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Displaying posts with tag: tokumxse (reset)
InnoDB vs TokuDB in LinkBench benchmark

Previously I tested Tokutek’s Fractal Trees (TokuMX & TokuMXse) as MongoDB storage engines – today let’s look into the MySQL area.

I am going to use modified LinkBench in a heavy IO-load.

I compared InnoDB without compression, InnoDB with 8k compression, TokuDB with quicklz compression.
Uncompressed datasize is 115GiB, and cachesize is 12GiB for InnoDB and 8GiB + 4GiB OS cache for TokuDB.

Important to note is that I used tokudb_fanout=128, which is only available in our latest Percona Server release.
I …

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Percona Acquires Tokutek : My Thoughts #2 : TokuMX and TokuMXse

A few days ago I wrote up my thoughts about the Percona acquisition of Tokutek with respect to TokuDB. In this blog I'm going to do the same for TokuMX and TokuMXse. And in a few days I'll wrap up this trilogy by sharing my thoughts about Fractal Tree Indexes.

Again, when I'm writing up something that I was very involved with in the past I think it's important to disclose that I worked at Tokutek for 3.5 years (08/2011 - 01/2015) as VP/Engineering and I do not have any equity in Tokutek or Percona.

Since much of the MySQL crowd might be hearing about Tokutek's "other products" for the first time I'll provide a little history of both of the products before I dive in deeper.

TokuMX is a fork of MongoDB …

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How to benchmark MongoDB

There are generally three components to any benchmark project:

  1. Create the benchmark application
  2. Execute it
  3. Publish your results

I assume many people think they want to run more benchmarks but give up since step 2 is extremely consuming as you expand the number of different configurations/scenarios.

I'm hoping that this blog post will encourage more people to dive-in and participate, as I'll be sharing the bash script I used to test the various compression options coming in the MongoDB 3.0 storage engines. It enabled me to run a few different tests against 8 different configurations, recording insertion speed and size-on-disk for each one.

If you're into this sort of thing, please read on and provide any feedback or improvements you can think of. …

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MongoDB Storage Engine Shootout : Round 1 : Indexed Insertion

The next release of MongoDB includes the ability to select a storage engine, the goal being that different storage engines will have different capabilities/advantages, and user's can select the one most beneficial to their particular use-case. Storage engines are cool. MySQL has offered them for quite a while. One very big difference between the MySQL and MongoDB implementations is that in MySQL the user gets to select a particular storage engine for each table, whereas in MongoDB it's a choice made at server startup. You get a single storage engine for everything on the particular mongod instance. I see pros and cons to each decision, but that's a blog for another day.

In MongoDB 3.0

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Diving deeper into MongoDB 2.8 collection level locking performance

Last month I wrote a blog about the closing of MongoDB ticket SERVER-1240, which brings Collection Level Locking (CLL) to the MMAPV1 storage engine in MongoDB 2.8. In MongoDB 2.6 there is a writer lock at the database level, so each database only allows one writer at a time. In concurrent write workloads, this means that all writers essentially form a single line and do their writes one at a time. In MongoDB 2.8 this lock has been moved to the collection level. Better yet is document level locking, but even though this feature was shown at MongoDB World 2014 it's not going to ship. But it did make for one amazing demo by …

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Showing entries 1 to 5