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From Wayne <wav...@gmail.com>
Subject Re: Read/Write Performance
Date Mon, 27 Dec 2010 19:47:41 GMT
Thank you very much for the detailed answers. Below is another round of too
many questions. We are swapping data stores late in the game and want to be
sure to start "deep" to avoid the same old problems we have seen in the
past. Thanks in advance for any advice you can provide.

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. 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.

Much of our data is cold, and we expect reads to be disk i/o based. 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), 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)? 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)?

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?

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? 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.



On Mon, Dec 27, 2010 at 1:49 PM, Stack <stack@duboce.net> wrote:

> On Fri, Dec 24, 2010 at 5:09 AM, Wayne <wav100@gmail.com> 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
>

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