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Showing entries 1 to 10 of 16 6 Older Entries

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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    Showing entries 1 to 10 of 16 6 Older Entries

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