data warehouse

How Partial Indexing helps you save space in #Oracle 12c

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Over time certain partitions may become less popular. In 12c, you don’t have to index these partitions anymore! This can save huge amounts of space and is one of the best 12c New Features in my opinion. Really a big deal if you are working with range partitioned tables where the phenomenon of old ranges becoming unpopular is very common. Let’s have a look, first at the problem:

How to change RANGE- to INTERVAL-Partitioning in #Oracle

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An existing RANGE partitioned table can easily be changed to be INTERVAL partitioned with the SET INTERVAL command. My table has been created initially like this:

Canberra Event – Next Let’s Talk Database presentation by Richard Foote

Let’s Talk Database – Thursday, 28 July 2016

The next in Richard Foote’s popular Let’s Talk Database series – Let’s Talk Database: Oracle Database 12c – Built for Data Warehousing – is on in Canberra on July 28th. These are free events but due to limited places have often “sold out” in the past, so booking early is recommended to avoid disappointment.

Session Details

The Oracle Database is the leading database in market but it might come as a surprise to some that it’s also the leading database with respect to Data Warehousing in terms of both sales and analyst rankings. The focus today is a detailed look at all the special database capabilities that makes the Oracle Database the perfect platform for Data Warehouse type applications.

OOW11: Exalytics Hits The Stage — In-Memory Analytics

News from Oracle OpenWorld flor… What is Exalytics? It’s a BI appliance machine — it’s like an application middle tier for complete Business Intellegence data warehousing solutions. You put it in front of Exadata and users get all the tools to work with that data – analyze, predict, run reports and etc. Exalytics is a [...]

The Core Performance Fundamentals Of Oracle Data Warehousing – Table Compression

[back to Introduction] Editor’s note: This blog post does not cover Exadata Hybrid Columnar Compression. The first thing that comes to most people’s mind when database table compression is mentioned is the savings it yields in terms of disk space. While reducing the footprint of data on disk is relevant, I would argue it is the lesser of the benefits for data warehouses. Disk capacity is very cheap and generally plentiful, however, disk bandwidth (scan speed) is proportional to the number of spindles, no mater what the disk capacity and thus is more expensive. Table compression reduces the footprint on the disk drives that a given data set occupies so the amount of physical data that must be read off the disk platters is reduced when compared to the uncompressed version. For example, if 4000 GB of raw data can compress to 1000 GB, it can be read off the same disk drives 4X as fast because it is reading and transferring 1/4 of the data off the spindles (relative to the uncompressed size). Likewise, table compression allows for the database buffer cache to contain more data without having to increase the memory allocation because more rows can be stored [...]

The Core Performance Fundamentals Of Oracle Data Warehousing – Balanced Hardware Configuration

[back to Introduction] If you want to build a house that will stand the test of time, you need to build on a solid foundation. The same goes for architecting computer systems that run databases. If the underlying hardware is not sized appropriately it will likely lead to people blaming software. All too often I [...]

The Core Performance Fundamentals Of Oracle Data Warehousing – Introduction

At the 2009 Oracle OpenWorld Unconference back in October I lead a chalk and talk session entitled The Core Performance Fundamentals Of Oracle Data Warehousing. Since this was a chalk and talk I spared the audience any powerpoint slides but I had several people request that make it into a presentation so they could share [...]