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Monthly Archives: June 2012

Stumbled across a type of index optimization which can be used with Oracle database tables. A Reverse Index, also known as a reverse key index stores the index entries as their bytes reversed, except rowids.

Reverse Key Index

by Yasin Baskan

In single instance databases there is also a case where reverse key indexes can be helpful. If you have a column populated by an increasing sequence, you delete some old rows from the table and you do not do range scans on that column and you have contention issues on index blocks, reverse key indexes can be considered. The reverse key index will scatter the entries accross different blocks during inserting and your many concurrent sessions will not have index block contention issues.

Read more: http://oracletoday.blogspot.com/2006/09/there-is-option-to-create-index.html#ixzz1wxx3qO4l

This method offers a new way of managing data entry and output from a situation of large data sets or multiple read/write database sessions involved.

The R language is an open source project run by a very large community of “clever” statisticians who have created to date over 2,500 plug-ins for analyzing different data sets tuned by industry and data type. More recently, Oracle has jumped into the picture by creating an analytical product that bridges the hard work of R across to their flagship 11g R2 database product.

R is Ready for Big Data: Take the Open Road to Statistical Analysis

By Timothy Prickett Morgan

Statistical analysis has been around since mainframes were introduced to academia and corporations back in the 1960s.

But the great diversity of telemetry collected by systems today, the need to sift through it for insight and the growing popularity of open-source alternatives is transforming the R programming language for statistical analysis and visualisation. Its new nickname is Red Hat for stats…

http://www.theregister.co.uk/2012/06/03/big_data_r_statistical_analysis/

In the Oracle implementation of R, there is some integration that allows the R console to work with Hadoop distributed file systems and NoSQL databases, both of which are also core components of the world of “Big Data”

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