FileSystem, GlobPattern, Path} +import org.apache.hadoop.mapred.JobConf +import org.apache.hudi.common.fs.FSUtils +import org.apache.hudi.common.table.view.HoodieTableFileSystemView +import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes +import org.apache.log4j.LogManager +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.execution.datasources.PartitionedFile +import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat +import org.apache.spark.sql.sources.{BaseRelation, Filter, GreaterThanOrEqual, IsNotNull, LessThanOrEqual, PrunedFilteredScan, TableScan} +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.{Row, SQLContext} + +import scala.collection.JavaConversions._ +import scala.collection.mutable.ListBuffer + +/** + * Experimental. + * Relation, that implements the Hoodie incremental view for Merge On Read table. + * + */ +class MergeOnReadIncrementalRelation(val sqlContext: SQLContext, + val optParams: Map[String, String], + val userSchema: StructType, + val metaClient: HoodieTableMetaClient) + extends BaseRelation with PrunedFilteredScan { + + private val log = LogManager.getLogger(classOf[MergeOnReadIncrementalRelation]) + private val conf = sqlContext.sparkContext.hadoopConfiguration + private val jobConf = new JobConf(conf) + private val fs = FSUtils.getFs(metaClient.getBasePath, conf) + private val commitTimeline = metaClient.getCommitsAndCompactionTimeline.filterCompletedInstants() + if (commitTimeline.empty()) { + throw new HoodieException("No instants to incrementally pull") + } + if (!optParams.contains(DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY)) { + throw new HoodieException(s"Specify the begin instant time to pull from using " + + s"option ${DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY}") + } + + private val lastInstant = commitTimeline.lastInstant().get() + private val mergeType = optParams.getOrElse( + DataSourceReadOptions.REALTIME_MERGE_OPT_KEY, + DataSourceReadOptions.DEFAULT_REALTIME_MERGE_OPT_VAL) + + private val commitsTimelineToReturn = commitTimeline.findInstantsInRange( + optParams(DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY), + optParams.getOrElse(DataSourceReadOptions.END_INSTANTTIME_OPT_KEY, lastInstant.getTimestamp)) + log.debug(s"${commitsTimelineToReturn.getInstants.iterator().toList.map(f => f.toString).mkString(",")}") + private val commitsToReturn = commitsTimelineToReturn.getInstants.iterator().toList + private val schemaUtil = new TableSchemaResolver(metaClient) + private val tableAvroSchema = schemaUtil.getTableAvroSchema + private val tableStructSchema = AvroConversionUtils.convertAvroSchemaToStructType(tableAvroSchema) + private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(jobConf) + private val fileIndex = buildFileIndex() + + override def schema: StructType = tableStructSchema + + override def needConversion: Boolean = false + + override def unhandledFilters(filters: Array[Filter]): Array[Filter] = { + val isNotNullFilter = IsNotNull(HoodieRecord.COMMIT_TIME_METADATA_FIELD) + val largerThanFilter = GreaterThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.head.getTimestamp) + val lessThanFilter = LessThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.last.getTimestamp) + filters :+isNotNullFilter :+ largerThanFilter :+ lessThanFilter + } + + override def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row] = { + log.debug(s"buildScan requiredColumns = ${requiredColumns.mkString(",")}") + log.debug(s"buildScan filters = ${filters.mkString(",")}") + // config to ensure the push down filter for parquet will be applied. + sqlContext.sparkSession.sessionState.conf.setConfString("spark.sql.parquet.recordLevelFilter.enabled", "true") + sqlContext.sparkSession.sessionState.conf.setConfString("spark.sql.parquet.enableVectorizedReader", "false") + val pushDownFilter = { + val isNotNullFilter = IsNotNull(HoodieRecord.COMMIT_TIME_METADATA_FIELD) + val largerThanFilter = GreaterThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.head.getTimestamp) + val lessThanFilter = LessThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.last.getTimestamp) + filters :+isNotNullFilter :+ largerThanFilter :+ lessThanFilter + } + var requiredStructSchema = StructType(Seq()) + requiredColumns.foreach(col => { + val field = tableStructSchema.find(_.name == col) + if (field.isDefined) { + requiredStructSchema = requiredStructSchema.add(field.get) + } + }) + val requiredAvroSchema = AvroConversionUtils + .convertStructTypeToAvroSchema(requiredStructSchema, tableAvroSchema.getName, tableAvroSchema.getNamespace) + val hoodieTableState = HoodieMergeOnReadTableState( + tableStructSchema, + requiredStructSchema, + tableAvroSchema.toString, + requiredAvroSchema.toString, + fileIndex + ) + val fullSchemaParquetReader = new ParquetFileFormat().buildReaderWithPartitionValues( + sparkSession = sqlContext.sparkSession, + dataSchema = tableStructSchema, + partitionSchema = StructType(Nil), + requiredSchema = tableStructSchema, + filters = pushDownFilter, + options = optParams, + hadoopConf = sqlContext.sparkSession.sessionState.newHadoopConf() + ) + val requiredSchemaParquetReader = new ParquetFileFormat().buildReaderWithPartitionValues( + sparkSession = sqlContext.sparkSession, + dataSchema = tableStructSchema, + partitionSchema = StructType(Nil), + requiredSchema = requiredStructSchema, + filters = pushDownFilter, + options = optParams, + hadoopConf = sqlContext.sparkSession.sessionState.newHadoopConf() + ) + + // Follow the implementation of Spark internal HadoopRDD to handle the broadcast configuration. + FileSystem.getLocal(jobConf) + SparkHadoopUtil.get.addCredentials(jobConf) + val rdd = new HoodieMergeOnReadRDD( + sqlContext.sparkContext, + jobConf, + fullSchemaParquetReader, + requiredSchemaParquetReader, + hoodieTableState + ) + rdd.asInstanceOf[RDD[Row]] + } + + def buildFileIndex(): List[HoodieMergeOnReadFileSplit] = { + val affectedFileStatus = new ListBuffer[FileStatus] + for (commit <- commitsToReturn) { + val metadata: HoodieCommitMetadata = HoodieCommitMetadata.fromBytes(commitsTimelineToReturn.getInstantDetails(commit) + .get, classOf[HoodieCommitMetadata]) + val idWithPath = metadata.getFileIdAndFullPaths(metaClient.getBasePath).toMap + idWithPath.foreach(p => { + val file = fs.getFileStatus(new Path(p._2)) + affectedFileStatus += file + }) + } + val fsView = new HoodieTableFileSystemView(metaClient, + commitsTimelineToReturn, affectedFileStatus.toArray) + val fileGroup = fsView.fetchAllStoredFileGroups().iterator().toList + val latestCommit = fsView.getLastInstant.get().getTimestamp + if (log.isDebugEnabled) { + fileGroup.foreach(f => log.debug(s"current file group id: " + + s"${f.getFileGroupId} and file slices ${f.getLatestFileSlice.get().toString}")) + } + val pathGlobPattern = optParams.getOrElse( + DataSourceReadOptions.INCR_PATH_GLOB_OPT_KEY, + DataSourceReadOptions.DEFAULT_INCR_PATH_GLOB_OPT_VAL) + val filteredFileGroup = if(!pathGlobPattern + .equals(DataSourceReadOptions.DEFAULT_INCR_PATH_GLOB_OPT_VAL)) { + val globMatcher = new GlobPattern("*" + pathGlobPattern) + fileGroup.filter(f => { + if (f.getLatestFileSlice.get().getBaseFile.isPresent) { + globMatcher.matches(f.getLatestFileSlice.get().getBaseFile.get.getPath) + } else { + globMatcher.matches(f.getLatestFileSlice.get().getLatestLogFile.get().getPath.toString) + } + }) + } else { + fileGroup + } + + filteredFileGroup.map(f => { + val baseFile = f.getLatestDataFile Review comment: correct, that's what I was trying to do here. sure, keep only one incremental query type makes sense to me. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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