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Showing entries 1 to 10 of 280 Next 10 Older Entries

Displaying posts with tag: TokuView (reset)

An Updated Description of Clustering Keys for TokuDB
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Covering indexes can result in orders of magnitude performance improvements for queries. Bradley’s presentation on covering indexes describes what a covering index is, how it can effect performance, and why it works. However, the definition of a covering index can get cumbersome since MySQL limits the number of columns in a key to 16 (32 on MariaDB).

Tokutek introduced multiple clustering indexes into MySQL to address these problems. Zardosht describes the multiple clustering indexes feature and how clustering indexes differ from covering indexes. Zardosht

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Best Practices for Partitioned Collections and Tables in TokuDB and TokuMX
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In my last post, I gave a technical explanation of the performance characteristics of partitioned collections in TokuMX 1.5 (which is right around the corner) and partitioned tables in relational databases. Given those performance characteristics, in this post, I will present some best practices when using this feature in TokuMX or TokuDB. Note that these best practices are designed for TokuMX and TokuDB only, which

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Understanding the Performance Characteristics of Partitioned Collections
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In TokuMX 1.5 that is right around the corner, the big feature will be partitioned collections. This feature is similar to partitioned tables in Oracle, MySQL, SQL Server, and Postgres. A question many have is “why should I use partitioned tables?” In short, it’s complicated. The answer depends on your workload, your schema, and your database of choice. For example, this Oracle related post states “Anyone with un-partitioned databases over 500 gigabytes is courting disaster.” That’s not true for TokuDB or TokuMX. Nevertheless,

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Thoughts on Small Datum – Part 3
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Background: If you did not read my first blog post about why I am sharing my thoughts on the benchmarks published by Mark Callaghan on Small Datum you may want to skim through it now for a little context: Thoughts on Small Datum – Part 1”

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Last time, in Thoughts on Small Datum – Part 2 I shared my cliff notes and a graph on Mark Callaghan’s (@markcallaghan) March 11th insertion rate benchmarks using flash storage media. In those tests he compares MySQL (http://www.mysql.com/) outfitted with the

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Maybe You Should Try Taking a Walk in My Shoes
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The title of this post should really be, “Maybe He Should Try Taking a Walk in Your Shoes.”

The he I’m referring to is economist and author, Tim Harford. The you is the people who use NewSQL and NoSQL approaches to mine big data with database platforms like MySQL (http://www.mysql.com" target="_blank) and MongoDB (or, preferably, our high-performance distributions of them, TokuDB and TokuMX).

Why should Mr. Harford take that walk? Well, he recently

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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) outfitted with the InnoDB storage engine with two NoSQL alternatives — basic MongoDB and TokuMX (the Tokutek high-performance

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Percona Live 2014 Impressions
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Three weeks ago I had the privilege of attending my first Percona Live MySQL conference, which was incredible! In particular, there were two things that I found impressive about the conference.

First, was the amount of knowledge sharing and support that MySQL users provide each other; it truly is a community. Coming from EMC, I’ve attended several conferences in the past, but I’ve always considered them more of a marketing focused event, mostly spent doing product launches and company roadmaps and not much time fostering knowledge sharing and informal get-togethers: Percona Live was different. There were well thought out tutorials, information packed presentations, and keynotes rife with practical knowledge culled from the real world. I had many great conversations at our booth with people that have evaluated TokuDB or TokuMX or were planning to as soon as they got back into

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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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How TokuMX Secondaries Work in Replication
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As I’ve mentioned in previous posts, TokuMX replication differs quite a bit from MongoDB’s replication. The differences are large enough such that we’ve completely redone some of MongoDB’s existing algorithms. One such area is how secondaries apply oplog data from a primary. In this post, I’ll explain how.

In designing how secondaries apply oplog data, we did not look closely at how MongoDB does it. In fact, I’ve currently forgotten all I’ve learned about MongoDB’s implementation, so I am not in a position to compare the two. I think I recall that MongoDB’s oplog idempotency was a key to their

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How Tokutek uses the Random Query Generator framework to test TokuDB
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During a typical release cycle for TokuDB at Tokutek, we spend time qualifying and hardening the product using numerous tools.  For example, we run stress and unit tests directly on the Fractal Tree indexes, MySQL Test Runner (MTR) tests on the storage engine as well as numerous performance benchmarks to prevent regressions. In addition, we have recently been implementing the Random Query Generator (RQG) framework internally here at Tokutek to more exhaustively stress TokuDB.  My name is Joel Epstein and I am a Quality Assurance Engineer here at Tokutek who has been integrating RQG into the overall test plan strategy.

At

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Showing entries 1 to 10 of 280 Next 10 Older Entries

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