umehrot2 commented on a change in pull request #1702: URL: https://github.com/apache/hudi/pull/1702#discussion_r447578932
########## File path: hudi-spark/src/main/scala/org/apache/hudi/HudiBootstrapRDD.scala ########## @@ -0,0 +1,131 @@ +/* + * 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.spark.{Partition, TaskContext} +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.SparkSession +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 + +class HudiBootstrapRDD(@transient spark: SparkSession, + dataReadFunction: PartitionedFile => Iterator[Any], + skeletonReadFunction: PartitionedFile => Iterator[Any], + regularReadFunction: PartitionedFile => Iterator[Any], + dataSchema: StructType, + skeletonSchema: StructType, + requiredColumns: Array[String], + tableState: HudiBootstrapTableState) + extends RDD[InternalRow](spark.sparkContext, Nil) { + + override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = { + val bootstrapPartition = split.asInstanceOf[HudiBootstrapPartition] + + if (log.isDebugEnabled) { + if (bootstrapPartition.split.skeletonFile.isDefined) { + logDebug("Got Split => Index: " + bootstrapPartition.index + ", Data File: " + + bootstrapPartition.split.dataFile.filePath + ", Skeleton File: " + + bootstrapPartition.split.skeletonFile.get.filePath) + } else { + logDebug("Got Split => Index: " + bootstrapPartition.index + ", Data File: " + + bootstrapPartition.split.dataFile.filePath) + } + } + + var partitionedFileIterator: Iterator[InternalRow] = null + + if (bootstrapPartition.split.skeletonFile.isDefined) { + // It is a bootstrap split. Check both skeleton and data files. + if (dataSchema.isEmpty) { + // No data column to fetch, hence fetch only from skeleton file + partitionedFileIterator = read(bootstrapPartition.split.skeletonFile.get, skeletonReadFunction) + } else if (skeletonSchema.isEmpty) { + // No metadata column to fetch, hence fetch only from data file + partitionedFileIterator = read(bootstrapPartition.split.dataFile, dataReadFunction) + } else { + // Fetch from both data and skeleton file, and merge + val dataFileIterator = read(bootstrapPartition.split.dataFile, dataReadFunction) + val skeletonFileIterator = read(bootstrapPartition.split.skeletonFile.get, skeletonReadFunction) + partitionedFileIterator = merge(skeletonFileIterator, dataFileIterator) + } + } else { + partitionedFileIterator = read(bootstrapPartition.split.dataFile, regularReadFunction) + } + partitionedFileIterator + } + + def merge(skeletonFileIterator: Iterator[InternalRow], dataFileIterator: Iterator[InternalRow]) + : Iterator[InternalRow] = { + new Iterator[InternalRow] { + override def hasNext: Boolean = dataFileIterator.hasNext && skeletonFileIterator.hasNext + override def next(): InternalRow = { + mergeInternalRow(skeletonFileIterator.next(), dataFileIterator.next()) + } + } + } + + def mergeInternalRow(skeletonRow: InternalRow, dataRow: InternalRow): InternalRow = { + val skeletonArr = skeletonRow.copy().toSeq(skeletonSchema) + val dataArr = dataRow.copy().toSeq(dataSchema) + // We need to return it in the order requested + val mergedArr = requiredColumns.map(col => { + if (skeletonSchema.fieldNames.contains(col)) { + val idx = skeletonSchema.fieldIndex(col) + skeletonArr(idx) + } else { + val idx = dataSchema.fieldIndex(col) + dataArr(idx) + } + }) + + logDebug("Merged data and skeleton values => " + mergedArr.mkString(",")) + val mergedRow = InternalRow.fromSeq(mergedArr) + mergedRow + } + + def read(partitionedFile: PartitionedFile, readFileFunction: PartitionedFile => Iterator[Any]) + : Iterator[InternalRow] = { + val fileIterator = readFileFunction(partitionedFile) + + import scala.collection.JavaConverters._ + + val rows = fileIterator.flatMap(_ match { + case r: InternalRow => Seq(r) + case b: ColumnarBatch => b.rowIterator().asScala Review comment: Will do some more research on this. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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