hbase-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Jean-Daniel Cryans <jdcry...@apache.org>
Subject Re: LZO vs GZIP vs NO COMPREESSION: why is GZIP the winner ???
Date Sun, 28 Feb 2010 23:56:57 GMT
As Dan said, your data is so small you don't really trigger many
different behaviors in HBase, it could very well kept mostly in the
memstores where compression has no impact at all.

WRT a benchmark, there's the PerformanceEvaluation (we call it PE for
short) which is well maintained and lets you set a compression level.
This page has an outdated help but it shows you how to run it:
http://wiki.apache.org/hadoop/Hbase/PerformanceEvaluation

Another option is importing the wikipedia dump, which is highly
compressible and not manufactured like the PE. Last summer I wrote a
small MR job to do the import easily and although the code is based on
a dev version 0.20.0, it should be fairly easy to make it work on
0.20.3 (probably just replacing the libs). See
http://code.google.com/p/hbase-wikipedia-loader/

See the last paragraph of the Getting Started in the Wiki, I show some
import numbers:

"For example, it took 29 min on a 6 nodes cluster (1 master and 5
region servers) with the same hardware (AMD Phenom(tm) 9550 Quad, 8GB,
2x1TB disks), 2 map slot per task tracker (that's 10 parallel maps),
and GZ compression. With LZO and a new table it took 23 min 20 ses.
Compressed the table is 32 regions big, uncompressed it's 93 and took
30 min 10 sec to import."

You can see that the import was a lot faster on LZO. I didn't do any
reading test tho...

Good luck!

J-D

On Sun, Feb 28, 2010 at 9:30 AM, Vincent Barat <vincent.barat@ubikod.com> wrote:
> The impact of my cluster architecture on the performances is obviously the
> same in my 3 test cases. Providing that I only change the compression type
> between tests, I don't understand why changing the number of regions or
> whatever else would change the speed ratio between my tests, especially
> between the GZIP & LZO tests.
>
> Is there some ready to use and easy to setup benchmarks I could use to try
> to reproduce the issue in a well known environment ?
>
> Le 25/02/10 19:29, Jean-Daniel Cryans a écrit :
>>
>> If only 1 region, providing more than one nodes will probably just
>> slow down the test since the load is handled by one machine which has
>> to replicate blocks 2 times. I think your test would have much more
>> value if you really grew at least to 10 regions. Also make sure to run
>> the tests more than once on completely new hbase setups (drop table +
>> restart should be enough).
>>
>> May I also recommend upgrading to hbase 0.20.3? It will provide a
>> better experience in general.
>>
>> J-D
>>
>> On Thu, Feb 25, 2010 at 2:49 AM, Vincent Barat<vincent.barat@ubikod.com>
>>  wrote:
>>>
>>> Unfortunately I can post only some snapshots.
>>>
>>> I have no region split (I insert just 100000 rows so there is no split,
>>> except when I don't use compression).
>>>
>>> I use HBase 0.20.2 and to insert I use the HTable.put(list<Put>);
>>>
>>> The only difference between my 3 tests is the way I create the test
>>> table:
>>>
>>> HBaseAdmin admin = new HBaseAdmin(config);
>>>
>>> HTableDescriptor desc = new HTableDescriptor(name);
>>>
>>> HColumnDescriptor colDesc;
>>>
>>> colDesc = new HColumnDescriptor(Bytes.toBytes("meta:"));
>>> colDesc.setMaxVersions(1);
>>> colDesc.setCompressionType(Algorithm.GZ);<- LZO or NONE
>>> desc.addFamily(colDesc);
>>>
>>> colDesc = new HColumnDescriptor(Bytes.toBytes("data:"));
>>> colDesc.setMaxVersions(1);
>>> colDesc.setCompressionType(Algorithm.GZ);<- LZO or NONE
>>> desc.addFamily(colDesc);
>>>
>>> admin.createTable(desc);
>>>
>>> A typical row inserted is made of 13 columns with a short content, as
>>> show
>>> here:
>>>
>>> 1264761195240/6ffc3fe659023 column=data:accuracy,
>>> timestamp=1267006115356,
>>> value=1317
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:alt, timestamp=1267006115356,
>>> value=0
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:country,
>>> timestamp=1267006115356,
>>> value=France
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:countrycode,
>>> timestamp=1267006115356, value=FR
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:lat, timestamp=1267006115356,
>>> value=48.65869706
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:locality,
>>> timestamp=1267006115356,
>>> value=Morsang-sur-Orge
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:lon, timestamp=1267006115356,
>>> value=2.36138182
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:postalcode,
>>> timestamp=1267006115356, value=91390
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=data:region, timestamp=1267006115356,
>>> value=Ile-de-France
>>>  a3c9cfed0a50a9f199ed42f2730
>>>  1264761195240/6ffc3fe659023 column=meta:imei, timestamp=1267006115356,
>>> value=6ffc3fe659023a3c9cfed0a50a9f199e
>>>  a3c9cfed0a50a9f199ed42f2730 d42f2730
>>>  1264761195240/6ffc3fe659023 column=meta:infoid, timestamp=1267006115356,
>>> value=ca30781e0c375a1236afbf323cbfa4
>>>  a3c9cfed0a50a9f199ed42f2730 0dc2c7c7af
>>>  1264761195240/6ffc3fe659023 column=meta:locid, timestamp=1267006115356,
>>> value=5e15a0281e83cfe55ec1c362f84a39f
>>>  a3c9cfed0a50a9f199ed42f2730 006f18128
>>>  1264761195240/6ffc3fe659023 column=meta:timestamp,
>>> timestamp=1267006115356,
>>> value=1264761195240
>>>  a3c9cfed0a50a9f199ed42f2730
>>>
>>> Maybe LZO works much better with fewer rows with bigger content?
>>>
>>> Le 24/02/10 19:10, Jean-Daniel Cryans a écrit :
>>>>
>>>> Are you able to post the code used for the insertion? It could be
>>>> something with your usage pattern or something wrong with the code
>>>> itself.
>>>>
>>>> How many rows are you inserting? Do you even have some region splits?
>>>>
>>>> J-D
>>>>
>>>> On Wed, Feb 24, 2010 at 1:52 AM, Vincent Barat<vincent.barat@ubikod.com>
>>>>  wrote:
>>>>>
>>>>> Yes of course.
>>>>>
>>>>> We use a 4 machine cluster (4 large instances on AWS): 8 GB RAM each,
>>>>> dual
>>>>> core CPU. 1 is for the Hadoop and HBase namenode / masters, and 3 are
>>>>> hosting the datanode / regionservers.
>>>>>
>>>>> The table used for testing is first created, then I insert sequentially
>>>>> a
>>>>> set of rows and count the nb of rows inserted by second.
>>>>>
>>>>> I insert rows by set of 1000 (using HTable.put(list<Put>);
>>>>>
>>>>> When reading, I read also sequentially by using a scanner (scanner
>>>>> caching
>>>>> is set to 1024 rows).
>>>>>
>>>>> Maybe our installation of LZO is not good ?
>>>>>
>>>>>
>>>>> Le 23/02/10 22:15, Jean-Daniel Cryans a écrit :
>>>>>>
>>>>>> Vincent,
>>>>>>
>>>>>> I don't expect that either, can you give us more info about your
test
>>>>>> environment?
>>>>>>
>>>>>> Thx,
>>>>>>
>>>>>> J-D
>>>>>>
>>>>>> On Tue, Feb 23, 2010 at 10:39 AM, Vincent Barat
>>>>>> <vincent.barat@ubikod.com>      wrote:
>>>>>>>
>>>>>>> Hello,
>>>>>>>
>>>>>>> I did some testing to figure out which compression algo I should
use
>>>>>>> for
>>>>>>> my
>>>>>>> HBase tables. I thought that LZO was the good candidate, but
it
>>>>>>> appears
>>>>>>> that
>>>>>>> it is the worst one.
>>>>>>>
>>>>>>> I uses one table with 2 families and 10 columns. Each row has
a total
>>>>>>> of
>>>>>>> 200
>>>>>>> to 400 bytes.
>>>>>>>
>>>>>>> Here is my results:
>>>>>>>
>>>>>>> GZIP:           2600 to 3200 inserts/s  12000 to 15000
reads/s
>>>>>>> NO COMPRESSION: 2000 to 2600 inserts/s  4900 to 5020 reads/s
>>>>>>> LZO             1600 to 2100 inserts/s  4020 to 4600 reads/s
>>>>>>>
>>>>>>> Do you have an explanation to this ? I though that the LZO
>>>>>>> compression
>>>>>>> was
>>>>>>> always faster at compression and decompression than GZIP ?
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>

Mime
View raw message