Please could you explain how to use pluggable WAL? After I implement the WriteAheadLog abstract class, how can I use it? I want to use it with a Custom Reliable Receiver. I am using Spark 1.4.1.
Thanks! On 17 September 2015 at 16:40, Tathagata Das <t...@databricks.com> wrote: > Actually, the current WAL implementation (as of Spark 1.5) does not work > with S3 because S3 does not support flushing. Basically, the current > implementation assumes that after write + flush, the data is immediately > durable, and readable if the system crashes without closing the WAL file. > This does not work with S3 as data is durable only and only if the S3 file > output stream is cleanly closed. > > > > > On Thu, Sep 17, 2015 at 1:30 PM, Ted Yu <yuzhih...@gmail.com> wrote: > >> I assume you don't use Kinesis. >> >> Are you running Spark 1.5.0 ? >> If you must use S3, is switching to Kinesis possible ? >> >> Cheers >> >> On Thu, Sep 17, 2015 at 1:09 PM, Michal Čizmazia <mici...@gmail.com> >> wrote: >> >>> How to make Write Ahead Logs to work with S3? Any pointers welcome! >>> >>> It seems as a known issue: >>> https://issues.apache.org/jira/browse/SPARK-9215 >>> >>> I am getting this exception when reading write ahead log: >>> >>> Exception in thread "main" org.apache.spark.SparkException: Job aborted >>> due to stage failure: Task 0 in stage 5.0 failed 1 times, most recent >>> failure: Lost task 0.0 in stage 5.0 (TID 14, localhost): >>> org.apache.spark.SparkException: Could not read data from write ahead log >>> record >>> FileBasedWriteAheadLogSegment(s3ax://test/test/0/log-1442512871968-1442512931968,0,1721) >>> at >>> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.org >>> $apache$spark$streaming$rdd$WriteAheadLogBackedBlockRDD$$getBlockFromWriteAheadLog$1(WriteAheadLogBackedBlockRDD.scala:144) >>> at >>> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.compute(WriteAheadLogBackedBlockRDD.scala:170) >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) >>> at >>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70) >>> at >>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) >>> at org.apache.spark.scheduler.Task.run(Task.scala:70) >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >>> at java.lang.Thread.run(Thread.java:745) >>> Caused by: java.lang.NullPointerException >>> at >>> org.apache.spark.streaming.util.FileBasedWriteAheadLog.read(FileBasedWriteAheadLog.scala:106) >>> at >>> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.org >>> $apache$spark$streaming$rdd$WriteAheadLogBackedBlockRDD$$getBlockFromWriteAheadLog$1(WriteAheadLogBackedBlockRDD.scala:141) >>> ... 13 more >>> >>> >>> >> >
