Hi, I cannot really answer your question as some rock solid truth. When we had problems, we did mainly two things
- Analyzed the GC logs (with censum from jClarity, this tool IS really awesome, it’s good investment even better if the production is running other java applications) - Heap dumped cassandra when there was a GC, this helped in narrowing down the actual issue I don’t know precisely how to answer, but : - concurrent_compactors could be lowered to 10, it seems from another thread here that it can be harmful, see https://issues.apache.org/jira/browse/CASSANDRA-6142 - memtable_flush_writers we set it to 2 - compaction_throughput_mb_per_sec could probably be increased, on SSDs that should help - trickle_fsync don’t forget this one too if you’re on SSDs Touching JVM heap parameters can be hazardous, increasing heap may seem like a nice thing, but it can increase GC time in the worst case scenario. Also increasing the MaxTenuringThreshold is probably wrong too, as you probably know it means objects will be copied from Eden to Survivor 0/1 and to the other Survivor on the next collection until that threshold is reached, then it will be copied in Old generation. That means that’s being applied to Memtables, so it *may* mean several copies to be done on each GCs, and memtables are not small objects that could take a little while for an *available* system. Another fact to take account for is that upon each collection the active survivor S0/S1 has to be big enough for the memtable to fit there, and there’s other objects too. So I would rather work on the real cause. rather than GC. One thing brought my attention Though still getting logs saying “compacting large row”. Could it be that the model is based on wide rows ? That could be a problem, for several reasons not limited to compactions. If that is so I’d advise to revise the datamodel -- Brice On Tue, Apr 21, 2015 at 7:53 PM, Anuj Wadehra <anujw_2...@yahoo.co.in> wrote: > Thanks Brice!! > > We are using Red Hat Linux 6.4..24 cores...64Gb Ram..SSDs in RAID5..CPU > are not overloaded even in peak load..I dont think IO is an issue as iostat > shows await<17 all times..util attrbute in iostat usually increases from 0 > to 100..and comes back immediately..m not an expert on analyzing IO but > things look ok..We are using STCS..and not using Logged batches..We are > making around 12k writes/sec in 5 cf (one with 4 sec index) and 2300 > reads/sec on each node of 3 node cluster. 2 CFs have wide rows with max > data of around 100mb per row. We have further reduced > in_memory_compaction_limit_in_mb to 125.Though still getting logs saying > "compacting large row". > > We are planning to upgrade to 2.0.14 as 2.1 is not yet production ready. > > I would appreciate if you could answer the queries posted in initial mail. > > Thanks > Anuj Wadehra > > Sent from Yahoo Mail on Android > <https://overview.mail.yahoo.com/mobile/?.src=Android> > ------------------------------ > *From*:"Brice Dutheil" <brice.duth...@gmail.com> > *Date*:Tue, 21 Apr, 2015 at 10:22 pm > > *Subject*:Re: Handle Write Heavy Loads in Cassandra 2.0.3 > > This is an intricate matter, I cannot say for sure what are good > parameters from the wrong ones, too many things changed at once. > > However there’s many things to consider > > - What is your OS ? > - Do your nodes have SSDs or mechanical drives ? How many cores do you > have ? > - Is it the CPUs or IOs that are overloaded ? > - What is the write request/s per node and cluster wide ? > - What is the compaction strategy of the tables you are writing into ? > - Are you using LOGGED BATCH statement. > > With heavy writes, it is *NOT* recommend to use LOGGED BATCH statements. > > In our 2.0.14 cluster we have experimented node unavailability due to long > Full GC pauses. We discovered bogus legacy data, a single outlier was so > wrong that it updated hundred thousand time the same CQL rows with > duplicate data. Given the tables we were writing to were configured to use > LCS, this resulted in keeping Memtables in memory long enough to promote > them in the old generation (the MaxTenuringThreshold default is 1). > Handling this data proved to be the thing to fix, with default GC settings > the cluster (10 nodes) handle 39 write requests/s. > > Note Memtables are allocated on heap with 2.0.x. With 2.1.x they will be > allocated off-heap. > > > -- Brice > > On Tue, Apr 21, 2015 at 5:12 PM, Anuj Wadehra <anujw_2...@yahoo.co.in> > wrote: > >> Any suggestions or comments on this one?? >> >> Thanks >> Anuj Wadhera >> >> Sent from Yahoo Mail on Android >> <https://overview.mail.yahoo.com/mobile/?.src=Android> >> ------------------------------ >> *From*:"Anuj Wadehra" <anujw_2...@yahoo.co.in> >> *Date*:Mon, 20 Apr, 2015 at 11:51 pm >> *Subject*:Re: Handle Write Heavy Loads in Cassandra 2.0.3 >> >> Small correction: we are making writes in 5 cf an reading frm one at high >> speeds. >> >> >> >> Thanks >> Anuj Wadehra >> >> Sent from Yahoo Mail on Android >> <https://overview.mail.yahoo.com/mobile/?.src=Android> >> ------------------------------ >> *From*:"Anuj Wadehra" <anujw_2...@yahoo.co.in> >> *Date*:Mon, 20 Apr, 2015 at 7:53 pm >> *Subject*:Handle Write Heavy Loads in Cassandra 2.0.3 >> >> Hi, >> >> Recently, we discovered that millions of mutations were getting dropped >> on our cluster. Eventually, we solved this problem by increasing the value >> of memtable_flush_writers from 1 to 3. We usually write 3 CFs >> simultaneously an one of them has 4 Secondary Indexes. >> >> New changes also include: >> concurrent_compactors: 12 (earlier it was default) >> compaction_throughput_mb_per_sec: 32(earlier it was default) >> in_memory_compaction_limit_in_mb: 400 ((earlier it was default 64) >> memtable_flush_writers: 3 (earlier 1) >> >> After, making above changes, our write heavy workload scenarios started >> giving "promotion failed" exceptions in gc logs. >> >> We have done JVM tuning and Cassandra config changes to solve this: >> >> MAX_HEAP_SIZE="12G" (Increased Heap to from 8G to reduce fragmentation) >> HEAP_NEWSIZE="3G" >> >> JVM_OPTS="$JVM_OPTS -XX:SurvivorRatio=2" (We observed that even at >> SurvivorRatio=4, our survivor space was getting 100% utilized under heavy >> write load and we thought that minor collections were directly promoting >> objects to Tenured generation) >> >> JVM_OPTS="$JVM_OPTS -XX:MaxTenuringThreshold=20" (Lots of objects were >> moving from Eden to Tenured on each minor collection..may be related to >> medium life objects related to Memtables and compactions as suggested by >> heapdump) >> >> JVM_OPTS="$JVM_OPTS -XX:ConcGCThreads=20" >> JVM_OPTS="$JVM_OPTS -XX:+UnlockDiagnosticVMOptions" >> JVM_OPTS="$JVM_OPTS -XX:+UseGCTaskAffinity" >> JVM_OPTS="$JVM_OPTS -XX:+BindGCTaskThreadsToCPUs" >> JVM_OPTS="$JVM_OPTS -XX:ParGCCardsPerStrideChunk=32768" >> JVM_OPTS="$JVM_OPTS -XX:+CMSScavengeBeforeRemark" >> JVM_OPTS="$JVM_OPTS -XX:CMSMaxAbortablePrecleanTime=30000" >> JVM_OPTS="$JVM_OPTS -XX:CMSWaitDuration=2000" //though it's default value >> JVM_OPTS="$JVM_OPTS -XX:+CMSEdenChunksRecordAlways" >> JVM_OPTS="$JVM_OPTS -XX:+CMSParallelInitialMarkEnabled" >> JVM_OPTS="$JVM_OPTS -XX:-UseBiasedLocking" >> JVM_OPTS="$JVM_OPTS -XX:CMSInitiatingOccupancyFraction=70" (to avoid >> concurrent failures we reduced value) >> >> Cassandra config: >> compaction_throughput_mb_per_sec: 24 >> memtable_total_space_in_mb: 1000 (to make memtable flush frequent.default >> is 1/4 heap which creates more long lived objects) >> >> Questions: >> 1. Why increasing memtable_flush_writers and >> in_memory_compaction_limit_in_mb caused promotion failures in JVM? Does >> more memtable_flush_writers mean more memtables in memory? >> >> 2. Still, objects are getting promoted at high speed to Tenured space. >> CMS is running on Old gen every 4-5 minutes under heavy write load. Around >> 750+ minor collections of upto 300ms happened in 45 mins. Do you see any >> problems with new JVM tuning and Cassandra config? Is the justification >> given against those changes sounds logical? Any suggestions? >> 3. What is the best practice for reducing heap fragmentation/promotion >> failure when allocation and promotion rates are high? >> >> Thanks >> Anuj >> >> >> >> >> >
