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From lars hofhansl <>
Subject Re: count on large table
Date Tue, 14 Oct 2014 07:10:45 GMT
Back on the envelope math - assuming disks that can sustain 120mb/s - suggests you'd need about
17 disks 100% busy in total to pull 120gb off the disks in 60s. (i.e. at least 6 servers completely
utilizing all of their disk). How many server do you have? HBase/HDFS will likely not quite
max out all disks so your 10 machines are cutting that close.

Not concerned about the 250 regions - at least not for this.

Are all machines/disks/CPUs equally busy? Is the table salted?
Note that HBase's block cache stores data uncompressed, and hence your dataset likely does
not fit into the aggregate block cache. Your query might run sightly better with the /*+ NO_CACHE
*/ hint.

Now from your 187541ms number, things look worse, though.Do you have OTSDB or Ganglia to record
metrics of that cluster? If so can you share some graphs of IO/CPU during the query time.Any
chance to attach a profiler to one of the busy region server, or at least get us stack trace?


-- Lars

      From: Abe Weinograd <>
 To: user <>; lars hofhansl <> 
 Sent: Monday, October 13, 2014 9:30 AM
 Subject: Re: count on large table
Hi Lars,
Thanks for following up.
Table Size - 120G doing a du on HDFS.  We are using Snappy compression on the table.Column
Family - We have 1 column family for all columns and are using the Phoenix default one.Regions
- right now we have a ton of regions (250) because we pre split to help out bulk loads. 
I haven't collapsed them yet, but in a DEV environment that is configured the same way, we
have ~50 regions and experience the same performance issues.  I am planning on squaring this
away and trying again.Resource Utilization - Really high CPU usage on the region servers and
noticing a spike in IO too.
Based on your questions and what I know, the # of regions needs to be compacted first, though
I am not sure this is going to solve my issue.  the data nodes in HDFS have 3 1TB disks so
I am not convinced that my IO is the bottleneck here.

On Thu, Oct 9, 2014 at 8:36 PM, lars hofhansl <> wrote:

Hi Abe,

this is interesting.

How big are your rows (i.e. how much data is in the table, you tell with du in HDFS)? And
how many columns do you have? Any column families?
How many regions are in this table? (you can tell that through the HBase HMaster UI page)
When you execute the query, are all HBase region servers busy? Do you see IO, or just high

Client batching won't help with an aggregate (such as count) where not much data is transferred
back to the client.

-- Lars

      From: Abe Weinograd <>
 To: user <> 
 Sent: Wednesday, October 8, 2014 9:15 AM
 Subject: Re: count on large table
Good point.  I have to figure out how to do that in a SQL Tool like Squirrel or workbench.
Is there any obvious thing i can do to help tune this?  I know that's a loaded question. 
My client scanner batches are 1000 (also tried 10000 with no luck).

On Tue, Oct 7, 2014 at 9:09 PM, <> wrote:

Hi, AbeMaybe setting the following property would help...<property>
    <value>3600000</value>  </property>

From: Abe WeinogradDate: 2014-10-08 04:34To: userSubject: count on large tableI have
a table with 1B  rows.  I know this can is very specific to my environment, but just doing
a SELECT COUNT(1) on the table   It never finished.  
We have a 10 node cluster with the RS's Heap size at 26GiB and skewed towards the block cache. 
In the RS logs, i see a lot of these:
2014-10-07 16:27:04,942 WARN org.apache.hadoop.ipc.RpcServer: (responseTooSlow): {"processingtimems":22770,"call":"Scan(org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ScanRequest)","client":"","starttimems":1412713602172,"queuetimems":0,"class":"HRegionServer","responsesize":8,"method":"Scan"}

They stop eventually, but i the query times out and the query tool reports: org.apache.phoenix.exception.PhoenixIOException:
187541ms passed since the last invocation, timeout is currently set to 60000
Any ideas of where I can start in order to figure this out?
using Phoenix 4.1 on CDH 5.1 (Hbase 0.98.1)


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