garyli1019 commented on a change in pull request #1848: URL: https://github.com/apache/hudi/pull/1848#discussion_r459230287
########## File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.scala ########## @@ -0,0 +1,195 @@ +/* + * 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.fs.FSUtils +import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils} +import org.apache.hudi.exception.HoodieException +import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig} +import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS + +import org.apache.avro.Schema +import org.apache.hadoop.conf.Configuration +import org.apache.spark.broadcast.Broadcast +import org.apache.spark.{Partition, SparkContext, TaskContext} +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters} +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.execution.datasources.PartitionedFile +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.vectorized.ColumnarBatch + +import scala.collection.JavaConverters._ +import scala.util.Try + +case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition + +class HudiMergeOnReadRDD(sc: SparkContext, + broadcastedConf: Broadcast[HadoopSerializableConfiguration], + dataReadFunction: PartitionedFile => Iterator[Any], + dataSchema: StructType, + hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) + extends RDD[InternalRow](sc, Nil) { + + // Broadcast the hadoop Configuration to executors. + def this(sc: SparkContext, + config: Configuration, + dataReadFunction: PartitionedFile => Iterator[Any], + dataSchema: StructType, + hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = { + this( + sc, + sc.broadcast(new HadoopSerializableConfiguration(config)) + .asInstanceOf[Broadcast[HadoopSerializableConfiguration]], + dataReadFunction, + dataSchema, + hudiRealtimeFileSplits) + } + + override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = { + val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition] + mergeParquetPartition.split match { + case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty => + read(mergeParquetPartition.split.dataFile, dataReadFunction) + case unMergeSplit if unMergeSplit.skipMerge => + unMergeFileIterator(mergeParquetPartition.split, dataReadFunction) + case mergeSplit if !mergeSplit.skipMerge => + mergeFileIterator(mergeParquetPartition.split, dataReadFunction) + case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split") + } + } + + override protected def getPartitions: Array[Partition] = { + hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray + } + + private def getConfig(): Configuration = { + broadcastedConf.value.config + } + + private def read(partitionedFile: PartitionedFile, + readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = { + val fileIterator = readFileFunction(partitionedFile) + val rows = fileIterator.flatMap(_ match { + case r: InternalRow => Seq(r) + case b: ColumnarBatch => b.rowIterator().asScala + }) + rows + } + + private def unMergeFileIterator(split: HudiMergeOnReadFileSplit, + readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = + new Iterator[InternalRow] { + private val dataFileIterator = read(split.dataFile, readFileFunction) + private val logSchema = getLogAvroSchema(split) + private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType] + private val converter = new AvroDeserializer(logSchema, sparkTypes) + private val hudiLogRecords = scanLog(split, logSchema).getRecords + private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala + + override def hasNext: Boolean = { + dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext + } + + override def next(): InternalRow = { + if (dataFileIterator.hasNext) { + dataFileIterator.next() + } else { + val curAvrokey = hudiLogRecordsIterator.next() + val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get() + converter.deserialize(curAvroRecord).asInstanceOf[InternalRow] + } + } + } + + private def mergeFileIterator(split: HudiMergeOnReadFileSplit, + readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = + new Iterator[InternalRow] { + private val dataFileIterator = read(split.dataFile, readFileFunction) + private val logSchema = getLogAvroSchema(split) + private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType] + private val converter = new AvroDeserializer(logSchema, sparkTypes) + private val hudiLogRecords = scanLog(split, logSchema).getRecords + private var parquetFinished = false + private var logRecordToRead = hudiLogRecords.keySet() + private var hudiLogRecordsIterator: Iterator[String] = _ + + override def hasNext: Boolean = { + if (dataFileIterator.hasNext) { + true + } else { + if (!parquetFinished) { + parquetFinished = true + hudiLogRecordsIterator = logRecordToRead.iterator().asScala + } + hudiLogRecordsIterator.hasNext Review comment: One partitioned file will go into one split if I understand this correctly https://github.com/apache/spark/blob/branch-2.4/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala#L355 That would be difficult to handle if Spark split one parquet into two splits somewhere else. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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