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From Josh Elser <josh.el...@gmail.com>
Subject Re: WAL - rate limiting factor x4.67
Date Wed, 04 Dec 2013 16:05:31 GMT
Peter --

I don't know if this was made entirely clear.

The reason that things are much slower when you have the WAL turned on 
is that you're suddenly writing N extra copies of your data to disk. 
When you don't have the WAL turned on, you're simply writing to 
Accumulo's in-memory data structures which are fast.

Keith's suggestion would ammortize the number of times you write to 
disk. Adam's suggestion will, like he said, reduce the number of copies 
you write to disk. There is no configuration that you can make that will 
make writing data with WALs as fast as writing without the WAL in normal 
situations. Writing one copy to memory will likely always be faster than 
writing to memory and writing multiple copies to disk.

- Josh

On 12/4/13, 10:53 AM, Peter Tillotson wrote:
> Keith
>
> I tried tserver.mutation.queue.max=4M and it improved but by no where
> near a significant difference. I my app records get turned into multiple
> Accumulo rows.
>
> So in terms of my record write rate.
>
> wal=true  & mutation.queue.max = 256K    |   ~8K records/s
> wal=true & mutation.queue.max = 4M        |   ~14K records/s
> wal=false                                                 |  ~25K records/s
>
> Adam,
>
> Its one box so replication is off, good thought tnx.
>
> BTW - I've been plying around with ZFS compression vs Accumulo Snappy.
> What I've found was quite interesting. The idea was that with ZFS dedup
> and being in charge of compression I'd get a boost later on when blocks
> merge. What I've found is that after a while with ZFS LZ4 the CPU and
> disk all tail off, as though timeouts are elapsing somewhere whereas
> SNAPPY maintains an average ~20k+.
>
> Anyway tnx and if I get a chance I may the 1.7 branch for the fix.
>
>
> On Wednesday, 4 December 2013, 14:56, Adam Fuchs <afuchs@apache.org> wrote:
> One thing you can do is reduce the replication factor for the WAL. We
> have found that makes a pretty significant different in write
> performance. That can be modified with the tserver.wal.replication
> property. Setting it to 2 instead of the default (probably 3) should
> give you some performance improvement, of course at some cost to
> durability.
>
> Adam
>
>
> On Wed, Dec 4, 2013 at 5:14 AM, Peter Tillotson <slatemine@yahoo.co.uk
> <mailto:slatemine@yahoo.co.uk>> wrote:
>
>     I've been trying to get the most out of streaming data into Accumulo
>     1.5 (Hadoop Cloudera CDH4). Having tried a number of settings,
>     re-writing client code etc I finally switched off the Write Ahead
>     Log (table.walog.enabled=false) and saw a huge leap in ingest
>     performance.
>
>     Ingest with table.walog.enabled= true:   ~6 MB/s
>     Ingest with table.walog.enabled= false:  ~28 MB/s
>
>     That is a factor of about x4.67 speed improvement.
>
>     Now my use case could probably live without or work around not
>     having a wal, but I wondered if this was a known issue??
>     (didn't see anything in jira), wal seem to be a significant rate
>     limiter this is either endemic to Accumulo or an HDFS / setup issue.
>     Though given everything is in HDFS these days and otherwise IO flies
>     it looks like Accumulo WAL is the most likely culprit.
>
>     I don't believe this to be an IO issue on the box, with wal off the
>     is significantly more IO (up to 80M/s reported by dstat), with wal
>     on (up to 12M/s reported by dstat). Testing the box with FIO
>     sequential write is 160M/s.
>
>     Further info:
>     Hadoop 2.00 (Cloudera cdh4)
>     Accumulo (1.5.0)
>     Zookeeper ( with Netty, minor improvement of <1MB/s  )
>     Filesystem ( HDFS is ZFS, compression=on, dedup=on, otherwise ext4 )
>
>     With large imports from scratch now I start off CPU bound and as
>     more shuffling is needed this becomes Disk bound later in the import
>     as expected. So I know pre-splitting would probably sort it.
>
>     Tnx
>
>     P
>
>
>
>

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