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From Michael Segel <michael_se...@hotmail.com>
Subject Re: Hbase scalability performance
Date Sat, 22 Dec 2012 16:23:30 GMT
I thought it was Doug Miel who said that HBase doesn't start to shine until you had at least
5 nodes. 
(Apologies if I misspelled Doug's name.) 

I happen to concur and if you want to start testing scalability, you will want to build a
bigger test rig. 

Just saying!

Oh and you're going to have a hot spot on that row key. 
Maybe do a hashed UUID ? 

I would suggest that you consider the following:

Create N number of rows... where N is a very large number of rows. 
Then to generate your random access, do a full table scan to get the N row keys in to memory.

Using a random number generator,  generate a random number and pop that row off the stack
so that the next iteration is between 1 and (N-1). 
Do this 200K times. 

Now time your 200K random fetches. 

It would be interesting to see how it performs  getting an average of a 'couple' of runs...
then increase the key space by an order of magnitude. 
(Start w 1 million rows, 10 million rows, 100 million rows.... ) 

In theory... if properly tuned. One should expect near linear results .  That is to say the
time it takes to get() a row across the data space should be consistent. Although I wonder
if you would have to somehow clear the cache? 

Sorry, just a random thought... 


On Dec 22, 2012, at 10:06 AM, Ted Yu <yuzhihong@gmail.com> wrote:

> By '3 datanodes', did you mean that you also increased the number of region
> servers to 3 ?
> When your test was running, did you look at Web UI to see whether load was
> balanced ? You can also use Ganglia for such purpose.
> What version of HBase are you using ?
> Thanks
> On Sat, Dec 22, 2012 at 7:43 AM, Dalia Sobhy <dalia.mohsobhy@hotmail.com>wrote:
>> Dear all,
>> I am testing a simple hbase application on a cluster of multiple nodes.
>> I am especially testing the scalability performance, by measuring the time
>> taken for random reads
>> Data size: 200,000 row
>> Row key : 0,1,2 very simple row key incremental
>> But i don't know why by increasing the cluster size, I see the same time.
>> For ex:
>> 2 Datanodes: 1000 random read: 1.757 sec
>> 3 datanodes: 1000 random read: 1.7 sec
>> So any help plzzz ??

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