How Long Will HBase Hold A Row Write Lock?
Hi, We are running on Amazon EMR based HBase 1.4.0 . We are currently seeing a situation where sometimes a particular region gets into a situation where a lot of write requests to any row in that region timeout saying they failed to obtain a lock on a row in a region and eventually they experience an IPC timeout. This causes the IPC queue to blow up in size as requests get backed up, and that region server experiences a much higher than normal timeout rate for all requests, not just those timing out for failing to obtain the row lock. The strange thing is the rows are always different but the region is always the same. So the question is, is there a region component to how long a row write lock would be held? I looked at the debug dump and the RowLocks section shows a long list of write row locks held, all of them are from the same region but different rows. Will trying to obtain a write row lock experience delays if no one else holds a lock on the same row but the region itself is experiencing read delays? We do have an incremental compaction tool running that major compacts one region per region server at a time, so that will drive out pages from the bucket cache. But for most regions the impact is transitional until the bucket cache gets populated by pages from the new HFile. But for this one region we start timing out trying to obtain write locks on rows in that region. Any insight anyone can provide would be most welcome. Cheers. Saad
How Long Will HBase Hold A Row Write Lock?
>>a) it was indeed one of the regions that was being compacted, major compaction in one case, minor compaction in another, the issue started just after compaction completed blowing away bucket cached blocks for the older HFile's About this part.Ya after the compaction, there is a step where the compacted away HFile's blocks getting removed from cache. This op takes a write lock for this region (In Bucket Cache layer).. Every read op which is part of checkAndPut will try read from BC and that in turn need a read lock for this region. So there is chances that the read locks starve because of so many frequent write locks . Each block evict will attain the write lock one after other. Will it be possible for you to patch this evict and test once? We can avoid the immediate evict from BC after compaction. I can help you with a patch if you wish Anoop On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < ramkrishna.s.vasude...@gmail.com> wrote: > Hi Saad > > Your argument here >>> The >>>theory is that since prefetch is an async operation, a lot of the reads in >>>the checkAndPut for the region in question start reading from S3 which is >>>slow. So the write lock obtained for the checkAndPut is held for a longer >>>duration than normal. This has cascading upstream effects. Does that sound >>>plausible? > > Seems very much plausible. So before even the prefetch happens say for > 'block 1' - and you have already issues N checkAndPut calls for the rows in > that 'block 1' - all those checkAndPut will have to read that block from > S3 to perform the get() and then apply the mutation. > > This may happen for multiple threads at the same time because we are not > sure when the prefetch would have actually been completed. I don know what > are the general read characteristics when a read happens from S3 but you > could try to see how things work when a read happens from S3 and after the > prefetch completes ensure the same checkandPut() is done (from cache this > time) to really know the difference what S3 does there. > > Regards > Ram > > On Fri, Mar 2, 2018 at 2:57 AM, Saad Mufti wrote: > >> So after much investigation I can confirm: >> >> a) it was indeed one of the regions that was being compacted, major >> compaction in one case, minor compaction in another, the issue started just >> after compaction completed blowing away bucket cached blocks for the older >> HFile's >> b) in another case there was no compaction just a newly opened region in a >> region server that hadn't finished perfetching its pages from S3 >> >> We have prefetch on open set to true. Our load is heavy on checkAndPut .The >> theory is that since prefetch is an async operation, a lot of the reads in >> the checkAndPut for the region in question start reading from S3 which is >> slow. So the write lock obtained for the checkAndPut is held for a longer >> duration than normal. This has cascading upstream effects. Does that sound >> plausible? >> >> The part I don't understand still is all the locks held are for the same >> region but are all for different rows. So once the prefetch is completed, >> shouldn't the problem clear up quickly? Or does the slow region slow down >> anyone trying to do checkAndPut on any row in the same region even after >> the prefetch has completed. That is, do the long held row locks prevent >> others from getting a row lock on a different row in the same region? >> >> In any case, we trying to use >> https://issues.apache.org/jira/browse/HBASE-16388 support in HBase 1.4.0 >> to >> both insulate the app a bit from this situation and hoping that it will >> reduce pressure on the region server in question, allowing it to recover >> faster. I haven't quite tested that yet, any advice in the meantime would >> be appreciated. >> >> Cheers. >> >> >> Saad >> >> >> >> On Thu, Mar 1, 2018 at 9:21 AM, Saad Mufti wrote: >> >> > Actually it happened again while some minior compactions were running, so >> > don't think it related to our major compaction tool, which isn't even >> > running right now. I will try to capture a debug dump of threads and >> > everything while the event is ongoing. Seems to last at least half an >> hour >> > or so and sometimes longer. >> > >> > >> > Saad >> > >> > >> > On Thu, Mar 1, 2018 at 7:54 AM, Saad Mufti wrote: >> > >> >> Unfortunately I lost the stack trace overnight. But it does seem related >> >> to compaction, because now that the compaction tool is done, I don't see >> >> the issue anymore. I will run our incremental major compaction tool >> again >> >> and see if I can reproduce the issue. >> >> >> >> On the plus side the system stayed stable and eventually recovered, >> >> although it did suffer all those timeouts. >> >> >> >> >> >> Saad >> >> >> >> >> >> On Wed, Feb 28, 2018 at 10:18 PM, Saad Mufti >> >> wrote: >> >> >> >>> I'll paste a thread dump later, writing this from my phone :-) >> >>> >> >>> So the same issue has happened at different times for dif
Re: How Long Will HBase Hold A Row Write Lock?
bq. timing out trying to obtain write locks on rows in that region. Can you confirm that the region under contention was the one being major compacted ? Can you pastebin thread dump so that we can have better idea of the scenario ? For the region being compacted, how long would the compaction take (just want to see if there was correlation between this duration and timeout) ? Cheers On Wed, Feb 28, 2018 at 6:31 PM, Saad Mufti wrote: > Hi, > > We are running on Amazon EMR based HBase 1.4.0 . We are currently seeing a > situation where sometimes a particular region gets into a situation where a > lot of write requests to any row in that region timeout saying they failed > to obtain a lock on a row in a region and eventually they experience an IPC > timeout. This causes the IPC queue to blow up in size as requests get > backed up, and that region server experiences a much higher than normal > timeout rate for all requests, not just those timing out for failing to > obtain the row lock. > > The strange thing is the rows are always different but the region is always > the same. So the question is, is there a region component to how long a row > write lock would be held? I looked at the debug dump and the RowLocks > section shows a long list of write row locks held, all of them are from the > same region but different rows. > > Will trying to obtain a write row lock experience delays if no one else > holds a lock on the same row but the region itself is experiencing read > delays? We do have an incremental compaction tool running that major > compacts one region per region server at a time, so that will drive out > pages from the bucket cache. But for most regions the impact is > transitional until the bucket cache gets populated by pages from the new > HFile. But for this one region we start timing out trying to obtain write > locks on rows in that region. > > Any insight anyone can provide would be most welcome. > > Cheers. > > > Saad >
Re: How Long Will HBase Hold A Row Write Lock?
One additional data point, I tried to manually re-assign the region in question from the shell, that for some reason caused the region server to restart and the region did get assigned to another region server. But then the problem moved to that region server almost immediately. Does that just mean our write load is disproportionately hitting that one region? We have a prefix scheme in place for all our keys where we prepend an MD5 hash based 4 digit prefix to all keys to make sure we get good randomization, so that would be surprising. As usual any feedback would be appreciated. Cheers. Saad On Wed, Feb 28, 2018 at 9:31 PM, Saad Mufti wrote: > Hi, > > We are running on Amazon EMR based HBase 1.4.0 . We are currently seeing a > situation where sometimes a particular region gets into a situation where a > lot of write requests to any row in that region timeout saying they failed > to obtain a lock on a row in a region and eventually they experience an IPC > timeout. This causes the IPC queue to blow up in size as requests get > backed up, and that region server experiences a much higher than normal > timeout rate for all requests, not just those timing out for failing to > obtain the row lock. > > The strange thing is the rows are always different but the region is > always the same. So the question is, is there a region component to how > long a row write lock would be held? I looked at the debug dump and the > RowLocks section shows a long list of write row locks held, all of them are > from the same region but different rows. > > Will trying to obtain a write row lock experience delays if no one else > holds a lock on the same row but the region itself is experiencing read > delays? We do have an incremental compaction tool running that major > compacts one region per region server at a time, so that will drive out > pages from the bucket cache. But for most regions the impact is > transitional until the bucket cache gets populated by pages from the new > HFile. But for this one region we start timing out trying to obtain write > locks on rows in that region. > > Any insight anyone can provide would be most welcome. > > Cheers. > > > Saad > >
Re: How Long Will HBase Hold A Row Write Lock?
I'll paste a thread dump later, writing this from my phone :-) So the same issue has happened at different times for different regions, but I couldn't see that the region in question was the one being compacted, either this time or earlier. Although I might have missed an earlier correlation in the logs where the issue started just after the compaction completed. Usually a compaction for this table's regions take around 5-10 minutes, much less for its smaller column family which is block cache enabled, around a minute or less, and 5-10 minutes for the much larger one for which we have block cache disabled in the schema, because we don't ever read it in the primary cluster. So the only impact on reads would be from that smaller column family which takes less than a minute to compact. But the issue once started doesn't seem to recover for a long time, long past when any compaction on the region itself could impact anything. The compaction tool which is our own code has long since moved to other regions. Cheers. Saad On Wed, Feb 28, 2018 at 9:39 PM Ted Yu wrote: > bq. timing out trying to obtain write locks on rows in that region. > > Can you confirm that the region under contention was the one being major > compacted ? > > Can you pastebin thread dump so that we can have better idea of the > scenario ? > > For the region being compacted, how long would the compaction take (just > want to see if there was correlation between this duration and timeout) ? > > Cheers > > On Wed, Feb 28, 2018 at 6:31 PM, Saad Mufti wrote: > > > Hi, > > > > We are running on Amazon EMR based HBase 1.4.0 . We are currently seeing > a > > situation where sometimes a particular region gets into a situation > where a > > lot of write requests to any row in that region timeout saying they > failed > > to obtain a lock on a row in a region and eventually they experience an > IPC > > timeout. This causes the IPC queue to blow up in size as requests get > > backed up, and that region server experiences a much higher than normal > > timeout rate for all requests, not just those timing out for failing to > > obtain the row lock. > > > > The strange thing is the rows are always different but the region is > always > > the same. So the question is, is there a region component to how long a > row > > write lock would be held? I looked at the debug dump and the RowLocks > > section shows a long list of write row locks held, all of them are from > the > > same region but different rows. > > > > Will trying to obtain a write row lock experience delays if no one else > > holds a lock on the same row but the region itself is experiencing read > > delays? We do have an incremental compaction tool running that major > > compacts one region per region server at a time, so that will drive out > > pages from the bucket cache. But for most regions the impact is > > transitional until the bucket cache gets populated by pages from the new > > HFile. But for this one region we start timing out trying to obtain write > > locks on rows in that region. > > > > Any insight anyone can provide would be most welcome. > > > > Cheers. > > > > > > Saad > > >
Re: How Long Will HBase Hold A Row Write Lock?
Unfortunately I lost the stack trace overnight. But it does seem related to compaction, because now that the compaction tool is done, I don't see the issue anymore. I will run our incremental major compaction tool again and see if I can reproduce the issue. On the plus side the system stayed stable and eventually recovered, although it did suffer all those timeouts. Saad On Wed, Feb 28, 2018 at 10:18 PM, Saad Mufti wrote: > I'll paste a thread dump later, writing this from my phone :-) > > So the same issue has happened at different times for different regions, > but I couldn't see that the region in question was the one being compacted, > either this time or earlier. Although I might have missed an earlier > correlation in the logs where the issue started just after the compaction > completed. > > Usually a compaction for this table's regions take around 5-10 minutes, > much less for its smaller column family which is block cache enabled, > around a minute or less, and 5-10 minutes for the much larger one for which > we have block cache disabled in the schema, because we don't ever read it > in the primary cluster. So the only impact on reads would be from that > smaller column family which takes less than a minute to compact. > > But the issue once started doesn't seem to recover for a long time, long > past when any compaction on the region itself could impact anything. The > compaction tool which is our own code has long since moved to other > regions. > > Cheers. > > > Saad > > > On Wed, Feb 28, 2018 at 9:39 PM Ted Yu wrote: > >> bq. timing out trying to obtain write locks on rows in that region. >> >> Can you confirm that the region under contention was the one being major >> compacted ? >> >> Can you pastebin thread dump so that we can have better idea of the >> scenario ? >> >> For the region being compacted, how long would the compaction take (just >> want to see if there was correlation between this duration and timeout) ? >> >> Cheers >> >> On Wed, Feb 28, 2018 at 6:31 PM, Saad Mufti wrote: >> >> > Hi, >> > >> > We are running on Amazon EMR based HBase 1.4.0 . We are currently >> seeing a >> > situation where sometimes a particular region gets into a situation >> where a >> > lot of write requests to any row in that region timeout saying they >> failed >> > to obtain a lock on a row in a region and eventually they experience an >> IPC >> > timeout. This causes the IPC queue to blow up in size as requests get >> > backed up, and that region server experiences a much higher than normal >> > timeout rate for all requests, not just those timing out for failing to >> > obtain the row lock. >> > >> > The strange thing is the rows are always different but the region is >> always >> > the same. So the question is, is there a region component to how long a >> row >> > write lock would be held? I looked at the debug dump and the RowLocks >> > section shows a long list of write row locks held, all of them are from >> the >> > same region but different rows. >> > >> > Will trying to obtain a write row lock experience delays if no one else >> > holds a lock on the same row but the region itself is experiencing read >> > delays? We do have an incremental compaction tool running that major >> > compacts one region per region server at a time, so that will drive out >> > pages from the bucket cache. But for most regions the impact is >> > transitional until the bucket cache gets populated by pages from the new >> > HFile. But for this one region we start timing out trying to obtain >> write >> > locks on rows in that region. >> > >> > Any insight anyone can provide would be most welcome. >> > >> > Cheers. >> > >> > >> > Saad >> > >> >
Re: How Long Will HBase Hold A Row Write Lock?
Actually it happened again while some minior compactions were running, so don't think it related to our major compaction tool, which isn't even running right now. I will try to capture a debug dump of threads and everything while the event is ongoing. Seems to last at least half an hour or so and sometimes longer. Saad On Thu, Mar 1, 2018 at 7:54 AM, Saad Mufti wrote: > Unfortunately I lost the stack trace overnight. But it does seem related > to compaction, because now that the compaction tool is done, I don't see > the issue anymore. I will run our incremental major compaction tool again > and see if I can reproduce the issue. > > On the plus side the system stayed stable and eventually recovered, > although it did suffer all those timeouts. > > > Saad > > > On Wed, Feb 28, 2018 at 10:18 PM, Saad Mufti wrote: > >> I'll paste a thread dump later, writing this from my phone :-) >> >> So the same issue has happened at different times for different regions, >> but I couldn't see that the region in question was the one being compacted, >> either this time or earlier. Although I might have missed an earlier >> correlation in the logs where the issue started just after the compaction >> completed. >> >> Usually a compaction for this table's regions take around 5-10 minutes, >> much less for its smaller column family which is block cache enabled, >> around a minute or less, and 5-10 minutes for the much larger one for which >> we have block cache disabled in the schema, because we don't ever read it >> in the primary cluster. So the only impact on reads would be from that >> smaller column family which takes less than a minute to compact. >> >> But the issue once started doesn't seem to recover for a long time, long >> past when any compaction on the region itself could impact anything. The >> compaction tool which is our own code has long since moved to other >> regions. >> >> Cheers. >> >> >> Saad >> >> >> On Wed, Feb 28, 2018 at 9:39 PM Ted Yu wrote: >> >>> bq. timing out trying to obtain write locks on rows in that region. >>> >>> Can you confirm that the region under contention was the one being major >>> compacted ? >>> >>> Can you pastebin thread dump so that we can have better idea of the >>> scenario ? >>> >>> For the region being compacted, how long would the compaction take (just >>> want to see if there was correlation between this duration and timeout) ? >>> >>> Cheers >>> >>> On Wed, Feb 28, 2018 at 6:31 PM, Saad Mufti >>> wrote: >>> >>> > Hi, >>> > >>> > We are running on Amazon EMR based HBase 1.4.0 . We are currently >>> seeing a >>> > situation where sometimes a particular region gets into a situation >>> where a >>> > lot of write requests to any row in that region timeout saying they >>> failed >>> > to obtain a lock on a row in a region and eventually they experience >>> an IPC >>> > timeout. This causes the IPC queue to blow up in size as requests get >>> > backed up, and that region server experiences a much higher than normal >>> > timeout rate for all requests, not just those timing out for failing to >>> > obtain the row lock. >>> > >>> > The strange thing is the rows are always different but the region is >>> always >>> > the same. So the question is, is there a region component to how long >>> a row >>> > write lock would be held? I looked at the debug dump and the RowLocks >>> > section shows a long list of write row locks held, all of them are >>> from the >>> > same region but different rows. >>> > >>> > Will trying to obtain a write row lock experience delays if no one else >>> > holds a lock on the same row but the region itself is experiencing read >>> > delays? We do have an incremental compaction tool running that major >>> > compacts one region per region server at a time, so that will drive out >>> > pages from the bucket cache. But for most regions the impact is >>> > transitional until the bucket cache gets populated by pages from the >>> new >>> > HFile. But for this one region we start timing out trying to obtain >>> write >>> > locks on rows in that region. >>> > >>> > Any insight anyone can provide would be most welcome. >>> > >>> > Cheers. >>> > >>> > >>> > Saad >>> > >>> >> >
Re: How Long Will HBase Hold A Row Write Lock?
So after much investigation I can confirm: a) it was indeed one of the regions that was being compacted, major compaction in one case, minor compaction in another, the issue started just after compaction completed blowing away bucket cached blocks for the older HFile's b) in another case there was no compaction just a newly opened region in a region server that hadn't finished perfetching its pages from S3 We have prefetch on open set to true. Our load is heavy on checkAndPut .The theory is that since prefetch is an async operation, a lot of the reads in the checkAndPut for the region in question start reading from S3 which is slow. So the write lock obtained for the checkAndPut is held for a longer duration than normal. This has cascading upstream effects. Does that sound plausible? The part I don't understand still is all the locks held are for the same region but are all for different rows. So once the prefetch is completed, shouldn't the problem clear up quickly? Or does the slow region slow down anyone trying to do checkAndPut on any row in the same region even after the prefetch has completed. That is, do the long held row locks prevent others from getting a row lock on a different row in the same region? In any case, we trying to use https://issues.apache.org/jira/browse/HBASE-16388 support in HBase 1.4.0 to both insulate the app a bit from this situation and hoping that it will reduce pressure on the region server in question, allowing it to recover faster. I haven't quite tested that yet, any advice in the meantime would be appreciated. Cheers. Saad On Thu, Mar 1, 2018 at 9:21 AM, Saad Mufti wrote: > Actually it happened again while some minior compactions were running, so > don't think it related to our major compaction tool, which isn't even > running right now. I will try to capture a debug dump of threads and > everything while the event is ongoing. Seems to last at least half an hour > or so and sometimes longer. > > > Saad > > > On Thu, Mar 1, 2018 at 7:54 AM, Saad Mufti wrote: > >> Unfortunately I lost the stack trace overnight. But it does seem related >> to compaction, because now that the compaction tool is done, I don't see >> the issue anymore. I will run our incremental major compaction tool again >> and see if I can reproduce the issue. >> >> On the plus side the system stayed stable and eventually recovered, >> although it did suffer all those timeouts. >> >> >> Saad >> >> >> On Wed, Feb 28, 2018 at 10:18 PM, Saad Mufti >> wrote: >> >>> I'll paste a thread dump later, writing this from my phone :-) >>> >>> So the same issue has happened at different times for different regions, >>> but I couldn't see that the region in question was the one being compacted, >>> either this time or earlier. Although I might have missed an earlier >>> correlation in the logs where the issue started just after the compaction >>> completed. >>> >>> Usually a compaction for this table's regions take around 5-10 minutes, >>> much less for its smaller column family which is block cache enabled, >>> around a minute or less, and 5-10 minutes for the much larger one for which >>> we have block cache disabled in the schema, because we don't ever read it >>> in the primary cluster. So the only impact on reads would be from that >>> smaller column family which takes less than a minute to compact. >>> >>> But the issue once started doesn't seem to recover for a long time, long >>> past when any compaction on the region itself could impact anything. The >>> compaction tool which is our own code has long since moved to other >>> regions. >>> >>> Cheers. >>> >>> >>> Saad >>> >>> >>> On Wed, Feb 28, 2018 at 9:39 PM Ted Yu wrote: >>> bq. timing out trying to obtain write locks on rows in that region. Can you confirm that the region under contention was the one being major compacted ? Can you pastebin thread dump so that we can have better idea of the scenario ? For the region being compacted, how long would the compaction take (just want to see if there was correlation between this duration and timeout) ? Cheers On Wed, Feb 28, 2018 at 6:31 PM, Saad Mufti wrote: > Hi, > > We are running on Amazon EMR based HBase 1.4.0 . We are currently seeing a > situation where sometimes a particular region gets into a situation where a > lot of write requests to any row in that region timeout saying they failed > to obtain a lock on a row in a region and eventually they experience an IPC > timeout. This causes the IPC queue to blow up in size as requests get > backed up, and that region server experiences a much higher than normal > timeout rate for all requests, not just those timing out for failing to > obtain the row lock. > > The strange thing is the rows are always different but the region is always > the same.
Re: How Long Will HBase Hold A Row Write Lock?
Hi Saad Your argument here >> The >>theory is that since prefetch is an async operation, a lot of the reads in >>the checkAndPut for the region in question start reading from S3 which is >>slow. So the write lock obtained for the checkAndPut is held for a longer >>duration than normal. This has cascading upstream effects. Does that sound >>plausible? Seems very much plausible. So before even the prefetch happens say for 'block 1' - and you have already issues N checkAndPut calls for the rows in that 'block 1' - all those checkAndPut will have to read that block from S3 to perform the get() and then apply the mutation. This may happen for multiple threads at the same time because we are not sure when the prefetch would have actually been completed. I don know what are the general read characteristics when a read happens from S3 but you could try to see how things work when a read happens from S3 and after the prefetch completes ensure the same checkandPut() is done (from cache this time) to really know the difference what S3 does there. Regards Ram On Fri, Mar 2, 2018 at 2:57 AM, Saad Mufti wrote: > So after much investigation I can confirm: > > a) it was indeed one of the regions that was being compacted, major > compaction in one case, minor compaction in another, the issue started just > after compaction completed blowing away bucket cached blocks for the older > HFile's > b) in another case there was no compaction just a newly opened region in a > region server that hadn't finished perfetching its pages from S3 > > We have prefetch on open set to true. Our load is heavy on checkAndPut .The > theory is that since prefetch is an async operation, a lot of the reads in > the checkAndPut for the region in question start reading from S3 which is > slow. So the write lock obtained for the checkAndPut is held for a longer > duration than normal. This has cascading upstream effects. Does that sound > plausible? > > The part I don't understand still is all the locks held are for the same > region but are all for different rows. So once the prefetch is completed, > shouldn't the problem clear up quickly? Or does the slow region slow down > anyone trying to do checkAndPut on any row in the same region even after > the prefetch has completed. That is, do the long held row locks prevent > others from getting a row lock on a different row in the same region? > > In any case, we trying to use > https://issues.apache.org/jira/browse/HBASE-16388 support in HBase 1.4.0 > to > both insulate the app a bit from this situation and hoping that it will > reduce pressure on the region server in question, allowing it to recover > faster. I haven't quite tested that yet, any advice in the meantime would > be appreciated. > > Cheers. > > > Saad > > > > On Thu, Mar 1, 2018 at 9:21 AM, Saad Mufti wrote: > > > Actually it happened again while some minior compactions were running, so > > don't think it related to our major compaction tool, which isn't even > > running right now. I will try to capture a debug dump of threads and > > everything while the event is ongoing. Seems to last at least half an > hour > > or so and sometimes longer. > > > > > > Saad > > > > > > On Thu, Mar 1, 2018 at 7:54 AM, Saad Mufti wrote: > > > >> Unfortunately I lost the stack trace overnight. But it does seem related > >> to compaction, because now that the compaction tool is done, I don't see > >> the issue anymore. I will run our incremental major compaction tool > again > >> and see if I can reproduce the issue. > >> > >> On the plus side the system stayed stable and eventually recovered, > >> although it did suffer all those timeouts. > >> > >> > >> Saad > >> > >> > >> On Wed, Feb 28, 2018 at 10:18 PM, Saad Mufti > >> wrote: > >> > >>> I'll paste a thread dump later, writing this from my phone :-) > >>> > >>> So the same issue has happened at different times for different > regions, > >>> but I couldn't see that the region in question was the one being > compacted, > >>> either this time or earlier. Although I might have missed an earlier > >>> correlation in the logs where the issue started just after the > compaction > >>> completed. > >>> > >>> Usually a compaction for this table's regions take around 5-10 minutes, > >>> much less for its smaller column family which is block cache enabled, > >>> around a minute or less, and 5-10 minutes for the much larger one for > which > >>> we have block cache disabled in the schema, because we don't ever read > it > >>> in the primary cluster. So the only impact on reads would be from that > >>> smaller column family which takes less than a minute to compact. > >>> > >>> But the issue once started doesn't seem to recover for a long time, > long > >>> past when any compaction on the region itself could impact anything. > The > >>> compaction tool which is our own code has long since moved to other > >>> regions. > >>> > >>> Cheers. > >>> > >>> > >>> Saad > >>> > >>> > >>> On Wed,
Re: How Long Will HBase Hold A Row Write Lock?
So if I understand correctly, we would mitigate the problem by not evicting blocks for archived files immediately? Wouldn't this potentially lead to problems later if the LRU algo chooses to evict blocks for active files and leave blocks for archived files in there? I would definitely love to test this!!! Unfortunately we are running on EMR and the details of how to patch HBase under EMR are not clear to me :-( What we would really love would be a setting for actually immediately caching blocks for a new compacted file. I have seen in the code that even is we have the cache on write setting set to true, it will refuse to cache blocks for a file that is a newly compacted one. In our case we have sized the bucket cache to be big enough to hold all our data, and really want to avoid having to go to S3 until the last possible moment. A config setting to test this would be great. But thanks everyone for your feedback. Any more would also be welcome on the idea to let a user cache all newly compacted files. Saad On Wed, Mar 7, 2018 at 12:00 AM, Anoop John wrote: > >>a) it was indeed one of the regions that was being compacted, major > compaction in one case, minor compaction in another, the issue started just > after compaction completed blowing away bucket cached blocks for the older > HFile's > > About this part.Ya after the compaction, there is a step where the > compacted away HFile's blocks getting removed from cache. This op takes a > write lock for this region (In Bucket Cache layer).. Every read op which > is part of checkAndPut will try read from BC and that in turn need a read > lock for this region. So there is chances that the read locks starve > because of so many frequent write locks . Each block evict will attain the > write lock one after other. Will it be possible for you to patch this > evict and test once? We can avoid the immediate evict from BC after > compaction. I can help you with a patch if you wish > > Anoop > > > > On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < > ramkrishna.s.vasude...@gmail.com> wrote: > > Hi Saad > > > > Your argument here > >>> The > >>>theory is that since prefetch is an async operation, a lot of the reads > in > >>>the checkAndPut for the region in question start reading from S3 which > is > >>>slow. So the write lock obtained for the checkAndPut is held for a > longer > >>>duration than normal. This has cascading upstream effects. Does that > sound > >>>plausible? > > > > Seems very much plausible. So before even the prefetch happens say for > > 'block 1' - and you have already issues N checkAndPut calls for the rows > in > > that 'block 1' - all those checkAndPut will have to read that block from > > S3 to perform the get() and then apply the mutation. > > > > This may happen for multiple threads at the same time because we are not > > sure when the prefetch would have actually been completed. I don know > what > > are the general read characteristics when a read happens from S3 but you > > could try to see how things work when a read happens from S3 and after > the > > prefetch completes ensure the same checkandPut() is done (from cache this > > time) to really know the difference what S3 does there. > > > > Regards > > Ram > > > > On Fri, Mar 2, 2018 at 2:57 AM, Saad Mufti wrote: > > > >> So after much investigation I can confirm: > >> > >> a) it was indeed one of the regions that was being compacted, major > >> compaction in one case, minor compaction in another, the issue started > just > >> after compaction completed blowing away bucket cached blocks for the > older > >> HFile's > >> b) in another case there was no compaction just a newly opened region in > a > >> region server that hadn't finished perfetching its pages from S3 > >> > >> We have prefetch on open set to true. Our load is heavy on checkAndPut > .The > >> theory is that since prefetch is an async operation, a lot of the reads > in > >> the checkAndPut for the region in question start reading from S3 which > is > >> slow. So the write lock obtained for the checkAndPut is held for a > longer > >> duration than normal. This has cascading upstream effects. Does that > sound > >> plausible? > >> > >> The part I don't understand still is all the locks held are for the same > >> region but are all for different rows. So once the prefetch is > completed, > >> shouldn't the problem clear up quickly? Or does the slow region slow > down > >> anyone trying to do checkAndPut on any row in the same region even after > >> the prefetch has completed. That is, do the long held row locks prevent > >> others from getting a row lock on a different row in the same region? > >> > >> In any case, we trying to use > >> https://issues.apache.org/jira/browse/HBASE-16388 support in HBase > 1.4.0 > >> to > >> both insulate the app a bit from this situation and hoping that it will > >> reduce pressure on the region server in question, allowing it to recover > >> faster. I haven't quite test
Re: How Long Will HBase Hold A Row Write Lock?
Also, for now we have mitigated this problem by using the new setting in HBase 1.4.0 that prevents one slow region server from blocking all client requests. Of course it causes some timeouts but our overall ecosystem contains Kafka queues for retries, so we can live with that. From what I can see, it looks like this setting also has the good effect of preventing clients from hammering a region server that is slow because its IPC queues are backed up, allowing it to recover faster. Does that make sense? Cheers. Saad On Sat, Mar 10, 2018 at 7:04 PM, Saad Mufti wrote: > So if I understand correctly, we would mitigate the problem by not > evicting blocks for archived files immediately? Wouldn't this potentially > lead to problems later if the LRU algo chooses to evict blocks for active > files and leave blocks for archived files in there? > > I would definitely love to test this!!! Unfortunately we are running on > EMR and the details of how to patch HBase under EMR are not clear to me :-( > > What we would really love would be a setting for actually immediately > caching blocks for a new compacted file. I have seen in the code that even > is we have the cache on write setting set to true, it will refuse to cache > blocks for a file that is a newly compacted one. In our case we have sized > the bucket cache to be big enough to hold all our data, and really want to > avoid having to go to S3 until the last possible moment. A config setting > to test this would be great. > > But thanks everyone for your feedback. Any more would also be welcome on > the idea to let a user cache all newly compacted files. > > > Saad > > > On Wed, Mar 7, 2018 at 12:00 AM, Anoop John wrote: > >> >>a) it was indeed one of the regions that was being compacted, major >> compaction in one case, minor compaction in another, the issue started >> just >> after compaction completed blowing away bucket cached blocks for the older >> HFile's >> >> About this part.Ya after the compaction, there is a step where the >> compacted away HFile's blocks getting removed from cache. This op takes a >> write lock for this region (In Bucket Cache layer).. Every read op which >> is part of checkAndPut will try read from BC and that in turn need a read >> lock for this region. So there is chances that the read locks starve >> because of so many frequent write locks . Each block evict will attain >> the >> write lock one after other. Will it be possible for you to patch this >> evict and test once? We can avoid the immediate evict from BC after >> compaction. I can help you with a patch if you wish >> >> Anoop >> >> >> >> On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < >> ramkrishna.s.vasude...@gmail.com> wrote: >> > Hi Saad >> > >> > Your argument here >> >>> The >> >>>theory is that since prefetch is an async operation, a lot of the reads >> in >> >>>the checkAndPut for the region in question start reading from S3 which >> is >> >>>slow. So the write lock obtained for the checkAndPut is held for a >> longer >> >>>duration than normal. This has cascading upstream effects. Does that >> sound >> >>>plausible? >> > >> > Seems very much plausible. So before even the prefetch happens say for >> > 'block 1' - and you have already issues N checkAndPut calls for the rows >> in >> > that 'block 1' - all those checkAndPut will have to read that block >> from >> > S3 to perform the get() and then apply the mutation. >> > >> > This may happen for multiple threads at the same time because we are not >> > sure when the prefetch would have actually been completed. I don know >> what >> > are the general read characteristics when a read happens from S3 but you >> > could try to see how things work when a read happens from S3 and after >> the >> > prefetch completes ensure the same checkandPut() is done (from cache >> this >> > time) to really know the difference what S3 does there. >> > >> > Regards >> > Ram >> > >> > On Fri, Mar 2, 2018 at 2:57 AM, Saad Mufti >> wrote: >> > >> >> So after much investigation I can confirm: >> >> >> >> a) it was indeed one of the regions that was being compacted, major >> >> compaction in one case, minor compaction in another, the issue started >> just >> >> after compaction completed blowing away bucket cached blocks for the >> older >> >> HFile's >> >> b) in another case there was no compaction just a newly opened region >> in >> a >> >> region server that hadn't finished perfetching its pages from S3 >> >> >> >> We have prefetch on open set to true. Our load is heavy on checkAndPut >> .The >> >> theory is that since prefetch is an async operation, a lot of the reads >> in >> >> the checkAndPut for the region in question start reading from S3 which >> is >> >> slow. So the write lock obtained for the checkAndPut is held for a >> longer >> >> duration than normal. This has cascading upstream effects. Does that >> sound >> >> plausible? >> >> >> >> The part I don't understand still is all the locks held
Re: How Long Will HBase Hold A Row Write Lock?
Although now that I think about this a bit more, all the failures we saw were failure to obtain a row lock, and in the thread stack traces we always saw it somewhere inside getRowLockInternal and similar. Never saw any contention on bucket cache lock that I could see. Cheers. Saad On Sat, Mar 10, 2018 at 8:04 PM, Saad Mufti wrote: > Also, for now we have mitigated this problem by using the new setting in > HBase 1.4.0 that prevents one slow region server from blocking all client > requests. Of course it causes some timeouts but our overall ecosystem > contains Kafka queues for retries, so we can live with that. From what I > can see, it looks like this setting also has the good effect of preventing > clients from hammering a region server that is slow because its IPC queues > are backed up, allowing it to recover faster. > > Does that make sense? > > Cheers. > > > Saad > > > On Sat, Mar 10, 2018 at 7:04 PM, Saad Mufti wrote: > >> So if I understand correctly, we would mitigate the problem by not >> evicting blocks for archived files immediately? Wouldn't this potentially >> lead to problems later if the LRU algo chooses to evict blocks for active >> files and leave blocks for archived files in there? >> >> I would definitely love to test this!!! Unfortunately we are running on >> EMR and the details of how to patch HBase under EMR are not clear to me :-( >> >> What we would really love would be a setting for actually immediately >> caching blocks for a new compacted file. I have seen in the code that even >> is we have the cache on write setting set to true, it will refuse to cache >> blocks for a file that is a newly compacted one. In our case we have sized >> the bucket cache to be big enough to hold all our data, and really want to >> avoid having to go to S3 until the last possible moment. A config setting >> to test this would be great. >> >> But thanks everyone for your feedback. Any more would also be welcome on >> the idea to let a user cache all newly compacted files. >> >> >> Saad >> >> >> On Wed, Mar 7, 2018 at 12:00 AM, Anoop John >> wrote: >> >>> >>a) it was indeed one of the regions that was being compacted, major >>> compaction in one case, minor compaction in another, the issue started >>> just >>> after compaction completed blowing away bucket cached blocks for the >>> older >>> HFile's >>> >>> About this part.Ya after the compaction, there is a step where the >>> compacted away HFile's blocks getting removed from cache. This op takes a >>> write lock for this region (In Bucket Cache layer).. Every read op which >>> is part of checkAndPut will try read from BC and that in turn need a read >>> lock for this region. So there is chances that the read locks starve >>> because of so many frequent write locks . Each block evict will attain >>> the >>> write lock one after other. Will it be possible for you to patch this >>> evict and test once? We can avoid the immediate evict from BC after >>> compaction. I can help you with a patch if you wish >>> >>> Anoop >>> >>> >>> >>> On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < >>> ramkrishna.s.vasude...@gmail.com> wrote: >>> > Hi Saad >>> > >>> > Your argument here >>> >>> The >>> >>>theory is that since prefetch is an async operation, a lot of the >>> reads >>> in >>> >>>the checkAndPut for the region in question start reading from S3 >>> which is >>> >>>slow. So the write lock obtained for the checkAndPut is held for a >>> longer >>> >>>duration than normal. This has cascading upstream effects. Does that >>> sound >>> >>>plausible? >>> > >>> > Seems very much plausible. So before even the prefetch happens say for >>> > 'block 1' - and you have already issues N checkAndPut calls for the >>> rows >>> in >>> > that 'block 1' - all those checkAndPut will have to read that block >>> from >>> > S3 to perform the get() and then apply the mutation. >>> > >>> > This may happen for multiple threads at the same time because we are >>> not >>> > sure when the prefetch would have actually been completed. I don know >>> what >>> > are the general read characteristics when a read happens from S3 but >>> you >>> > could try to see how things work when a read happens from S3 and after >>> the >>> > prefetch completes ensure the same checkandPut() is done (from cache >>> this >>> > time) to really know the difference what S3 does there. >>> > >>> > Regards >>> > Ram >>> > >>> > On Fri, Mar 2, 2018 at 2:57 AM, Saad Mufti >>> wrote: >>> > >>> >> So after much investigation I can confirm: >>> >> >>> >> a) it was indeed one of the regions that was being compacted, major >>> >> compaction in one case, minor compaction in another, the issue started >>> just >>> >> after compaction completed blowing away bucket cached blocks for the >>> older >>> >> HFile's >>> >> b) in another case there was no compaction just a newly opened region >>> in >>> a >>> >> region server that hadn't finished perfetching its pages from S3 >>> >> >>> >> We
Re: How Long Will HBase Hold A Row Write Lock?
Hi Saad In your initial mail you mentioned that there are lots of checkAndPut ops but on different rows. The failure in obtaining locks (write lock as it is checkAndPut) means there is contention on the same row key. If that is the case , ya that is the 1st step before BC reads and it make sense. On the Q on why not caching the compacted file content, yes it is this way. Even if cache on write is true. This is because some times the compacted result file could be so large (what is major compaction) and that will exhaust the BC if written. Also it might contain some data which are very old. There is a jira recently raised jira which discuss abt this. Pls see HBASE-20045 -Anoop- On Sun, Mar 11, 2018 at 7:57 AM, Saad Mufti wrote: > Although now that I think about this a bit more, all the failures we saw > were failure to obtain a row lock, and in the thread stack traces we always > saw it somewhere inside getRowLockInternal and similar. Never saw any > contention on bucket cache lock that I could see. > > Cheers. > > > Saad > > > On Sat, Mar 10, 2018 at 8:04 PM, Saad Mufti wrote: > >> Also, for now we have mitigated this problem by using the new setting in >> HBase 1.4.0 that prevents one slow region server from blocking all client >> requests. Of course it causes some timeouts but our overall ecosystem >> contains Kafka queues for retries, so we can live with that. From what I >> can see, it looks like this setting also has the good effect of preventing >> clients from hammering a region server that is slow because its IPC queues >> are backed up, allowing it to recover faster. >> >> Does that make sense? >> >> Cheers. >> >> >> Saad >> >> >> On Sat, Mar 10, 2018 at 7:04 PM, Saad Mufti wrote: >> >>> So if I understand correctly, we would mitigate the problem by not >>> evicting blocks for archived files immediately? Wouldn't this potentially >>> lead to problems later if the LRU algo chooses to evict blocks for active >>> files and leave blocks for archived files in there? >>> >>> I would definitely love to test this!!! Unfortunately we are running on >>> EMR and the details of how to patch HBase under EMR are not clear to me :-( >>> >>> What we would really love would be a setting for actually immediately >>> caching blocks for a new compacted file. I have seen in the code that even >>> is we have the cache on write setting set to true, it will refuse to cache >>> blocks for a file that is a newly compacted one. In our case we have sized >>> the bucket cache to be big enough to hold all our data, and really want to >>> avoid having to go to S3 until the last possible moment. A config setting >>> to test this would be great. >>> >>> But thanks everyone for your feedback. Any more would also be welcome on >>> the idea to let a user cache all newly compacted files. >>> >>> >>> Saad >>> >>> >>> On Wed, Mar 7, 2018 at 12:00 AM, Anoop John >>> wrote: >>> >>a) it was indeed one of the regions that was being compacted, major compaction in one case, minor compaction in another, the issue started just after compaction completed blowing away bucket cached blocks for the older HFile's About this part.Ya after the compaction, there is a step where the compacted away HFile's blocks getting removed from cache. This op takes a write lock for this region (In Bucket Cache layer).. Every read op which is part of checkAndPut will try read from BC and that in turn need a read lock for this region. So there is chances that the read locks starve because of so many frequent write locks . Each block evict will attain the write lock one after other. Will it be possible for you to patch this evict and test once? We can avoid the immediate evict from BC after compaction. I can help you with a patch if you wish Anoop On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < ramkrishna.s.vasude...@gmail.com> wrote: > Hi Saad > > Your argument here >>> The >>>theory is that since prefetch is an async operation, a lot of the reads in >>>the checkAndPut for the region in question start reading from S3 which is >>>slow. So the write lock obtained for the checkAndPut is held for a longer >>>duration than normal. This has cascading upstream effects. Does that sound >>>plausible? > > Seems very much plausible. So before even the prefetch happens say for > 'block 1' - and you have already issues N checkAndPut calls for the rows in > that 'block 1' - all those checkAndPut will have to read that block from > S3 to perform the get() and then apply the mutation. > > This may happen for multiple threads at the same time because we are not > sure when the prefetch would have actually been completed. I don know what > are the general read characteris
Re: How Long Will HBase Hold A Row Write Lock?
Thanks. I left a comment on that ticket. Saad On Sat, Mar 10, 2018 at 11:57 PM, Anoop John wrote: > Hi Saad >In your initial mail you mentioned that there are lots > of checkAndPut ops but on different rows. The failure in obtaining > locks (write lock as it is checkAndPut) means there is contention on > the same row key. If that is the case , ya that is the 1st step > before BC reads and it make sense. > > On the Q on why not caching the compacted file content, yes it is this > way. Even if cache on write is true. This is because some times the > compacted result file could be so large (what is major compaction) and > that will exhaust the BC if written. Also it might contain some data > which are very old. There is a jira recently raised jira which > discuss abt this. Pls see HBASE-20045 > > > -Anoop- > > On Sun, Mar 11, 2018 at 7:57 AM, Saad Mufti wrote: > > Although now that I think about this a bit more, all the failures we saw > > were failure to obtain a row lock, and in the thread stack traces we > always > > saw it somewhere inside getRowLockInternal and similar. Never saw any > > contention on bucket cache lock that I could see. > > > > Cheers. > > > > > > Saad > > > > > > On Sat, Mar 10, 2018 at 8:04 PM, Saad Mufti > wrote: > > > >> Also, for now we have mitigated this problem by using the new setting in > >> HBase 1.4.0 that prevents one slow region server from blocking all > client > >> requests. Of course it causes some timeouts but our overall ecosystem > >> contains Kafka queues for retries, so we can live with that. From what I > >> can see, it looks like this setting also has the good effect of > preventing > >> clients from hammering a region server that is slow because its IPC > queues > >> are backed up, allowing it to recover faster. > >> > >> Does that make sense? > >> > >> Cheers. > >> > >> > >> Saad > >> > >> > >> On Sat, Mar 10, 2018 at 7:04 PM, Saad Mufti > wrote: > >> > >>> So if I understand correctly, we would mitigate the problem by not > >>> evicting blocks for archived files immediately? Wouldn't this > potentially > >>> lead to problems later if the LRU algo chooses to evict blocks for > active > >>> files and leave blocks for archived files in there? > >>> > >>> I would definitely love to test this!!! Unfortunately we are running on > >>> EMR and the details of how to patch HBase under EMR are not clear to > me :-( > >>> > >>> What we would really love would be a setting for actually immediately > >>> caching blocks for a new compacted file. I have seen in the code that > even > >>> is we have the cache on write setting set to true, it will refuse to > cache > >>> blocks for a file that is a newly compacted one. In our case we have > sized > >>> the bucket cache to be big enough to hold all our data, and really > want to > >>> avoid having to go to S3 until the last possible moment. A config > setting > >>> to test this would be great. > >>> > >>> But thanks everyone for your feedback. Any more would also be welcome > on > >>> the idea to let a user cache all newly compacted files. > >>> > >>> > >>> Saad > >>> > >>> > >>> On Wed, Mar 7, 2018 at 12:00 AM, Anoop John > >>> wrote: > >>> > >>a) it was indeed one of the regions that was being compacted, major > compaction in one case, minor compaction in another, the issue started > just > after compaction completed blowing away bucket cached blocks for the > older > HFile's > > About this part.Ya after the compaction, there is a step where the > compacted away HFile's blocks getting removed from cache. This op > takes a > write lock for this region (In Bucket Cache layer).. Every read op > which > is part of checkAndPut will try read from BC and that in turn need a > read > lock for this region. So there is chances that the read locks starve > because of so many frequent write locks . Each block evict will > attain > the > write lock one after other. Will it be possible for you to patch this > evict and test once? We can avoid the immediate evict from BC after > compaction. I can help you with a patch if you wish > > Anoop > > > > On Mon, Mar 5, 2018 at 11:07 AM, ramkrishna vasudevan < > ramkrishna.s.vasude...@gmail.com> wrote: > > Hi Saad > > > > Your argument here > >>> The > >>>theory is that since prefetch is an async operation, a lot of the > reads > in > >>>the checkAndPut for the region in question start reading from S3 > which is > >>>slow. So the write lock obtained for the checkAndPut is held for a > longer > >>>duration than normal. This has cascading upstream effects. Does > that > sound > >>>plausible? > > > > Seems very much plausible. So before even the prefetch happens say > for > > 'block 1' - and you have already issues N checkAndPut calls for the > >>