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From stack <st...@duboce.net>
Subject Re: comparing hbase backed by HDFS verses S3
Date Thu, 01 May 2008 17:32:09 GMT
Thanks for trying this "interesting" experiment Clint.  I'm a little 
surprised the thing worked at all (smile).

What do you need for HBASE-50?  Is it sufficient forcing the cluster to 
go read-only flushing all in memory while the copy runs?

CopyFiles/distcp should be able to go between filesystems, running the 
copy in an MR job which is probably what you want.  You could go hdfs:// 
to s3://.  Upside would be that all of the s3 vagaries would be managed 
for you (size limits, etc.).  Downside would be that you'd have to put 
up an s3 dfs as copy sink.   Alternatively, maybe you can convince 
distcp to go between hdfs:// and http://?  Hbase files should never 
really be bigger than a 1G or so, so it should be 'safe'.

St.Ack

Clint Morgan wrote:
> Thanks for the input as it confirmed my suspicions.
>
> We were debating running off of S3 just to minimize moving parts. But
> it does not look feasible.
>
> We are wanting the cluster to "live forever" in that once the app is
> live, hbase will always be needed to serve data.
>
> A primary concern is data lose, so will probably still want to use S3
> as a backup medium. Moreover, we'd like to be able to quickly recover
> from HDFS failures to minimize downtime.This makes HBASE-50 look like
> the way to go.
>
> cheers,
> -clint
>
> On Wed, Apr 30, 2008 at 5:30 PM, Chris K Wensel <chris@wensel.net> wrote:
>   
>> Anything relating to S3 will be slower thus it probably shouldn't be used as
>> the default FileSystem for Hadoop.
>>
>>  It works great if you need to park data between cluster runs, assuming you
>> do not need external (from Hadoop and the cluster) applications to be able
>> to read the data, as data in S3FS are stuffed into S3 as blocks (similar to
>> HDFS).
>>
>>  Further,  once support for appends is added to Hadoop/HDFS, I am unsure if
>> it will be inherited by S3FS. I think this is a critical issue for HBase.
>>
>>  Assuming your aren't expecting this cluster to live forever, maybe you
>> should keep your authoritative data on s3 (native or s3fs) and just reload
>> HBase on cluster init?
>>
>>  ckw
>>
>>  Chris K Wensel
>>  chris@wensel.net
>>  http://chris.wensel.net/
>>  http://www.cascading.org/
>>
>>
>>
>>  On Apr 30, 2008, at 1:02 PM, Clint Morgan wrote:
>>
>>
>>     
>>> We are considering using S3 as the DFS impl for hbase. I ran some
>>> benchmarks to get an idea for the performance differences. We are
>>> particularly interested in being able to serve data to users from
>>> hbase, so want low latency responses for getting 10s of rows.
>>>
>>> Each row ("transaction") has about 1K worth of data in about 5 columns
>>> in two families. I'm using HBASE-605 to maintain a secondary index on
>>> the transaction amount. There is also a "relation" to a customer
>>> table, so some reads will also do a get from this other table.
>>>
>>> First ran hbase backed by hdfs. Everything was run on EC2 small nodes.
>>> 1 node for Name node, 1 node for Data
>>> node, 1 node with Master and Region server, 1 node to load/read data
>>> from.
>>>
>>> Adding 50K transactions: [56610.166]ms
>>> Find all transactions: [35388.601]ms
>>> FindAll page 1: [125.058]ms (PageSize is 10)
>>> FindAll page 11: [71.89]ms
>>> FindAll page 51: [145.54]ms
>>> FindAll page 61: [268.486]ms
>>>
>>> FindAll sorted page 1: [139.881]ms
>>> FindAll sorted page 11: [1521.655]ms
>>> FindAll sorted page 21: [2729.641]ms
>>> FindAll sorted page 31: [3035.18]ms
>>>
>>> Then I ran hbase backed by s3. Everything else the same
>>>
>>> Adding 50K transaction: [104826.437]ms
>>> Findall transaction: [51622.039]ms
>>> Findall page 1: [5694.974]ms
>>> Findall page 11: [4878.234]ms
>>> Findall page 51: [5743.882]ms
>>> Findall page 61: [4167.133]ms
>>>
>>> Findall sorted page 1: [18535.306]ms
>>> Then the other sorted finds timed out on the RPC call.
>>>
>>> So to summarize:
>>> loading data: almost twice as slow
>>> A long scan is about 1.5 times slower
>>> short scans are over an order of magnitude slower
>>> and random reads (done on the sorted "scan") are over 2 orders of
>>> magnitude slower
>>>
>>> Do these results sound reasonable? Is S3 really that costly compared
>>> to HDFS? Thanks for your input.
>>> -clint
>>>
>>>       
>>
>>
>>
>>
>>     


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