[KYUUBI #5377] Spark engine query result save to file #5591
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| Original file line number | Diff line number | Diff line change |
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@@ -19,14 +19,16 @@ package org.apache.kyuubi.engine.spark.operation | |
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| import java.util.concurrent.RejectedExecutionException | ||
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| import scala.Array._ | ||
| import scala.collection.JavaConverters._ | ||
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| import org.apache.hadoop.fs.Path | ||
| import org.apache.spark.sql.DataFrame | ||
| import org.apache.spark.sql.kyuubi.SparkDatasetHelper._ | ||
| import org.apache.spark.sql.types._ | ||
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| import org.apache.kyuubi.{KyuubiSQLException, Logging} | ||
| import org.apache.kyuubi.config.KyuubiConf.{OPERATION_RESULT_MAX_ROWS, OPERATION_RESULT_SAVE_TO_FILE, OPERATION_RESULT_SAVE_TO_FILE_DIR, OPERATION_RESULT_SAVE_TO_FILE_MINSIZE} | ||
| import org.apache.kyuubi.engine.spark.KyuubiSparkUtil._ | ||
| import org.apache.kyuubi.engine.spark.session.SparkSessionImpl | ||
| import org.apache.kyuubi.operation.{ArrayFetchIterator, FetchIterator, IterableFetchIterator, OperationHandle, OperationState} | ||
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@@ -46,6 +48,8 @@ class ExecuteStatement( | |
| override def getOperationLog: Option[OperationLog] = Option(operationLog) | ||
| override protected def supportProgress: Boolean = true | ||
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| private var fetchOrcStatement: Option[FetchOrcStatement] = None | ||
| private var saveFileName: Option[String] = None | ||
| override protected def resultSchema: StructType = { | ||
| if (result == null || result.schema.isEmpty) { | ||
| new StructType().add("Result", "string") | ||
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@@ -64,6 +68,15 @@ class ExecuteStatement( | |
| OperationLog.removeCurrentOperationLog() | ||
| } | ||
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| override def close(): Unit = { | ||
| super.close() | ||
| fetchOrcStatement.foreach(_.close()) | ||
| saveFileName.foreach { p => | ||
| val path = new Path(p) | ||
| path.getFileSystem(spark.sparkContext.hadoopConfiguration).delete(path, true) | ||
| } | ||
| } | ||
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| protected def incrementalCollectResult(resultDF: DataFrame): Iterator[Any] = { | ||
| resultDF.toLocalIterator().asScala | ||
| } | ||
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@@ -158,6 +171,29 @@ class ExecuteStatement( | |
| override def iterator: Iterator[Any] = incrementalCollectResult(resultDF) | ||
| }) | ||
| } else { | ||
| val resultSaveEnabled = getSessionConf(OPERATION_RESULT_SAVE_TO_FILE, spark) | ||
| lazy val resultSaveThreshold = getSessionConf(OPERATION_RESULT_SAVE_TO_FILE_MINSIZE, spark) | ||
| if (hasResultSet && resultSaveEnabled && shouldSaveResultToFs( | ||
| resultMaxRows, | ||
| resultSaveThreshold, | ||
| result)) { | ||
| val sessionId = session.handle.identifier.toString | ||
| val savePath = session.sessionManager.getConf.get(OPERATION_RESULT_SAVE_TO_FILE_DIR) | ||
| saveFileName = Some(s"$savePath/$engineId/$sessionId/$statementId") | ||
| // Rename all col name to avoid duplicate columns | ||
| val colName = range(0, result.schema.size).map(x => "col" + x) | ||
| // df.write will introduce an extra shuffle for the outermost limit, and hurt performance | ||
| if (resultMaxRows > 0) { | ||
| result.toDF(colName: _*).limit(resultMaxRows).write | ||
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There was a problem hiding this comment. Use There was a problem hiding this comment. If the result has duplicate columns, we can not write it to file, so we rename all col name to avoid this case There was a problem hiding this comment. @lsm1 let's add such information to the comments There was a problem hiding this comment. there is another known issue as I mentioned in the issue comment
I think we should also add this known issue to the comment and create a new ticket to track this issue. |
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| .option("compression", "zstd").format("orc").save(saveFileName.get) | ||
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There was a problem hiding this comment. IIRC, the zstd implementation of ORC is powered by aircompressor, I'm not sure if it's powerful as zstd-jni does. Anyway, it's internal implementation detail, we can change it latter if we have better solution There was a problem hiding this comment. should we also make the written format configurable? There was a problem hiding this comment. I prefer to keep it internally, it may be out of control if we expose the internal implementation early There was a problem hiding this comment. [SPARK-33978][SQL] Support ZSTD compression in ORC data source Maybe we need a configuration item, or the Spark version less than 3.2.0 is compressed with zlib. 3.1.1 bin/spark-shell scala> spark.range(10).write.option("compression", "zstd").orc("/tmp/zstd")
java.lang.IllegalArgumentException: Codec [zstd] is not available. Available codecs are uncompressed, lzo, snappy, zlib, none.There was a problem hiding this comment. maybe it's time to have a discussion for dropping support of Spark 3.1 There was a problem hiding this comment. 😅we are still using spark 3.1， It need time to migrate to new spark version |
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| } else { | ||
| result.toDF(colName: _*).write | ||
| .option("compression", "zstd").format("orc").save(saveFileName.get) | ||
| } | ||
| info(s"Save result to $saveFileName") | ||
| fetchOrcStatement = Some(new FetchOrcStatement(spark)) | ||
| return fetchOrcStatement.get.getIterator(saveFileName.get, resultSchema) | ||
| } | ||
| val internalArray = if (resultMaxRows <= 0) { | ||
| info("Execute in full collect mode") | ||
| fullCollectResult(resultDF) | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,151 @@ | ||
| /* | ||
| * 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.kyuubi.engine.spark.operation | ||
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| import scala.Array._ | ||
| import scala.collection.mutable.ListBuffer | ||
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| import org.apache.hadoop.conf.Configuration | ||
| import org.apache.hadoop.fs.{LocatedFileStatus, Path} | ||
| import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType} | ||
| import org.apache.hadoop.mapreduce.lib.input.FileSplit | ||
| import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl | ||
| import org.apache.orc.mapred.OrcStruct | ||
| import org.apache.orc.mapreduce.OrcInputFormat | ||
| import org.apache.spark.sql.{Row, SparkSession} | ||
| import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow} | ||
| import org.apache.spark.sql.catalyst.expressions.AttributeReference | ||
| import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection | ||
| import org.apache.spark.sql.execution.datasources.RecordReaderIterator | ||
| import org.apache.spark.sql.execution.datasources.orc.OrcDeserializer | ||
| import org.apache.spark.sql.types.StructType | ||
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| import org.apache.kyuubi.KyuubiException | ||
| import org.apache.kyuubi.engine.spark.KyuubiSparkUtil.SPARK_ENGINE_RUNTIME_VERSION | ||
| import org.apache.kyuubi.operation.{FetchIterator, IterableFetchIterator} | ||
| import org.apache.kyuubi.util.reflect.DynConstructors | ||
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| class FetchOrcStatement(spark: SparkSession) { | ||
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| var orcIter: OrcFileIterator = _ | ||
| def getIterator(path: String, orcSchema: StructType): FetchIterator[Row] = { | ||
| val conf = spark.sparkContext.hadoopConfiguration | ||
| val savePath = new Path(path) | ||
| val fsIterator = savePath.getFileSystem(conf).listFiles(savePath, false) | ||
| val list = new ListBuffer[LocatedFileStatus] | ||
| while (fsIterator.hasNext) { | ||
| val file = fsIterator.next() | ||
| if (file.getPath.getName.endsWith(".orc") && file.getLen > 0) { | ||
| list += file | ||
| } | ||
| } | ||
| val toRowConverter: InternalRow => Row = { | ||
| CatalystTypeConverters.createToScalaConverter(orcSchema) | ||
| .asInstanceOf[InternalRow => Row] | ||
| } | ||
| val colId = range(0, orcSchema.size) | ||
| val fullSchema = orcSchema.map(f => | ||
| AttributeReference(f.name, f.dataType, f.nullable, f.metadata)()) | ||
| val unsafeProjection = GenerateUnsafeProjection.generate(fullSchema, fullSchema) | ||
| val deserializer = getOrcDeserializer(orcSchema, colId) | ||
| orcIter = new OrcFileIterator(list) | ||
| val iterRow = orcIter.map(value => | ||
| unsafeProjection(deserializer.deserialize(value))) | ||
| .map(value => toRowConverter(value)) | ||
| new IterableFetchIterator[Row](iterRow.toIterable) | ||
| } | ||
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| def close(): Unit = { | ||
| orcIter.close() | ||
| } | ||
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| private def getOrcDeserializer(orcSchema: StructType, colId: Array[Int]): OrcDeserializer = { | ||
| try { | ||
| if (SPARK_ENGINE_RUNTIME_VERSION >= "3.2") { | ||
| // SPARK-34535 changed the constructor signature of OrcDeserializer | ||
| DynConstructors.builder() | ||
| .impl(classOf[OrcDeserializer], classOf[StructType], classOf[Array[Int]]) | ||
| .build[OrcDeserializer]() | ||
| .newInstance( | ||
| orcSchema, | ||
| colId) | ||
| } else { | ||
| DynConstructors.builder() | ||
| .impl( | ||
| classOf[OrcDeserializer], | ||
| classOf[StructType], | ||
| classOf[StructType], | ||
| classOf[Array[Int]]) | ||
| .build[OrcDeserializer]() | ||
| .newInstance( | ||
| new StructType, | ||
| orcSchema, | ||
| colId) | ||
| } | ||
| } catch { | ||
| case e: Throwable => | ||
| throw new KyuubiException("Failed to create OrcDeserializer", e) | ||
| } | ||
| } | ||
| } | ||
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| class OrcFileIterator(fileList: ListBuffer[LocatedFileStatus]) extends Iterator[OrcStruct] { | ||
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| private val iters = fileList.map(x => getOrcFileIterator(x)) | ||
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| var idx = 0 | ||
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| override def hasNext: Boolean = { | ||
| val hasNext = iters(idx).hasNext | ||
| if (!hasNext) { | ||
| iters(idx).close() | ||
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| idx += 1 | ||
| // skip empty file | ||
| while (idx < iters.size) { | ||
| if (iters(idx).hasNext) { | ||
| return true | ||
| } else { | ||
| iters(idx).close() | ||
| idx = idx + 1 | ||
| } | ||
| } | ||
| } | ||
| hasNext | ||
| } | ||
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| override def next(): OrcStruct = { | ||
| iters(idx).next() | ||
| } | ||
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| def close(): Unit = { | ||
| iters.foreach(_.close()) | ||
| } | ||
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| private def getOrcFileIterator(file: LocatedFileStatus): RecordReaderIterator[OrcStruct] = { | ||
| val orcRecordReader = { | ||
| val split = | ||
| new FileSplit(file.getPath, 0, file.getLen, Array.empty[String]) | ||
| val attemptId = new TaskAttemptID(new TaskID(new JobID(), TaskType.MAP, 0), 0) | ||
| val hadoopAttemptContext = | ||
| new TaskAttemptContextImpl(new Configuration(), attemptId) | ||
| val oif = new OrcInputFormat[OrcStruct] | ||
| oif.createRecordReader(split, hadoopAttemptContext) | ||
| } | ||
| new RecordReaderIterator[OrcStruct](orcRecordReader) | ||
| } | ||
| } | ||
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