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From Keith Turner <>
Subject Re: Feedback about techniques for tuning batch scanning for my problem
Date Mon, 23 May 2016 15:16:25 GMT

You could experiment with adjusting table.file.compress.blocksize[1] and
table.file.compress.blocksize.index[2].  Making the data block size smaller
will increase the files index size and may lower random seek times
depending on how much of the index fits in memory.  Adjusting the index
block size will control the depth of the index tree.   You can adjust these
settings, compact, and run "accumulo rfile-info" on a file to see
information about the index size, depth, and number of data blocks.  You
can also adjust the index[6] and data[5] cache size settings and turn
data[3] and index[4] caching on or off for your table.



On Thu, May 19, 2016 at 11:08 AM, Mario Pastorelli <> wrote:

> Hey people,
> I'm trying to tune a bit the query performance to see how fast it can go
> and I thought it would be great to have comments from the community. The
> problem that I'm trying to solve in Accumulo is the following: we want to
> store the entities that have been in a certain location in a certain day.
> The location is a Long and the entity id is a Long. I want to be able to
> scan ~1M of rows in few seconds, possibly less than one. Right now, I'm
> doing the following things:
>    1. I'm using a sharding byte at the start of the rowId to keep the
>    data in the same range distributed in the cluster
>    2. all the records are encoded, one single record is composed by
>       1. rowId: 1 shard byte + 3 bytes for the day
>       2. column family: 8 byte for the long corresponding to the hash of
>       the location
>       3. column qualifier: 8 byte corresponding to the identifier of the
>       entity
>       4. value: 2 bytes for some additional information
>    3. I use a batch scanner because I don't need sorting and it's faster
> As expected, it takes few seconds to scan 1M rows but now I'm wondering if
> I can improve it. My ideas are the following:
>    1. set table.compaction.major.ration to 1 because I don't care about
>    the ingestion performance and this should improve the query performance
>    2. pre-split tables to match the number of servers and then use a byte
>    of shard as first byte of the rowId. This should improve both writing and
>    reading the data because both should work in parallel for what I understood
>    3. enable bloom filter on the table
> Do you think those ideas make sense? Furthermore, I have two questions:
>    1. considering that a single entry is only 22 bytes but I'm going to
>    scan ~1M records per query, do you think I should change the BatchScanner
>    buffers somehow?
>    2. anything else to improve the scan speed? Again, I don't care about
>    the ingestion time
> Thanks for the help!
> --
> Mario Pastorelli | TERALYTICS
> *software engineer*
> Teralytics AG | Zollstrasse 62 | 8005 Zurich | Switzerland
> phone: +41794381682
> email:
> Company registration number: CH- | Trade register Canton
> Zurich
> Board of directors: Georg Polzer, Luciano Franceschina, Mark Schmitz, Yann
> de Vries
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