[
https://issues.apache.org/jira/browse/CARBONDATA-1794?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ramakrishna S updated CARBONDATA-1794:
--------------------------------------
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
was:
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
> (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
> Labels: DFX
>
> 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
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