On Thu, Jun 30, 2016 at 5:39 PM, Benjamin Kim <bbuil...@gmail.com> wrote:
> Hi Todd, > > I changed the key to be what you suggested, and I can’t tell the > difference since it was already fast. But, I did get more numbers. > Yea, you won't see a substantial difference until you're inserting billions of rows, etc, and the keys and/or bloom filters no longer fit in cache. > > > 104M rows in Kudu table > - read: 8s > - count: 16s > - aggregate: 9s > > The time to read took much longer from 0.2s to 8s, counts were the same > 16s, and aggregate queries look longer from 6s to 9s. > > I’m still impressed. > We aim to please ;-) If you have any interest in writing up these experiments as a blog post, would be cool to post them for others to learn from. -Todd > On Jun 15, 2016, at 12:47 AM, Todd Lipcon <t...@cloudera.com> wrote: > > Hi Benjamin, > > What workload are you using for benchmarks? Using spark or something more > custom? rdd or data frame or SQL, etc? Maybe you can share the schema and > some queries > > Todd > > Todd > On Jun 15, 2016 8:10 AM, "Benjamin Kim" <bbuil...@gmail.com> wrote: > >> Hi Todd, >> >> Now that Kudu 0.9.0 is out. I have done some tests. Already, I am >> impressed. Compared to HBase, read and write performance are better. Write >> performance has the greatest improvement (> 4x), while read is > 1.5x. >> Albeit, these are only preliminary tests. Do you know of a way to really do >> some conclusive tests? I want to see if I can match your results on my 50 >> node cluster. >> >> Thanks, >> Ben >> >> On May 30, 2016, at 10:33 AM, Todd Lipcon <t...@cloudera.com> wrote: >> >> On Sat, May 28, 2016 at 7:12 AM, Benjamin Kim <bbuil...@gmail.com> wrote: >> >>> Todd, >>> >>> It sounds like Kudu can possibly top or match those numbers put out by >>> Aerospike. Do you have any performance statistics published or any >>> instructions as to measure them myself as good way to test? In addition, >>> this will be a test using Spark, so should I wait for Kudu version 0.9.0 >>> where support will be built in? >>> >> >> We don't have a lot of benchmarks published yet, especially on the write >> side. I've found that thorough cross-system benchmarks are very difficult >> to do fairly and accurately, and often times users end up misguided if they >> pay too much attention to them :) So, given a finite number of developers >> working on Kudu, I think we've tended to spend more time on the project >> itself and less time focusing on "competition". I'm sure there are use >> cases where Kudu will beat out Aerospike, and probably use cases where >> Aerospike will beat Kudu as well. >> >> From my perspective, it would be great if you can share some details of >> your workload, especially if there are some areas you're finding Kudu >> lacking. Maybe we can spot some easy code changes we could make to improve >> performance, or suggest a tuning variable you could change. >> >> -Todd >> >> >>> On May 27, 2016, at 9:19 PM, Todd Lipcon <t...@cloudera.com> wrote: >>> >>> On Fri, May 27, 2016 at 8:20 PM, Benjamin Kim <bbuil...@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 3.8.2.3, 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 <mpe...@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 <bbuil...@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 >>> >>> >>> >> >> >> -- >> Todd Lipcon >> Software Engineer, Cloudera >> >> >> > -- Todd Lipcon Software Engineer, Cloudera
