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Showing entries 1 to 7

Displaying posts with tag: fulltext search (reset)

InnoDB Full-text Search in MySQL 5.6: Part 3, Performance
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This is part 3 of a 3 part series covering the new InnoDB full-text search features in MySQL 5.6. To catch up on the previous parts, see part 1 or part 2

Some of you may recall a few months ago that I promised a third part in my InnoDB full-text search (FTS) series, in which I’d actually take a look at the performance of InnoDB FTS in MySQL 5.6 versus traditional MyISAM FTS. I hadn’t planned on quite such a gap between part 2 and part 3, but as they say, better late than never. Recall that we have been working with two data sets, one which I call SEO (8000-keyword-stuffed web pages) and the other which I call

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InnoDB Full-text Search in MySQL 5.6: Part 2, The Queries!
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InnoDB Full-text Search in MySQL 5.6: Part 2, The Queries!

This is part 2 in a 3 part series. In part 1, we took a quick look at some initial configuration of InnoDB full-text search and discovered a little bit of quirky behavior; here, we are going to run some queries and compare the result sets. Our hope is that the one of two things will happen; either the results returned from a MyISAM FTS query will be exactly identical to the same query when performed against InnoDB data, OR that the results returned by InnoDB FTS will somehow be

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InnoDB Full-text Search in MySQL 5.6 (part 1)
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I’ve never been a very big fan of MyISAM; I would argue that in most situations, any possible advantages to using MyISAM are far outweighed by the potential disadvantages and the strengths of InnoDB. However, up until MySQL 5.6, MyISAM was the only storage engine with support for full-text search (FTS). And I’ve encountered many customers for whom the prudent move would be a migration to InnoDB, but due to their use of MyISAM FTS, the idea of a complete or partial migration was, for one reason or another, an impractical solution. So, when FTS for InnoDB was first announced, I thought this might end up being the magic bullet that would help these sorts of customers realize all of the benefits that have been engineered into InnoDB over the past few years and still keep their FTS capability without having to make any significant code

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Sphinx search performance optimization: multi-threaded search
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Queries in MySQL, Sphinx and many other database or search engines are typically single-threaded. That is when you issue a single query on your brand new r910 with 32 CPU cores and 16 disks, the maximum that is going to be used to process this query at any given point is 1 CPU core and 1 disk. In fact, only one or the other.

Seriously, if query is CPU intensive, it is only going to be using 3% of the available CPU capacity (for the same 32-core machine). If disk IO intensive – 6% of the available IO capacity (for the 16-disk RAID10 or RAID0 for that matter).

Let me put it another way. If your MySQL or Sphinx query takes 10s to run on a machine with a single CPU core and single disk, putting it on a machine with 32 such cores and 16 such disks will not make it any better.

But you knew this already. Question is



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Sphinx search performance optimization: attribute-based filters
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One of the most common causes of a poor Sphinx search performance I find our customers face is misuse of search filters. In this article I will cover how Sphinx attributes (which are normally used for filtering) work, when they are a good idea to use and what to do when they are not, but you still want to take advantage of otherwise superb Sphinx performance.

The Problem

While Sphinx is great for full text search, you can certainly go beyond full text search, but before you go there, it is a good idea to make sure you’re doing it the right way.

In Sphinx, columns are basically one of two kinds:

a) full text
b)


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Webinar for Full Text Search Throwdown
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Tomorrow, August 22 at 10:00am PDT, I’ll present a webinar called Full Text Search Throwdown.  This is a no-nonsense performance comparison of solutions for full text indexing for MySQL applications, including:

  • LIKE predicates and regular expressions
  • MyISAM FULLTEXT indexes
  • InnoDB FULLTEXT indexes
  • Apache Solr
  • Sphinx Search
  • Trigraphs

I’ll compare the performance for building indexes and querying indexes.

If you’re developing an application with text search features, this will be a very practical and informative overview of your technology options!

Register for this free webinar at http://www.percona.com/webinars/2012-08-22-full-text-search-throwdown

MySQL: How do you enable sphinxse (Sphinx Storage Engine) in your mysql installation?
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As you may know mysql fulltext search is not highly scalable.  One of the options to get around this scalability limitation, which I prefer, is to use Sphinx.  You can use Sphinx with out having to alter your mysql installation.  But, if you would like to use from within mysql and not have to worry about how to pass data between Sphinx and MySQL, you can enable sphinxse (sphinx storage engine).  It is not included with mysql by default so you will have to compile it yourself.

Here are the instructions on how to get sphinxse compiled with your mysql installation on CentOS x64.  I am sure same instructions will work for other flavors but I have not tested it.  I will be compiling the most current version of sphinx (0.9.8) with most current stable version of mysql (5.0.51b) at the time of the writing.  Let’s get the

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Showing entries 1 to 7

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