spark delta如何读数据

小编给大家分享一下spark delta如何读数据，相信大部分人都还不怎么了解，因此分享这篇文章给大家参考一下，希望大家阅读完这篇文章后大有收获，下面让我们一起去了解一下吧！

分析

spark 的delta datasource的构建要从DataSource.lookupDataSourceV2开始，之后会流向到loadV1Source，这里会进行dataSource.createRelation进行构建datasource的Relation的构建,直接转到deltaDataSource 的createRelation：

override def createRelation(      sqlContext: SQLContext,      parameters: Map[String, String]): BaseRelation = {    val maybePath = parameters.getOrElse("path", {      throw DeltaErrors.pathNotSpecifiedException    })    // Log any invalid options that are being passed in    DeltaOptions.verifyOptions(CaseInsensitiveMap(parameters))    val timeTravelByParams = DeltaDataSource.getTimeTravelVersion(parameters)    DeltaTableV2(      sqlContext.sparkSession,      new Path(maybePath),      timeTravelOpt = timeTravelByParams).toBaseRelation  }

1. DeltaOptions.verifyOptions进行参数校验,有效的参数如下：

val validOptionKeys : Set[String] = Set(    REPLACE_WHERE_OPTION,    MERGE_SCHEMA_OPTION,    EXCLUDE_REGEX_OPTION,    OVERWRITE_SCHEMA_OPTION,    USER_METADATA_OPTION,    MAX_FILES_PER_TRIGGER_OPTION,    IGNORE_FILE_DELETION_OPTION,    IGNORE_CHANGES_OPTION,    IGNORE_DELETES_OPTION,    OPTIMIZE_WRITE_OPTION,    DATA_CHANGE_OPTION,    "queryName",    "checkpointLocation",    "path",    "timestampAsOf",    "versionAsOf"  )

2. DeltaDataSource.getTimeTravelVersion根据指定的timestampAsOf或者versionAsOf获取指定的版本

3. 直接调用DeltaTableV2的toBaseRelation方法：

def toBaseRelation: BaseRelation = {    if (deltaLog.snapshot.version == -1) {      val id = catalogTable.map(ct => DeltaTableIdentifier(table = Some(ct.identifier)))        .getOrElse(DeltaTableIdentifier(path = Some(path.toString)))      throw DeltaErrors.notADeltaTableException(id)    }    val partitionPredicates = DeltaDataSource.verifyAndCreatePartitionFilters(      path.toString, deltaLog.snapshot, partitionFilters)    // TODO(burak): We should pass in the snapshot here    deltaLog.createRelation(partitionPredicates, timeTravelSpec)  }

• 如果存在分区，则DeltaDataSource.verifyAndCreatePartitionFilter创建partitionPredicates

• timeTravelSpec，这里优先选择用户指定的timeTravelByParams，否则通过DeltaDataSource.parsePathIdentifier选择path指定的version，格式如:/some/path/partition=1@v1234 或者/some/path/partition=1@yyyyMMddHHmmssSSS

• 直接调用deltaLog.createRelation:

  def createRelation(   partitionFilters: Seq[Expression] = Nil,   timeTravel: Option[DeltaTimeTravelSpec] = None): BaseRelation = { val versionToUse = timeTravel.map { tt =>   val (version, accessType) = DeltaTableUtils.resolveTimeTravelVersion(     spark.sessionState.conf, this, tt)   val source = tt.creationSource.getOrElse("unknown")   recordDeltaEvent(this, s"delta.timeTravel.$source", data = Map(     "tableVersion" -> snapshot.version,     "queriedVersion" -> version,     "accessType" -> accessType   ))   version } /** Used to link the files present in the table into the query planner. */ val snapshotToUse = versionToUse.map(getSnapshotAt(_)).getOrElse(snapshot) val fileIndex = TahoeLogFileIndex(   spark, this, dataPath, snapshotToUse.metadata.schema, partitionFilters, versionToUse) new HadoopFsRelation(   fileIndex,   partitionSchema = snapshotToUse.metadata.partitionSchema,   dataSchema = snapshotToUse.metadata.schema,   bucketSpec = None,   snapshotToUse.fileFormat,   snapshotToUse.metadata.format.options)(spark) with InsertableRelation {   def insert(data: DataFrame, overwrite: Boolean): Unit = {     val mode = if (overwrite) SaveMode.Overwrite else SaveMode.Append     WriteIntoDelta(       deltaLog = DeltaLog.this,       mode = mode,       new DeltaOptions(Map.empty[String, String], spark.sessionState.conf),       partitionColumns = Seq.empty,       configuration = Map.empty,       data = data).run(spark)   } }

  override def inputFiles: Array[String] = {getSnapshot(stalenessAcceptable = false).filesForScan(  projection = Nil, partitionFilters).files.map(f => absolutePath(f.path).toString).toArray}

  
  

  该方法调用了snapshot的filesForScan方法：

  def filesForScan(projection: Seq[Attribute], filters: Seq[Expression]): DeltaScan = {implicit val enc = SingleAction.addFileEncoderval partitionFilters = filters.flatMap { filter =>  DeltaTableUtils.splitMetadataAndDataPredicates(filter, metadata.partitionColumns, spark)._1}val files = DeltaLog.filterFileList(  metadata.partitionSchema,  allFiles.toDF(),  partitionFilters).as[AddFile].collect()DeltaScan(version = version, files, null, null, null)(null, null, null, null)}

  
  

• . 通过指定版本获取对应的snapshot

• . 构建TahoeLogFileIndex，因为这里构建的是HadoopFsRelation，所以我们关注TahoeLogFileIndex的inputfiles方法：

通过之前文章的分析，我们直到deltalog记录了AddFile和Remove记录，那现在读数据怎么读取呢？全部在allFiles方法。
重点看一下：allFiles方法：

def allFiles: Dataset[AddFile] = { val implicits = spark.implicits import implicits._ state.where("add IS NOT NULL").select($"add".as[AddFile]) }

这里调用了state方法，而它又调用了stateReconstruction方法，

private lazy val cachedState = cacheDS(stateReconstruction, s"Delta Table State #$version - $redactedPath") /** The current set of actions in this [[Snapshot]]. */ def state: Dataset[SingleAction] = cachedState.getDS

stateReconstruction方法在checkpoint的时用到了，在这里也用到了，主要是重新构造文件状态，合并AddFile和RemoveFile：

private def stateReconstruction: Dataset[SingleAction] = { ... loadActions.mapPartitions { actions =>     val hdpConf = hadoopConf.value.value     actions.flatMap {       _.unwrap match {         case add: AddFile => Some(add.copy(path = canonicalizePath(add.path, hdpConf)).wrap)         case rm: RemoveFile => Some(rm.copy(path = canonicalizePath(rm.path, hdpConf)).wrap)         case other if other == null => None         case other => Some(other.wrap)       }     }    }   ...   .mapPartitions { iter =>     val state = new InMemoryLogReplay(time)     state.append(0, iter.map(_.unwrap))     state.checkpoint.map(_.wrap)   }  }

而关键在于InMemoryLogReplay的append方法和checkpoint方法，这里做到了文件状态的合并：

  assert(currentVersion == -1 || version == currentVersion + 1,   s"Attempted to replay version $version, but state is at $currentVersion") currentVersion = version actions.foreach {   case a: SetTransaction =>     transactions(a.appId) = a   case a: Metadata =>     currentMetaData = a   case a: Protocol =>     currentProtocolVersion = a   case add: AddFile =>     activeFiles(add.pathAsUri) = add.copy(dataChange = false)     // Remove the tombstone to make sure we only output one `FileAction`.     tombstones.remove(add.pathAsUri)   case remove: RemoveFile =>     activeFiles.remove(remove.pathAsUri)     tombstones(remove.pathAsUri) = remove.copy(dataChange = false)   case ci: CommitInfo => // do nothing   case null => // Some crazy future feature. Ignore  } }

重点就在case add: AddFile和 case remove: RemoveFile处理以及checkpoint方法，能够很好的合并文件状态。

再调用collect方法,返回DeltaScan，之后获取文件路径作为要处理的文件路径。

• 把TahoeLogFileIndex传入HadoopFsRelation得到最后的BaseRelation 返回

注意：spark读取delta格式整个流程和spark读取其他数据格式流程一致，主要区别在于读取数据之前，会把文件状态在内存中进行一次合并，这样只需要读取文件状态为Addfile的就行了

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