Home | About | Sematext search-lucene.com search-hadoop.com
 Search Hadoop and all its subprojects:

Switch to Threaded View
HBase >> mail # user >> Poor HBase map-reduce scan performance

Copy link to this message
Re: Poor HBase map-reduce scan performance
If you can, try 0.94.4+; it should significantly reduce the amount of bytes copied around in RAM during scanning, especially if you have wide rows and/or large key portions. That in turns makes scans scale better across cores, since RAM is shared resource between cores (much like disk).
It's not hard to build the latest HBase against Cloudera's version of Hadoop. I can send along a simple patch to pom.xml to do that.

-- Lars

 From: Bryan Keller <[EMAIL PROTECTED]>
Sent: Tuesday, April 30, 2013 11:02 PM
Subject: Re: Poor HBase map-reduce scan performance

The table has hashed keys so rows are evenly distributed amongst the regionservers, and load on each regionserver is pretty much the same. I also have per-table balancing turned on. I get mostly data local mappers with only a few rack local (maybe 10 of the 250 mappers).

Currently the table is a wide table schema, with lists of data structures stored as columns with column prefixes grouping the data structures (e.g. 1_name, 1_address, 1_city, 2_name, 2_address, 2_city). I was thinking of moving those data structures to protobuf which would cut down on the number of columns. The downside is I can't filter on one value with that, but it is a tradeoff I would make for performance. I was also considering restructuring the table into a tall table.

Something interesting is that my old regionserver machines had five 15k SCSI drives instead of 2 SSDs, and performance was about the same. Also, my old network was 1gbit, now it is 10gbit. So neither network nor disk I/O appear to be the bottleneck. The CPU is rather high for the regionserver so it seems like the best candidate to investigate. I will try profiling it tomorrow and will report back. I may revisit compression on vs off since that is adding load to the CPU.

I'll also come up with a sample program that generates data similar to my table.
On Apr 30, 2013, at 10:01 PM, lars hofhansl <[EMAIL PROTECTED]> wrote:

> Your average row is 35k so scanner caching would not make a huge difference, although I would have expected some improvements by setting it to 10 or 50 since you have a wide 10ge pipe.
> I assume your table is split sufficiently to touch all RegionServer... Do you see the same load/IO on all region servers?
> A bunch of scan improvements went into HBase since 0.94.2.
> I blogged about some of these changes here: http://hadoop-hbase.blogspot.com/2012/12/hbase-profiling.html
> In your case - since you have many columns, each of which carry the rowkey - you might benefit a lot from HBASE-7279.
> In the end HBase *is* slower than straight HDFS for full scans. How could it not be?
> So I would start by looking at HDFS first. Make sure Nagle's is disbaled in both HBase and HDFS.
> And lastly SSDs are somewhat new territory for HBase. Maybe Andy Purtell is listening, I think he did some tests with HBase on SSDs.
> With rotating media you typically see an improvement with compression. With SSDs the added CPU needed for decompression might outweigh the benefits.
> At the risk of starting a larger discussion here, I would posit that HBase's LSM based design, which trades random IO with sequential IO, might be a bit more questionable on SSDs.
> If you can, it would be nice to run a profiler against one of the RegionServers (or maybe do it with the single RS setup) and see where it is bottlenecked.
> (And if you send me a sample program to generate some data - not 700g, though :) - I'll try to do a bit of profiling during the next days as my day job permits, but I do not have any machines with SSDs).
> -- Lars
> ________________________________
> From: Bryan Keller <[EMAIL PROTECTED]>
> Sent: Tuesday, April 30, 2013 9:31 PM
> Subject: Re: Poor HBase map-reduce scan performance
> Yes, I have tried various settings for setCaching() and I have setCacheBlocks(false)
> On Apr 30, 2013, at 9:17 PM, Ted Yu <[EMAIL PROTECTED]> wrote: