haven't really figured this out yet. it's not a big problem but it is annoying for sure! the cluster was upgraded from 2.1.16 to 3.11.4. now my only thing is i'm not sure if had this type of behavior before the upgrade. i'm leaning toward a no based on my data but i'm just not 100% sure.
just 1 table, out of all the ones on the cluster has this behavior. repair has been run few times via reaper. even did a nodetool compact on the nodes (since this table is like 1GB per node..) . just don't see why there would be any inconsistency that would trigger read repair. any insight you may have would be appreciated! the real thing that started this digging into the cluster was during some stress test application team complained about high latency (30ms at p98). this cluster is oversized already for this use case with only 14GB of data per node, there is more than enough ram so all the data is basically cached in ram. the only thing that stands out is this crazy read repair. so this read repair may not be my root issue but definitely shouldn't be happening like this. the vm's.. 12 cores 82GB ram 1.2TB local ephemeral ssd's attached the info from 1 of the nodes. On Tue, Oct 15, 2019 at 2:36 PM Alain RODRIGUEZ <arodr...@gmail.com> wrote: > Hello Patrick, > > Still in trouble with this? I must admit I'm really puzzled by your issue. > I have no real idea of what's going on. Would you share with us the output > of: > > - nodetool status <keyspace> > - nodetool describecluster > - nodetool gossipinfo > - nodetool tpstats > > Also you said the app is running for a long time, with no changes. What > about Cassandra? Any recent operations? > > I hope that with this information we might be able to understand better > and finally be able to help. > > ----------------------- > Alain Rodriguez - al...@thelastpickle.com > France / Spain > > The Last Pickle - Apache Cassandra Consulting > http://www.thelastpickle.com > > Le ven. 4 oct. 2019 à 00:25, Patrick Lee <patrickclee0...@gmail.com> a > écrit : > >> this table was actually leveled compaction before, just changed it to >> size tiered yesterday while researching this. >> >> On Thu, Oct 3, 2019 at 4:31 PM Patrick Lee <patrickclee0...@gmail.com> >> wrote: >> >>> its not really time series data. and it's not updated very often, it >>> would have some updates but pretty infrequent. this thing should be super >>> fast, on avg it's like 1 to 2ms p99 currently but if they double - triple >>> the traffic on that table latencies go upward to 20ms to 50ms.. the only >>> odd thing i see is just that there are constant read repairs that follow >>> the same traffic pattern on the reads, which shows constant writes on the >>> table (from the read repairs), which after read repair or just normal full >>> repairs (all full through reaper, never ran any incremental repair) i would >>> expect it to not have any mismatches. the other 5 tables they use on the >>> cluster can have the same level traffic all very simple select from table >>> by partition key which returns a single record >>> >>> On Thu, Oct 3, 2019 at 4:21 PM John Belliveau <belliveau.j...@gmail.com> >>> wrote: >>> >>>> Hi Patrick, >>>> >>>> >>>> >>>> Is this time series data? If so, I have run into issues with repair on >>>> time series data using the SizeTieredCompactionStrategy. I have had >>>> better luck using the TimeWindowCompactionStrategy. >>>> >>>> >>>> >>>> John >>>> >>>> >>>> >>>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for >>>> Windows 10 >>>> >>>> >>>> >>>> *From: *Patrick Lee <patrickclee0...@gmail.com> >>>> *Sent: *Thursday, October 3, 2019 5:14 PM >>>> *To: *user@cassandra.apache.org >>>> *Subject: *Constant blocking read repair for such a tiny table >>>> >>>> >>>> >>>> I have a cluster that is running 3.11.4 ( was upgraded a while back >>>> from 2.1.16 ). what I see is a steady rate of read repair which is about >>>> 10% constantly on only this 1 table. Repairs have been run (actually >>>> several times). The table does not have a lot of writes to it so after >>>> repair, or even after a read repair I would expect it to be fine. the >>>> reason i'm having to dig into this so much is for the fact that under a >>>> much large traffic load than their normal traffic, latencies are higher >>>> than the app team wants >>>> >>>> >>>> >>>> I mean this thing is tiny, it's a 12x12 cluster but this 1 table is >>>> like 1GB per node on disk. >>>> >>>> >>>> >>>> the application team is doing reads at LOCAL_QUORUM and I can simulate >>>> this on that cluster by running a query using quorum and/or local_quorum >>>> and in the trace can see every time running the query it comes back with a >>>> DigestMismatchException no matter how many times I run it. that record >>>> hasn't been updated by the application for several months. >>>> >>>> >>>> >>>> repairs are scheduled and run every 7 days via reaper, recently in the >>>> past week this table has been repaired at least 3 times. every time there >>>> are mismatches and data streams back and forth but yet still a constant >>>> rate of read repairs. >>>> >>>> >>>> >>>> curious if anyone has any recommendations to look info further or have >>>> experienced anything like this? >>>> >>>> >>>> >>>> this node has been up for 24 hours.. this is the netstats for read >>>> repairs >>>> >>>> Mode: NORMAL >>>> Not sending any streams. >>>> Read Repair Statistics: >>>> Attempted: 7481 >>>> Mismatch (Blocking): 11425375 >>>> Mismatch (Background): 17 >>>> Pool Name Active Pending Completed Dropped >>>> Large messages n/a 0 1232 0 >>>> Small messages n/a 0 395903678 0 >>>> Gossip messages n/a 0 603746 0 >>>> >>>> >>>> >>>> example of the schema... some modifications have been made to reduce >>>> read_reapair and speculative_retry while troubleshooting.. >>>> >>>> CREATE TABLE keyspace.table1 ( >>>> >>>> item bigint, >>>> >>>> price int, >>>> >>>> start_date timestamp, >>>> >>>> end_date timestamp, >>>> >>>> created_date timestamp, >>>> >>>> cost decimal, >>>> >>>> list decimal, >>>> >>>> item_id int, >>>> >>>> modified_date timestamp, >>>> >>>> status int, >>>> >>>> PRIMARY KEY ((item, price), start_date, end_date) >>>> >>>> ) WITH CLUSTERING ORDER BY (start_date ASC, end_date ASC) >>>> >>>> AND read_repair_chance = 0.0 >>>> >>>> AND dclocal_read_repair_chance = 0.0 >>>> >>>> AND gc_grace_seconds = 864000 >>>> >>>> AND bloom_filter_fp_chance = 0.01 >>>> >>>> AND caching = { 'keys' : 'ALL', 'rows_per_partition' : 'NONE' } >>>> >>>> AND comment = '' >>>> >>>> AND compaction = { 'class' : >>>> 'org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy', >>>> 'max_threshold' : 32, 'min_threshold' : 4 } >>>> >>>> AND compression = { 'chunk_length_in_kb' : 4, 'class' : >>>> 'org.apache.cassandra.io.compress.LZ4Compressor' } >>>> >>>> AND default_time_to_live = 0 >>>> >>>> AND speculative_retry = 'NONE' >>>> >>>> AND min_index_interval = 128 >>>> >>>> AND max_index_interval = 2048 >>>> >>>> AND crc_check_chance = 1.0 >>>> >>>> AND cdc = false >>>> >>>> AND memtable_flush_period_in_ms = 0; >>>> >>>> >>>> >>>
pricing-servicecluster-info
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