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/*
* 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.json
import java.io.CharArrayWriter
import com.fasterxml.jackson.core.JsonFactory
import com.google.common.base.Objects
import org.apache.hadoop.fs.{FileStatus, Path}
import org.apache.hadoop.io.{Text, LongWritable, NullWritable}
import org.apache.hadoop.mapred.{JobConf, TextInputFormat}
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat
import org.apache.hadoop.mapreduce.{RecordWriter, TaskAttemptContext, Job}
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat
import org.apache.spark.Logging
import org.apache.spark.mapred.SparkHadoopMapRedUtil
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.execution.datasources.PartitionSpec
import org.apache.spark.sql.sources._
import org.apache.spark.sql.types.StructType
import org.apache.spark.sql.{AnalysisException, Row, SQLContext}
private[sql] class DefaultSource extends HadoopFsRelationProvider {
override def createRelation(
sqlContext: SQLContext,
paths: Array[String],
dataSchema: Option[StructType],
partitionColumns: Option[StructType],
parameters: Map[String, String]): HadoopFsRelation = {
val samplingRatio = parameters.get("samplingRatio").map(_.toDouble).getOrElse(1.0)
new JSONRelation(None, samplingRatio, dataSchema, None, partitionColumns, paths)(sqlContext)
}
}
private[sql] class JSONRelation(
val inputRDD: Option[RDD[String]],
val samplingRatio: Double,
val maybeDataSchema: Option[StructType],
val maybePartitionSpec: Option[PartitionSpec],
override val userDefinedPartitionColumns: Option[StructType],
override val paths: Array[String] = Array.empty[String])(@transient val sqlContext: SQLContext)
extends HadoopFsRelation(maybePartitionSpec) {
/** Constraints to be imposed on schema to be stored. */
private def checkConstraints(schema: StructType): Unit = {
if (schema.fieldNames.length != schema.fieldNames.distinct.length) {
val duplicateColumns = schema.fieldNames.groupBy(identity).collect {
case (x, ys) if ys.length > 1 => "\"" + x + "\""
}.mkString(", ")
throw new AnalysisException(s"Duplicate column(s) : $duplicateColumns found, " +
s"cannot save to JSON format")
}
}
override val needConversion: Boolean = false
private def createBaseRdd(inputPaths: Array[FileStatus]): RDD[String] = {
val job = new Job(sqlContext.sparkContext.hadoopConfiguration)
val conf = job.getConfiguration
val paths = inputPaths.map(_.getPath)
if (paths.nonEmpty) {
FileInputFormat.setInputPaths(job, paths: _*)
}
sqlContext.sparkContext.hadoopRDD(
conf.asInstanceOf[JobConf],
classOf[TextInputFormat],
classOf[LongWritable],
classOf[Text]).map(_._2.toString) // get the text line
}
override lazy val dataSchema = {
val jsonSchema = maybeDataSchema.getOrElse {
val files = cachedLeafStatuses().filterNot { status =>
val name = status.getPath.getName
name.startsWith("_") || name.startsWith(".")
}.toArray
InferSchema(
inputRDD.getOrElse(createBaseRdd(files)),
samplingRatio,
sqlContext.conf.columnNameOfCorruptRecord)
}
checkConstraints(jsonSchema)
jsonSchema
}
override def buildScan(
requiredColumns: Array[String],
filters: Array[Filter],
inputPaths: Array[FileStatus]): RDD[Row] = {
JacksonParser(
inputRDD.getOrElse(createBaseRdd(inputPaths)),
StructType(requiredColumns.map(dataSchema(_))),
sqlContext.conf.columnNameOfCorruptRecord).asInstanceOf[RDD[Row]]
}
override def equals(other: Any): Boolean = other match {
case that: JSONRelation =>
((inputRDD, that.inputRDD) match {
case (Some(thizRdd), Some(thatRdd)) => thizRdd eq thatRdd
case (None, None) => true
case _ => false
}) && paths.toSet == that.paths.toSet &&
dataSchema == that.dataSchema &&
schema == that.schema
case _ => false
}
override def hashCode(): Int = {
Objects.hashCode(
inputRDD,
paths.toSet,
dataSchema,
schema,
partitionColumns)
}
override def prepareJobForWrite(job: Job): OutputWriterFactory = {
new OutputWriterFactory {
override def newInstance(
path: String,
dataSchema: StructType,
context: TaskAttemptContext): OutputWriter = {
new JsonOutputWriter(path, dataSchema, context)
}
}
}
}
private[json] class JsonOutputWriter(
path: String,
dataSchema: StructType,
context: TaskAttemptContext)
extends OutputWriterInternal with SparkHadoopMapRedUtil with Logging {
val writer = new CharArrayWriter()
// create the Generator without separator inserted between 2 records
val gen = new JsonFactory().createGenerator(writer).setRootValueSeparator(null)
val result = new Text()
private val recordWriter: RecordWriter[NullWritable, Text] = {
new TextOutputFormat[NullWritable, Text]() {
override def getDefaultWorkFile(context: TaskAttemptContext, extension: String): Path = {
val uniqueWriteJobId = context.getConfiguration.get("spark.sql.sources.writeJobUUID")
val split = context.getTaskAttemptID.getTaskID.getId
new Path(path, f"part-r-$split%05d-$uniqueWriteJobId$extension")
}
}.getRecordWriter(context)
}
override def writeInternal(row: InternalRow): Unit = {
JacksonGenerator(dataSchema, gen, row)
gen.flush()
result.set(writer.toString)
writer.reset()
recordWriter.write(NullWritable.get(), result)
}
override def close(): Unit = {
gen.close()
recordWriter.close(context)
}
}
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