Le 01/03/10 01:20, Dan Washusen a écrit :
My (very rough) calculation of the data size came up with around 50MB. That
was assuming 400 bytes * 100,000 for the values, 32 + 8 * 13 * 100,000 for
the keys and an extra meg or two for extra key stuff. I didn't understand
how that resulted in the a region split, so I assume we are still missing
some information (or I made a mistake). As you mention, that should mean
that everything is in the MemStore and compression has not come into play
yet. Puzzling...
You are right, there is no region split when I use no compression.
Nevertheless, as you say, if everything is in the memstore, how can
it be that I see a so big difference between my tests ?
On PE; there isn't currently a way to specify compression options on the
testtable without extending PE and overriding
org.apache.hadoop.hbase.PerformanceEvaluation#getTableDescriptor method.
Maybe it could be added as an option?
Cheers,
Dan
On 1 March 2010 10:56, Jean-Daniel Cryans<jdcry...@apache.org> wrote:
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This page has an outdated help but it shows you how to run it: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.ba...@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.ba...@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.ba...@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.ba...@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 ?