Michael, have you tried jstack on your client application?

Best regards,
Vladimir Rodionov
Principal Platform Engineer
Carrier IQ, www.carrieriq.com
e-mail: vrodio...@carrieriq.com

________________________________________
From: michael.grund...@high5games.com [michael.grund...@high5games.com]
Sent: Sunday, November 03, 2013 7:46 PM
To: user@hbase.apache.org
Subject: HBase Client Performance Bottleneck in a Single Virtual Machine

Hi all; I posted this as a question on StackOverflow as well but realized I 
should have gone straight ot the horses-mouth with my question. Sorry for the 
double post!

We are running a series of HBase tests to see if we can migrate one of our 
existing datasets from a RDBMS to HBase. We are running 15 nodes with 5 
zookeepers and HBase 0.94.12 for this test.

We have a single table with three column families and a key that is 
distributing very well across the cluster. All of our queries are running a 
direct look-up; no searching or scanning. Since the HTablePool is now frowned 
upon, we are using the Apache commons pool and a simple connection factory to 
create a pool of connections and use them in our threads. Each thread creates 
an HTableInstance as needed and closes it when done. There are no leaks we can 
identify.

If we run a single thread and just do lots of random calls sequentially, the 
performance is quite good. Everything works great until we start trying to 
scale the performance. As we add more threads and try and get more work done in 
a single VM, we start seeing performance degrade quickly. The client code is 
simply attempting to run either one of several gets or a single put at a given 
frequency. It then waits until the next time to run, we use this to simulate 
the workload from external clients. With a single thread, we will see call 
times in the 2-3 milliseconds which is acceptable.

As we add more threads, this call time starts increasing quickly. What gets 
strange is if we add more VMs, the times hold steady across them all so clearly 
it's a bottleneck in the running instance and not the cluster. We can get a 
huge amount of processing happening across the cluster very easily - it just 
has to use a lot of VMs on the client side to do it. We know the contention 
isn't in the connection pool as we see the problem even when we have more 
connections than threads. Unfortunately, the times are spiraling out of control 
very quickly. We need it to support at least 128 threads in practice, but most 
important I want to support 500 updates/sec and 250 gets/sec. In theory, this 
should be a piece of cake for the cluster as we can do FAR more work than that 
with a few VMs, but we don't even get close to this with a single VM.

So my question: how do people building high-performance apps with HBase get 
around this? What approach are others using for connection pooling in a 
multi-threaded environment? There seems to be a surprisingly little amount of 
info about this on the web considering the popularity. Is there some client 
setting we need to use that makes it perform better in a threaded environment? 
We are going to try to cache HTable instances next but that's a total guess. 
There are solutions to offloading work to other VMs but we really want to avoid 
this as clearly the cluster can handle the load and it will dramatically 
decrease the application performance in critical areas.

Any help is greatly appreciated! Thanks!
-Mike

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