Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/4450#discussion_r29118645
--- Diff:
core/src/main/scala/org/apache/spark/util/collection/PartitionedSerializedPairBuffer.scala
---
@@ -0,0 +1,254 @@
+/*
+ * 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.util.collection
+
+import java.io.InputStream
+import java.nio.IntBuffer
+import java.util.Comparator
+
+import org.apache.spark.SparkEnv
+import org.apache.spark.serializer.{JavaSerializerInstance,
SerializerInstance}
+import org.apache.spark.storage.BlockObjectWriter
+import org.apache.spark.util.collection.PartitionedSerializedPairBuffer._
+
+/**
+ * Append-only buffer of key-value pairs, each with a corresponding
partition ID, that serializes
+ * its records upon insert and stores them as raw bytes.
+ *
+ * We use two data-structures to store the contents. The serialized
records are stored in a
+ * ChainedBuffer that can expand gracefully as records are added. This
buffer is accompanied by a
+ * metadata buffer that stores pointers into the data buffer as well as
the partition ID of each
+ * record. Each entry in the metadata buffer takes up a fixed amount of
space.
+ *
+ * Sorting the collection means swapping entries in the metadata buffer -
the record buffer need not
+ * be modified at all. Storing the partition IDs in the metadata buffer
means that comparisons can
+ * happen without following any pointers, which should minimize cache
misses.
+ *
+ * Currently, only sorting by partition is supported.
+ *
+ * @param metaInitialRecords The initial number of entries in the metadata
buffer.
+ * @param kvBlockSize The size of each byte buffer in the ChainedBuffer
used to store the records.
+ * @param serializerInstance the serializer used for serializing inserted
records.
+ */
+private[spark] class PartitionedSerializedPairBuffer[K, V](
+ metaInitialRecords: Int,
+ kvBlockSize: Int,
+ serializerInstance: SerializerInstance =
SparkEnv.get.serializer.newInstance)
+ extends WritablePartitionedPairCollection[K, V] {
+
+ if (serializerInstance.isInstanceOf[JavaSerializerInstance]) {
+ throw new IllegalArgumentException("PartitionedSerializedPairBuffer
does not support" +
+ " Java-serialized objects.")
+ }
+
+ private var metaBuffer = IntBuffer.allocate(metaInitialRecords * NMETA)
+
+ private val kvBuffer: ChainedBuffer = new ChainedBuffer(kvBlockSize)
+ private val kvOutputStream = new ChainedBufferOutputStream(kvBuffer)
+ private val kvSerializationStream =
serializerInstance.serializeStream(kvOutputStream)
+
+ def insert(partition: Int, key: K, value: V): Unit = {
+ if (metaBuffer.position == metaBuffer.capacity) {
+ growMetaBuffer()
+ }
+
+ val keyStart = kvBuffer.size
+ if (keyStart < 0) {
+ throw new Exception(s"Can't grow buffer beyond ${1 << 31} bytes")
+ }
+ kvSerializationStream.writeObject[Any](key)
+ kvSerializationStream.flush()
+ val valueStart = kvBuffer.size
+ kvSerializationStream.writeObject[Any](value)
+ kvSerializationStream.flush()
+ val valueEnd = kvBuffer.size
+
+ metaBuffer.put(keyStart)
+ metaBuffer.put(valueStart)
+ metaBuffer.put(valueEnd)
+ metaBuffer.put(partition)
+ }
+
+ /** Double the size of the array because we've reached capacity */
+ private def growMetaBuffer(): Unit = {
+ if (metaBuffer.capacity * 4 >= (1 << 30)) {
+ // Doubling the capacity would create an array bigger than
Int.MaxValue, so don't
+ throw new Exception(
+ s"Can't grow buffer beyond ${(1 << 30) / (NMETA * 4)} elements")
+ }
+ val newMetaBuffer = IntBuffer.allocate(metaBuffer.capacity * 2)
+ newMetaBuffer.put(metaBuffer.array)
+ metaBuffer = newMetaBuffer
+ }
+
+ /** Iterate through the data in a given order. For this class this is
not really destructive. */
+ override def partitionedDestructiveSortedIterator(keyComparator:
Comparator[K])
+ : Iterator[((Int, K), V)] = {
+ sort(keyComparator)
+ val is = orderedInputStream
+ val deserStream = serializerInstance.deserializeStream(is)
+ new Iterator[((Int, K), V)] {
+ var metaBufferPos = 0
+ def hasNext: Boolean = metaBufferPos < metaBuffer.position
+ def next(): ((Int, K), V) = {
+ val key = deserStream.readObject[Any]().asInstanceOf[K]
+ val value = deserStream.readObject[Any]().asInstanceOf[V]
+ val partition = metaBuffer.get(metaBufferPos + PARTITION)
+ metaBufferPos += NMETA
+ ((partition, key), value)
+ }
+ }
+ }
+
+ override def estimateSize: Long = metaBuffer.capacity * 4 +
kvBuffer.capacity
--- End diff --
Should this use NMETA (or RECORD_SIZE if you change it)?
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