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Showing entries 1 to 16

Displaying posts with tag: olap (reset)

MySQL webinar: ‘Introduction to open source column stores’
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Join me Wednesday, September 18 at 10 a.m. PDT for an hour-long webinar where I will introduce the basic concepts behind column store technology. The webinar’s title is: “Introduction to open source column stores.”

What will be discussed?

This webinar will talk about Infobright, LucidDB, MonetDB, Hadoop (Impala) and other column stores

  • I will compare features between major column stores (both open and closed source).
  • Some benchmarks will be used to demonstrate the basic
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Using Flexviews – part one, introduction to materialized views
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If you know me, then you probably have heard of Flexviews. If not, then it might not be familiar to you. I’m giving a talk on it at the MySQL 2011 CE, and I figured I should blog about it before then. For those unfamiliar, Flexviews enables you to create and maintain incrementally refreshable materialized views.

You might be asking yourself “what is an incrementally refreshable materialized view?”. If so, then keep reading. This is the first in a multi-part series describing Flexviews.

edit:
You can find part 2 of the series here:

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Intro to OLAP
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This is the first of a series of posts about business intelligence tools, particularly OLAP (or online analytical processing) tools using MySQL and other free open source software. OLAP tools are a part of the larger topic of business intelligence, a topic that has not had a lot of coverage on MPB. Because of this, I am going to start out talking about these topics in general, rather than getting right to gritty details of their performance.

I plan on covering the following topics:

  • Introduction to OLAP and business intelligence. (this post)
  • Identifying the differences between a data warehouse, and a data mart.
  • Introduction to MDX queries and the kind of SQL which a ROLAP tool must generate to answer those queries.
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    New OLAP Wikistat benchmark: Introduction and call for feedbacks
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    I've seen my posts on Ontime Air traffic and Star Schema Benchmark got a lot of interest
    (links:


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    Star Schema Bechmark: InfoBright, InfiniDB and LucidDB
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    In my previous rounds with DataWarehouse oriented engines I used single table without joins, and with small (as for DW) datasize (see http://www.mysqlperformanceblog.com/2009/10/02/analyzing-air-traffic-performance-with-infobright-and-monetdb/, http://www.mysqlperformanceblog.com/2009/10/26/air-traffic-queries-in-luciddb/, http://www.mysqlperformanceblog.com/2009/11/02/air-traffic-queries-in-infinidb-early-alpha/). Addressing these issues, I took Star Schema Benchmark, which is TPC-H modification, and tried run queries against

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    A review of Pentaho Solutions by Roland Bouman and Jos van Dongen
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    Pentaho Solutions

    Pentaho Solutions, Business Intelligence and Data Warehousing with Pentaho and MySQL. By Roland Bouman and Jos van Dongen, Wiley 2009. Page count: about 570 pages. (Here’s a link to the publisher’s site.)

    The book is big in part because it’s about a GUI tool, so there are the requisite number of screenshots (but not too many). It is structured into four parts, each on a different topic.

    The first part is 4

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    Air traffic queries in MyISAM and Tokutek (TokuDB)
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    This is next post in series
    Analyzing air traffic performance with InfoBright and MonetDB
    Air traffic queries in LucidDB
    Air traffic queries in InfiniDB: early alpha

    Let me explain the reason of choosing these engines. After initial three posts I am often asked "What is baseline ? Can we compare results with standard MySQL engines ?". So there come MyISAM to consider it as base point to see how column-oriented-analytic engines are better here.

    However, take into account, that for MyISAM we need to




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    Air traffic queries in InfiniDB: early alpha
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    As Calpont announced availability of InfiniDB I surely couldn't miss a chance to compare it with previously tested databases in the same environment.
    See my previous posts on this topic:
    Analyzing air traffic performance with InfoBright and MonetDB
    Air traffic queries in LucidDB

    I could not run all queries against InfiniDB and I met some hiccups during my experiment, so it was less plain experience than with other databases.

    So let's go by the same steps:

    Load data

    InfiniDB supports MySQL's LOAD DATA statement and it's own colxml




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    Analyzing air traffic performance with InfoBright and MonetDB
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    Accidentally me and Baron played with InfoBright (see http://www.mysqlperformanceblog.com/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron's example I also run the same load against MonetDB. Reading comments to Baron's post I tied to load the same data to LucidDB, but I was not successful in this.

    I tried to analyze a bigger dataset and I took public available data
    http://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time about USA domestic flights with information about flight length and delays.

    The data is available from 1988 to 2009


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    Starring Sakila: MySQL university recording, slides and materials available onMySQLForge
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    Hi!

    Yesterday I had the honour of presenting my mini-bi/datawarehousing tutorial "Starring Sakila" for MySQL University. I did a modified version of the presentation I did together with Matt Casters at the MySQL user's conference 2009. The structure of the presentation is still largely the same, although I condensed various bits, and I added practical examples of setting up the ETL process and creating a Pentaho Analysis View (OLAP pivot table) on top of a Mondrian Cube.

    The slides, session recording, and materials such as SQL script, pentaho data integration jobs and transformations, and Sakila Rentals Cube for Mondrian are all available here on MySQL



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    Monolith MySQL DBA Console - version 1.2a Released
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    Ok folks, just after testing out some new changes to this week’s release - I’ve uploaded a new version. Here are the following changes:

    Changelog 1.2a
    - changes line thickness to 1 for all graphs, 2 was too thick for running at 5 minute intervals for the poller
    - added several scripts for running and logging monitor agent and report_generator
    - changes talkback sripts to one script instead of 3

    Data Warehousing 101: The purpose of a data warehouse
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    When your company decides that "it is time to build a data warehouse", what thoughts come to mind?1) A magical fairy ice cream land where data is presented in chocolate shells for everyone to digest perfectly;2) A big literal warehouse in the industrial section of town with rusty old containers;3) Another place to put data, which means another place for you to track and monitor additional
    MySQL Archiver can now archive each row to a different table
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    One of the enhancements I added to MySQL Archiver in the recent release was listed innocently in the changelog as "Destination plugins can now rewrite the INSERT statement." Not very exciting or informative, huh? Keep reading.

    Archive strategies for OLTP servers, Part 3
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    In the first two articles in this series, I discussed archiving basics, relationships and dependencies, and specific archiving techniques for online transaction processing (OLTP) database servers. This article covers how to move the data from the OLTP source to the archive destination, what the archive destination might look like, and how to un-archive data. If you can un-archive easily and reliably, a whole new world of possibilities opens up.

    Archive strategies for OLTP servers, Part 2
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    In the first article in this series on archiving strategies for online transaction processing (OLTP) database servers, I covered some basics: why to archive, and what to consider when gathering requirements for the archived data itself. This article is more technical. I want to help you understand how to choose which rows are archivable, and how to deal with complex data relationships and dependencies. In that context, I'll also discuss a few concrete archiving strategies, their strengths and shortcomings, and how they can satisfy your requirements, especially requirements for data consistency, which as you will see is one of the most difficult problems in archiving.

    Archive strategies for OLTP servers, Part 1
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    In May 2005, I wrote a widely-referenced article about how to efficiently archive and/or purge data from online transaction processing (OLTP) database servers. That article focused on how to write efficient archiving SQL. In this article I'll discuss archiving strategy, not tactics. OLTP servers tend to have complex schemas, which makes it important and sometimes difficult to design a good archiving strategy.

    Showing entries 1 to 16

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