Re: OOM at Bootstrap Time
Well, the answer was Secondary indexes. I am guessing they were corrupted somehow. I dropped all of them, cleanup, and now nodes are bootstrapping fine. On Thu, Oct 30, 2014 at 3:50 PM, Maxime wrote: > I've been trying to go through the logs but I can't say I understand very > well the details: > > INFO [SlabPoolCleaner] 2014-10-30 19:20:18,446 ColumnFamilyStore.java:856 > - Enqueuing flush of loc: 7977119 (1%) on-heap, 0 (0%) off-heap > DEBUG [SharedPool-Worker-22] 2014-10-30 19:20:18,446 > AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row > 2c95cbbb61fb8ec3bd06d70058bfa236ccad5195e48fd00c056f7e1e3fdd4368 in > ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815026000 > !63072000,]) > DEBUG [SharedPool-Worker-6] 2014-10-30 19:20:18,446 > AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row > 41fc260427a88d2f084971702fdcb32756e0731c6042f93e9761e03db5197990 in > ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815333000 > !63072000,]) > DEBUG [SharedPool-Worker-25] 2014-10-30 19:20:18,446 > AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row > 2e8c4dab33faade0a4fc265e4126e43dc2e58fb72830f73d7e9b8e836101d413 in > ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815335000 > !63072000,]) > DEBUG [SharedPool-Worker-26] 2014-10-30 19:20:18,446 > AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row > 245bec68c5820364a72db093d5c9899b631e692006881c98f0abf4da5fbff4cd in > ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815344000 > !63072000,]) > DEBUG [SharedPool-Worker-20] 2014-10-30 19:20:18,446 > AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row > ea8dfb47177bd40f46aac4fe41d3cfea3316cf35451ace0825f46b6e0fa9e3ef in > ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815262000 > !63072000,]) > > This is a sample of Enqueuing flush events in the storm. > > On Thu, Oct 30, 2014 at 12:20 PM, Maxime wrote: > >> I will give a shot adding the logging. >> >> I've tried some experiments and I have no clue what could be happening >> anymore: >> >> I tried setting all nodes to a streamthroughput of 1 except 1, to see if >> somehow it was getting overloaded by too many streams coming in at once, >> nope. >> I went through the source at ColumnFamilyStore.java:856 where the huge >> burst of "Enqueuing flush..." occurs, and it's clearly at the moment >> memtables get converted to SSTables on disk. So I started the bootstrap >> process and using a bash script trigerred a 'nodetool flush' every minute >> during the processes. At first it seemed to work, but again after what >> seems to be a locally-trigered cue, the burst (many many thousands of >> Enqueuing flush...). But through my previous experiment, I am fairly >> certain it's not a question of volume of data coming in (throughput), or >> number of SSTables being streamed (dealing at max 150 files pr node). >> >> Does anyone know if such Enqueuing bursts are normal during bootstrap? >> I'd like to be able to say "it's because my nodes are underpowered", but at >> the moment, I'm leaning towards a bug of some kind. >> >> On Wed, Oct 29, 2014 at 3:05 PM, DuyHai Doan >> wrote: >> >>> Some ideas: >>> >>> 1) Put on DEBUG log on the joining node to see what is going on in >>> details with the stream with 1500 files >>> >>> 2) Check the stream ID to see whether it's a new stream or an old one >>> pending >>> >>> >>> >>> On Wed, Oct 29, 2014 at 2:21 AM, Maxime wrote: >>> Doan, thanks for the tip, I just read about it this morning, just waiting for the new version to pop up on the debian datastax repo. Michael, I do believe you are correct in the general running of the cluster and I've reset everything. So it took me a while to reply, I finally got the SSTables down, as seen in the OpsCenter graphs. I'm stumped however because when I bootstrap the new node, I still see very large number of files being streamed (~1500 for some nodes) and the bootstrap process is failing exactly as it did before, in a flury of "Enqueuing flush of ..." Any ideas? I'm reaching the end of what I know I can do, OpsCenter says around 32 SStables per CF, but still streaming tons of "files". :-/ On Mon, Oct 27, 2014 at 1:12 PM, DuyHai Doan wrote: > "Tombstones will be a very important issue for me since the dataset > is very much a rolling dataset using TTLs heavily." > > --> You can try the new DateTiered compaction strategy ( > https://issues.apache.org/jira/browse/CASSANDRA-6602) released on > 2.1.1 if you have a time series data model to eliminate tombstones > > On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael < > michael.la...@nytimes.com> wrote: > >> Again, from our experience w 2.0.x: >> >> Revert to the defaults - you are manually setting heap way too high >> IMHO. >> >>
Re: OOM at Bootstrap Time
I've been trying to go through the logs but I can't say I understand very well the details: INFO [SlabPoolCleaner] 2014-10-30 19:20:18,446 ColumnFamilyStore.java:856 - Enqueuing flush of loc: 7977119 (1%) on-heap, 0 (0%) off-heap DEBUG [SharedPool-Worker-22] 2014-10-30 19:20:18,446 AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row 2c95cbbb61fb8ec3bd06d70058bfa236ccad5195e48fd00c056f7e1e3fdd4368 in ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815026000 !63072000,]) DEBUG [SharedPool-Worker-6] 2014-10-30 19:20:18,446 AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row 41fc260427a88d2f084971702fdcb32756e0731c6042f93e9761e03db5197990 in ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815333000 !63072000,]) DEBUG [SharedPool-Worker-25] 2014-10-30 19:20:18,446 AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row 2e8c4dab33faade0a4fc265e4126e43dc2e58fb72830f73d7e9b8e836101d413 in ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815335000 !63072000,]) DEBUG [SharedPool-Worker-26] 2014-10-30 19:20:18,446 AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row 245bec68c5820364a72db093d5c9899b631e692006881c98f0abf4da5fbff4cd in ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815344000 !63072000,]) DEBUG [SharedPool-Worker-20] 2014-10-30 19:20:18,446 AbstractSimplePerColumnSecondaryIndex.java:124 - applying index row ea8dfb47177bd40f46aac4fe41d3cfea3316cf35451ace0825f46b6e0fa9e3ef in ColumnFamily(loc.loc_id_idx [66652e312e31332e3830:0:false:0@1414696815262000 !63072000,]) This is a sample of Enqueuing flush events in the storm. On Thu, Oct 30, 2014 at 12:20 PM, Maxime wrote: > I will give a shot adding the logging. > > I've tried some experiments and I have no clue what could be happening > anymore: > > I tried setting all nodes to a streamthroughput of 1 except 1, to see if > somehow it was getting overloaded by too many streams coming in at once, > nope. > I went through the source at ColumnFamilyStore.java:856 where the huge > burst of "Enqueuing flush..." occurs, and it's clearly at the moment > memtables get converted to SSTables on disk. So I started the bootstrap > process and using a bash script trigerred a 'nodetool flush' every minute > during the processes. At first it seemed to work, but again after what > seems to be a locally-trigered cue, the burst (many many thousands of > Enqueuing flush...). But through my previous experiment, I am fairly > certain it's not a question of volume of data coming in (throughput), or > number of SSTables being streamed (dealing at max 150 files pr node). > > Does anyone know if such Enqueuing bursts are normal during bootstrap? I'd > like to be able to say "it's because my nodes are underpowered", but at the > moment, I'm leaning towards a bug of some kind. > > On Wed, Oct 29, 2014 at 3:05 PM, DuyHai Doan wrote: > >> Some ideas: >> >> 1) Put on DEBUG log on the joining node to see what is going on in >> details with the stream with 1500 files >> >> 2) Check the stream ID to see whether it's a new stream or an old one >> pending >> >> >> >> On Wed, Oct 29, 2014 at 2:21 AM, Maxime wrote: >> >>> Doan, thanks for the tip, I just read about it this morning, just >>> waiting for the new version to pop up on the debian datastax repo. >>> >>> Michael, I do believe you are correct in the general running of the >>> cluster and I've reset everything. >>> >>> So it took me a while to reply, I finally got the SSTables down, as seen >>> in the OpsCenter graphs. I'm stumped however because when I bootstrap the >>> new node, I still see very large number of files being streamed (~1500 for >>> some nodes) and the bootstrap process is failing exactly as it did before, >>> in a flury of "Enqueuing flush of ..." >>> >>> Any ideas? I'm reaching the end of what I know I can do, OpsCenter says >>> around 32 SStables per CF, but still streaming tons of "files". :-/ >>> >>> >>> On Mon, Oct 27, 2014 at 1:12 PM, DuyHai Doan >>> wrote: >>> "Tombstones will be a very important issue for me since the dataset is very much a rolling dataset using TTLs heavily." --> You can try the new DateTiered compaction strategy ( https://issues.apache.org/jira/browse/CASSANDRA-6602) released on 2.1.1 if you have a time series data model to eliminate tombstones On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael < michael.la...@nytimes.com> wrote: > Again, from our experience w 2.0.x: > > Revert to the defaults - you are manually setting heap way too high > IMHO. > > On our small nodes we tried LCS - way too much compaction - switch all > CFs to STCS. > > We do a major rolling compaction on our small nodes weekly during less > busy hours - works great. Be sure you have enough disk. > > We never explicitly delete and only use ttls or truncation. You can > set GC to 0 in that c
Re: OOM at Bootstrap Time
I will give a shot adding the logging. I've tried some experiments and I have no clue what could be happening anymore: I tried setting all nodes to a streamthroughput of 1 except 1, to see if somehow it was getting overloaded by too many streams coming in at once, nope. I went through the source at ColumnFamilyStore.java:856 where the huge burst of "Enqueuing flush..." occurs, and it's clearly at the moment memtables get converted to SSTables on disk. So I started the bootstrap process and using a bash script trigerred a 'nodetool flush' every minute during the processes. At first it seemed to work, but again after what seems to be a locally-trigered cue, the burst (many many thousands of Enqueuing flush...). But through my previous experiment, I am fairly certain it's not a question of volume of data coming in (throughput), or number of SSTables being streamed (dealing at max 150 files pr node). Does anyone know if such Enqueuing bursts are normal during bootstrap? I'd like to be able to say "it's because my nodes are underpowered", but at the moment, I'm leaning towards a bug of some kind. On Wed, Oct 29, 2014 at 3:05 PM, DuyHai Doan wrote: > Some ideas: > > 1) Put on DEBUG log on the joining node to see what is going on in details > with the stream with 1500 files > > 2) Check the stream ID to see whether it's a new stream or an old one > pending > > > > On Wed, Oct 29, 2014 at 2:21 AM, Maxime wrote: > >> Doan, thanks for the tip, I just read about it this morning, just waiting >> for the new version to pop up on the debian datastax repo. >> >> Michael, I do believe you are correct in the general running of the >> cluster and I've reset everything. >> >> So it took me a while to reply, I finally got the SSTables down, as seen >> in the OpsCenter graphs. I'm stumped however because when I bootstrap the >> new node, I still see very large number of files being streamed (~1500 for >> some nodes) and the bootstrap process is failing exactly as it did before, >> in a flury of "Enqueuing flush of ..." >> >> Any ideas? I'm reaching the end of what I know I can do, OpsCenter says >> around 32 SStables per CF, but still streaming tons of "files". :-/ >> >> >> On Mon, Oct 27, 2014 at 1:12 PM, DuyHai Doan >> wrote: >> >>> "Tombstones will be a very important issue for me since the dataset is >>> very much a rolling dataset using TTLs heavily." >>> >>> --> You can try the new DateTiered compaction strategy ( >>> https://issues.apache.org/jira/browse/CASSANDRA-6602) released on 2.1.1 >>> if you have a time series data model to eliminate tombstones >>> >>> On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael < >>> michael.la...@nytimes.com> wrote: >>> Again, from our experience w 2.0.x: Revert to the defaults - you are manually setting heap way too high IMHO. On our small nodes we tried LCS - way too much compaction - switch all CFs to STCS. We do a major rolling compaction on our small nodes weekly during less busy hours - works great. Be sure you have enough disk. We never explicitly delete and only use ttls or truncation. You can set GC to 0 in that case, so tombstones are more readily expunged. There are a couple threads in the list that discuss this... also normal rolling repair becomes optional, reducing load (still repair if something unusual happens tho...). In your current situation, you need to kickstart compaction - are there any CFs you can truncate at least temporarily? Then try compacting a small CF, then another, etc. Hopefully you can get enough headroom to add a node. ml On Sun, Oct 26, 2014 at 6:24 PM, Maxime wrote: > Hmm, thanks for the reading. > > I initially followed some (perhaps too old) maintenance scripts, which > included weekly 'nodetool compact'. Is there a way for me to undo the > damage? Tombstones will be a very important issue for me since the dataset > is very much a rolling dataset using TTLs heavily. > > On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan > wrote: > >> "Should doing a major compaction on those nodes lead to a restructuration >> of the SSTables?" --> Beware of the major compaction on SizeTiered, it >> will >> create 2 giant SSTables and the expired/outdated/tombstone columns in >> this >> big file will be never cleaned since the SSTable will never get a chance >> to >> be compacted again >> >> Essentially to reduce the fragmentation of small SSTables you can >> stay with SizeTiered compaction and play around with compaction >> properties >> (the thresholds) to make C* group a bunch of files each time it compacts >> so >> that the file number shrinks to a reasonable count >> >> Since you're using C* 2.1 and anti-compaction has been introduced, I >> hesitate advising you to use Leveled compaction as a work-a
Re: OOM at Bootstrap Time
Some ideas: 1) Put on DEBUG log on the joining node to see what is going on in details with the stream with 1500 files 2) Check the stream ID to see whether it's a new stream or an old one pending On Wed, Oct 29, 2014 at 2:21 AM, Maxime wrote: > Doan, thanks for the tip, I just read about it this morning, just waiting > for the new version to pop up on the debian datastax repo. > > Michael, I do believe you are correct in the general running of the > cluster and I've reset everything. > > So it took me a while to reply, I finally got the SSTables down, as seen > in the OpsCenter graphs. I'm stumped however because when I bootstrap the > new node, I still see very large number of files being streamed (~1500 for > some nodes) and the bootstrap process is failing exactly as it did before, > in a flury of "Enqueuing flush of ..." > > Any ideas? I'm reaching the end of what I know I can do, OpsCenter says > around 32 SStables per CF, but still streaming tons of "files". :-/ > > > On Mon, Oct 27, 2014 at 1:12 PM, DuyHai Doan wrote: > >> "Tombstones will be a very important issue for me since the dataset is >> very much a rolling dataset using TTLs heavily." >> >> --> You can try the new DateTiered compaction strategy ( >> https://issues.apache.org/jira/browse/CASSANDRA-6602) released on 2.1.1 >> if you have a time series data model to eliminate tombstones >> >> On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael < >> michael.la...@nytimes.com> wrote: >> >>> Again, from our experience w 2.0.x: >>> >>> Revert to the defaults - you are manually setting heap way too high IMHO. >>> >>> On our small nodes we tried LCS - way too much compaction - switch all >>> CFs to STCS. >>> >>> We do a major rolling compaction on our small nodes weekly during less >>> busy hours - works great. Be sure you have enough disk. >>> >>> We never explicitly delete and only use ttls or truncation. You can set >>> GC to 0 in that case, so tombstones are more readily expunged. There are a >>> couple threads in the list that discuss this... also normal rolling repair >>> becomes optional, reducing load (still repair if something unusual happens >>> tho...). >>> >>> In your current situation, you need to kickstart compaction - are there >>> any CFs you can truncate at least temporarily? Then try compacting a small >>> CF, then another, etc. >>> >>> Hopefully you can get enough headroom to add a node. >>> >>> ml >>> >>> >>> >>> >>> On Sun, Oct 26, 2014 at 6:24 PM, Maxime wrote: >>> Hmm, thanks for the reading. I initially followed some (perhaps too old) maintenance scripts, which included weekly 'nodetool compact'. Is there a way for me to undo the damage? Tombstones will be a very important issue for me since the dataset is very much a rolling dataset using TTLs heavily. On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan wrote: > "Should doing a major compaction on those nodes lead to a restructuration > of the SSTables?" --> Beware of the major compaction on SizeTiered, it > will > create 2 giant SSTables and the expired/outdated/tombstone columns in this > big file will be never cleaned since the SSTable will never get a chance > to > be compacted again > > Essentially to reduce the fragmentation of small SSTables you can stay > with SizeTiered compaction and play around with compaction properties (the > thresholds) to make C* group a bunch of files each time it compacts so > that > the file number shrinks to a reasonable count > > Since you're using C* 2.1 and anti-compaction has been introduced, I > hesitate advising you to use Leveled compaction as a work-around to reduce > SSTable count. > > Things are a little bit more complicated because of the incremental > repair process (I don't know whether you're using incremental repair or > not > in production). The Dev blog says that Leveled compaction is performed > only > on repaired SSTables, the un-repaired ones still use SizeTiered, more > details here: > http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 > > Regards > > > > > > On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad > wrote: > >> If the issue is related to I/O, you're going to want to determine if >> you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz >> (queue size) and svctm, (service time).The higher those numbers >> are, the most overwhelmed your disk is. >> >> On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan >> wrote: >> > Hello Maxime >> > >> > Increasing the flush writers won't help if your disk I/O is not >> keeping up. >> > >> > I've had a look into the log file, below are some remarks: >> > >> > 1) There are a lot of SSTables on disk for some tables (events for >> example, >> > but not only). I've seen that some compacti
Re: OOM at Bootstrap Time
Doan, thanks for the tip, I just read about it this morning, just waiting for the new version to pop up on the debian datastax repo. Michael, I do believe you are correct in the general running of the cluster and I've reset everything. So it took me a while to reply, I finally got the SSTables down, as seen in the OpsCenter graphs. I'm stumped however because when I bootstrap the new node, I still see very large number of files being streamed (~1500 for some nodes) and the bootstrap process is failing exactly as it did before, in a flury of "Enqueuing flush of ..." Any ideas? I'm reaching the end of what I know I can do, OpsCenter says around 32 SStables per CF, but still streaming tons of "files". :-/ On Mon, Oct 27, 2014 at 1:12 PM, DuyHai Doan wrote: > "Tombstones will be a very important issue for me since the dataset is > very much a rolling dataset using TTLs heavily." > > --> You can try the new DateTiered compaction strategy ( > https://issues.apache.org/jira/browse/CASSANDRA-6602) released on 2.1.1 > if you have a time series data model to eliminate tombstones > > On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael > wrote: > >> Again, from our experience w 2.0.x: >> >> Revert to the defaults - you are manually setting heap way too high IMHO. >> >> On our small nodes we tried LCS - way too much compaction - switch all >> CFs to STCS. >> >> We do a major rolling compaction on our small nodes weekly during less >> busy hours - works great. Be sure you have enough disk. >> >> We never explicitly delete and only use ttls or truncation. You can set >> GC to 0 in that case, so tombstones are more readily expunged. There are a >> couple threads in the list that discuss this... also normal rolling repair >> becomes optional, reducing load (still repair if something unusual happens >> tho...). >> >> In your current situation, you need to kickstart compaction - are there >> any CFs you can truncate at least temporarily? Then try compacting a small >> CF, then another, etc. >> >> Hopefully you can get enough headroom to add a node. >> >> ml >> >> >> >> >> On Sun, Oct 26, 2014 at 6:24 PM, Maxime wrote: >> >>> Hmm, thanks for the reading. >>> >>> I initially followed some (perhaps too old) maintenance scripts, which >>> included weekly 'nodetool compact'. Is there a way for me to undo the >>> damage? Tombstones will be a very important issue for me since the dataset >>> is very much a rolling dataset using TTLs heavily. >>> >>> On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan >>> wrote: >>> "Should doing a major compaction on those nodes lead to a restructuration of the SSTables?" --> Beware of the major compaction on SizeTiered, it will create 2 giant SSTables and the expired/outdated/tombstone columns in this big file will be never cleaned since the SSTable will never get a chance to be compacted again Essentially to reduce the fragmentation of small SSTables you can stay with SizeTiered compaction and play around with compaction properties (the thresholds) to make C* group a bunch of files each time it compacts so that the file number shrinks to a reasonable count Since you're using C* 2.1 and anti-compaction has been introduced, I hesitate advising you to use Leveled compaction as a work-around to reduce SSTable count. Things are a little bit more complicated because of the incremental repair process (I don't know whether you're using incremental repair or not in production). The Dev blog says that Leveled compaction is performed only on repaired SSTables, the un-repaired ones still use SizeTiered, more details here: http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 Regards On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad wrote: > If the issue is related to I/O, you're going to want to determine if > you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz > (queue size) and svctm, (service time).The higher those numbers > are, the most overwhelmed your disk is. > > On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan > wrote: > > Hello Maxime > > > > Increasing the flush writers won't help if your disk I/O is not > keeping up. > > > > I've had a look into the log file, below are some remarks: > > > > 1) There are a lot of SSTables on disk for some tables (events for > example, > > but not only). I've seen that some compactions are taking up to 32 > SSTables > > (which corresponds to the default max value for SizeTiered > compaction). > > > > 2) There is a secondary index that I found suspicious : > loc.loc_id_idx. As > > its name implies I have the impression that it's an index on the id > of the > > loc which would lead to almost an 1-1 relationship between the > indexed value > > and the original loc. Such inde
Re: OOM at Bootstrap Time
"Tombstones will be a very important issue for me since the dataset is very much a rolling dataset using TTLs heavily." --> You can try the new DateTiered compaction strategy ( https://issues.apache.org/jira/browse/CASSANDRA-6602) released on 2.1.1 if you have a time series data model to eliminate tombstones On Mon, Oct 27, 2014 at 5:47 PM, Laing, Michael wrote: > Again, from our experience w 2.0.x: > > Revert to the defaults - you are manually setting heap way too high IMHO. > > On our small nodes we tried LCS - way too much compaction - switch all CFs > to STCS. > > We do a major rolling compaction on our small nodes weekly during less > busy hours - works great. Be sure you have enough disk. > > We never explicitly delete and only use ttls or truncation. You can set GC > to 0 in that case, so tombstones are more readily expunged. There are a > couple threads in the list that discuss this... also normal rolling repair > becomes optional, reducing load (still repair if something unusual happens > tho...). > > In your current situation, you need to kickstart compaction - are there > any CFs you can truncate at least temporarily? Then try compacting a small > CF, then another, etc. > > Hopefully you can get enough headroom to add a node. > > ml > > > > > On Sun, Oct 26, 2014 at 6:24 PM, Maxime wrote: > >> Hmm, thanks for the reading. >> >> I initially followed some (perhaps too old) maintenance scripts, which >> included weekly 'nodetool compact'. Is there a way for me to undo the >> damage? Tombstones will be a very important issue for me since the dataset >> is very much a rolling dataset using TTLs heavily. >> >> On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan >> wrote: >> >>> "Should doing a major compaction on those nodes lead to a restructuration >>> of the SSTables?" --> Beware of the major compaction on SizeTiered, it will >>> create 2 giant SSTables and the expired/outdated/tombstone columns in this >>> big file will be never cleaned since the SSTable will never get a chance to >>> be compacted again >>> >>> Essentially to reduce the fragmentation of small SSTables you can stay >>> with SizeTiered compaction and play around with compaction properties (the >>> thresholds) to make C* group a bunch of files each time it compacts so that >>> the file number shrinks to a reasonable count >>> >>> Since you're using C* 2.1 and anti-compaction has been introduced, I >>> hesitate advising you to use Leveled compaction as a work-around to reduce >>> SSTable count. >>> >>> Things are a little bit more complicated because of the incremental >>> repair process (I don't know whether you're using incremental repair or not >>> in production). The Dev blog says that Leveled compaction is performed only >>> on repaired SSTables, the un-repaired ones still use SizeTiered, more >>> details here: >>> http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 >>> >>> Regards >>> >>> >>> >>> >>> >>> On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad >>> wrote: >>> If the issue is related to I/O, you're going to want to determine if you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz (queue size) and svctm, (service time).The higher those numbers are, the most overwhelmed your disk is. On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan wrote: > Hello Maxime > > Increasing the flush writers won't help if your disk I/O is not keeping up. > > I've had a look into the log file, below are some remarks: > > 1) There are a lot of SSTables on disk for some tables (events for example, > but not only). I've seen that some compactions are taking up to 32 SSTables > (which corresponds to the default max value for SizeTiered compaction). > > 2) There is a secondary index that I found suspicious : loc.loc_id_idx. As > its name implies I have the impression that it's an index on the id of the > loc which would lead to almost an 1-1 relationship between the indexed value > and the original loc. Such index should be avoided because they do not > perform well. If it's not an index on the loc_id, please disregard my remark > > 3) There is a clear imbalance of SSTable count on some nodes. In the log, I > saw: > > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 163 files(4 111 187 195 bytes), sending 0 > files(0 bytes) > > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 154 files(3 332 779 920 bytes), sending 0 > files(0 bytes) > > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 > StreamResultFuture.j
Re: OOM at Bootstrap Time
Again, from our experience w 2.0.x: Revert to the defaults - you are manually setting heap way too high IMHO. On our small nodes we tried LCS - way too much compaction - switch all CFs to STCS. We do a major rolling compaction on our small nodes weekly during less busy hours - works great. Be sure you have enough disk. We never explicitly delete and only use ttls or truncation. You can set GC to 0 in that case, so tombstones are more readily expunged. There are a couple threads in the list that discuss this... also normal rolling repair becomes optional, reducing load (still repair if something unusual happens tho...). In your current situation, you need to kickstart compaction - are there any CFs you can truncate at least temporarily? Then try compacting a small CF, then another, etc. Hopefully you can get enough headroom to add a node. ml On Sun, Oct 26, 2014 at 6:24 PM, Maxime wrote: > Hmm, thanks for the reading. > > I initially followed some (perhaps too old) maintenance scripts, which > included weekly 'nodetool compact'. Is there a way for me to undo the > damage? Tombstones will be a very important issue for me since the dataset > is very much a rolling dataset using TTLs heavily. > > On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan wrote: > >> "Should doing a major compaction on those nodes lead to a restructuration >> of the SSTables?" --> Beware of the major compaction on SizeTiered, it will >> create 2 giant SSTables and the expired/outdated/tombstone columns in this >> big file will be never cleaned since the SSTable will never get a chance to >> be compacted again >> >> Essentially to reduce the fragmentation of small SSTables you can stay >> with SizeTiered compaction and play around with compaction properties (the >> thresholds) to make C* group a bunch of files each time it compacts so that >> the file number shrinks to a reasonable count >> >> Since you're using C* 2.1 and anti-compaction has been introduced, I >> hesitate advising you to use Leveled compaction as a work-around to reduce >> SSTable count. >> >> Things are a little bit more complicated because of the incremental >> repair process (I don't know whether you're using incremental repair or not >> in production). The Dev blog says that Leveled compaction is performed only >> on repaired SSTables, the un-repaired ones still use SizeTiered, more >> details here: >> http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 >> >> Regards >> >> >> >> >> >> On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad >> wrote: >> >>> If the issue is related to I/O, you're going to want to determine if >>> you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz >>> (queue size) and svctm, (service time).The higher those numbers >>> are, the most overwhelmed your disk is. >>> >>> On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan >>> wrote: >>> > Hello Maxime >>> > >>> > Increasing the flush writers won't help if your disk I/O is not >>> keeping up. >>> > >>> > I've had a look into the log file, below are some remarks: >>> > >>> > 1) There are a lot of SSTables on disk for some tables (events for >>> example, >>> > but not only). I've seen that some compactions are taking up to 32 >>> SSTables >>> > (which corresponds to the default max value for SizeTiered compaction). >>> > >>> > 2) There is a secondary index that I found suspicious : >>> loc.loc_id_idx. As >>> > its name implies I have the impression that it's an index on the id of >>> the >>> > loc which would lead to almost an 1-1 relationship between the indexed >>> value >>> > and the original loc. Such index should be avoided because they do not >>> > perform well. If it's not an index on the loc_id, please disregard my >>> remark >>> > >>> > 3) There is a clear imbalance of SSTable count on some nodes. In the >>> log, I >>> > saw: >>> > >>> > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 >>> > StreamResultFuture.java:166 - [Stream >>> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >>> > ID#0] Prepare completed. Receiving 163 files(4 111 187 195 bytes), >>> sending 0 >>> > files(0 bytes) >>> > >>> > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 >>> > StreamResultFuture.java:166 - [Stream >>> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >>> > ID#0] Prepare completed. Receiving 154 files(3 332 779 920 bytes), >>> sending 0 >>> > files(0 bytes) >>> > >>> > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 >>> > StreamResultFuture.java:166 - [Stream >>> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >>> > ID#0] Prepare completed. Receiving 1315 files(4 606 316 933 bytes), >>> sending >>> > 0 files(0 bytes) >>> > >>> > INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 >>> > StreamResultFuture.java:166 - [Stream >>> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >>> > ID#0] Prepare completed. Receiving 1640 files(3 208 023 573 bytes), >>> sending >>> > 0 files(0 bytes) >>> > >>> > As you can see, the existing 4 nodes are streaming data to the
Re: OOM at Bootstrap Time
Hmm, thanks for the reading. I initially followed some (perhaps too old) maintenance scripts, which included weekly 'nodetool compact'. Is there a way for me to undo the damage? Tombstones will be a very important issue for me since the dataset is very much a rolling dataset using TTLs heavily. On Sun, Oct 26, 2014 at 6:04 PM, DuyHai Doan wrote: > "Should doing a major compaction on those nodes lead to a restructuration > of the SSTables?" --> Beware of the major compaction on SizeTiered, it will > create 2 giant SSTables and the expired/outdated/tombstone columns in this > big file will be never cleaned since the SSTable will never get a chance to > be compacted again > > Essentially to reduce the fragmentation of small SSTables you can stay > with SizeTiered compaction and play around with compaction properties (the > thresholds) to make C* group a bunch of files each time it compacts so that > the file number shrinks to a reasonable count > > Since you're using C* 2.1 and anti-compaction has been introduced, I > hesitate advising you to use Leveled compaction as a work-around to reduce > SSTable count. > > Things are a little bit more complicated because of the incremental > repair process (I don't know whether you're using incremental repair or not > in production). The Dev blog says that Leveled compaction is performed only > on repaired SSTables, the un-repaired ones still use SizeTiered, more > details here: > http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 > > Regards > > > > > > On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad > wrote: > >> If the issue is related to I/O, you're going to want to determine if >> you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz >> (queue size) and svctm, (service time).The higher those numbers >> are, the most overwhelmed your disk is. >> >> On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan >> wrote: >> > Hello Maxime >> > >> > Increasing the flush writers won't help if your disk I/O is not keeping >> up. >> > >> > I've had a look into the log file, below are some remarks: >> > >> > 1) There are a lot of SSTables on disk for some tables (events for >> example, >> > but not only). I've seen that some compactions are taking up to 32 >> SSTables >> > (which corresponds to the default max value for SizeTiered compaction). >> > >> > 2) There is a secondary index that I found suspicious : loc.loc_id_idx. >> As >> > its name implies I have the impression that it's an index on the id of >> the >> > loc which would lead to almost an 1-1 relationship between the indexed >> value >> > and the original loc. Such index should be avoided because they do not >> > perform well. If it's not an index on the loc_id, please disregard my >> remark >> > >> > 3) There is a clear imbalance of SSTable count on some nodes. In the >> log, I >> > saw: >> > >> > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 >> > StreamResultFuture.java:166 - [Stream >> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >> > ID#0] Prepare completed. Receiving 163 files(4 111 187 195 bytes), >> sending 0 >> > files(0 bytes) >> > >> > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 >> > StreamResultFuture.java:166 - [Stream >> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >> > ID#0] Prepare completed. Receiving 154 files(3 332 779 920 bytes), >> sending 0 >> > files(0 bytes) >> > >> > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 >> > StreamResultFuture.java:166 - [Stream >> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >> > ID#0] Prepare completed. Receiving 1315 files(4 606 316 933 bytes), >> sending >> > 0 files(0 bytes) >> > >> > INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 >> > StreamResultFuture.java:166 - [Stream >> #a6e54ea0-5bed-11e4-8df5-f357715e1a79 >> > ID#0] Prepare completed. Receiving 1640 files(3 208 023 573 bytes), >> sending >> > 0 files(0 bytes) >> > >> > As you can see, the existing 4 nodes are streaming data to the new >> node and >> > on average the data set size is about 3.3 - 4.5 Gb. However the number >> of >> > SSTables is around 150 files for nodes ...20 and >> > ...81 but goes through the roof to reach 1315 files for >> > ...71 and 1640 files for ...217 >> > >> > The total data set size is roughly the same but the file number is x10, >> > which mean that you'll have a bunch of tiny files. >> > >> > I guess that upon reception of those files, there will be a massive >> flush >> > to disk, explaining the behaviour you're facing (flush storm) >> > >> > I would suggest looking on nodes ...71 and >> ...217 to >> > check for the total SSTable count for each table to confirm this >> intuition >> > >> > Regards >> > >> > >> > On Sun, Oct 26, 2014 at 4:58 PM, Maxime wrote: >> >> >> >> I've emailed you a raw log file of an instance of this happening. >> >> >> >> I've been monitoring more closely the timing of events in tpstats and >> the >> >> lo
Re: OOM at Bootstrap Time
"Should doing a major compaction on those nodes lead to a restructuration of the SSTables?" --> Beware of the major compaction on SizeTiered, it will create 2 giant SSTables and the expired/outdated/tombstone columns in this big file will be never cleaned since the SSTable will never get a chance to be compacted again Essentially to reduce the fragmentation of small SSTables you can stay with SizeTiered compaction and play around with compaction properties (the thresholds) to make C* group a bunch of files each time it compacts so that the file number shrinks to a reasonable count Since you're using C* 2.1 and anti-compaction has been introduced, I hesitate advising you to use Leveled compaction as a work-around to reduce SSTable count. Things are a little bit more complicated because of the incremental repair process (I don't know whether you're using incremental repair or not in production). The Dev blog says that Leveled compaction is performed only on repaired SSTables, the un-repaired ones still use SizeTiered, more details here: http://www.datastax.com/dev/blog/anticompaction-in-cassandra-2-1 Regards On Sun, Oct 26, 2014 at 9:44 PM, Jonathan Haddad wrote: > If the issue is related to I/O, you're going to want to determine if > you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz > (queue size) and svctm, (service time).The higher those numbers > are, the most overwhelmed your disk is. > > On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan > wrote: > > Hello Maxime > > > > Increasing the flush writers won't help if your disk I/O is not keeping > up. > > > > I've had a look into the log file, below are some remarks: > > > > 1) There are a lot of SSTables on disk for some tables (events for > example, > > but not only). I've seen that some compactions are taking up to 32 > SSTables > > (which corresponds to the default max value for SizeTiered compaction). > > > > 2) There is a secondary index that I found suspicious : loc.loc_id_idx. > As > > its name implies I have the impression that it's an index on the id of > the > > loc which would lead to almost an 1-1 relationship between the indexed > value > > and the original loc. Such index should be avoided because they do not > > perform well. If it's not an index on the loc_id, please disregard my > remark > > > > 3) There is a clear imbalance of SSTable count on some nodes. In the > log, I > > saw: > > > > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 > > StreamResultFuture.java:166 - [Stream > #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > > ID#0] Prepare completed. Receiving 163 files(4 111 187 195 bytes), > sending 0 > > files(0 bytes) > > > > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 > > StreamResultFuture.java:166 - [Stream > #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > > ID#0] Prepare completed. Receiving 154 files(3 332 779 920 bytes), > sending 0 > > files(0 bytes) > > > > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 > > StreamResultFuture.java:166 - [Stream > #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > > ID#0] Prepare completed. Receiving 1315 files(4 606 316 933 bytes), > sending > > 0 files(0 bytes) > > > > INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 > > StreamResultFuture.java:166 - [Stream > #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > > ID#0] Prepare completed. Receiving 1640 files(3 208 023 573 bytes), > sending > > 0 files(0 bytes) > > > > As you can see, the existing 4 nodes are streaming data to the new node > and > > on average the data set size is about 3.3 - 4.5 Gb. However the number of > > SSTables is around 150 files for nodes ...20 and > > ...81 but goes through the roof to reach 1315 files for > > ...71 and 1640 files for ...217 > > > > The total data set size is roughly the same but the file number is x10, > > which mean that you'll have a bunch of tiny files. > > > > I guess that upon reception of those files, there will be a massive > flush > > to disk, explaining the behaviour you're facing (flush storm) > > > > I would suggest looking on nodes ...71 and > ...217 to > > check for the total SSTable count for each table to confirm this > intuition > > > > Regards > > > > > > On Sun, Oct 26, 2014 at 4:58 PM, Maxime wrote: > >> > >> I've emailed you a raw log file of an instance of this happening. > >> > >> I've been monitoring more closely the timing of events in tpstats and > the > >> logs and I believe this is what is happening: > >> > >> - For some reason, C* decides to provoke a flush storm (I say some > reason, > >> I'm sure there is one but I have had difficulty determining the > behaviour > >> changes between 1.* and more recent releases). > >> - So we see ~ 3000 flush being enqueued. > >> - This happens so suddenly that even boosting the number of flush > writers > >> to 20 does not suffice. I don't even see "all time blocked" numbers for > it > >> before C* stops resp
Re: OOM at Bootstrap Time
If the issue is related to I/O, you're going to want to determine if you're saturated. Take a look at `iostat -dmx 1`, you'll see avgqu-sz (queue size) and svctm, (service time).The higher those numbers are, the most overwhelmed your disk is. On Sun, Oct 26, 2014 at 12:01 PM, DuyHai Doan wrote: > Hello Maxime > > Increasing the flush writers won't help if your disk I/O is not keeping up. > > I've had a look into the log file, below are some remarks: > > 1) There are a lot of SSTables on disk for some tables (events for example, > but not only). I've seen that some compactions are taking up to 32 SSTables > (which corresponds to the default max value for SizeTiered compaction). > > 2) There is a secondary index that I found suspicious : loc.loc_id_idx. As > its name implies I have the impression that it's an index on the id of the > loc which would lead to almost an 1-1 relationship between the indexed value > and the original loc. Such index should be avoided because they do not > perform well. If it's not an index on the loc_id, please disregard my remark > > 3) There is a clear imbalance of SSTable count on some nodes. In the log, I > saw: > > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 163 files(4 111 187 195 bytes), sending 0 > files(0 bytes) > > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 154 files(3 332 779 920 bytes), sending 0 > files(0 bytes) > > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 1315 files(4 606 316 933 bytes), sending > 0 files(0 bytes) > > INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving 1640 files(3 208 023 573 bytes), sending > 0 files(0 bytes) > > As you can see, the existing 4 nodes are streaming data to the new node and > on average the data set size is about 3.3 - 4.5 Gb. However the number of > SSTables is around 150 files for nodes ...20 and > ...81 but goes through the roof to reach 1315 files for > ...71 and 1640 files for ...217 > > The total data set size is roughly the same but the file number is x10, > which mean that you'll have a bunch of tiny files. > > I guess that upon reception of those files, there will be a massive flush > to disk, explaining the behaviour you're facing (flush storm) > > I would suggest looking on nodes ...71 and ...217 to > check for the total SSTable count for each table to confirm this intuition > > Regards > > > On Sun, Oct 26, 2014 at 4:58 PM, Maxime wrote: >> >> I've emailed you a raw log file of an instance of this happening. >> >> I've been monitoring more closely the timing of events in tpstats and the >> logs and I believe this is what is happening: >> >> - For some reason, C* decides to provoke a flush storm (I say some reason, >> I'm sure there is one but I have had difficulty determining the behaviour >> changes between 1.* and more recent releases). >> - So we see ~ 3000 flush being enqueued. >> - This happens so suddenly that even boosting the number of flush writers >> to 20 does not suffice. I don't even see "all time blocked" numbers for it >> before C* stops responding. I suspect this is due to the sudden OOM and GC >> occurring. >> - The last tpstat that comes back before the node goes down indicates 20 >> active and 3000 pending and the rest 0. It's by far the anomalous activity. >> >> Is there a way to throttle down this generation of Flush? C* complains if >> I set the queue_size to any value (deprecated now?) and boosting the threads >> does not seem to help since even at 20 we're an order of magnitude off. >> >> Suggestions? Comments? >> >> >> On Sun, Oct 26, 2014 at 2:26 AM, DuyHai Doan wrote: >>> >>> Hello Maxime >>> >>> Can you put the complete logs and config somewhere ? It would be >>> interesting to know what is the cause of the OOM. >>> >>> On Sun, Oct 26, 2014 at 3:15 AM, Maxime wrote: Thanks a lot that is comforting. We are also small at the moment so I definitely can relate with the idea of keeping small and simple at a level where it just works. I see the new Apache version has a lot of fixes so I will try to upgrade before I look into downgrading. On Saturday, October 25, 2014, Laing, Michael wrote: > > Since no one else has stepped in... > > We have run clusters with ridiculously small nodes - I have a > production cluster in AWS with 4GB nodes each with 1 CPU and disk-based > instance storage. It works fine but you can see those li
Re: OOM at Bootstrap Time
Thank you very much for your reply. This is a deeper interpretation of the logs than I can do at the moment. Regarding 2) it's a good assumption on your part but in this case, non-obviously the loc table's primary key is actually not id, the scheme changed historically which has led to this odd naming of the field. What you are describing makes me think it may be related to an odd state left behind from an experiment I made a few days ago. I switched all tables from SizeTiered to Level compaction strategy (in an attempt to make better use of the limited disk space on the machines, compaction was starting to lead to nodes out of space). Afterwards I reverted a few of the more write-heavy tables to SizeTiered. The whole experiment seemed shaky. Should doing a major compaction on those nodes lead to a restructuration of the SSTables? I would think so. On Sunday, October 26, 2014, DuyHai Doan wrote: > Hello Maxime > > Increasing the flush writers won't help if your disk I/O is not keeping up. > > I've had a look into the log file, below are some remarks: > > 1) There are a lot of SSTables on disk for some tables (events for > example, but not only). I've seen that some compactions are taking up to 32 > SSTables (which corresponds to the default max value for SizeTiered > compaction). > > 2) There is a secondary index that I found suspicious : loc.loc_id_idx. As > its name implies I have the impression that it's an index on the id of the > loc which would lead to almost an 1-1 relationship between the indexed > value and the original loc. Such index should be avoided because they do > not perform well. If it's not an index on the loc_id, please disregard my > remark > > 3) There is a clear imbalance of SSTable count on some nodes. In the log, > I saw: > > INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving *163* files(*4 111 187 195* bytes), > sending 0 files(0 bytes) > > INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving *154* files(*3 332 779 920* bytes), > sending 0 files(0 bytes) > > INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving *1315* files(*4 606 316 933* bytes), > sending 0 files(0 bytes) > > INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 > StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 > ID#0] Prepare completed. Receiving *1640* files(*3 208 023 573* bytes), > sending 0 files(0 bytes) > > As you can see, the existing 4 nodes are streaming data to the new node > and on average the data set size is about 3.3 - 4.5 Gb. However the number > of SSTables is around 150 files for nodes ...20 and > ...81 but goes through the roof to reach *1315* files for > ...71 and *1640* files for ...217 > > The total data set size is roughly the same but the file number is x10, > which mean that you'll have a bunch of tiny files. > > I guess that upon reception of those files, there will be a massive flush > to disk, explaining the behaviour you're facing (flush storm) > > I would suggest looking on nodes ...71 and ...217 > to check for the total SSTable count for each table to confirm this > intuition > > Regards > > > On Sun, Oct 26, 2014 at 4:58 PM, Maxime > wrote: > >> I've emailed you a raw log file of an instance of this happening. >> >> I've been monitoring more closely the timing of events in tpstats and the >> logs and I believe this is what is happening: >> >> - For some reason, C* decides to provoke a flush storm (I say some >> reason, I'm sure there is one but I have had difficulty determining the >> behaviour changes between 1.* and more recent releases). >> - So we see ~ 3000 flush being enqueued. >> - This happens so suddenly that even boosting the number of flush writers >> to 20 does not suffice. I don't even see "all time blocked" numbers for it >> before C* stops responding. I suspect this is due to the sudden OOM and GC >> occurring. >> - The last tpstat that comes back before the node goes down indicates 20 >> active and 3000 pending and the rest 0. It's by far the anomalous activity. >> >> Is there a way to throttle down this generation of Flush? C* complains if >> I set the queue_size to any value (deprecated now?) and boosting the >> threads does not seem to help since even at 20 we're an order of magnitude >> off. >> >> Suggestions? Comments? >> >> >> On Sun, Oct 26, 2014 at 2:26 AM, DuyHai Doan > > wrote: >> >>> Hello Maxime >>> >>> Can you put the complete logs and config somewhere ? It would be >>> interesting to know what is the cause of the OOM. >>> >>> On Sun, Oct 26, 2014 at 3:15 AM, Maxime >> > w
Re: OOM at Bootstrap Time
Hello Maxime Increasing the flush writers won't help if your disk I/O is not keeping up. I've had a look into the log file, below are some remarks: 1) There are a lot of SSTables on disk for some tables (events for example, but not only). I've seen that some compactions are taking up to 32 SSTables (which corresponds to the default max value for SizeTiered compaction). 2) There is a secondary index that I found suspicious : loc.loc_id_idx. As its name implies I have the impression that it's an index on the id of the loc which would lead to almost an 1-1 relationship between the indexed value and the original loc. Such index should be avoided because they do not perform well. If it's not an index on the loc_id, please disregard my remark 3) There is a clear imbalance of SSTable count on some nodes. In the log, I saw: INFO [STREAM-IN-/...20] 2014-10-25 02:21:43,360 StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 ID#0] Prepare completed. Receiving *163* files(*4 111 187 195* bytes), sending 0 files(0 bytes) INFO [STREAM-IN-/...81] 2014-10-25 02:21:46,121 StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 ID#0] Prepare completed. Receiving *154* files(*3 332 779 920* bytes), sending 0 files(0 bytes) INFO [STREAM-IN-/...71] 2014-10-25 02:21:50,494 StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 ID#0] Prepare completed. Receiving *1315* files(*4 606 316 933* bytes), sending 0 files(0 bytes) INFO [STREAM-IN-/...217] 2014-10-25 02:21:51,036 StreamResultFuture.java:166 - [Stream #a6e54ea0-5bed-11e4-8df5-f357715e1a79 ID#0] Prepare completed. Receiving *1640* files(*3 208 023 573* bytes), sending 0 files(0 bytes) As you can see, the existing 4 nodes are streaming data to the new node and on average the data set size is about 3.3 - 4.5 Gb. However the number of SSTables is around 150 files for nodes ...20 and ...81 but goes through the roof to reach *1315* files for ...71 and *1640* files for ...217 The total data set size is roughly the same but the file number is x10, which mean that you'll have a bunch of tiny files. I guess that upon reception of those files, there will be a massive flush to disk, explaining the behaviour you're facing (flush storm) I would suggest looking on nodes ...71 and ...217 to check for the total SSTable count for each table to confirm this intuition Regards On Sun, Oct 26, 2014 at 4:58 PM, Maxime wrote: > I've emailed you a raw log file of an instance of this happening. > > I've been monitoring more closely the timing of events in tpstats and the > logs and I believe this is what is happening: > > - For some reason, C* decides to provoke a flush storm (I say some reason, > I'm sure there is one but I have had difficulty determining the behaviour > changes between 1.* and more recent releases). > - So we see ~ 3000 flush being enqueued. > - This happens so suddenly that even boosting the number of flush writers > to 20 does not suffice. I don't even see "all time blocked" numbers for it > before C* stops responding. I suspect this is due to the sudden OOM and GC > occurring. > - The last tpstat that comes back before the node goes down indicates 20 > active and 3000 pending and the rest 0. It's by far the anomalous activity. > > Is there a way to throttle down this generation of Flush? C* complains if > I set the queue_size to any value (deprecated now?) and boosting the > threads does not seem to help since even at 20 we're an order of magnitude > off. > > Suggestions? Comments? > > > On Sun, Oct 26, 2014 at 2:26 AM, DuyHai Doan wrote: > >> Hello Maxime >> >> Can you put the complete logs and config somewhere ? It would be >> interesting to know what is the cause of the OOM. >> >> On Sun, Oct 26, 2014 at 3:15 AM, Maxime wrote: >> >>> Thanks a lot that is comforting. We are also small at the moment so I >>> definitely can relate with the idea of keeping small and simple at a level >>> where it just works. >>> >>> I see the new Apache version has a lot of fixes so I will try to >>> upgrade before I look into downgrading. >>> >>> >>> On Saturday, October 25, 2014, Laing, Michael >>> wrote: >>> Since no one else has stepped in... We have run clusters with ridiculously small nodes - I have a production cluster in AWS with 4GB nodes each with 1 CPU and disk-based instance storage. It works fine but you can see those little puppies struggle... And I ran into problems such as you observe... Upgrading Java to the latest 1.7 and - most importantly - *reverting to the default configuration, esp. for heap*, seemed to settle things down completely. Also make sure that you are using the 'recommended production settings' from the docs on your boxen. However we are running 2.0.x not 2.1.0 so YMMV. >>
Re: OOM at Bootstrap Time
I've emailed you a raw log file of an instance of this happening.
I've been monitoring more closely the timing of events in tpstats and the
logs and I believe this is what is happening:
- For some reason, C* decides to provoke a flush storm (I say some reason,
I'm sure there is one but I have had difficulty determining the behaviour
changes between 1.* and more recent releases).
- So we see ~ 3000 flush being enqueued.
- This happens so suddenly that even boosting the number of flush writers
to 20 does not suffice. I don't even see "all time blocked" numbers for it
before C* stops responding. I suspect this is due to the sudden OOM and GC
occurring.
- The last tpstat that comes back before the node goes down indicates 20
active and 3000 pending and the rest 0. It's by far the anomalous activity.
Is there a way to throttle down this generation of Flush? C* complains if I
set the queue_size to any value (deprecated now?) and boosting the threads
does not seem to help since even at 20 we're an order of magnitude off.
Suggestions? Comments?
On Sun, Oct 26, 2014 at 2:26 AM, DuyHai Doan wrote:
> Hello Maxime
>
> Can you put the complete logs and config somewhere ? It would be
> interesting to know what is the cause of the OOM.
>
> On Sun, Oct 26, 2014 at 3:15 AM, Maxime wrote:
>
>> Thanks a lot that is comforting. We are also small at the moment so I
>> definitely can relate with the idea of keeping small and simple at a level
>> where it just works.
>>
>> I see the new Apache version has a lot of fixes so I will try to upgrade
>> before I look into downgrading.
>>
>>
>> On Saturday, October 25, 2014, Laing, Michael
>> wrote:
>>
>>> Since no one else has stepped in...
>>>
>>> We have run clusters with ridiculously small nodes - I have a production
>>> cluster in AWS with 4GB nodes each with 1 CPU and disk-based instance
>>> storage. It works fine but you can see those little puppies struggle...
>>>
>>> And I ran into problems such as you observe...
>>>
>>> Upgrading Java to the latest 1.7 and - most importantly - *reverting to
>>> the default configuration, esp. for heap*, seemed to settle things down
>>> completely. Also make sure that you are using the 'recommended production
>>> settings' from the docs on your boxen.
>>>
>>> However we are running 2.0.x not 2.1.0 so YMMV.
>>>
>>> And we are switching to 15GB nodes w 2 heftier CPUs each and SSD storage
>>> - still a 'small' machine, but much more reasonable for C*.
>>>
>>> However I can't say I am an expert, since I deliberately keep things so
>>> simple that we do not encounter problems - it just works so I dig into
>>> other stuff.
>>>
>>> ml
>>>
>>>
>>> On Sat, Oct 25, 2014 at 5:22 PM, Maxime wrote:
>>>
Hello, I've been trying to add a new node to my cluster ( 4 nodes ) for
a few days now.
I started by adding a node similar to my current configuration, 4 GB or
RAM + 2 Cores on DigitalOcean. However every time, I would end up getting
OOM errors after many log entries of the type:
INFO [SlabPoolCleaner] 2014-10-25 13:44:57,240
ColumnFamilyStore.java:856 - Enqueuing flush of mycf: 5383 (0%) on-heap, 0
(0%) off-heap
leading to:
ka-120-Data.db (39291 bytes) for commitlog position
ReplayPosition(segmentId=1414243978538, position=23699418)
WARN [SharedPool-Worker-13] 2014-10-25 13:48:18,032
AbstractTracingAwareExecutorService.java:167 - Uncaught exception on thread
Thread[SharedPool-Worker-13,5,main]: {}
java.lang.OutOfMemoryError: Java heap space
Thinking it had to do with either compaction somehow or streaming, 2
activities I've had tremendous issues with in the past; I tried to slow
down the setstreamthroughput to extremely low values all the way to 5. I
also tried setting setcompactionthoughput to 0, and then reading that in
some cases it might be too fast, down to 8. Nothing worked, it merely
vaguely changed the mean time to OOM but not in a way indicating either was
anywhere a solution.
The nodes were configured with 2 GB of Heap initially, I tried to crank
it up to 3 GB, stressing the host memory to its limit.
After doing some exploration (I am considering writing a Cassandra Ops
documentation with lessons learned since there seems to be little of it in
organized fashions), I read that some people had strange issues on
lower-end boxes like that, so I bit the bullet and upgraded my new node to
a 8GB + 4 Core instance, which was anecdotally better.
To my complete shock, exact same issues are present, even raising the
Heap memory to 6 GB. I figure it can't be a "normal" situation anymore, but
must be a bug somehow.
My cluster is 4 nodes, RF of 2, about 160 GB of data across all nodes.
About 10 CF of varying sizes. Runtime writes are between 300 to 900 /
second. Cassandra 2.1.0, nothing too wild.
Has anyone encountered th
Re: OOM at Bootstrap Time
Hello Maxime
Can you put the complete logs and config somewhere ? It would be
interesting to know what is the cause of the OOM.
On Sun, Oct 26, 2014 at 3:15 AM, Maxime wrote:
> Thanks a lot that is comforting. We are also small at the moment so I
> definitely can relate with the idea of keeping small and simple at a level
> where it just works.
>
> I see the new Apache version has a lot of fixes so I will try to upgrade
> before I look into downgrading.
>
>
> On Saturday, October 25, 2014, Laing, Michael
> wrote:
>
>> Since no one else has stepped in...
>>
>> We have run clusters with ridiculously small nodes - I have a production
>> cluster in AWS with 4GB nodes each with 1 CPU and disk-based instance
>> storage. It works fine but you can see those little puppies struggle...
>>
>> And I ran into problems such as you observe...
>>
>> Upgrading Java to the latest 1.7 and - most importantly - *reverting to
>> the default configuration, esp. for heap*, seemed to settle things down
>> completely. Also make sure that you are using the 'recommended production
>> settings' from the docs on your boxen.
>>
>> However we are running 2.0.x not 2.1.0 so YMMV.
>>
>> And we are switching to 15GB nodes w 2 heftier CPUs each and SSD storage
>> - still a 'small' machine, but much more reasonable for C*.
>>
>> However I can't say I am an expert, since I deliberately keep things so
>> simple that we do not encounter problems - it just works so I dig into
>> other stuff.
>>
>> ml
>>
>>
>> On Sat, Oct 25, 2014 at 5:22 PM, Maxime wrote:
>>
>>> Hello, I've been trying to add a new node to my cluster ( 4 nodes ) for
>>> a few days now.
>>>
>>> I started by adding a node similar to my current configuration, 4 GB or
>>> RAM + 2 Cores on DigitalOcean. However every time, I would end up getting
>>> OOM errors after many log entries of the type:
>>>
>>> INFO [SlabPoolCleaner] 2014-10-25 13:44:57,240
>>> ColumnFamilyStore.java:856 - Enqueuing flush of mycf: 5383 (0%) on-heap, 0
>>> (0%) off-heap
>>>
>>> leading to:
>>>
>>> ka-120-Data.db (39291 bytes) for commitlog position
>>> ReplayPosition(segmentId=1414243978538, position=23699418)
>>> WARN [SharedPool-Worker-13] 2014-10-25 13:48:18,032
>>> AbstractTracingAwareExecutorService.java:167 - Uncaught exception on thread
>>> Thread[SharedPool-Worker-13,5,main]: {}
>>> java.lang.OutOfMemoryError: Java heap space
>>>
>>> Thinking it had to do with either compaction somehow or streaming, 2
>>> activities I've had tremendous issues with in the past; I tried to slow
>>> down the setstreamthroughput to extremely low values all the way to 5. I
>>> also tried setting setcompactionthoughput to 0, and then reading that in
>>> some cases it might be too fast, down to 8. Nothing worked, it merely
>>> vaguely changed the mean time to OOM but not in a way indicating either was
>>> anywhere a solution.
>>>
>>> The nodes were configured with 2 GB of Heap initially, I tried to crank
>>> it up to 3 GB, stressing the host memory to its limit.
>>>
>>> After doing some exploration (I am considering writing a Cassandra Ops
>>> documentation with lessons learned since there seems to be little of it in
>>> organized fashions), I read that some people had strange issues on
>>> lower-end boxes like that, so I bit the bullet and upgraded my new node to
>>> a 8GB + 4 Core instance, which was anecdotally better.
>>>
>>> To my complete shock, exact same issues are present, even raising the
>>> Heap memory to 6 GB. I figure it can't be a "normal" situation anymore, but
>>> must be a bug somehow.
>>>
>>> My cluster is 4 nodes, RF of 2, about 160 GB of data across all nodes.
>>> About 10 CF of varying sizes. Runtime writes are between 300 to 900 /
>>> second. Cassandra 2.1.0, nothing too wild.
>>>
>>> Has anyone encountered these kinds of issues before? I would really
>>> enjoy hearing about the experiences of people trying to run small-sized
>>> clusters like mine. From everything I read, Cassandra operations go very
>>> well on large (16 GB + 8 Cores) machines, but I'm sad to report I've had
>>> nothing but trouble trying to run on smaller machines, perhaps I can learn
>>> from other's experience?
>>>
>>> Full logs can be provided to anyone interested.
>>>
>>> Cheers
>>>
>>
>>
Re: OOM at Bootstrap Time
Thanks a lot that is comforting. We are also small at the moment so I
definitely can relate with the idea of keeping small and simple at a level
where it just works.
I see the new Apache version has a lot of fixes so I will try to upgrade
before I look into downgrading.
On Saturday, October 25, 2014, Laing, Michael
wrote:
> Since no one else has stepped in...
>
> We have run clusters with ridiculously small nodes - I have a production
> cluster in AWS with 4GB nodes each with 1 CPU and disk-based instance
> storage. It works fine but you can see those little puppies struggle...
>
> And I ran into problems such as you observe...
>
> Upgrading Java to the latest 1.7 and - most importantly - *reverting to
> the default configuration, esp. for heap*, seemed to settle things down
> completely. Also make sure that you are using the 'recommended production
> settings' from the docs on your boxen.
>
> However we are running 2.0.x not 2.1.0 so YMMV.
>
> And we are switching to 15GB nodes w 2 heftier CPUs each and SSD storage -
> still a 'small' machine, but much more reasonable for C*.
>
> However I can't say I am an expert, since I deliberately keep things so
> simple that we do not encounter problems - it just works so I dig into
> other stuff.
>
> ml
>
>
> On Sat, Oct 25, 2014 at 5:22 PM, Maxime > wrote:
>
>> Hello, I've been trying to add a new node to my cluster ( 4 nodes ) for a
>> few days now.
>>
>> I started by adding a node similar to my current configuration, 4 GB or
>> RAM + 2 Cores on DigitalOcean. However every time, I would end up getting
>> OOM errors after many log entries of the type:
>>
>> INFO [SlabPoolCleaner] 2014-10-25 13:44:57,240
>> ColumnFamilyStore.java:856 - Enqueuing flush of mycf: 5383 (0%) on-heap, 0
>> (0%) off-heap
>>
>> leading to:
>>
>> ka-120-Data.db (39291 bytes) for commitlog position
>> ReplayPosition(segmentId=1414243978538, position=23699418)
>> WARN [SharedPool-Worker-13] 2014-10-25 13:48:18,032
>> AbstractTracingAwareExecutorService.java:167 - Uncaught exception on thread
>> Thread[SharedPool-Worker-13,5,main]: {}
>> java.lang.OutOfMemoryError: Java heap space
>>
>> Thinking it had to do with either compaction somehow or streaming, 2
>> activities I've had tremendous issues with in the past; I tried to slow
>> down the setstreamthroughput to extremely low values all the way to 5. I
>> also tried setting setcompactionthoughput to 0, and then reading that in
>> some cases it might be too fast, down to 8. Nothing worked, it merely
>> vaguely changed the mean time to OOM but not in a way indicating either was
>> anywhere a solution.
>>
>> The nodes were configured with 2 GB of Heap initially, I tried to crank
>> it up to 3 GB, stressing the host memory to its limit.
>>
>> After doing some exploration (I am considering writing a Cassandra Ops
>> documentation with lessons learned since there seems to be little of it in
>> organized fashions), I read that some people had strange issues on
>> lower-end boxes like that, so I bit the bullet and upgraded my new node to
>> a 8GB + 4 Core instance, which was anecdotally better.
>>
>> To my complete shock, exact same issues are present, even raising the
>> Heap memory to 6 GB. I figure it can't be a "normal" situation anymore, but
>> must be a bug somehow.
>>
>> My cluster is 4 nodes, RF of 2, about 160 GB of data across all nodes.
>> About 10 CF of varying sizes. Runtime writes are between 300 to 900 /
>> second. Cassandra 2.1.0, nothing too wild.
>>
>> Has anyone encountered these kinds of issues before? I would really enjoy
>> hearing about the experiences of people trying to run small-sized clusters
>> like mine. From everything I read, Cassandra operations go very well on
>> large (16 GB + 8 Cores) machines, but I'm sad to report I've had nothing
>> but trouble trying to run on smaller machines, perhaps I can learn from
>> other's experience?
>>
>> Full logs can be provided to anyone interested.
>>
>> Cheers
>>
>
>
Re: OOM at Bootstrap Time
Since no one else has stepped in...
We have run clusters with ridiculously small nodes - I have a production
cluster in AWS with 4GB nodes each with 1 CPU and disk-based instance
storage. It works fine but you can see those little puppies struggle...
And I ran into problems such as you observe...
Upgrading Java to the latest 1.7 and - most importantly - *reverting to the
default configuration, esp. for heap*, seemed to settle things down
completely. Also make sure that you are using the 'recommended production
settings' from the docs on your boxen.
However we are running 2.0.x not 2.1.0 so YMMV.
And we are switching to 15GB nodes w 2 heftier CPUs each and SSD storage -
still a 'small' machine, but much more reasonable for C*.
However I can't say I am an expert, since I deliberately keep things so
simple that we do not encounter problems - it just works so I dig into
other stuff.
ml
On Sat, Oct 25, 2014 at 5:22 PM, Maxime wrote:
> Hello, I've been trying to add a new node to my cluster ( 4 nodes ) for a
> few days now.
>
> I started by adding a node similar to my current configuration, 4 GB or
> RAM + 2 Cores on DigitalOcean. However every time, I would end up getting
> OOM errors after many log entries of the type:
>
> INFO [SlabPoolCleaner] 2014-10-25 13:44:57,240 ColumnFamilyStore.java:856
> - Enqueuing flush of mycf: 5383 (0%) on-heap, 0 (0%) off-heap
>
> leading to:
>
> ka-120-Data.db (39291 bytes) for commitlog position
> ReplayPosition(segmentId=1414243978538, position=23699418)
> WARN [SharedPool-Worker-13] 2014-10-25 13:48:18,032
> AbstractTracingAwareExecutorService.java:167 - Uncaught exception on thread
> Thread[SharedPool-Worker-13,5,main]: {}
> java.lang.OutOfMemoryError: Java heap space
>
> Thinking it had to do with either compaction somehow or streaming, 2
> activities I've had tremendous issues with in the past; I tried to slow
> down the setstreamthroughput to extremely low values all the way to 5. I
> also tried setting setcompactionthoughput to 0, and then reading that in
> some cases it might be too fast, down to 8. Nothing worked, it merely
> vaguely changed the mean time to OOM but not in a way indicating either was
> anywhere a solution.
>
> The nodes were configured with 2 GB of Heap initially, I tried to crank it
> up to 3 GB, stressing the host memory to its limit.
>
> After doing some exploration (I am considering writing a Cassandra Ops
> documentation with lessons learned since there seems to be little of it in
> organized fashions), I read that some people had strange issues on
> lower-end boxes like that, so I bit the bullet and upgraded my new node to
> a 8GB + 4 Core instance, which was anecdotally better.
>
> To my complete shock, exact same issues are present, even raising the Heap
> memory to 6 GB. I figure it can't be a "normal" situation anymore, but must
> be a bug somehow.
>
> My cluster is 4 nodes, RF of 2, about 160 GB of data across all nodes.
> About 10 CF of varying sizes. Runtime writes are between 300 to 900 /
> second. Cassandra 2.1.0, nothing too wild.
>
> Has anyone encountered these kinds of issues before? I would really enjoy
> hearing about the experiences of people trying to run small-sized clusters
> like mine. From everything I read, Cassandra operations go very well on
> large (16 GB + 8 Cores) machines, but I'm sad to report I've had nothing
> but trouble trying to run on smaller machines, perhaps I can learn from
> other's experience?
>
> Full logs can be provided to anyone interested.
>
> Cheers
>
OOM at Bootstrap Time
Hello, I've been trying to add a new node to my cluster ( 4 nodes ) for a
few days now.
I started by adding a node similar to my current configuration, 4 GB or RAM
+ 2 Cores on DigitalOcean. However every time, I would end up getting OOM
errors after many log entries of the type:
INFO [SlabPoolCleaner] 2014-10-25 13:44:57,240 ColumnFamilyStore.java:856
- Enqueuing flush of mycf: 5383 (0%) on-heap, 0 (0%) off-heap
leading to:
ka-120-Data.db (39291 bytes) for commitlog position
ReplayPosition(segmentId=1414243978538, position=23699418)
WARN [SharedPool-Worker-13] 2014-10-25 13:48:18,032
AbstractTracingAwareExecutorService.java:167 - Uncaught exception on thread
Thread[SharedPool-Worker-13,5,main]: {}
java.lang.OutOfMemoryError: Java heap space
Thinking it had to do with either compaction somehow or streaming, 2
activities I've had tremendous issues with in the past; I tried to slow
down the setstreamthroughput to extremely low values all the way to 5. I
also tried setting setcompactionthoughput to 0, and then reading that in
some cases it might be too fast, down to 8. Nothing worked, it merely
vaguely changed the mean time to OOM but not in a way indicating either was
anywhere a solution.
The nodes were configured with 2 GB of Heap initially, I tried to crank it
up to 3 GB, stressing the host memory to its limit.
After doing some exploration (I am considering writing a Cassandra Ops
documentation with lessons learned since there seems to be little of it in
organized fashions), I read that some people had strange issues on
lower-end boxes like that, so I bit the bullet and upgraded my new node to
a 8GB + 4 Core instance, which was anecdotally better.
To my complete shock, exact same issues are present, even raising the Heap
memory to 6 GB. I figure it can't be a "normal" situation anymore, but must
be a bug somehow.
My cluster is 4 nodes, RF of 2, about 160 GB of data across all nodes.
About 10 CF of varying sizes. Runtime writes are between 300 to 900 /
second. Cassandra 2.1.0, nothing too wild.
Has anyone encountered these kinds of issues before? I would really enjoy
hearing about the experiences of people trying to run small-sized clusters
like mine. From everything I read, Cassandra operations go very well on
large (16 GB + 8 Cores) machines, but I'm sad to report I've had nothing
but trouble trying to run on smaller machines, perhaps I can learn from
other's experience?
Full logs can be provided to anyone interested.
Cheers
