hbase-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Michael Segel <michael_se...@hotmail.com>
Subject Re: Poor HBase map-reduce scan performance
Date Wed, 01 May 2013 14:24:40 GMT
I'd say go to Avro over protobufs in terms of redesigning your schema. 

With respect to CPUs, you don't say what your system looks like. Intel vs AMD , Num physical
cores, what else you're running on the machine (#Mappers/Reducer slots) etc ... 

In terms of the schema... 

How are you accessing your data? 
You said that you want to filter on a column value... using avro to store the address record
in lets say a JSON string... write a custom filter? 

And people laughed at me when I said that schema design was critical and often misunderstood.
(Ok the truth was that they laughed at me because I thought I looked cool wearing a plaid


On May 1, 2013, at 1:02 AM, Bryan Keller <bryanck@gmail.com> wrote:

> 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
> 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 <larsh@apache.org> 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
>> 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
>> 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 <bryanck@gmail.com>
>> To: user@hbase.apache.org 
>> 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 <yuzhihong@gmail.com> wrote:
>>> From http://hbase.apache.org/book.html#mapreduce.example :
>>> scan.setCaching(500);        // 1 is the default in Scan, which will
>>> be bad for MapReduce jobs
>>> scan.setCacheBlocks(false);  // don't set to true for MR jobs
>>> I guess you have used the above setting.
>>> 0.94.x releases are compatible. Have you considered upgrading to, say
>>> 0.94.7 which was recently released ?
>>> Cheers
>>> On Tue, Apr 30, 2013 at 9:01 PM, Bryan Keller <bryanck@gmail.com> wrote:
>>>> I have been attempting to speed up my HBase map-reduce scans for a while
>>>> now. I have tried just about everything without much luck. I'm running out
>>>> of ideas and was hoping for some suggestions. This is HBase 0.94.2 and
>>>> Hadoop 2.0.0 (CDH4.2.1).
>>>> The table I'm scanning:
>>>> 20 mil rows
>>>> Hundreds of columns/row
>>>> Column keys can be 30-40 bytes
>>>> Column values are generally not large, 1k would be on the large side
>>>> 250 regions
>>>> Snappy compression
>>>> 8gb region size
>>>> 512mb memstore flush
>>>> 128k block size
>>>> 700gb of data on HDFS
>>>> My cluster has 8 datanodes which are also regionservers. Each has 8 cores
>>>> (16 HT), 64gb RAM, and 2 SSDs. The network is 10gbit. I have a separate
>>>> machine acting as namenode, HMaster, and zookeeper (single instance). I
>>>> have disk local reads turned on.
>>>> I'm seeing around 5 gbit/sec on average network IO. Each disk is getting
>>>> 400mb/sec read IO. Theoretically I could get 400mb/sec * 16 = 6.4gb/sec.
>>>> Using Hadoop's TestDFSIO tool, I'm seeing around 1.4gb/sec read speed. Not
>>>> really that great compared to the theoretical I/O. However this is far
>>>> better than I am seeing with HBase map-reduce scans of my table.
>>>> I have a simple no-op map-only job (using TableInputFormat) that scans the
>>>> table and does nothing with data. This takes 45 minutes. That's about
>>>> 260mb/sec read speed. This is over 5x slower than straight HDFS.
>>>> Basically, with HBase I'm seeing read performance of my 16 SSD cluster
>>>> performing nearly 35% slower than a single SSD.
>>>> Here are some things I have changed to no avail:
>>>> Scan caching values
>>>> HDFS block sizes
>>>> HBase block sizes
>>>> Region file sizes
>>>> Memory settings
>>>> GC settings
>>>> Number of mappers/node
>>>> Compressed vs not compressed
>>>> One thing I notice is that the regionserver is using quite a bit of CPU
>>>> during the map reduce job. When dumping the jstack of the process, it seems
>>>> like it is usually in some type of memory allocation or decompression
>>>> routine which didn't seem abnormal.
>>>> I can't seem to pinpoint the bottleneck. CPU use by the regionserver is
>>>> high but not maxed out. Disk I/O and network I/O are low, IO wait is low.
>>>> I'm on the verge of just writing the dataset out to sequence files once a
>>>> day for scan purposes. Is that what others are doing?

View raw message