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From Puneet Kumar Ojha <>
Subject RE: count on large table
Date Tue, 21 Oct 2014 13:04:57 GMT
Please check IPV6 , if enabled …disable it and synchronize the ntpd and restart. It might

From: Abe Weinograd []
Sent: Tuesday, October 21, 2014 6:19 PM
To: user; lars hofhansl
Subject: Re: count on large table

Hi Lars,

We have 10 Region Servers and 2 1TB on each.  The table is not salted, but we pre split regions
when we bulk load so that we force equal distribution of our data.  the data is relatively
distributed across our region servers, with no one Region Server being the "long tail."

I don't have any metrics from Ganglia.  We are running CDH on EC2, for what it is work.  The
CPUs spike to 100% and IO jumps pretty equallyon the Region Servers.  Attached is the RS log
from one of them when all I am doing on the entire cluster is a COUNT in phoenix.

Thanks again for your help,

On Tue, Oct 14, 2014 at 3:10 AM, lars hofhansl <<>>
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


-- 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
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 <<>>
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, Abe
Maybe setting the following property would help...



From: Abe Weinograd<>
Date: 2014-10-08 04:34
To: user<>
Subject: count on large table
I 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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