advancedxy commented on code in PR #206: URL: https://github.com/apache/arrow-datafusion-comet/pull/206#discussion_r1529591834
########## common/src/main/scala/org/apache/spark/sql/comet/execution/arrow/CometArrowConverters.scala: ########## @@ -0,0 +1,117 @@ +/* + * 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.comet.execution.arrow + +import scala.collection.JavaConverters.asScalaBufferConverter + +import org.apache.arrow.vector.VectorSchemaRoot +import org.apache.spark.TaskContext +import org.apache.spark.internal.Logging +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.execution.arrow.ArrowWriter +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.util.ArrowUtils +import org.apache.spark.sql.vectorized.ColumnarBatch + +import org.apache.comet.vector.CometVector + +object CometArrowConverters extends Logging { + // this is similar how Spark converts internal row to Arrow format except that we are transforming + // the result batch to Comet's Internal ColumnarBatch instead of serialized bytes. + private[sql] class ArrowBatchIterator( + rowIter: Iterator[InternalRow], + schema: StructType, + maxRecordsPerBatch: Long, + timeZoneId: String, + context: TaskContext) + extends Iterator[ColumnarBatch] + with AutoCloseable { + + // todo: hmm, we need to handle arrow shading problem, as Spark may use a different version of + // arrow. + private val arrowSchema = + ArrowUtils.toArrowSchema(schema, timeZoneId) + // Reuse the same root allocator here, maybe we should also reuse the same allocator in the + // comet code base + private val allocator = + ArrowUtils.rootAllocator.newChildAllocator( + s"to${this.getClass.getSimpleName}", + 0, + Long.MaxValue) + + private val root = VectorSchemaRoot.create(arrowSchema, allocator) + private val arrowWriter = ArrowWriter.create(root) + private var columnarBatch: ColumnarBatch = null + + Option(context).foreach { + _.addTaskCompletionListener[Unit] { _ => + close() + } + } + + override def hasNext: Boolean = rowIter.hasNext || { + close() + false + } + + override def next(): ColumnarBatch = { + if (columnarBatch != null) { + // reset the arrowWrite and columnarBatch. The reset method is called only after the + // columnarBatch is consumed by the caller. + arrowWriter.reset() + columnarBatch = null + } + var rowCount = 0L + while (rowIter.hasNext && (maxRecordsPerBatch <= 0 || rowCount < maxRecordsPerBatch)) { + val row = rowIter.next() + arrowWriter.write(row) + rowCount += 1 + } + arrowWriter.finish() + columnarBatch = wrapperFor(root) + columnarBatch + } + + override def close(): Unit = { + if (columnarBatch != null) { + arrowWriter.reset() + columnarBatch = null + } + root.close() + allocator.close() + } + } + + private def wrapperFor(root: VectorSchemaRoot) = { + val columns = root.getFieldVectors.asScala.map { vector => + CometVector.getVector(vector, false) + } + new ColumnarBatch(columns.toArray, root.getRowCount) + } + + def toArrowBatchIterator( Review Comment: > Regarding memory management, it would be nice if we can somehow hook it with the TaskMemoryManager since the row to columnar conversion does require non-trivial amount of memory. It might be fine as long as the memory occupied by the record batch is released timely. In theory, the additional memory required by `row to columnar` is only **one** `RecordBatch`'s memory. Of course, it would be nice that `TaskMemoryManager` is aware of that allocation. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
