[CARBONDATA-1790] (Carbon1.3.0 - Streaming) Data load in Stream Segment fails if batch load is performed in between the streaming

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 1.3.0
• Component/s: data-query
• Labels: DFX
• Environment: 3 node ant cluster
• Assignee: Bhavya Aggarwal
• Reporter: Ramakrishna S
• Due: 31/Dec/17
• Created: 21/Nov/17 13:45
• Updated: 02/Jan/18 04:59
• Resolved: 02/Jan/18 04:59

Description

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-rr- 2 root users 62 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/0
rw-rr- 2 root users 63 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/1
rw-rr- 2 root users 63 2017-11-21 21:42 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/10
rw-rr- 2 root users 63 2017-11-21 21:40 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/2
rw-rr- 2 root users 63 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/3
rw-rr- 2 root users 64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/4
rw-rr- 2 root users 64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/5
rw-rr- 2 root users 64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/6
rw-rr- 2 root users 64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/7
rw-rr- 2 root users 64 2017-11-21 21:41 /user/hive/warehouse/Ram/default/stream_table5/.streaming/checkpoint/offsets/8
rw-rr- 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

Issue Links

• is cloned by: CARBONDATA-1794 Table delete in Beeline does not work on stream table