> Could it be an issue that this optimization does not really take effect until > the memtable with the hoisted data is flushed? No. The read path in collectTimeOrderedData() reads from the memtable first. It then reads the SStable meta data (maxTimestamp) and checks if the candidate columns are both 1) all the columns in the query 2) the only possible values .
So immediately after the columns are hoisted a read will touch the and the sstable meta data (always in memory) for the most recent sstable. > In my simple example below, the same row is updated and multiple selects of > the same row will result in multiple writes to the memtable. with some overlapping reads this would be possible, once one of them has completed subsequent operations would read from the memtable only. > It seems it maybe possible (although unlikely) where, if you go from a > write-mostly to a read-mostly scenario, you could get into a state where you > are stuck rewriting to the same memtable, and the memtable is not flushed > because it absorbs the over-writes. Memtable would still be flushed due to other CF's generating memory pressure and/or the commit log check pointing. Also reads go to the memtable first. > However, are there any hidden gotcha's there because this optimization is not > occurring? Not that I can think off, the optimisation is not occurring because all the work getTimeOrderedData() does to read from disk has been done. You're good to to. Assuming you have narrow rows, or a good feel for how big they will get. > https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a "compaction > is behind" problem. Any history on that? I couldn't find too much > information on it. I assume it means cases where minor compaction cannot keep up. E.g. it has been throttled down, or a concurrent repair / upgradesstables is slowing things. Cheers ----------------- Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 18/12/2012, at 4:01 AM, Mike <mthero...@yahoo.com> wrote: > Thank you Aaron, this was very helpful. > > Could it be an issue that this optimization does not really take effect until > the memtable with the hoisted data is flushed? In my simple example below, > the same row is updated and multiple selects of the same row will result in > multiple writes to the memtable. It seems it maybe possible (although > unlikely) where, if you go from a write-mostly to a read-mostly scenario, you > could get into a state where you are stuck rewriting to the same memtable, > and the memtable is not flushed because it absorbs the over-writes. I can > foresee this especially if you are reading the same rows repeatedly. > > I also noticed from the codepaths that if Row caching is enabled, this > optimization will not occur. We made some changes this weekend to make this > column family more suitable to row-caching and enabled row-caching with a > small cache. Our initial results is that it seems to have corrected the > write counts, and has increased performance quite a bit. However, are there > any hidden gotcha's there because this optimization is not occurring? > https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a "compaction > is behind" problem. Any history on that? I couldn't find too much > information on it. > > Thanks, > -Mike > > On 12/16/2012 8:41 PM, aaron morton wrote: >> >>> 1) Am I reading things correctly? >> Yes. >> If you do a read/slice by name and more than min compaction level nodes >> where read the data is re-written so that the next read uses fewer SSTables. >> >>> 2) What is really happening here? Essentially minor compactions can occur >>> between 4 and 32 memtable flushes. Looking through the code, this seems to >>> only effect a couple types of select statements (when selecting a specific >>> column on a specific key being one of them). During the time between these >>> two values, every "select" statement will perform a write. >> Yup, only for readying a row where the column names are specified. >> Remember minor compaction when using SizedTiered Compaction (the default) >> works on buckets of the same size. >> >> Imagine a row that had been around for a while and had fragments in more >> than Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier >> and 2 sstables in the 1st. So it takes (potentially) 5 SSTable reads. If >> this row is read it will get hoisted back up. >> >> But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier >> it will not hoisted. >> >> There are a few short circuits in the SliceByName read path. One of them is >> to end the search when we know that no other SSTables contain >> columns that should be considered. So if the 4 columns you read frequently >> are hoisted into the 1st bucket your reads will get handled by that one >> bucket. >> >> It's not every select. Just those that touched more the min compaction >> sstables. >> >> >>> 3) Is this desired behavior? Is there something else I should be looking >>> at that could be causing this behavior? >> Yes. >> https://issues.apache.org/jira/browse/CASSANDRA-2503 >> >> Cheers >> >> >> ----------------- >> Aaron Morton >> Freelance Cassandra Developer >> New Zealand >> >> @aaronmorton >> http://www.thelastpickle.com >> >> On 15/12/2012, at 12:58 PM, Michael Theroux <mthero...@yahoo.com> wrote: >> >>> Hello, >>> >>> We have an unusual situation that I believe I've reproduced, at least >>> temporarily, in a test environment. I also think I see where this issue is >>> occurring in the code. >>> >>> We have a specific column family that is under heavy read and write load on >>> a nightly basis. For the purposes of this description, I'll refer to this >>> column family as "Bob". During this nightly processing, sometimes Bob is >>> under very write load, other times it is very heavy read load. >>> >>> The application is such that when something is written to Bob, a write is >>> made to one of two other tables. We've witnessed a situation where the >>> write count on Bob far outstrips the write count on either of the other >>> tables, by a factor of 3->10. This is based on the WriteCount available on >>> the column family JMX MBean. We have not been able to find where in our >>> code this is happening, and we have gone as far as tracing our CQL calls to >>> determine that the relationship between Bob and the other tables are what >>> we expect. >>> >>> I brought up a test node to experiment, and see a situation where, when a >>> "select" statement is executed, a write will occur. >>> >>> In my test, I perform the following (switching between nodetool and cqlsh): >>> >>> update bob set 'about'='coworker' where key='<hex key>'; >>> nodetool flush >>> update bob set 'about'='coworker' where key='<hex key>'; >>> nodetool flush >>> update bob set 'about'='coworker' where key='<hex key>'; >>> nodetool flush >>> update bob set 'about'='coworker' where key='<hex key>'; >>> nodetool flush >>> update bob set 'about'='coworker' where key='<hex key>'; >>> nodetool flush >>> >>> Then, for a period of time (before a minor compaction occurs), a select >>> statement that selects specific columns will cause writes to occur in the >>> write count of the column family: >>> >>> select about,changed,data from bob where key='<hex key>'; >>> >>> This situation will continue until a minor compaction is completed. >>> >>> I went into the code and added some traces to CollationController.java: >>> >>> private ColumnFamily collectTimeOrderedData() >>> { >>> logger.debug("collectTimeOrderedData"); >>> >>> ... <snip> ... >>> >>> ---> HERE logger.debug( "tables iterated: " + sstablesIterated + " Min >>> compact: " + cfs.getMinimumCompactionThreshold() ); >>> // "hoist up" the requested data into a more recent sstable >>> if (sstablesIterated > cfs.getMinimumCompactionThreshold() >>> && !cfs.isCompactionDisabled() >>> && cfs.getCompactionStrategy() instanceof >>> SizeTieredCompactionStrategy) >>> { >>> RowMutation rm = new RowMutation(cfs.table.name, new >>> Row(filter.key, returnCF.cloneMe())); >>> try >>> { >>> ---> HERE logger.debug( "Apply hoisted up row mutation" ); >>> // skipping commitlog and index updates is fine since >>> we're just de-fragmenting existing data >>> Table.open(rm.getTable()).apply(rm, false, false); >>> } >>> catch (IOException e) >>> { >>> // log and allow the result to be returned >>> logger.error("Error re-writing read results", e); >>> } >>> } >>> ... >>> <snip> ... >>> >>> >>> >>> Performing >>> the steps above, I see the following traces >>> (in the test environment I decreased the >>> minimum compaction threshold to make this >>> easier to reproduce). After I do a couple of >>> update/flush, I see this in the log: >>> >>> >>> >>> DEBUG [FlushWriter:7] 2012-12-14 22:54:40,106 CompactionManager.java (line >>> 117) Scheduling a background task check for bob with >>> SizeTieredCompactionStrategy >>> >>> >>> >>> Then, until compaction occurs, I see (when performing a select): >>> >>> DEBUG [ScheduledTasks:1] 2012-12-14 22:55:15,998 LoadBroadcaster.java (line >>> 86) Disseminating load info ... >>> DEBUG [Thrift:12] 2012-12-14 22:55:16,990 CassandraServer.java (line 1227) >>> execute_cql_query >>> DEBUG [Thrift:12] 2012-12-14 22:55:16,991 QueryProcessor.java (line 445) >>> CQL statement type: SELECT >>> DEBUG [Thrift:12] 2012-12-14 22:55:16,991 StorageProxy.java (line 653) >>> Command/ConsistencyLevel is SliceByNamesReadCommand(table='open', >>> key=804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce21b5f402a5342, >>> columnParent='QueryPath(columnFamilyName='bob', superColumnName='null', >>> columnName='null')', columns=[about,changed,data,])/ONE >>> DEBUG [Thrift:12] 2012-12-14 22:55:16,992 ReadCallback.java (line 79) >>> Blockfor is 1; setting up requests to /10.0.4.20 >>> DEBUG [Thrift:12] 2012-12-14 22:55:16,992 StorageProxy.java (line 669) >>> reading data locally >>> DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 StorageProxy.java (line 813) >>> LocalReadRunnable reading SliceByNamesReadCommand(table='open', >>> key=804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce21b5f402a5342, >>> columnParent='QueryPath(columnFamilyName='bob', superColumnName='null', >>> columnName='null')', columns=[about,changed,data,]) >>> DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 CollationController.java (line >>> 68) In get top level columns: class >>> org.apache.cassandra.db.filter.NamesQueryFilter type: Standard valid: class >>> org.apache.cassandra.db.marshal.BytesType >>> DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 CollationController.java (line >>> 84) collectTimeOrderedData >>> ---> DEBUG [ReadStage:61] 2012-12-14 22:55:17,192 CollationController.java >>> (line 188) tables iterated: 4 Min compact: 2 >>> ----> DEBUG [ReadStage:61] 2012-12-14 22:55:17,192 CollationController.java >>> (line 198) Apply hoisted up row mutation >>> DEBUG [ReadStage:61] 2012-12-14 22:55:17,193 Table.java (line 395) applying >>> mutation of row >>> 804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce21b5f402a5342 >>> >>> The above traces will occur every time I repeat the above select statement. >>> >>> Minor compaction doesn't start until a few minutes after the request was >>> submitted above (note, this is an unloaded test node): >>> >>> DEBUG [CompactionExecutor:11] 2012-12-14 22:57:03,278 IntervalNode.java >>> (line 45) Creating IntervalNode from >>> [Interval(DecoratedKey(Token(bytes[804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce... >>> >>> Once minor compaction occurs, the behavior around write count being >>> incremented stops, until more than the minimum compaction threshold >>> memtables are flush to disk. >>> >>> So, my questions are: >>> >>> 1) Am I reading things correctly? >>> >>> 2) What is really happening here? Essentially minor compactions can occur >>> between 4 and 32 memtable flushes. Looking through the code, this seems to >>> only effect a couple types of select statements (when selecting a specific >>> column on a specific key being one of them). During the time between these >>> two values, every "select" statement will perform a write. >>> >>> 3) Is this desired behavior? Is there something else I should be looking >>> at that could be causing this behavior? >>> >>> We are running Cassandra 1.1.2, with SizeTieredCompactionStrategy. >>> Any help is appreciated, >>> Thanks, >>> -Mike >>> >>> >>> >> >
