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Displaying posts with tag: Benchmarking (reset)

Benchmarking Presentation at Percona Live London 2014
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In a few weeks I’m presenting “Performance Benchmarking: Tips, Tricks, and Lessons Learned” at Percona Live London 2014 (November 3-4). I continue to learn lessons and improve my benchmarking capabilities, so the content is a full upgrade from my presentation at Percona Live Santa Clara in April 2013. Anyone interested in achieving and sustaining the best performance out of their software/hardware/application should attend.

Also, Tokutek is sponsoring so we’ll be available in the expo hall throughout the

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TokuDB v7.5 Read Free Replication : The Benchmark
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New to TokuDB® v7.5 is a feature we’re calling “Read Free Replication” (RFR). RFR allows TokuDB replication slaves to process insert, update, and delete statements with almost no read IO. As a result, the slave can easily keep up with the master (no lag) as well as brings all the read IO capacity of the slave for read-scaling your workload.

The goal of this blog is two-fold: (1) to cover why RFR is important and how RFR works and (2) to run a simple before/after benchmark showing the impact of RFR on a well known workload. Later this week I’ll post another blog showing other interesting use-cases for RFR beyond this first benchmark.

Read Free Replication: The Why and How

In MySQL, a replication slave does less work than the master because there is no need for a slave to execute SELECT statements (only INSERT, UPDATE, and

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Sysbench Benchmarking of Tesora’s Database Virtualization Engine
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Tesora, previously called Parelastic, asked Percona to do a sysbench benchmark evaluation of its Database Virtualization Engine on specific architectures on Amazon EC2.

The focus of Tesora is to provide a scalable Database As A Service platform for OpenStack. The Database Virtualization Engine (DVE) plays a part in this as it aims at allowing databases to scale transparently across multiple MySQL shards.

DVE was open sourced last

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Thoughts on Small Datum – Part 2
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If you did not read my first blog post about Mark Callaghan’s (@markcallaghan) benchmarks as documented in his blog, Small Datum, you may want to skim through it now for a little context.

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On March 11th, Mark, a former Google and now Facebook database guru, published an insertion rate benchmark comparing MySQL (http://www.mysql.com" target="_blank) outfitted with the InnoDB storage engine with two NoSQL alternatives — basic MongoDB

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Thoughts on Small Datum – Part 1
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A little background…

When I ventured into sales and marketing (I’m an engineer by education) I learned I would often have to interpret and simply summarize the business value that is sometimes hidden in benchmarks. Simply put, the people who approve the purchase of products like TokuDB® and TokuMX™ appreciate the executive summary.

Therefore, I plan to publish a multipart series here on TokuView where I will share my simple summaries and thoughts on business value for the benchmarks Mark Callaghan (@markcallaghan), a former Google and now Facebook database guru, is publishing on his blog, Small Datum.

I’m going to start with his first benchmark post and work my way forward to

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Benchmarking the Cloud
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Benchmarking, and benchmarking the cloud, is incredibly error prone. I provided guidance though this minefield in the benchmarking chapter of my book (Systems Performance: Enterprise and the Cloud); that chapter can be read online on the InformIT site. I also gave a lightning talk about benchmarking gone wrong at Surge last year. In this post, I’m going to cut to the chase and show you the tools I commonly use for basic cloud benchmarking.

As explained in the benchmarking chapter, I do not run these tools passively. I perform Active Benchmarking, where I use a variety of other

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TokuMX vs. MongoDB : In-Memory Sysbench Performance
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In talking to existing MongoDB users and TokuMX evaluators, I’ve often heard that the performance of MongoDB is very good as long as your working data set fits in RAM. The story continues that if your working data set grows to be larger than the RAM on your server, the built-in sharding capabilities of MongoDB allow you to scale horizontally.

As my benchmarking presentation at Percona Live 2013 pointed out, I’m never one to accept something without at least running it once myself. I decided to run my

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iiBench Benchmark: TokuMX vs. MongoDB
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Tokutek created the iiBench benchmark back in 2008. The point of the benchmark is to measure the performance of indexed insertions over time. It uses an extremely simple schema, one table with a sequential insertion pattern for the primary key along with three integer fields storing random values. The table maintains 3 secondary indexes, each including several of the random integer fields. The iiBench application itself is currently maintained on Launchpad.

B-tree implementations generally require maintenance operations to update leaf nodes (an insertion is one such operation). When the entire B-tree index does not fit in RAM an IO is required, and performance drops dramatically. Fractal Tree

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Sysbench Benchmark for MongoDB – v0.1.0 Performance Update
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Two months ago I posted a performance comparison running Sysbench on MongoDB versus MongoDB with Fractal Tree Indexes v0.0.2. The benchmark showed a 133% improvement in throughput. Nice, but our engineering team had an effort on our road-map for lock refinement that we believed would really boost our performance, which is now available in v0.1.0. The benchmark application itself is unchanged and available on GitHub.

For anyone curious about Sysbench itself, the details are available from the prior blog. The only change for this run was hardware. Our Sun x4150 server recently began rebooting

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Slides from my Percona Live “Benchmarking” presentation
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I finally posted a copy of the slides from my Percona Live presentation, “Creating a Benchmarking Infrastructure that Just Works”.  The PDF is available via this link.

The content comes from my personal experiences over many years benchmarking and testing databases, usually focusing on performance.  It was an opportunity to see how far my personal benchmark infrastructure has evolved, but even better has inspired me to improve it in several areas.

I never had a chance to to my own post-conference wrap-up regarding the Percona Live show.  While waiting for my flight home at SFO airport I concluded that

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