1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
|
/*
* 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.execution.datasources
import org.apache.spark.{Partition, TaskContext}
import org.apache.spark.rdd.{RDD, SqlNewHadoopRDDState}
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.InternalRow
/**
* A single file that should be read, along with partition column values that
* need to be prepended to each row. The reading should start at the first
* valid record found after `offset`.
*/
case class PartitionedFile(
partitionValues: InternalRow,
filePath: String,
start: Long,
length: Long) {
override def toString: String = {
s"path: $filePath, range: $start-${start + length}, partition values: $partitionValues"
}
}
/**
* A collection of files that should be read as a single task possibly from multiple partitioned
* directories.
*
* TODO: This currently does not take locality information about the files into account.
*/
case class FilePartition(index: Int, files: Seq[PartitionedFile]) extends Partition
class FileScanRDD(
@transient val sqlContext: SQLContext,
readFunction: (PartitionedFile) => Iterator[InternalRow],
@transient val filePartitions: Seq[FilePartition])
extends RDD[InternalRow](sqlContext.sparkContext, Nil) {
override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
val iterator = new Iterator[Object] with AutoCloseable {
private[this] val files = split.asInstanceOf[FilePartition].files.toIterator
private[this] var currentIterator: Iterator[Object] = null
def hasNext = (currentIterator != null && currentIterator.hasNext) || nextIterator()
def next() = currentIterator.next()
/** Advances to the next file. Returns true if a new non-empty iterator is available. */
private def nextIterator(): Boolean = {
if (files.hasNext) {
val nextFile = files.next()
logInfo(s"Reading File $nextFile")
SqlNewHadoopRDDState.setInputFileName(nextFile.filePath)
currentIterator = readFunction(nextFile)
hasNext
} else {
SqlNewHadoopRDDState.unsetInputFileName()
false
}
}
override def close() = {
SqlNewHadoopRDDState.unsetInputFileName()
}
}
// Register an on-task-completion callback to close the input stream.
context.addTaskCompletionListener(context => iterator.close())
iterator.asInstanceOf[Iterator[InternalRow]] // This is an erasure hack.
}
override protected def getPartitions: Array[Partition] = filePartitions.toArray
}
|
