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From Sean Bigdatafun <sean.bigdata...@gmail.com>
Subject Re: Read/Write Performance
Date Mon, 03 Jan 2011 01:11:44 GMT
Has this cured the GC pause at all? I do not see why turning on LZO is
relavent at all (I read your email, and it sounds that you saw pause after
the LZO is turned on).

BTW, are you using CMS on a 8GB Heapsize JVM and experiencing a 4 mins
pause? That sounds a lot.

On Thu, Dec 30, 2010 at 1:51 PM, Wayne <wav100@gmail.com> wrote:

> Lesson learned...restart thrift servers *after* restarting hadoop+hbase.
>
> On Thu, Dec 30, 2010 at 3:39 PM, Wayne <wav100@gmail.com> wrote:
>
> > We have restarted with lzop compression, and now I am seeing some really
> > long and frequent stop the world pauses of the entire cluster. The load
> > requests for all regions all go to zero except for the meta table region.
> No
> > data batches are getting in (no loads are occurring) and everything seems
> > frozen. It seems to last for 5+ seconds. Is this GC on the master or GC
> in
> > the meta region? What could cause everything to stop for several seconds?
> It
> > appears to happen on a recurring basis as well. I think we saw it before
> > switching to lzo but it seems much worse now (lasts longer and occurs
> more
> > frequently).
> >
> > Thanks.
> >
> >
> >
> > On Thu, Dec 30, 2010 at 12:20 PM, Wayne <wav100@gmail.com> wrote:
> >
> >> 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 <stack@duboce.net> wrote:
> >>
> >>> Oh, what versions are you using?
> >>> St.Ack
> >>>
> >>> On Thu, Dec 30, 2010 at 9:00 AM, Stack <stack@duboce.net> 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 <wav100@gmail.com> 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 <stack@duboce.net>
wrote:
> >>> >>
> >>> >>> On Mon, Dec 27, 2010 at 11:47 AM, Wayne <wav100@gmail.com>
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/~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/~stack/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 <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
> >>> >>> >>
> >>> >>> >
> >>> >>>
> >>> >>
> >>> >
> >>>
> >>
> >>
> >
>



-- 
--Sean

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