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[SPARK-18087] [SQL] Optimize insert to not require REPAIR TABLE #15633

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[SPARK-18087] [SQL] Optimize insert to not require REPAIR TABLE #15633

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8c4ae5e
Thu Oct 27 14:45:52 PDT 2016
ericl Oct 27, 2016
2484809
Thu Oct 27 17:53:13 PDT 2016
ericl Oct 28, 2016
4d96725
Thu Oct 27 17:53:29 PDT 2016
ericl Oct 28, 2016
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2 changes: 1 addition & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -528,7 +528,7 @@ case class DataSource(
columns,
bucketSpec,
format,
() => Unit, // No existing table needs to be refreshed.
_ => Unit, // No existing table needs to be refreshed.
options,
data.logicalPlan,
mode)
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27 changes: 17 additions & 10 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
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Expand Up @@ -26,6 +26,7 @@ import org.apache.spark.sql.catalyst.{CatalystConf, CatalystTypeConverters, Inte
import org.apache.spark.sql.catalyst.CatalystTypeConverters.convertToScala
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.catalog.{CatalogTable, SimpleCatalogRelation}
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
import org.apache.spark.sql.catalyst.expressions
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.planning.PhysicalOperation
Expand All @@ -34,7 +35,7 @@ import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project, Union}
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, UnknownPartitioning}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.execution.{RowDataSourceScanExec, SparkPlan}
import org.apache.spark.sql.execution.command.{AlterTableRecoverPartitionsCommand, DDLUtils, ExecutedCommandExec}
import org.apache.spark.sql.execution.command.{AlterTableAddPartitionCommand, DDLUtils, ExecutedCommandExec}
import org.apache.spark.sql.sources._
import org.apache.spark.sql.types._
import org.apache.spark.unsafe.types.UTF8String
Expand Down Expand Up @@ -179,24 +180,30 @@ case class DataSourceAnalysis(conf: CatalystConf) extends Rule[LogicalPlan] {
"Cannot overwrite a path that is also being read from.")
}

def refreshPartitionsCallback(updatedPartitions: Seq[TablePartitionSpec]): Unit = {
if (l.catalogTable.isDefined &&
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@cloud-fan cloud-fan Oct 30, 2016 •
edited
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shall we move this if out of the function? e.g.

val refreshPartitionsCallback = if (...) {
  ...
} else {
  _ => ()
}

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imo that is a little harder to read, since you have two anonymous function declarations instead of one.

l.catalogTable.get.partitionColumnNames.nonEmpty &&
l.catalogTable.get.partitionProviderIsHive) {
val metastoreUpdater = AlterTableAddPartitionCommand(
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shall we just copy the main logic of AlterTableAddPartitionCommand here? or we have to fetch the table metadata from metastore everytime.

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I'd rather keep it, since the fetch overhead is pretty small

l.catalogTable.get.identifier,
updatedPartitions.map(p => (p, None)),
ifNotExists = true)
metastoreUpdater.run(t.sparkSession)
}
t.location.refresh()
}

val insertCmd = InsertIntoHadoopFsRelationCommand(
outputPath,
query.resolve(t.partitionSchema, t.sparkSession.sessionState.analyzer.resolver),
t.bucketSpec,
t.fileFormat,
() => t.location.refresh(),
refreshPartitionsCallback,
t.options,
query,
mode)

if (l.catalogTable.isDefined && l.catalogTable.get.partitionColumnNames.nonEmpty &&
l.catalogTable.get.partitionProviderIsHive) {
// TODO(ekl) we should be more efficient here and only recover the newly added partitions
val recoverPartitionCmd = AlterTableRecoverPartitionsCommand(l.catalogTable.get.identifier)
Union(insertCmd, recoverPartitionCmd)
} else {
insertCmd
}
insertCmd
}
}

Expand Down
3 changes: 2 additions & 1 deletion .../scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelationCommand.scala
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Expand Up @@ -23,6 +23,7 @@ import org.apache.hadoop.fs.Path

import org.apache.spark.sql._
import org.apache.spark.sql.catalyst.catalog.BucketSpec
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
import org.apache.spark.sql.catalyst.expressions.Attribute
import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
import org.apache.spark.sql.execution.command.RunnableCommand
Expand All @@ -40,7 +41,7 @@ case class InsertIntoHadoopFsRelationCommand(
partitionColumns: Seq[Attribute],
bucketSpec: Option[BucketSpec],
fileFormat: FileFormat,
refreshFunction: () => Unit,
refreshFunction: (Seq[TablePartitionSpec]) => Unit,
options: Map[String, String],
@transient query: LogicalPlan,
mode: SaveMode)
Expand Down
12 changes: 12 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
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Expand Up @@ -30,6 +30,7 @@ import org.apache.hadoop.util.Shell
import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.Resolver
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
import org.apache.spark.sql.catalyst.expressions.{Cast, Literal}
import org.apache.spark.sql.types._

Expand Down Expand Up @@ -244,6 +245,17 @@ object PartitioningUtils {
}
}

/**
* Given a partition path fragment, e.g. `fieldOne=1/fieldTwo=2`, returns a parsed spec
* for that fragment, e.g. `Map(("fieldOne", "1"), ("fieldTwo", "2"))`.
*/
def parsePathFragment(pathFragment: String): TablePartitionSpec = {
pathFragment.split("/").map { kv =>
val pair = kv.split("=", 2)
(unescapePathName(pair(0)), unescapePathName(pair(1)))
}.toMap
}

/**
* Normalize the column names in partition specification, w.r.t. the real partition column names
* and case sensitivity. e.g., if the partition spec has a column named `monTh`, and there is a
Expand Down
29 changes: 20 additions & 9 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriteOutput.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@ package org.apache.spark.sql.execution.datasources

import java.util.{Date, UUID}

import scala.collection.mutable

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path
import org.apache.hadoop.mapreduce._
Expand All @@ -30,6 +32,7 @@ import org.apache.spark.internal.Logging
import org.apache.spark.mapred.SparkHadoopMapRedUtil
import org.apache.spark.sql.{Dataset, SparkSession}
import org.apache.spark.sql.catalyst.catalog.BucketSpec
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.physical.HashPartitioning
import org.apache.spark.sql.catalyst.InternalRow
Expand Down Expand Up @@ -85,7 +88,7 @@ object WriteOutput extends Logging {
hadoopConf: Configuration,
partitionColumns: Seq[Attribute],
bucketSpec: Option[BucketSpec],
refreshFunction: () => Unit,
refreshFunction: (Seq[TablePartitionSpec]) => Unit,
options: Map[String, String],
isAppend: Boolean): Unit = {

Expand Down Expand Up @@ -120,19 +123,19 @@ object WriteOutput extends Logging {
val committer = setupDriverCommitter(job, outputPath.toString, isAppend)

try {
sparkSession.sparkContext.runJob(queryExecution.toRdd,
val updatedPartitions = sparkSession.sparkContext.runJob(queryExecution.toRdd,
(taskContext: TaskContext, iter: Iterator[InternalRow]) => {
executeTask(
description = description,
sparkStageId = taskContext.stageId(),
sparkPartitionId = taskContext.partitionId(),
sparkAttemptNumber = taskContext.attemptNumber(),
iterator = iter)
})
}).flatten.distinct

committer.commitJob(job)
logInfo(s"Job ${job.getJobID} committed.")
refreshFunction()
refreshFunction(updatedPartitions.map(PartitioningUtils.parsePathFragment))
} catch { case cause: Throwable =>
logError(s"Aborting job ${job.getJobID}.", cause)
committer.abortJob(job, JobStatus.State.FAILED)
Expand All @@ -147,7 +150,7 @@ object WriteOutput extends Logging {
sparkStageId: Int,
sparkPartitionId: Int,
sparkAttemptNumber: Int,
iterator: Iterator[InternalRow]): Unit = {
iterator: Iterator[InternalRow]): Set[String] = {

val jobId = SparkHadoopWriter.createJobID(new Date, sparkStageId)
val taskId = new TaskID(jobId, TaskType.MAP, sparkPartitionId)
Expand Down Expand Up @@ -187,11 +190,12 @@ object WriteOutput extends Logging {
try {
Utils.tryWithSafeFinallyAndFailureCallbacks(block = {
// Execute the task to write rows out
writeTask.execute(iterator)
val outputPaths = writeTask.execute(iterator)
writeTask.releaseResources()

// Commit the task
SparkHadoopMapRedUtil.commitTask(committer, taskAttemptContext, jobId.getId, taskId.getId)
outputPaths
})(catchBlock = {
// If there is an error, release resource and then abort the task
try {
Expand All @@ -213,7 +217,7 @@ object WriteOutput extends Logging {
* automatically trigger task aborts.
*/
private trait ExecuteWriteTask {
def execute(iterator: Iterator[InternalRow]): Unit
def execute(iterator: Iterator[InternalRow]): Set[String]
def releaseResources(): Unit

final def filePrefix(split: Int, uuid: String, bucketId: Option[Int]): String = {
Expand All @@ -240,11 +244,12 @@ object WriteOutput extends Logging {
outputWriter
}

override def execute(iter: Iterator[InternalRow]): Unit = {
override def execute(iter: Iterator[InternalRow]): Set[String] = {
while (iter.hasNext) {
val internalRow = iter.next()
outputWriter.writeInternal(internalRow)
}
Set.empty
}

override def releaseResources(): Unit = {
Expand Down Expand Up @@ -327,7 +332,7 @@ object WriteOutput extends Logging {
newWriter
}

override def execute(iter: Iterator[InternalRow]): Unit = {
override def execute(iter: Iterator[InternalRow]): Set[String] = {
// We should first sort by partition columns, then bucket id, and finally sorting columns.
val sortingExpressions: Seq[Expression] =
description.partitionColumns ++ bucketIdExpression ++ sortColumns
Expand Down Expand Up @@ -375,6 +380,7 @@ object WriteOutput extends Logging {

// If anything below fails, we should abort the task.
var currentKey: UnsafeRow = null
val updatedPartitions = mutable.Set[String]()
while (sortedIterator.next()) {
val nextKey = getBucketingKey(sortedIterator.getKey).asInstanceOf[UnsafeRow]
if (currentKey != nextKey) {
Expand All @@ -386,13 +392,18 @@ object WriteOutput extends Logging {
logDebug(s"Writing partition: $currentKey")

currentWriter = newOutputWriter(currentKey, getPartitionString)
val partitionPath = getPartitionString(currentKey).getString(0)
if (partitionPath.nonEmpty) {
updatedPartitions.add(partitionPath)
}
}
currentWriter.writeInternal(sortedIterator.getValue)
}
if (currentWriter != null) {
currentWriter.close()
currentWriter = null
}
updatedPartitions.toSet
}

override def releaseResources(): Unit = {
Expand Down