Question

我正在尝试使用集合生成一些测试数据，并将该数据写入s3，当我这样做时，Flink似乎根本没有做任何检查点，但它确实在源来自s3时进行了检查点。

例如，这个DOES检查点并使输出文件保持完成状态：

val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
env.setMaxParallelism(128)
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.enableCheckpointing(2000L)
env.setStateBackend(new RocksDBStateBackend("s3a://my_bucket/simple_job/rocksdb_checkpoints"))

val lines: DataStream[String] = {
  val path = "s3a://my_bucket/simple_job/in"
  env
    .readFile(
      inputFormat = new TextInputFormat(new Path(path)),
      filePath = path,
      watchType = FileProcessingMode.PROCESS_CONTINUOUSLY,
      interval = 5000L
    )
}

val sinkFunction: BucketingSink[String] =
  new BucketingSink[String]("s3a://my_bucket/simple_job/out")
    .setBucketer(new DateTimeBucketer("yyyy-MM-dd--HHmm"))

lines.addSink(sinkFunction)

env.execute()

同时，这不是检查点，即使在作业完成后也会将文件保留在.pending状态：

val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
env.setMaxParallelism(128)
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.enableCheckpointing(2000L)
env.setStateBackend(new RocksDBStateBackend("s3a://my_bucket/simple_job/rocksdb_checkpoints"))

val lines: DataStream[String] = env.fromCollection((1 to 100).map(_.toString))

val sinkFunction: BucketingSink[String] =
  new BucketingSink[String]("s3a://my_bucket/simple_job/out")
    .setBucketer(new DateTimeBucketer("yyyy-MM-dd--HHmm"))

lines.addSink(sinkFunction)

env.execute()

Answer 1

事实证明，这是因为这张票：https://issues.apache.org/jira/browse/FLINK-2646而且只是因为来自集合的流在应用程序有时间制作单个检查点之前完成。

当从Collection生成源时，Flink不会检查点，BucketingSink会将文件保留为挂起状态

1 个答案: