You could override the spark conf called "spark.streaming.receiver.writeAheadLog.class" with the class name. https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogUtils.scala#L30
On Thu, Sep 17, 2015 at 2:04 PM, Michal Čizmazia <mici...@gmail.com> wrote: > 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 >>>> >>>> >>>> >>> >> >
