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From Pablo Vazquez <pablo.vazq...@globant.com>
Subject Re: Performance Question
Date Sat, 28 May 2016 04:49:18 GMT
Hi Todd.

In order to reach that performance ( +1M /sec) did you change any Kudu
parameters? I read some papers about flush parameters in tablet servers.

I started playing with Kudu with just 2 nodes and my best was 30k per
second with 30 columns row. Nothing compared with your testing but any
advice would be great.

Thank all you guys for sharing your thoughts.
El 27 may. 2016 23:19, "Todd Lipcon" <todd@cloudera.com> escribió:

> On Fri, May 27, 2016 at 8:20 PM, Benjamin Kim <bbuild11@gmail.com> wrote:
>> Hi Mike,
>> First of all, thanks for the link. It looks like an interesting read. I
>> checked that Aerospike is currently at version, and in the article,
>> they are evaluating version 3.5.4. The main thing that impressed me was
>> their claim that they can beat Cassandra and HBase by 8x for writing and
>> 25x for reading. Their big claim to fame is that Aerospike can write 1M
>> records per second with only 50 nodes. I wanted to see if this is real.
> 1M records per second on 50 nodes is pretty doable by Kudu as well,
> depending on the size of your records and the insertion order. I've been
> playing with a ~70 node cluster recently and seen 1M+ writes/second
> sustained, and bursting above 4M. These are 1KB rows with 11 columns, and
> with pretty old HDD-only nodes. I think newer flash-based nodes could do
> better.
>> To answer your questions, we have a DMP with user profiles with many
>> attributes. We create segmentation information off of these attributes to
>> classify them. Then, we can target advertising appropriately for our sales
>> department. Much of the data processing is for applying models on all or if
>> not most of every profile’s attributes to find similarities (nearest
>> neighbor/clustering) over a large number of rows when batch processing or a
>> small subset of rows for quick online scoring. So, our use case is a
>> typical advanced analytics scenario. We have tried HBase, but it doesn’t
>> work well for these types of analytics.
>> I read, that Aerospike in the release notes, they did do many
>> improvements for batch and scan operations.
>> I wonder what your thoughts are for using Kudu for this.
> Sounds like a good Kudu use case to me. I've heard great things about
> Aerospike for the low latency random access portion, but I've also heard
> that it's _very_ expensive, and not particularly suited to the columnar
> scan workload. Lastly, I think the Apache license of Kudu is much more
> appealing than the AGPL3 used by Aerospike. But, that's not really a direct
> answer to the performance question :)
>> Thanks,
>> Ben
>> On May 27, 2016, at 6:21 PM, Mike Percy <mpercy@cloudera.com> wrote:
>> Have you considered whether you have a scan heavy or a random access
>> heavy workload? Have you considered whether you always access / update a
>> whole row vs only a partial row? Kudu is a column store so has some
>> awesome performance characteristics when you are doing a lot of scanning of
>> just a couple of columns.
>> I don't know the answer to your question but if your concern is
>> performance then I would be interested in seeing comparisons from a perf
>> perspective on certain workloads.
>> Finally, a year ago Aerospike did quite poorly in a Jepsen test:
>> https://aphyr.com/posts/324-jepsen-aerospike
>> I wonder if they have addressed any of those issues.
>> Mike
>> On Friday, May 27, 2016, Benjamin Kim <bbuild11@gmail.com> wrote:
>>> I am just curious. How will Kudu compare with Aerospike (
>>> http://www.aerospike.com)? I went to a Spark Roadshow and found out
>>> about this piece of software. It appears to fit our use case perfectly
>>> since we are an ad-tech company trying to leverage our user profiles data.
>>> Plus, it already has a Spark connector and has a SQL-like client. The
>>> tables can be accessed using Spark SQL DataFrames and, also, made into SQL
>>> tables for direct use with Spark SQL ODBC/JDBC Thriftserver. I see from the
>>> work done here http://gerrit.cloudera.org:8080/#/c/2992/ that the Spark
>>> integration is well underway and, from the looks of it lately, almost
>>> complete. I would prefer to use Kudu since we are already a Cloudera shop,
>>> and Kudu is easy to deploy and configure using Cloudera Manager. I also
>>> hope that some of Aerospike’s speed optimization techniques can make it
>>> into Kudu in the future, if they have not been already thought of or
>>> included.
>>> Just some thoughts…
>>> Cheers,
>>> Ben
>> --
>> --
>> Mike Percy
>> Software Engineer, Cloudera
> --
> Todd Lipcon
> Software Engineer, Cloudera


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