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Displaying posts with tag: LSM (reset)

Why Percona Acquired Tokutek: by Peter Zaitsev
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It is my pleasure to announce that Percona has acquired Tokutek and will take over development and support for TokuDB® and TokuMX™ as well as the revolutionary Fractal Tree® indexing technology that enables those products to deliver improved performance, reliability and compression for modern Big Data applications.

At Percona we have been working with the Tokutek team since 2009, helping to improve performance and scalability. The TokuDB storage engine has been available for Percona Server for about a year, so joining forces is quite a natural step for us.

Fractal Tree indexing technology—developed by years of data science research at …

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XLDB Tutorial on Data Structures and Algorithms
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Next week Michael and I (Bradley) will be travelling to Silicon Valley to present a tutorial on Data Structures and Algorithms for Big Databases at the 6th XLDB Conference.

The tutorial, which is 4 hours on Monday afternoon, aims to cover the following topics (but it’s looking like we’ll have to drop several items for lack of time.)

This tutorial will explore data structures and algorithms for big databases. The topics include:

  • Data structures …
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Write Optimization: Myths, Comparison, Clarifications, Part 2
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In my last post, we talked about the read/write tradeoff of indexing data structures, and some ways that people augment B-trees in order to get better write performance. We also talked about the significant drawbacks of each method, and I promised to show some more fundamental approaches.

We had two “workload-based” techniques: inserting in sequential order, and using fewer indexes, and two “data structure-based” techniques: a write buffer, and OLAP. Remember, the most common thing people do when faced with an …

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Write Optimization: Myths, Comparison, Clarifications
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Some indexing structures are write optimized in that they are better than B-trees at ingesting data. Other indexing structures are read optimized in that they are better than B-trees at query time. Even within B-trees, there is a tradeoff between write performance and read performance. For example, non-clustering B-trees (such as MyISAM) are typically faster at indexing than clustering B-trees (such as InnoDB), but are then slower at queries.

This post is the first of two about how to understand write optimization, what it means for overall performance, and what the difference is between different …

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Showing entries 1 to 4

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