Hey Jeff, Thanks for the clarification, I did not explain my self clearly, the max_stable_age_days is set to 30 days and the ttl on every insert is set to 30 days also by default. gc_grace_seconds is 0, so i would think the sstable as a whole would be deleted.
Because of the problems mentioned by at 1) above it looks like, there might be cases where the table just lies around since no compaction is happening on it and even though everything is expired it would still not be deleted? for 3) the average read is pretty good, though the throughput doesn't seem to be that great, when no repair is running we get GCIns > 200ms every couple of hours once, otherwise its every 10-20 mins INFO [ScheduledTasks:1] 2016-02-23 05:15:03,070 GCInspector.java (line 116) GC for ParNew: 205 ms for 1 collections, 1712439128 used; max is 7784628224 INFO [ScheduledTasks:1] 2016-02-23 08:30:47,709 GCInspector.java (line 116) GC for ParNew: 242 ms for 1 collections, 1819126928 used; max is 7784628224 INFO [ScheduledTasks:1] 2016-02-23 09:09:55,085 GCInspector.java (line 116) GC for ParNew: 374 ms for 1 collections, 1829660304 used; max is 7784628224 INFO [ScheduledTasks:1] 2016-02-23 09:11:21,245 GCInspector.java (line 116) GC for ParNew: 419 ms for 1 collections, 2309875224 used; max is 7784628224 INFO [ScheduledTasks:1] 2016-02-23 09:35:50,717 GCInspector.java (line 116) GC for ParNew: 231 ms for 1 collections, 2515325328 used; max is 7784628224 INFO [ScheduledTasks:1] 2016-02-23 09:38:47,194 GCInspector.java (line 116) GC for ParNew: 252 ms for 1 collections, 1724241952 used; max is 7784628224 our reading patterns are dependent on BF to work efficiently as we do a lot of reads for keys that may not exists because its time series and we segregate data based on hourly boundary from epoch. hey Christoper, yes every row in the stable that should have been deleted has "d" in that column. Also the key for one of the row is as "key": "0008000000000cdd5edd000008000000000006251000" how do i get it back to normal readable format to get the (long,long) -- composite partition key back? Looks like i have to force a major compaction to delete a lot of data ? are there any other solutions ? thanks anishek On Mon, Feb 22, 2016 at 11:21 PM, Jeff Jirsa <jeff.ji...@crowdstrike.com> wrote: > 1) getFullyExpiredSSTables in 2.0 isn’t as thorough as many expect, so > it’s very likely that some sstables stick around longer than you expect. > > 2) max_sstable_age_days tells cassandra when to stop compacting that file, > not when to delete it. > > 3) You can change the window size using both the base_time_seconds > parameter and max_sstable_age_days parameter (use the former to set the > size of the first window, and the latter to determine how long before you > stop compacting that window). It’s somewhat non-intuitive. > > Your read latencies actually look pretty reasonable, are you sure you’re > not simply hitting GC pauses that cause your queries to run longer than you > expect? Do you have graphs of GC time (first derivative of total gc time is > common for tools like graphite), or do you see ‘gcinspector’ in your logs > indicating pauses > 200ms? > > From: Anishek Agarwal > Reply-To: "user@cassandra.apache.org" > Date: Sunday, February 21, 2016 at 11:13 PM > To: "user@cassandra.apache.org" > Subject: Re: High Bloom filter false ratio > > Hey guys, > > Just did some more digging ... looks like DTCS is not removing old data > completely, I used sstable2json for one such table and saw old data there. > we have a value of 30 for max_stable_age_days for the table. > > One of the columns showed data as :["2015-12-10 11\\:03+0530:", > "56690ea2", 1449725602552000, "d"] what is the meaning of "d" in the last > IS_MARKED_FOR_DELETE column ? > > I see data from 10 dec 2015 still there, looks like there are a few issues > with DTCS, Operationally what choices do i have to rectify this, We are on > version 2.0.15. > > thanks > anishek > > > > > On Mon, Feb 22, 2016 at 10:23 AM, Anishek Agarwal <anis...@gmail.com> > wrote: > >> We are using DTCS have a 30 day window for them before they are cleaned >> up. I don't think with DTCS we can do anything about table sizing. Please >> do let me know if there are other ideas. >> >> On Sat, Feb 20, 2016 at 12:51 AM, Jaydeep Chovatia < >> chovatia.jayd...@gmail.com> wrote: >> >>> To me following three looks on higher side: >>> SSTable count: 1289 >>> >>> In order to reduce SSTable count see if you are compacting of not (If >>> using STCS). Is it possible to change this to LCS? >>> >>> >>> Number of keys (estimate): 345137664 (345M partition keys) >>> >>> I don't have any suggestion about reducing this unless you partition >>> your data. >>> >>> >>> Bloom filter space used, bytes: 493777336 (400MB is huge) >>> >>> If number of keys are reduced then this will automatically reduce bloom >>> filter size I believe. >>> >>> >>> >>> Jaydeep >>> >>> On Thu, Feb 18, 2016 at 7:52 PM, Anishek Agarwal <anis...@gmail.com> >>> wrote: >>> >>>> Hey all, >>>> >>>> @Jaydeep here is the cfstats output from one node. >>>> >>>> Read Count: 1721134722 >>>> >>>> Read Latency: 0.04268825050756254 ms. >>>> >>>> Write Count: 56743880 >>>> >>>> Write Latency: 0.014650376727851532 ms. >>>> >>>> Pending Tasks: 0 >>>> >>>> Table: user_stay_points >>>> >>>> SSTable count: 1289 >>>> >>>> Space used (live), bytes: 122141272262 >>>> >>>> Space used (total), bytes: 224227850870 >>>> >>>> Off heap memory used (total), bytes: 653827528 >>>> >>>> SSTable Compression Ratio: 0.4959736121441446 >>>> >>>> Number of keys (estimate): 345137664 >>>> >>>> Memtable cell count: 339034 >>>> >>>> Memtable data size, bytes: 106558314 >>>> >>>> Memtable switch count: 3266 >>>> >>>> Local read count: 1721134803 >>>> >>>> Local read latency: 0.048 ms >>>> >>>> Local write count: 56743898 >>>> >>>> Local write latency: 0.018 ms >>>> >>>> Pending tasks: 0 >>>> >>>> Bloom filter false positives: 40664437 >>>> >>>> Bloom filter false ratio: 0.69058 >>>> >>>> Bloom filter space used, bytes: 493777336 >>>> >>>> Bloom filter off heap memory used, bytes: 493767024 >>>> >>>> Index summary off heap memory used, bytes: 91677192 >>>> >>>> Compression metadata off heap memory used, bytes: 68383312 >>>> >>>> Compacted partition minimum bytes: 104 >>>> >>>> Compacted partition maximum bytes: 1629722 >>>> >>>> Compacted partition mean bytes: 1773 >>>> >>>> Average live cells per slice (last five minutes): 0.0 >>>> >>>> Average tombstones per slice (last five minutes): 0.0 >>>> >>>> >>>> @Tyler Hobbs >>>> >>>> we are using cassandra 2.0.15 so >>>> https://issues.apache.org/jira/browse/CASSANDRA-8525 shouldnt occur. >>>> Other problems looks like will be fixed in 3.0 .. we will mostly try and >>>> slot in an upgrade to 3.x version towards second quarter of this year. >>>> >>>> >>>> @Daemon >>>> >>>> Latencies seem to have higher ratios, attached is the graph. >>>> >>>> >>>> I am mostly trying to look at Bloom filters, because the way we do >>>> reads, we read data with non existent partition keys and it seems to be >>>> taking long to respond, like for 720 queries it takes 2 seconds, with all >>>> 721 queries not returning anything. the 720 queries are done in >>>> sequence of 180 queries each with 180 of them running in parallel. >>>> >>>> >>>> thanks >>>> >>>> anishek >>>> >>>> >>>> >>>> On Fri, Feb 19, 2016 at 3:09 AM, Jaydeep Chovatia < >>>> chovatia.jayd...@gmail.com> wrote: >>>> >>>>> How many partition keys exists for the table which shows this problem >>>>> (or provide nodetool cfstats for that table)? >>>>> >>>>> On Thu, Feb 18, 2016 at 11:38 AM, daemeon reiydelle < >>>>> daeme...@gmail.com> wrote: >>>>> >>>>>> The bloom filter buckets the values in a small number of buckets. I >>>>>> have been surprised by how many cases I see with large cardinality where >>>>>> a >>>>>> few values populate a given bloom leaf, resulting in high false >>>>>> positives, >>>>>> and a surprising impact on latencies! >>>>>> >>>>>> Are you seeing 2:1 ranges between mean and worse case latencies >>>>>> (allowing for gc times)? >>>>>> >>>>>> Daemeon Reiydelle >>>>>> On Feb 18, 2016 8:57 AM, "Tyler Hobbs" <ty...@datastax.com> wrote: >>>>>> >>>>>>> You can try slightly lowering the bloom_filter_fp_chance on your >>>>>>> table. >>>>>>> >>>>>>> Otherwise, it's possible that you're repeatedly querying one or two >>>>>>> partitions that always trigger a bloom filter false positive. You could >>>>>>> try manually tracing a few queries on this table (for non-existent >>>>>>> partitions) to see if the bloom filter rejects them. >>>>>>> >>>>>>> Depending on your Cassandra version, your false positive ratio could >>>>>>> be inaccurate: https://issues.apache.org/jira/browse/CASSANDRA-8525 >>>>>>> >>>>>>> There are also a couple of recent improvements to bloom filters: >>>>>>> * https://issues.apache.org/jira/browse/CASSANDRA-8413 >>>>>>> * https://issues.apache.org/jira/browse/CASSANDRA-9167 >>>>>>> >>>>>>> >>>>>>> On Thu, Feb 18, 2016 at 1:35 AM, Anishek Agarwal <anis...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Hello, >>>>>>>> >>>>>>>> We have a table with composite partition key with humungous >>>>>>>> cardinality, its a combination of (long,long). On the table we have >>>>>>>> bloom_filter_fp_chance=0.010000. >>>>>>>> >>>>>>>> On doing "nodetool cfstats" on the 5 nodes we have in the cluster >>>>>>>> we are seeing "Bloom filter false ratio:" in the range of 0.7 -0.9. >>>>>>>> >>>>>>>> I thought over time the bloom filter would adjust to the key space >>>>>>>> cardinality, we have been running the cluster for a long time now but >>>>>>>> have >>>>>>>> added significant traffic from Jan this year, which would not lead to >>>>>>>> writes in the db but would lead to high reads to see if are any values. >>>>>>>> >>>>>>>> Are there any settings that can be changed to allow better ratio. >>>>>>>> >>>>>>>> Thanks >>>>>>>> Anishek >>>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Tyler Hobbs >>>>>>> DataStax <http://datastax.com/> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
