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Displaying posts with tag: B-Tree (reset)
Top Ten for 2011


It’s almost the end of the year – that means holiday cards, shopping, cooking, parties, and the inevitable year-end top lists (including gems like this one).

In the spirit of end of year list making, we fed our 60+ blogs this year through Google Analytics to find out what our own top ten blogs were (outside of product announcements). So if you missed an episode of the View (TokuView that is) we’ve got a Tokutek Top Ten for you (spoiler alert – they are mostly technical):

10. Cage Match: OldSQL, NoSQL and NewSQL – References to mud …

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Slides of my talk on B+Tree Indexes and InnoDB

The slides of my talk on B+Tree Indexes and InnoDB are now available for download. This slide was presented during Percona Live London 2011. You can download the slides from here.
There are many other interesting and informative talks that were presented during Percona Live London 2011, and I think you should definitely check them out, if you haven't. They are available here.

The post Slides of my talk on B+Tree Indexes and InnoDB appeared first on ovais.tariq.

Fractal Tree Indexes – MySQL Meetup

At next month’s Boston MySQL Meetup, I will give a talk: “Fractal Tree Indexes – Theoretical Overview and Customer Use Cases.” The meetup is 7 pm Monday, January 9th, 2012, and will be held at MIT Building E51 Room 337e (corner of Ames & Amherst St, Cambridge, MA). Thanks to host Sheeri Cabral for the invitation.

Most databases employ B-trees to achieve a good tradeoff between the ability to update data quickly and to search it quickly. It turns out that B-trees are far from the optimum in this tradeoff …

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It Actually is Easy Being Green

(Fractal) Tree Frog

Fractal Tree™ indexes are green. They have the potential to be greener still. Here’s why:

Remarkably, data centers consume 1-3 percent of all the US electricity. A majority of this power is used to drive servers and storage systems. Significant energy savings remain on the table.

Here’s why Fractal Tree indexing enables more energy-efficient storage: Data centers typically use many small-capacity disks rather than a few large-capacity disks. Why? One reason is to harness more spindles to obtain more I/Os per second. In some high-performance applications, users go so far as to employ techniques such as “ …

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Indexing: The Director’s Cut

Thanks again to Erin O’Neill and Mike Tougeron for having me at the SF MySQL Meetup last month for the talk on “Understanding Indexing.” The crowd was very interactive, and I appreciated that over 100 people signed up for the event and left some very positive comments and reviews.

Thanks to Mike, a video of the talk is now available:

As a brief overview – Application performance often depends on how fast a query can respond and query performance almost always depends on good indexing. So one of the quickest and least expensive ways to increase application performance is to optimize the indexes. This talk presents three simple and effective rules on how to construct indexes around queries that …

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Don’t Thrash: How to Cache your Hash on Flash

Last week I gave a talk entitled “Don’t Thrash: How to Cache your Hash.” The talk took place at the Workshop on Algorithms and Data Structures (ADS) in a medieval castle turned conference center in Bertinoro, Italy. An earlier version of this work (with the same title) appeared at the HotStorage conference in Portland, OR. Tokutek co-founders Bradley, Martin, and I are coauthors on the work, along with students and other faculty at Stony Brook University.

The talk title is colorful and doggerel-y. Here’s what the title means. “Cache your hash”—the so-called Bloom Filter type data structure. A Bloom filter acts like a negative cache, …

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Percona Live, NYC

Yesterday, Percona held Percona Live NYC, which they describe as an “intensive one-day MySQL summit.” They meant it. It was like drinking from a firehose. There was too much for me to give a complete report, so I’d like to highlight two sessions that stuck out for me.

Why SQL Wins

Sergei Tsarev (Clustrix) gave a great overview of the last 50 years of database development. He talked about the early days, in which what we now think of as database functionality had to be implemented in each application. Programmer productivity was therefore low.

As modern SQL databases emerged, productivity shot up since databases bundled up common functionality with an easy-to-code interface. This now seems like a golden age of databases, in which transactional semantics were hashed out.

Fast forward to today. Database performance has failed to keep up with …

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OldSQL Tricks or NewSQL Treats

Why do B-trees need “Tricks” to work?

Marko Mäkelä recently posted a couple of “tips and tricks” you can use to improve InnoDB performance. Tips and tricks. A general purpose relational database like MySQL shouldn’t need “tips and tricks” to perform well, and I lay the blame on design choices that were made in the early ’70s: the B-tree data structure underlying all OldSQL databases. B-trees were designed for machines that had very different performance characteristics than the machines of today. Hardware has changed, but B-trees are the same. Tips and Tricks are an attempt to make up the difference.

So B-tree implementers — InnoDB, Oracle, MS SQL Server — are fighting an uphill battle; they’re fighting the future. B-trees just aren’t meant to cope with high-bandwidth, slow-seek-time storage systems, because …

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Understanding InnoDB clustered indexes

Some people don't probably know, but there is a difference between how indexes work in MyISAM and how they work in InnoDB, particularly when talking from the point of view of performance enhancement. Now since, InnoDB is starting to be widely used, it is important we understand how indexing works in InnoDB. Hence, the reason for this post!

On “Replace Into”, “Insert Ignore”, Triggers, and Row Based Replication

In posts on June 30 and July 6, I explained how implementing the commands “replace into” and “insert ignore” with TokuDB’s fractal trees data structures can be two orders of magnitude faster than implementing them with B-trees. Towards the end of each post, I hinted at that there are some caveats that complicate the story a little. On July 21st I explained one caveat, secondary keys, and on August 3rd, Rich explained another caveat. In this post, I explain the other …

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