[ 
https://issues.apache.org/jira/browse/CASSANDRA-14653?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Peter Xie updated CASSANDRA-14653:
----------------------------------
    Description: 
We use cassandra as backend storage for Janusgraph. when we loading huge data 
(~2 billion vertex, ~10 billion edges), we met some problems.

 

At first, we use STCS as compaction strategy , but met below exception.  we 
checked the value of  "max memory lock" is unlimited and "file map count" is 1 
million, these values should enough for loading data. last , we found this 
problem is caused by the virtual memory are all cosumed by cassandra.  So not 
additional virtual memory can be used by compaction task , and below exception 
is thrower out.   
{quote}ERROR [CompactionExecutor:267] 2018-08-09 02:28:40,952 
JVMStabilityInspector.javv
 a:74 - OutOfMemory error letting the JVM handle the error:
 java.lang.OutOfMemoryError: Map failed
{quote}
So, we change compaction strategy to LCS, this change seems can resolve the 
virtual memory problem. But we found another problem : Many sstables which has 
been compacted are still retained on disk, at last these old sstable consume so 
many disk space, it's causing no enough disk for saving real data. we found 
that so many files like "mc_txn_compaction_xxx.log" are created under the data 
directory. 

After some times' investigaton, we found that this problem is caused by 
"NonPeriodicTasks" thread pools.  this pools is always using only one thread 
for processing clean task and compaction. this thread pool is instanced with 
class DebuggableScheduledThreadPoolExecutor,

and DebuggableScheduledThreadPoolExecutor is inherit from class  
ScheduledThreadPoolExecutor.

By reading the code of class DebuggableScheduledThreadPoolExecutor,  found 
DebuggableScheduledThreadPoolExecutor is using an unbound task queue, and core 
pool size is 1.   Why here use the unbound queue for queuing submitted tasks?  
If we using unbound queue, the thread pool wouldn't  increasing thread even 
there so many task are blocked in queue, because unbound queue never would be 
full.  I think here should use bound queue, so when task is heavily, more 
threads would created for processing them. 
{quote}public DebuggableScheduledThreadPoolExecutor(int corePoolSize, String 
threadPoolName, int priority)
 Unknown macro: \{ super(corePoolSize, new NamedThreadFactory(threadPoolName, 
priority)); setRejectedExecutionHandler(rejectedExecutionHandler); }
  

public ScheduledThreadPoolExecutor(int corePoolSize,
 ThreadFactory threadFactory)
 Unknown macro: \{ super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS, new 
DelayedWorkQueue(), threadFactory); }
{quote}
 Below is the case about clean task after compaction.  there nearly 3 hours 
delay for removing file "mc-56525". 
{quote} 

TRACE [CompactionExecutor:81] 2018-08-16 21:22:29,664 
LifecycleTransaction.java:363 - Staging for obsolescence 
BigTableReader(path='/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big-Data.db')
 ..........
 TRACE [CompactionExecutor:81] 2018-08-16 21:22:41,162 Tracker.java:165 - 
removing 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big from 
list of files tracked for test_2.edgestore
 ............
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,179 SSTableReader.java:2175 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
before barrier
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,180 SSTableReader.java:2181 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, after 
barrier
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,182 SSTableReader.java:2196 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
completed
{quote}
 

 

 

 

 

 

 

  was:
We use cassandra as backend storage for Janusgraph. when we loading huge data 
(~2 billion vertex, ~10 billion edges), we met some problems.

 

At first, we use STCS as compaction strategy , but met below exception.  we 
checked the value of  "max memory lock" is unlimited and "file map count" is 1 
million, these values should enough for loading. last , we found this problem 
is caused by the virtual memory are all cosumed by cassandra.  So not 
additional virtual memory can be used by compaction task , and below exception 
is thrower out.   
{quote}ERROR [CompactionExecutor:267] 2018-08-09 02:28:40,952 
JVMStabilityInspector.javv
 a:74 - OutOfMemory error letting the JVM handle the error:
 java.lang.OutOfMemoryError: Map failed
{quote}
So, we change compaction strategy to LCS, this change seems can resolve the 
virtual memory problem. But we found another problem : Many sstables which has 
been compacted are still retained on disk, at last these old sstable consume so 
many disk space, it's causing no enough disk for saving real data. we found 
that so many files like "mc_txn_compaction_xxx.log" are created under the data 
directory. 

After some times' investigaton, we found that this problem is caused by 
"NonPeriodicTasks" thread pools.  this pools is always using only one thread 
for processing clean task and compaction. this thread pool is instanced with 
class DebuggableScheduledThreadPoolExecutor,

and DebuggableScheduledThreadPoolExecutor is inherit from class  
ScheduledThreadPoolExecutor.

By reading the code of class DebuggableScheduledThreadPoolExecutor,  found 
DebuggableScheduledThreadPoolExecutor is using an unbound task queue, and core 
pool size is 1.   Why here use the unbound queue for queuing submitted tasks?  
If we using unbound queue, the thread pool wouldn't  increasing thread even 
there so many task are blocked in queue, because unbound queue never would be 
full.  I think here should use bound queue, so when task is heavily, more 
threads would created for processing them. 
{quote}public DebuggableScheduledThreadPoolExecutor(int corePoolSize, String 
threadPoolName, int priority)
 Unknown macro: \{ super(corePoolSize, new NamedThreadFactory(threadPoolName, 
priority)); setRejectedExecutionHandler(rejectedExecutionHandler); }
  

public ScheduledThreadPoolExecutor(int corePoolSize,
 ThreadFactory threadFactory)
 Unknown macro: \{ super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS, new 
DelayedWorkQueue(), threadFactory); }
{quote}
 Below is the case about clean task after compaction.  there nearly 3 hours 
delay for removing file "mc-56525". 
{quote} 

TRACE [CompactionExecutor:81] 2018-08-16 21:22:29,664 
LifecycleTransaction.java:363 - Staging for obsolescence 
BigTableReader(path='/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big-Data.db')
 ..........
 TRACE [CompactionExecutor:81] 2018-08-16 21:22:41,162 Tracker.java:165 - 
removing 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big from 
list of files tracked for test_2.edgestore
 ............
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,179 SSTableReader.java:2175 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
before barrier
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,180 SSTableReader.java:2181 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, after 
barrier
 TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,182 SSTableReader.java:2196 - 
Async instance tidier for 
/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
completed
{quote}
 

 

 

 

 

 

 


> The performance of "NonPeriodicTasks" pools defined in class 
> ScheduledExecutors is low
> --------------------------------------------------------------------------------------
>
>                 Key: CASSANDRA-14653
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-14653
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Compaction
>         Environment: Cassandra nodes :
> 3 nodes, 330G physical memory per node , and four data directory (ssd)  per 
> node.
>            Reporter: Peter Xie
>            Priority: Major
>
> We use cassandra as backend storage for Janusgraph. when we loading huge data 
> (~2 billion vertex, ~10 billion edges), we met some problems.
>  
> At first, we use STCS as compaction strategy , but met below exception.  we 
> checked the value of  "max memory lock" is unlimited and "file map count" is 
> 1 million, these values should enough for loading data. last , we found this 
> problem is caused by the virtual memory are all cosumed by cassandra.  So not 
> additional virtual memory can be used by compaction task , and below 
> exception is thrower out.   
> {quote}ERROR [CompactionExecutor:267] 2018-08-09 02:28:40,952 
> JVMStabilityInspector.javv
>  a:74 - OutOfMemory error letting the JVM handle the error:
>  java.lang.OutOfMemoryError: Map failed
> {quote}
> So, we change compaction strategy to LCS, this change seems can resolve the 
> virtual memory problem. But we found another problem : Many sstables which 
> has been compacted are still retained on disk, at last these old sstable 
> consume so many disk space, it's causing no enough disk for saving real data. 
> we found that so many files like "mc_txn_compaction_xxx.log" are created 
> under the data directory. 
> After some times' investigaton, we found that this problem is caused by 
> "NonPeriodicTasks" thread pools.  this pools is always using only one thread 
> for processing clean task and compaction. this thread pool is instanced with 
> class DebuggableScheduledThreadPoolExecutor,
> and DebuggableScheduledThreadPoolExecutor is inherit from class  
> ScheduledThreadPoolExecutor.
> By reading the code of class DebuggableScheduledThreadPoolExecutor,  found 
> DebuggableScheduledThreadPoolExecutor is using an unbound task queue, and 
> core pool size is 1.   Why here use the unbound queue for queuing submitted 
> tasks?  If we using unbound queue, the thread pool wouldn't  increasing 
> thread even there so many task are blocked in queue, because unbound queue 
> never would be full.  I think here should use bound queue, so when task is 
> heavily, more threads would created for processing them. 
> {quote}public DebuggableScheduledThreadPoolExecutor(int corePoolSize, String 
> threadPoolName, int priority)
>  Unknown macro: \{ super(corePoolSize, new NamedThreadFactory(threadPoolName, 
> priority)); setRejectedExecutionHandler(rejectedExecutionHandler); }
>   
> public ScheduledThreadPoolExecutor(int corePoolSize,
>  ThreadFactory threadFactory)
>  Unknown macro: \{ super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS, new 
> DelayedWorkQueue(), threadFactory); }
> {quote}
>  Below is the case about clean task after compaction.  there nearly 3 hours 
> delay for removing file "mc-56525". 
> {quote} 
> TRACE [CompactionExecutor:81] 2018-08-16 21:22:29,664 
> LifecycleTransaction.java:363 - Staging for obsolescence 
> BigTableReader(path='/sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big-Data.db')
>  ..........
>  TRACE [CompactionExecutor:81] 2018-08-16 21:22:41,162 Tracker.java:165 - 
> removing 
> /sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big from 
> list of files tracked for test_2.edgestore
>  ............
>  TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,179 SSTableReader.java:2175 - 
> Async instance tidier for 
> /sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
> before barrier
>  TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,180 SSTableReader.java:2181 - 
> Async instance tidier for 
> /sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
> after barrier
>  TRACE [NonPeriodicTasks:1] 2018-08-17 00:28:47,182 SSTableReader.java:2196 - 
> Async instance tidier for 
> /sdb/data/test_2/edgestore-365b0b70a05911e8806001ebe60a5ce7/mc-56525-big, 
> completed
> {quote}
>  
>  
>  
>  
>  
>  
>  



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