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[SPARK-14078] Streaming Parquet Based FileSink #11897
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81 changes: 81 additions & 0 deletions
81
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FileStreamSink.scala
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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. | ||
*/ | ||
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package org.apache.spark.sql.execution.streaming | ||
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import java.util.UUID | ||
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import org.apache.hadoop.fs.Path | ||
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import org.apache.spark.internal.Logging | ||
import org.apache.spark.sql.{DataFrame, SQLContext} | ||
import org.apache.spark.sql.sources.FileFormat | ||
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object FileStreamSink { | ||
// The name of the subdirectory that is used to store metadata about which files are valid. | ||
val metadataDir = "_spark_metadata" | ||
} | ||
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/** | ||
* A sink that writes out results to parquet files. Each batch is written out to a unique | ||
* directory. After all of the files in a batch have been succesfully written, the list of | ||
* file paths is appended to the log atomically. In the case of partial failures, some duplicate | ||
* data may be present in the target directory, but only one copy of each file will be present | ||
* in the log. | ||
*/ | ||
class FileStreamSink( | ||
sqlContext: SQLContext, | ||
path: String, | ||
fileFormat: FileFormat) extends Sink with Logging { | ||
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private val basePath = new Path(path) | ||
private val logPath = new Path(basePath, FileStreamSink.metadataDir) | ||
private val fileLog = new HDFSMetadataLog[Seq[String]](sqlContext, logPath.toUri.toString) | ||
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override def addBatch(batchId: Long, data: DataFrame): Unit = { | ||
if (fileLog.get(batchId).isDefined) { | ||
logInfo(s"Skipping already committed batch $batchId") | ||
} else { | ||
val files = writeFiles(data) | ||
if (fileLog.add(batchId, files)) { | ||
logInfo(s"Committed batch $batchId") | ||
} else { | ||
logWarning(s"Race while writing batch $batchId") | ||
} | ||
} | ||
} | ||
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/** Writes the [[DataFrame]] to a UUID-named dir, returning the list of files paths. */ | ||
private def writeFiles(data: DataFrame): Seq[String] = { | ||
val ctx = sqlContext | ||
val outputDir = path | ||
val format = fileFormat | ||
val schema = data.schema | ||
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val file = new Path(basePath, UUID.randomUUID().toString).toUri.toString | ||
data.write.parquet(file) | ||
sqlContext.read | ||
.schema(data.schema) | ||
.parquet(file) | ||
.inputFiles | ||
.map(new Path(_)) | ||
.filterNot(_.getName.startsWith("_")) | ||
.map(_.toUri.toString) | ||
} | ||
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override def toString: String = s"FileSink[$path]" | ||
} |
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59 changes: 59 additions & 0 deletions
59
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamFileCatalog.scala
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,59 @@ | ||
/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.streaming | ||
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import org.apache.hadoop.fs.{FileStatus, Path} | ||
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import org.apache.spark.internal.Logging | ||
import org.apache.spark.sql.SQLContext | ||
import org.apache.spark.sql.catalyst.InternalRow | ||
import org.apache.spark.sql.catalyst.expressions.Expression | ||
import org.apache.spark.sql.execution.datasources.PartitionSpec | ||
import org.apache.spark.sql.sources.{FileCatalog, Partition} | ||
import org.apache.spark.sql.types.StructType | ||
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class StreamFileCatalog(sqlContext: SQLContext, path: Path) extends FileCatalog with Logging { | ||
val metadataDirectory = new Path(path, FileStreamSink.metadataDir) | ||
logInfo(s"Reading streaming file log from $metadataDirectory") | ||
val metadataLog = new HDFSMetadataLog[Seq[String]](sqlContext, metadataDirectory.toUri.toString) | ||
val fs = path.getFileSystem(sqlContext.sparkContext.hadoopConfiguration) | ||
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override def paths: Seq[Path] = path :: Nil | ||
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override def partitionSpec(): PartitionSpec = PartitionSpec(StructType(Nil), Nil) | ||
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/** | ||
* Returns all valid files grouped into partitions when the data is partitioned. If the data is | ||
* unpartitioned, this will return a single partition with not partition values. | ||
* | ||
* @param filters the filters used to prune which partitions are returned. These filters must | ||
* only refer to partition columns and this method will only return files | ||
* where these predicates are guaranteed to evaluate to `true`. Thus, these | ||
* filters will not need to be evaluated again on the returned data. | ||
*/ | ||
override def listFiles(filters: Seq[Expression]): Seq[Partition] = | ||
Partition(InternalRow.empty, allFiles()) :: Nil | ||
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override def getStatus(path: Path): Array[FileStatus] = fs.listStatus(path) | ||
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override def refresh(): Unit = {} | ||
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override def allFiles(): Seq[FileStatus] = { | ||
fs.listStatus(metadataLog.get(None, None).flatMap(_._2).map(new Path(_))) | ||
} | ||
} |
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@@ -27,6 +27,8 @@ import org.apache.spark.sql.test.SharedSQLContext | |
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class HDFSMetadataLogSuite extends SparkFunSuite with SharedSQLContext { | ||
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private implicit def toOption[A](a: A): Option[A] = Option(a) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. nit: remove it There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. it (or some other change) is required for compilation |
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test("basic") { | ||
withTempDir { temp => | ||
val metadataLog = new HDFSMetadataLog[String](sqlContext, temp.getAbsolutePath) | ||
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This is the file source :D
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Haha, yes. I'll fix this in a follow up.