HBase Version 0.89.20100924, r1001068 w/ 8GB heap I plan to run for 1 week straight maxed out. I am worried about GC pauses, especially concurrent mode failures (does hbase/hadoop suffer these under extended load?). What should I be looking for in the gc log in terms of problem signs? The ParNews are quick but the CMS concurrent marks are taking as much as 4 mins with an average of 20-30 secs.
Thanks. On Thu, Dec 30, 2010 at 12:00 PM, Stack <[email protected]> wrote: > Oh, what versions are you using? > St.Ack > > On Thu, Dec 30, 2010 at 9:00 AM, Stack <[email protected]> wrote: > > Keep going. Let it run longer. Get the servers as loaded as you think > > they'll be in production. Make sure the perf numbers are not because > > cluster is 'fresh'. > > St.Ack > > > > On Thu, Dec 30, 2010 at 5:51 AM, Wayne <[email protected]> wrote: > >> We finally got our cluster up and running and write performance looks > very > >> good. We are getting sustained 8-10k writes/sec/node on a 10 node > cluster > >> from Python through thrift. These are values written to 3 CFs so actual > >> hbase performance is 25-30k writes/sec/node. The nodes are currently > disk > >> i/o bound (40-50% utilization) but hopefully once we get lzop working > this > >> will go down. We have been running for 12 hours without a problem. We > hope > >> to get lzop going today and then load all through the long weekend. > >> > >> We plan to then test reads next week after we get some data in there. > Looks > >> good so far! Below are our settings in case there are some > >> suggestions/concerns. > >> > >> Thanks for everyone's help. It is pretty exciting to get performance > like > >> this from the start. > >> > >> > >> *Global* > >> > >> client.write.buffer = 10485760 (10MB = 5x default) > >> > >> optionalLogFlushInterval = 10000 (10 secs = 10x default) > >> > >> memstore.flush.size = 268435456 (256MB = 4x default) > >> > >> hregion.max.filesize = 1073741824 (1GB = 4x default) > >> > >> *Table* > >> > >> alter 'xxx', METHOD => 'table_att', DEFERRED_LOG_FLUSH => true > >> > >> > >> > >> > >> > >> On Wed, Dec 29, 2010 at 12:55 AM, Stack <[email protected]> wrote: > >> > >>> On Mon, Dec 27, 2010 at 11:47 AM, Wayne <[email protected]> wrote: > >>> > All data is written to 3 CFs. Basically 2 of the CFs are secondary > >>> indexes > >>> > (manually managed as normal CFs). It sounds like we should try hard > to > >>> get > >>> > as much out of thrift as we can before going to a lower level. > >>> > >>> Yes. > >>> > >>> Writes need > >>> > to be "fast enough", but reads are more important in the end (and are > the > >>> > reason we are switching from a different solution). The numbers you > >>> quoted > >>> > below sound like they are in the ballpark of what we are looking to > do. > >>> > > >>> > >>> Even the tens per second that I threw in there to CMA? > >>> > >>> > Much of our data is cold, and we expect reads to be disk i/o based. > >>> > >>> OK. FYI, we're not the best at this -- cache-miss cold reads -- what > >>> w/ a network hop in the way and currently we'll open a socket per > >>> access. > >>> > >>> > Given > >>> > this is 8GB heap a good place to start on the data nodes (24GB ram)? > Is > >>> the > >>> > block cache managed on its own (being it won't blow up causing OOM), > >>> > >>> It won't. Its constrained. Does our home-brewed sizeof. Default, > >>> its 0.2 of total heap. If you think cache will help, you could go up > >>> from there. 0.4 or 0.5 of heap. > >>> > >>> > and if > >>> > we do not use it (block cache) should we go even lower for the heap > (we > >>> want > >>> > to avoid CMF and long GC pauses)? > >>> > >>> If you are going to be doing cache-miss most of the time and cold > >>> reads, then yes, you can do away with cache. > >>> > >>> In testing of 0.90.x I've been running w/ 1MB heaps with 1k regions > >>> but this is my trying to break stuff. > >>> > >>> > Are there any timeouts we need to tweak to > >>> > make the cluster more "accepting" of long GC pauses while under > sustained > >>> > load (7+ days of 10k/inserts/sec/node)? > >>> > > >>> > >>> If zookeeper client timesout, the regionserver will shut itself down. > >>> In 0.90.0RC2, the client sessionout is set high -- 3 minutes. If you > >>> timeout that, then thats pretty extreme... something badly wrong I'd > >>> say. Heres' a few notes on the config and others that you might want > >>> to twiddle (see previous section on required configs... make sure > >>> you've got those too): > >>> > >>> > http://people.apache.org/~stack/hbase-0.90.0-candidate-2/docs/important_configurations.html#recommended_configurations<http://people.apache.org/%7Estack/hbase-0.90.0-candidate-2/docs/important_configurations.html#recommended_configurations> > < > http://people.apache.org/%7Estack/hbase-0.90.0-candidate-2/docs/important_configurations.html#recommended_configurations > > > >>> > >>> > >>> > Does LZO compression speed up reads/writes where there is excess CPU > to > >>> do > >>> > the compression? I assume it would lower disk i/o but increase CPU a > lot. > >>> Is > >>> > data compressed on the initial write or only after compaction? > >>> > > >>> > >>> LZO is pretty frictionless -- i.e. little CPU cost -- and yes, usually > >>> helps speed things up (grab more in the one go). What size are your > >>> records? You might want to mess w/ hfile block sizes though the 64k > >>> default is usually good enough for all but very small cell sizes. > >>> > >>> > >>> > With the replication in the HDFS layer how are reads managed in terms > of > >>> > load balancing across region servers? Does HDFS know to spread > multiple > >>> > requests across the 3 region servers that contain the same data? > >>> > >>> You only read from one of the replicas, always the 'closest'. If the > >>> DFSClient has trouble getting the first of the replicas, it moves on > >>> to the second, etc. > >>> > >>> > >>> > For example > >>> > with 10 data nodes if we have 50 concurrent readers with very > "random" > >>> key > >>> > requests we would expect to have 5 reads occurring on each data node > at > >>> the > >>> > same time. We plan to have a thrift server on each data node, so 5 > >>> > concurrent readers will be connected to each thrift server at any > given > >>> time > >>> > (50 in aggregate across 10 nodes). We want to be sure everything is > >>> designed > >>> > to evenly spread this load to avoid any possible hot-spots. > >>> > > >>> > >>> This is different. This is key design. A thrift server will be doing > >>> some subset of the key space. If the requests are evenly distributed > >>> over all of the key space, then you should be fine; all thrift servers > >>> will be evenly loaded. If not, then there could be hot spots. > >>> > >>> We have a balancer that currently only counts regions per server, not > >>> regions per server plus hits per region so it could be the case that a > >>> server by chance ends up carrying all of the hot regions. HBase > >>> itself is not too smart dealing with this. In 0.90.0, there is > >>> facility for manually moving regions -- i.e. closing in current > >>> location and moving the region off to another server w/ some outage > >>> while the move is happening (usually seconds) -- or you could split > >>> the hot region manually and then the daughters could be moved off to > >>> other servers... Primitive for now but should be better in next HBase > >>> versions. > >>> > >>> Have you been able to test w/ your data and your query pattern? > >>> That'll tell you way more than I ever could. > >>> > >>> Good luck, > >>> St.Ack > >>> > >>> > >>> > > >>> > > >>> > On Mon, Dec 27, 2010 at 1:49 PM, Stack <[email protected]> wrote: > >>> > > >>> >> On Fri, Dec 24, 2010 at 5:09 AM, Wayne <[email protected]> wrote: > >>> >> > We are in the process of evaluating hbase in an effort to switch > from > >>> a > >>> >> > different nosql solution. Performance is of course an important > part > >>> of > >>> >> our > >>> >> > evaluation. We are a python shop and we are very worried that we > can > >>> not > >>> >> get > >>> >> > any real performance out of hbase using thrift (and must drop down > to > >>> >> java). > >>> >> > We are aware of the various lower level options for bulk insert or > >>> java > >>> >> > based inserts with turning off WAL etc. but none of these are > >>> available > >>> >> to > >>> >> > us in python so are not part of our evaluation. > >>> >> > >>> >> I can understand python for continuous updates from your frontend or > >>> >> whatever but you might consider hacking up a bit of java to make us > of > >>> >> the bulk updater; you'll get upload rates orders of magnitude beyond > >>> >> what you'd achieve going via the API via python (or java for that > >>> >> matter). You can also do incremental updates using the bulk loader. > >>> >> > >>> >> > >>> >> We have a 10 node cluster > >>> >> > (24gb, 6 x 1TB, 16 core) that we setting up as data/region nodes, > and > >>> we > >>> >> are > >>> >> > looking for suggestions on configuration as well as benchmarks in > >>> terms > >>> >> of > >>> >> > expectations of performance. Below are some specific questions. I > >>> realize > >>> >> > there are a million factors that help determine specific > performance > >>> >> > numbers, so any examples of performance from running clusters > would be > >>> >> great > >>> >> > as examples of what can be done. > >>> >> > >>> >> Yeah, you have been around the block obviously. Its hard to give out > >>> >> 'numbers' since so many different factors involved. > >>> >> > >>> >> > >>> >> Again thrift seems to be our "problem" so > >>> >> > non java based solutions are preferred (do any non java based > shops > >>> run > >>> >> > large scale hbase clusters?). Our total production cluster size is > >>> >> estimated > >>> >> > to be 50TB. > >>> >> > > >>> >> > >>> >> There are some substantial shops running non-java; e.g. the yfrog > >>> >> folks go via REST, the mozilla fellas are python over thrift, > >>> >> Stumbleupon is php over thrift. > >>> >> > >>> >> > Our data model is 3 CFs, one primary and 2 secondary indexes. All > >>> writes > >>> >> go > >>> >> > to all 3 CFs and are grouped as a batch of row mutations which > should > >>> >> avoid > >>> >> > row locking issues. > >>> >> > > >>> >> > >>> >> A write updates 3CFs and secondary indices? Thats an expensive Put > >>> >> relatively. You have to run w/ 3CFs? It facilitates fast querying? > >>> >> > >>> >> > >>> >> > What heap size is recommended for master, and for region servers > (24gb > >>> >> ram)? > >>> >> > >>> >> Master doesn't take much heap, at least not in the coming 0.90.0 > HBase > >>> >> (Is that what you intend to run)? > >>> >> > >>> >> The more RAM you give the regionservers, the more cache your cluster > >>> will > >>> >> have. > >>> >> > >>> >> Whats important to you read or write times? > >>> >> > >>> >> > >>> >> > What other settings can/should be tweaked in hbase to optimize > >>> >> performance > >>> >> > (we have looked at the wiki page)? > >>> >> > >>> >> Thats a good place to start. Take a look through this mailing list > >>> >> for others (Its time for a trawl of mailing list and then distilling > >>> >> the findings into a reedit of our perf page). > >>> >> > >>> >> > What is a good batch size for writes? We will start with 10k > >>> >> values/batch. > >>> >> > >>> >> Start small with defaults. Make sure its all running smooth first. > >>> >> Then rachet it up. > >>> >> > >>> >> > >>> >> > How many concurrent writers/readers can a single data node handle > with > >>> >> > evenly distributed load? Are there settings specific to this? > >>> >> > >>> >> How many clients you going to have writing HBase? > >>> >> > >>> >> > >>> >> > What is "very good" read/write latency for a single put/get in > hbase > >>> >> using > >>> >> > thrift? > >>> >> > >>> >> "Very Good" would be < a few milliseconds. > >>> >> > >>> >> > >>> >> > What is "very good" read/write throughput per node in hbase using > >>> thrift? > >>> >> > > >>> >> > >>> >> Thousands of ops per second per regionserver (Sorry, can't be more > >>> >> specific than that). If the Puts are multi-family + updates on > >>> >> secondary indices, hundreds -- maybe even tens... I'm not sure -- > >>> >> rather than thousands. > >>> >> > >>> >> > We are looking to get performance numbers in the range of 10k > >>> aggregate > >>> >> > inserts/sec/node and read latency < 30ms/read with 3-4 concurrent > >>> >> > readers/node. Can our expectations be met with hbase through > thrift? > >>> Can > >>> >> > they be met with hbase through java? > >>> >> > > >>> >> > >>> >> > >>> >> I wouldn't fixate on the thrift hop. At SU we can do thousands of > ops > >>> >> a second per node np from PHP frontend over thrift. > >>> >> > >>> >> 10k inserts a second per node into single CF might be doable. If > into > >>> >> 3CFs, then you need to recalibrate your expectations (I'd say). > >>> >> > >>> >> > Thanks in advance for any help, examples, or recommendations that > you > >>> can > >>> >> > provide! > >>> >> > > >>> >> Sorry, the above is light on recommendations (for reasons cited by > >>> >> Ryan above -- smile). > >>> >> St.Ack > >>> >> > >>> > > >>> > >> > > >
