Actually not sure why the machine was originally configured at 6GB since we even started it on an r3.large with 15GB.
Re: Batches Not using batches. I actually have that as a separate question on the list. Currently I fan out async single inserts and I'm wondering if batches are better since my data is inherently inserted in blocks of ordered rows for a single partition key. Re: Traffic There isn't all that much traffic. Inserts come in as blocks per partition key, but then can be 5k-200k rows for that partition key. Each of these rows is less than 100k. It's small, lots of ordered rows. It's frame and sub-frame information for media. and rows for one piece of media is inserted at once (the partition key). For the last 12 hours, where the load on all these machine has been stuck there's been virtually no traffic at all. This is the nodes basically sitting idle, except that they had load of 4 each. BTW, how do you determine widest row or for that matter number of tombstones in a row? thanks, arne On Tue, Dec 16, 2014 at 1:24 PM, Ryan Svihla <rsvi...@datastax.com> wrote: > > So 1024 is still a good 2.5 times what I'm suggesting, 6GB is hardly > enough to run Cassandra well in, especially if you're going full bore on > loads. However, you maybe just flat out be CPU bound on your write > throughput, how many TPS and what size writes do you have? Also what is > your widest row? > > Final question what is compaction throughput at? > > > On Tue, Dec 16, 2014 at 3:20 PM, Arne Claassen <a...@emotient.com> wrote: >> >> The starting configuration I had, which is still running on two of the >> nodes, was 6GB Heap, 1024MB parnew which is close to what you are >> suggesting and those have been pegged at load 4 for the over 12 hours with >> hardly and read or write traffic. I will set one to 8GB/400MB and see if >> its load changes. >> >> On Tue, Dec 16, 2014 at 1:12 PM, Ryan Svihla <rsvi...@datastax.com> >> wrote: >> >>> So heap of that size without some tuning will create a number of >>> problems (high cpu usage one of them), I suggest either 8GB heap and 400mb >>> parnew (which I'd only set that low for that low cpu count) , or attempt >>> the tunings as indicated in >>> https://issues.apache.org/jira/browse/CASSANDRA-8150 >>> >>> On Tue, Dec 16, 2014 at 3:06 PM, Arne Claassen <a...@emotient.com> >>> wrote: >>>> >>>> Changed the 15GB node to 25GB heap and the nice CPU is down to ~20% >>>> now. Checked my dev cluster to see if the ParNew log entries are just par >>>> for the course, but not seeing them there. However, both have the following >>>> every 30 seconds: >>>> >>>> DEBUG [BatchlogTasks:1] 2014-12-16 21:00:44,898 BatchlogManager.java >>>> (line 165) Started replayAllFailedBatches >>>> DEBUG [MemtablePostFlusher:1] 2014-12-16 21:00:44,899 >>>> ColumnFamilyStore.java (line 866) forceFlush requested but everything is >>>> clean in batchlog >>>> DEBUG [BatchlogTasks:1] 2014-12-16 21:00:44,899 BatchlogManager.java >>>> (line 200) Finished replayAllFailedBatches >>>> >>>> Is that just routine scheduled house-keeping or a sign of something >>>> else? >>>> >>>> On Tue, Dec 16, 2014 at 12:52 PM, Arne Claassen <a...@emotient.com> >>>> wrote: >>>>> >>>>> Sorry, I meant 15GB heap on the one machine that has less nice CPU% >>>>> now. The others are 6GB >>>>> >>>>> On Tue, Dec 16, 2014 at 12:50 PM, Arne Claassen <a...@emotient.com> >>>>> wrote: >>>>>> >>>>>> AWS r3.xlarge, 30GB, but only using a Heap of 10GB, new 2GB because >>>>>> we might go c3.2xlarge instead if CPU is more important than RAM >>>>>> Storage is optimized EBS SSD (but iostat shows no real IO going on) >>>>>> Each node only has about 10GB with ownership of 67%, 64.7% & 68.3%. >>>>>> >>>>>> The node on which I set the Heap to 10GB from 6GB the utlilization >>>>>> has dropped to 46%nice now, but the ParNew log messages still continue at >>>>>> the same pace. I'm gonna up the HEAP to 20GB for a bit, see if that >>>>>> brings >>>>>> that nice CPU further down. >>>>>> >>>>>> No TombstoneOverflowingExceptions. >>>>>> >>>>>> On Tue, Dec 16, 2014 at 11:50 AM, Ryan Svihla <rsvi...@datastax.com> >>>>>> wrote: >>>>>>> >>>>>>> What's CPU, RAM, Storage layer, and data density per node? Exact >>>>>>> heap settings would be nice. In the logs look for >>>>>>> TombstoneOverflowingException >>>>>>> >>>>>>> >>>>>>> On Tue, Dec 16, 2014 at 1:36 PM, Arne Claassen <a...@emotient.com> >>>>>>> wrote: >>>>>>>> >>>>>>>> I'm running 2.0.10. >>>>>>>> >>>>>>>> The data is all time series data and as we change our pipeline, >>>>>>>> we've been periodically been reprocessing the data sources, which >>>>>>>> causes >>>>>>>> each time series to be overwritten, i.e. every row per partition key is >>>>>>>> deleted and re-written, so I assume i've been collecting a bunch of >>>>>>>> tombstones. >>>>>>>> >>>>>>>> Also, the presence of the ever present and never completing >>>>>>>> compaction types, i assumed were an artifact of tombstoning, but i >>>>>>>> fully >>>>>>>> admit to conjecture based on about ~20 blog posts and stackoverflow >>>>>>>> questions i've surveyed. >>>>>>>> >>>>>>>> I doubled the Heap on one node and it changed nothing regarding the >>>>>>>> load or the ParNew log statements. New Generation Usage is 50%, Eden >>>>>>>> itself >>>>>>>> is 56%. >>>>>>>> >>>>>>>> Anything else i should look at and report, let me know. >>>>>>>> >>>>>>>> On Tue, Dec 16, 2014 at 11:14 AM, Jonathan Lacefield < >>>>>>>> jlacefi...@datastax.com> wrote: >>>>>>>>> >>>>>>>>> Hello, >>>>>>>>> >>>>>>>>> What version of Cassandra are you running? >>>>>>>>> >>>>>>>>> If it's 2.0, we recently experienced something similar with 8447 >>>>>>>>> [1], which 8485 [2] should hopefully resolve. >>>>>>>>> >>>>>>>>> Please note that 8447 is not related to tombstones. Tombstone >>>>>>>>> processing can put a lot of pressure on the heap as well. Why do you >>>>>>>>> think >>>>>>>>> you have a lot of tombstones in that one particular table? >>>>>>>>> >>>>>>>>> [1] https://issues.apache.org/jira/browse/CASSANDRA-8447 >>>>>>>>> [2] https://issues.apache.org/jira/browse/CASSANDRA-8485 >>>>>>>>> >>>>>>>>> Jonathan >>>>>>>>> >>>>>>>>> [image: datastax_logo.png] >>>>>>>>> >>>>>>>>> Jonathan Lacefield >>>>>>>>> >>>>>>>>> Solution Architect | (404) 822 3487 | jlacefi...@datastax.com >>>>>>>>> >>>>>>>>> [image: linkedin.png] <http://www.linkedin.com/in/jlacefield/> [image: >>>>>>>>> facebook.png] <https://www.facebook.com/datastax> [image: >>>>>>>>> twitter.png] <https://twitter.com/datastax> [image: g+.png] >>>>>>>>> <https://plus.google.com/+Datastax/about> >>>>>>>>> <http://feeds.feedburner.com/datastax> >>>>>>>>> <https://github.com/datastax/> >>>>>>>>> >>>>>>>>> On Tue, Dec 16, 2014 at 2:04 PM, Arne Claassen <a...@emotient.com> >>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>> I have a three node cluster that has been sitting at a load of 4 >>>>>>>>>> (for each node), 100% CPI utilization (although 92% nice) for that >>>>>>>>>> last 12 >>>>>>>>>> hours, ever since some significant writes finished. I'm trying to >>>>>>>>>> determine >>>>>>>>>> what tuning I should be doing to get it out of this state. The debug >>>>>>>>>> log is >>>>>>>>>> just an endless series of: >>>>>>>>>> >>>>>>>>>> DEBUG [ScheduledTasks:1] 2014-12-16 19:03:35,042 GCInspector.java >>>>>>>>>> (line 118) GC for ParNew: 166 ms for 10 collections, 4400928736 >>>>>>>>>> used; max >>>>>>>>>> is 8000634880 >>>>>>>>>> DEBUG [ScheduledTasks:1] 2014-12-16 19:03:36,043 GCInspector.java >>>>>>>>>> (line 118) GC for ParNew: 165 ms for 10 collections, 4440011176 >>>>>>>>>> used; max >>>>>>>>>> is 8000634880 >>>>>>>>>> DEBUG [ScheduledTasks:1] 2014-12-16 19:03:37,043 GCInspector.java >>>>>>>>>> (line 118) GC for ParNew: 135 ms for 8 collections, 4402220568 >>>>>>>>>> used; max is 8000634880 >>>>>>>>>> >>>>>>>>>> iostat shows virtually no I/O. >>>>>>>>>> >>>>>>>>>> Compaction may enter into this, but i don't really know what to >>>>>>>>>> make of compaction stats since they never change: >>>>>>>>>> >>>>>>>>>> [root@cassandra-37919c3a ~]# nodetool compactionstats >>>>>>>>>> pending tasks: 10 >>>>>>>>>> compaction type keyspace table >>>>>>>>>> completed total unit progress >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 271651482 563615497 bytes 48.20% >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 30308910 21676695677 bytes 0.14% >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 1198384080 1815603161 bytes 66.00% >>>>>>>>>> Active compaction remaining time : 0h22m24s >>>>>>>>>> >>>>>>>>>> 5 minutes later: >>>>>>>>>> >>>>>>>>>> [root@cassandra-37919c3a ~]# nodetool compactionstats >>>>>>>>>> pending tasks: 9 >>>>>>>>>> compaction type keyspace table >>>>>>>>>> completed total unit progress >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 271651482 563615497 bytes 48.20% >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 30308910 21676695677 bytes 0.14% >>>>>>>>>> Compaction mediamedia_tracks_raw >>>>>>>>>> 1198384080 1815603161 bytes 66.00% >>>>>>>>>> Active compaction remaining time : 0h22m24s >>>>>>>>>> >>>>>>>>>> Sure the pending tasks went down by one, but the rest is >>>>>>>>>> identical. media_tracks_raw likely has a bunch of tombstones (can't >>>>>>>>>> figure >>>>>>>>>> out how to get stats on that). >>>>>>>>>> >>>>>>>>>> Is this behavior something that indicates that i need more Heap, >>>>>>>>>> larger new generation? Should I be manually running compaction on >>>>>>>>>> tables >>>>>>>>>> with lots of tombstones? >>>>>>>>>> >>>>>>>>>> Any suggestions or places to educate myself better on performance >>>>>>>>>> tuning would be appreciated. >>>>>>>>>> >>>>>>>>>> arne >>>>>>>>>> >>>>>>>>> >>>>>>> >>>>>>> -- >>>>>>> >>>>>>> [image: datastax_logo.png] <http://www.datastax.com/> >>>>>>> >>>>>>> Ryan Svihla >>>>>>> >>>>>>> Solution Architect >>>>>>> >>>>>>> [image: twitter.png] <https://twitter.com/foundev> [image: >>>>>>> linkedin.png] <http://www.linkedin.com/pub/ryan-svihla/12/621/727/> >>>>>>> >>>>>>> DataStax is the fastest, most scalable distributed database >>>>>>> technology, delivering Apache Cassandra to the world’s most innovative >>>>>>> enterprises. Datastax is built to be agile, always-on, and predictably >>>>>>> scalable to any size. With more than 500 customers in 45 countries, >>>>>>> DataStax >>>>>>> is the database technology and transactional backbone of choice for the >>>>>>> worlds most innovative companies such as Netflix, Adobe, Intuit, and >>>>>>> eBay. >>>>>>> >>>>>>> >>> >>> -- >>> >>> [image: datastax_logo.png] <http://www.datastax.com/> >>> >>> Ryan Svihla >>> >>> Solution Architect >>> >>> [image: twitter.png] <https://twitter.com/foundev> [image: linkedin.png] >>> <http://www.linkedin.com/pub/ryan-svihla/12/621/727/> >>> >>> DataStax is the fastest, most scalable distributed database technology, >>> delivering Apache Cassandra to the world’s most innovative enterprises. >>> Datastax is built to be agile, always-on, and predictably scalable to any >>> size. With more than 500 customers in 45 countries, DataStax is the >>> database technology and transactional backbone of choice for the worlds >>> most innovative companies such as Netflix, Adobe, Intuit, and eBay. >>> >>> > > -- > > [image: datastax_logo.png] <http://www.datastax.com/> > > Ryan Svihla > > Solution Architect > > [image: twitter.png] <https://twitter.com/foundev> [image: linkedin.png] > <http://www.linkedin.com/pub/ryan-svihla/12/621/727/> > > DataStax is the fastest, most scalable distributed database technology, > delivering Apache Cassandra to the world’s most innovative enterprises. > Datastax is built to be agile, always-on, and predictably scalable to any > size. With more than 500 customers in 45 countries, DataStax is the > database technology and transactional backbone of choice for the worlds > most innovative companies such as Netflix, Adobe, Intuit, and eBay. > >
