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使用Spark从同一区域的多个s3桶中读取

宋淑婷 2019-04-22 17:06:10 227

我正在尝试从多个s3存储桶中读取文件。

最初桶应该在不同的区域,但看起来这是不可能的。

所以现在我已经将另一个桶复制到与要读取的第一个桶相同的区域,这与我正在执行spark作业的区域相同。

SparkSession设置:

val sparkConf = new SparkConf()

      .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .registerKryoClasses(Array(classOf[Event]))

    SparkSession.builder
      .appName("Merge application")
      .config(sparkConf)
      .getOrCreate()

使用创建SparkSession中的SQLContext调用的函数:

private def parseEvents(bucketPath: String, service: String)(

implicit sqlContext: SQLContext

): Try[RDD[Event]] =

Try(
  sqlContext.read
    .option("codec", "org.apache.hadoop.io.compress.GzipCodec")
    .json(bucketPath)
    .toJSON
    .rdd
    .map(buildEvent(_, bucketPath, service).get)
)

主流程:

for {

  bucketOnePath               <- buildBucketPath(config.bucketOne.name)
  _                           <- log(s"Reading events from $bucketOnePath")
  bucketOneEvents: RDD[Event] <- parseEvents(bucketOnePath, config.service)
  _                           <- log(s"Enriching events from $bucketOnePath with originating region data")
  bucketOneEventsWithRegion: RDD[Event] <- enrichEventsWithRegion(
    bucketOneEvents,
    config.bucketOne.region
  )

  bucketTwoPath               <- buildBucketPath(config.bucketTwo.name)
  _                           <- log(s"Reading events from $bucketTwoPath")
  bucketTwoEvents: RDD[Event] <- parseEvents(config.bucketTwo.name, config.service)
  _                           <- log(s"Enriching events from $bucketTwoPath with originating region data")
  bucketTwoEventsWithRegion: RDD[Event] <- enrichEventsWithRegion(
    bucketTwoEvents,
    config.bucketTwo.region
  )

  _                        <- log("Merging events")
  mergedEvents: RDD[Event] <- merge(bucketOneEventsWithRegion, bucketTwoEventsWithRegion)
  if mergedEvents.isEmpty() == false
  _ <- log("Grouping merged events by partition key")
  mergedEventsByPartitionKey: RDD[(EventsPartitionKey, Iterable[Event])] <- eventsByPartitionKey(
    mergedEvents
  )

  _ <- log(s"Storing merged events to ${config.outputBucket.name}")
  _ <- store(config.outputBucket.name, config.service, mergedEventsByPartitionKey)
} yield ()

我在日志中得到的错误(实际存储桶名称已更改,但实际名称确实存在):

19/04/09 13:10:20 INFO SparkContext: Created broadcast 4 from rdd at MergeApp.scala:141
19/04/09 13:10:21 INFO FileSourceScanExec: Planning scan with bin packing, max size: 134217728 bytes, open cost is considered as scanning 4194304 bytes.
org.apache.spark.sql.AnalysisException: Path does not exist: hdfs:someBucket2
我的stdout日志显示主要代码在失败之前走了多远:

Reading events from s3://someBucket/////*.gz
Enriching events from s3://someBucket/////*.gz with originating region data
Reading events from s3://someBucket2/////*.gz
Merge failed: Path does not exist: hdfs://someBucket2
奇怪的是,无论我选择哪个桶,第一次读取总是有效。但是第二次读取总是失败,无论是什么桶。这告诉我水桶没什么问题,但是在使用多个s3水桶时会有些奇怪。

我只能看到从单个s3存储桶读取多个文件的线程,而不是来自多个s3存储桶的多个文件。

存储 JSON 分布式计算 Spark 数据格式
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全部回答(1)
  • 宋淑婷
    2019-07-17 23:34:00

    你在someBucket2路径中缺少一个s3://前缀,所以它试图(默认)在hdfs中找到它

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