The discard due to oom is causing the zero returned. I would guess a cache miss problem of some sort, but not sure. Are you using row, index, etc. caches? Are you seeing the failed prep statement on random nodes (duh, nodes that have the relevant data ranges)?
*.......* *Daemeon C.M. ReiydelleUSA (+1) 415.501.0198London (+44) (0) 20 8144 9872* On Thu, Mar 16, 2017 at 10:56 AM, Ryan Svihla <r...@foundev.pro> wrote: > Depends actually, restore just restores what's there, so if only one node > had a copy of the data then only one node had a copy of the data meaning > quorum will still be wrong sometimes. > > On Thu, Mar 16, 2017 at 1:53 PM, Arvydas Jonusonis < > arvydas.jonuso...@gmail.com> wrote: > >> If the data was written at ONE, consistency is not guaranteed. ..but >> considering you just restored the cluster, there's a good chance something >> else is off. >> >> On Thu, Mar 16, 2017 at 18:19 srinivasarao daruna <sree.srin...@gmail.com> >> wrote: >> >>> Want to make read and write QUORUM as well. >>> >>> >>> On Mar 16, 2017 1:09 PM, "Ryan Svihla" <r...@foundev.pro> wrote: >>> >>> Replication factor is 3, and write consistency is ONE and read >>> consistency is QUORUM. >>> >>> That combination is not gonna work well: >>> >>> *Write succeeds to NODE A but fails on node B,C* >>> >>> *Read goes to NODE B, C* >>> >>> If you can tolerate some temporary inaccuracy you can use QUORUM but may >>> still have the situation where >>> >>> Write succeeds on node A a timestamp 1, B succeeds at timestamp 2 >>> Read succeeds on node B and C at timestamp 1 >>> >>> If you need fully race condition free counts I'm afraid you need to use >>> SERIAL or LOCAL_SERIAL (for in DC only accuracy) >>> >>> On Thu, Mar 16, 2017 at 1:04 PM, srinivasarao daruna < >>> sree.srin...@gmail.com> wrote: >>> >>> Replication strategy is SimpleReplicationStrategy. >>> >>> Smith is : EC2 snitch. As we deployed cluster on EC2 instances. >>> >>> I was worried that CL=ALL have more read latency and read failures. But >>> won't rule out trying it. >>> >>> Should I switch select count (*) to select partition_key column? Would >>> that be of any help.? >>> >>> >>> Thank you >>> Regards >>> Srini >>> >>> On Mar 16, 2017 12:46 PM, "Arvydas Jonusonis" < >>> arvydas.jonuso...@gmail.com> wrote: >>> >>> What are your replication strategy and snitch settings? >>> >>> Have you tried doing a read at CL=ALL? If it's an actual inconsistency >>> issue (missing data), this should cause the correct results to be returned. >>> You'll need to run a repair to fix the inconsistencies. >>> >>> If all the data is actually there, you might have one or several nodes >>> that aren't identifying the correct replicas. >>> >>> Arvydas >>> >>> >>> >>> On Thu, Mar 16, 2017 at 5:31 PM, srinivasarao daruna < >>> sree.srin...@gmail.com> wrote: >>> >>> Hi Team, >>> >>> We are struggling with a problem related to cassandra counts, after >>> backup and restore of the cluster. Aaron Morton has suggested to send this >>> to user list, so some one of the list will be able to help me. >>> >>> We are have a rest api to talk to cassandra and one of our query which >>> fetches count is creating problems for us. >>> >>> We have done backup and restore and copied all the data to new cluster. >>> We have done nodetool refresh on the tables, and did the nodetool repair as >>> well. >>> >>> However, one of our key API call is returning inconsistent results. The >>> result count is 0 in the first call and giving the actual values for later >>> calls. The query frequency is bit high and failure rate has also raised >>> considerably. >>> >>> 1) The count query has partition keys in it. Didnt see any read timeout >>> or any errors from api logs. >>> >>> 2) This is how our code of creating session looks. >>> >>> val poolingOptions = new PoolingOptions >>> poolingOptions >>> .setCoreConnectionsPerHost(HostDistance.LOCAL, 4) >>> .setMaxConnectionsPerHost(HostDistance.LOCAL, 10) >>> .setCoreConnectionsPerHost(HostDistance.REMOTE, 4) >>> .setMaxConnectionsPerHost( HostDistance.REMOTE, 10) >>> >>> val builtCluster = clusterBuilder.withCredentials(username, password) >>> .withPoolingOptions(poolingOptions) >>> .build() >>> val cassandraSession = builtCluster.get.connect() >>> >>> val preparedStatement = cassandraSession.prepare(state >>> ment).setConsistencyLevel(ConsistencyLevel.QUORUM) >>> cassandraSession.execute(preparedStatement.bind(args :_*)) >>> >>> Query: SELECT count(*) FROM table_name WHERE parition_column=? AND >>> text_column_of_clustering_key=? AND date_column_of_clustering_key<=? >>> AND date_column_of_clustering_key>=? >>> >>> 3) Cluster configuration: >>> >>> 6 Machines: 3 seeds, we are using apache cassandra 3.9 version. Each >>> machine is equipped with 16 Cores and 64 GB Ram. >>> >>> Replication factor is 3, and write consistency is ONE and read >>> consistency is QUORUM. >>> >>> 4) cassandra is never down on any machine >>> >>> 5) Using cassandra-driver-core artifact with 3.1.1 version in the api. >>> >>> 6) nodetool tpstats shows no read failures, and no other failures. >>> >>> 7) Do not see any other issues from system.log of cassandra. We just see >>> few warnings as below. >>> >>> Maximum memory usage reached (512.000MiB), cannot allocate chunk of >>> 1.000MiB >>> WARN [ScheduledTasks:1] 2017-03-14 14:58:37,141 QueryProcessor.java:103 >>> - 88 prepared statements discarded in the last minute because cache limit >>> reached (32 MB) >>> The first api call returns 0 and the api calls later gives right values. >>> >>> Please let me know, if any other details needed. >>> Could you please have a look at this issue once and kindly give me your >>> inputs? This issue literally broke the confidence on Cassandra from our >>> business team. >>> >>> Your inputs will be really helpful. >>> >>> Thank You, >>> Regards, >>> Srini >>> >>> >>> >>> >>> >>> >>> -- >>> >>> Thanks, >>> Ryan Svihla >>> >>> > > > -- > > Thanks, > Ryan Svihla > >
