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Posted to issues@carbondata.apache.org by "Ramakrishna S (JIRA)" <ji...@apache.org> on 2017/11/22 06:15:00 UTC

[jira] [Created] (CARBONDATA-1794) (Carbon1.3.0 - Streaming) Data load in Stream Segment fails if batch load is performed in between the streaming

Ramakrishna S created CARBONDATA-1794:
-----------------------------------------

             Summary: (Carbon1.3.0 - Streaming) Data load in Stream Segment fails if batch load is performed in between the streaming
                 Key: CARBONDATA-1794
                 URL: https://issues.apache.org/jira/browse/CARBONDATA-1794
             Project: CarbonData
          Issue Type: Bug
          Components: data-query
    Affects Versions: 1.3.0
         Environment: 3 node ant cluster
            Reporter: Ramakrishna S


Steps :
1. Create a streaming table and do a batch load
2. Set up the Streaming , so that it does streaming in chunk of 1000 records 20 times
3. Do another batch load on the table
4. Do one more time streaming
+-------------+------------+--------------------------+--------------------------+--------------+------------+--+
| Segment Id  |   Status   |     Load Start Time      |      Load End Time       | File Format  | Merged To  |
+-------------+------------+--------------------------+--------------------------+--------------+------------+--+
| 2           | Success    | 2017-11-21 21:42:36.77   | 2017-11-21 21:42:40.396  | COLUMNAR_V3  | NA         |
| 1           | Streaming  | 2017-11-21 21:40:46.2    | NULL                     | ROW_V1       | NA         |
| 0           | Success    | 2017-11-21 21:40:39.782  | 2017-11-21 21:40:43.168  | COLUMNAR_V3  | NA         |
+-------------+------------+--------------------------+--------------------------+--------------+------------+--+


*+Expected:+* Data should be loaded
*+Actual+* : Data load fiails
1. One addition offset file is created(marked in bold)
-rw-r--r--   2 root users         62 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/0
-rw-r--r--   2 root users         63 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/1
-rw-r--r--   2 root users         63 2017-11-21 21:42 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/10
-rw-r--r--   2 root users         63 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/2
-rw-r--r--   2 root users         63 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/3
-rw-r--r--   2 root users         64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/4
-rw-r--r--   2 root users         64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/5
-rw-r--r--   2 root users         64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/6
-rw-r--r--   2 root users         64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/7
-rw-r--r--   2 root users         64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/8
*-rw-r--r--   2 root users         63 2017-11-21 21:42 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/9*
2. Following error thrown:
=== Streaming Query ===
Identifier: [id = 3a5334bc-d471-4676-b6ce-f21105d491d1, runId = b2be9f97-8141-46be-89db-9a0f98d13369]
Current Offsets: {org.apache.spark.sql.execution.streaming.TextSocketSource@14c45193: 1000}

Current State: ACTIVE
Thread State: RUNNABLE

Logical Plan:
org.apache.spark.sql.execution.streaming.TextSocketSource@14c45193




        at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:284)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:177)
Caused by: java.lang.RuntimeException: Offsets committed out of order: 20019 followed by 1000
        at scala.sys.package$.error(package.scala:27)
        at org.apache.spark.sql.execution.streaming.TextSocketSource.commit(socket.scala:151)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:421)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:420)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
        at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply$mcV$sp(StreamExecution.scala:420)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply(StreamExecution.scala:404)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply(StreamExecution.scala:404)
        at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:262)
        at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:46)
        at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch(StreamExecution.scala:404)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply$mcV$sp(StreamExecution.scala:250)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply(StreamExecution.scala:244)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply(StreamExecution.scala:244)
        at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:262)
        at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:46)
        at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:244)
        at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:43)
        at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:239)
        ... 1 more
Done reading and writing streaming data
Socket closed




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