Wednesday Oct 30, 2013

Oracle Magazine: Getting started with SQL Analytics

I am currently working on a series of podcasts covering the broad categories of our SQL analytical functions and features and while I was doing some research I came across of series of four articles in the Oracle Magazine.

This series of article is written by Melanie Caffrey who is a senior development manager at Oracle. She is a coauthor of Expert PL/SQL Practices for Oracle Developers and DBAs (Apress, 2011) and Expert Oracle Practices: Oracle Database Administration from the Oak Table (Apress, 2010).

The four articles are under the banner "Technology: SQL 101" and parts 9, 10, 11 and 12 cover SQL analytics. Here are the links to the four articles:

The articles cover topics such as GROUP BY, SUM, AVG, HAVING, window functions, RANK, FIRST, LAST, LAG, LEAD etc.  

The great news is that  you can try out the examples in this series. All you need is access to an Oracle Database instance. All the schemas, data sets and SQL statements that you will need can be downloaded from a link included in the January article.  

 I hope you find this series of articles useful.

Tuesday Oct 22, 2013

OOW content for Pattern Matching....

If you missed my sessions at OpenWorld then don't worry - all the content we used for pattern matching (presentation and hands-on lab) is now available for download.

My presentation "SQL: The Best Development Language for Big Data?" is available for download from the OOW Content Catalog, see here: https://oracleus.activeevents.com/2013/connect/sessionDetail.ww?SESSION_ID=9101

For the hands-on lab ("Pattern Matching at the Speed of Thought with Oracle Database 12c") we used the Oracle-By-Example content. The OOW hands-on lab uses Oracle Database 12c Release 1 (12.1) and uses the MATCH_RECOGNIZE clause to perform some basic pattern matching examples in SQL. This lab is broken down into four main steps:
  • Logically partition and order the data that is used in the MATCH_RECOGNIZE clause with its PARTITION BY and ORDER BY clauses.
  • Define patterns of rows to seek using the PATTERN clause of the MATCH_RECOGNIZE clause. These patterns use regular expressions syntax, a powerful and expressive feature, applied to the pattern variables you define.
  • Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause.
  • Define measures, which are expressions usable in the MEASURES clause of the SQL query.
You can download the setup files to build the ticker schema and the student notes from the Oracle Learning Library. The direct link to the example on using pattern matching is here: http://apex.oracle.com/pls/apex/f?p=44785:24:0::NO:24:P24_CONTENT_ID,P24_PREV_PAGE:6781,2.
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The data warehouse insider is written by the Oracle product management team and sheds lights on all thing data warehousing and big data.

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