One of the most powerful features of the multidimensional engine behind analytic workspaces is the ability to create formulas. Formulas, or "calculated measures" as they're referred to in AWM10g, are measures that are derived from other measures. Using AWM, you can create simple formulas that reference other measures in a cube, allowing you for example to create a "margin" measure derived from sales and costs measures. If you're an old Express hand though, you'll know that this simple type of formulas is just the tip of the iceberg, and what you often used to end up doing was creating for example a three dimensional formula based on measures from four and five dimensional variables, rolling up unneeded dimensions and pulling in variables held in what would now be referred to as "cubes".
DBAs wanting to create a 10g Real Applications Cluster face many configuration decisions. One of the more potentially confusing decisions involves the choice of filesystems. Gone are the days when DBAs simply had to choose between "raw" and "cooked". DBAs setting up a 10g RAC can still choose raw devices, but they also have several filesystem options, and these options vary considerably from platform to platform. Further, some storage options cannot be used for all the files in the RAC setup. This article gives an overview of the RAC storage options available.
When Oracle released RMAN (Recovery Manager) in Oracle 8 they changed the way databases can be backed up and recovered in the event of disaster. Unfortunately, Oracle shops have been slow to embrace RMAN often times because the change required a leap of faith into the new backup / recovery process as well changes to scripts, procedures, etc. This article will introduce the reader to RMAN and explain why every DBA should use it.
The last couple articles I have written focused on meta-data or DDL extraction for Oracle. The search for a part III to those articles lead me to Oracle's Data Pump utility. Not necessarily for the data movement piece but because it has an API for meta-data. Well even though I have been using 10g for quite some time, I have yet to use Data Pump. I thought this would be a great way to introduce myself, and possibly you the reader, to this new utility. This article will serve as a basic introduction to Data Pump and then in subsequent articles we will walk through the new command line options for Data Pump's export and import (expdp & impdp), and look at the PL/SQL packages DBMS_DATAPUMP and DBMS_METADATA.
If you're looking to tune an SQL statement or a batch job, a common way to find out what happened during the execution of the SQL is to run an extended SQL trace and examine the wait events. But what happens if you are using parallel execution, and all your trace file contains is the parallel execution wait events that are generally considered idle events? Your trace file shows how long your query took to run, and the work involved in controlling the PQ slaves, but the real details of what took up all the execution time are actually to be found in the corresponding PQ slave trace files in the BDUMP directory.
This article is the result of observations of the UNDO tablespace of Oracle 9i and Oracle 10g in various situations. We start with a simple query showing how to monitor the amount of undo generated in a session for a specific time. We investigate the creation, expansion, and resize of UNDO tablespace, and the issues that guide the reuse of UNDO segments. The impact of parameters like UNDO_RETENTION in Oracle 9i and UNDO_RETENTION and the GUARANTEE clause in CREATE UNDO statements is discussed using simple reproducible examples.
In this article James continues to explore the Oracle's Metadata API and provides a powerful function to compare objects and schemas and print the DDL required to bring them in sync.
This article shows how Oracle's Heterogeneous Services can be configured to allow a database to connect to a Microsoft Access database using standard databases links. The method described can be used to connect to MS-Access from about any platform - Unix/ Linux or Windows.
In this article James explores the Oracle's Metadata API (DBMS_METADATA) and shows how database users can extract object definitions (DDL statements) from an Oracle database without having to go through a stack of dictionary views.
Jared explains how Oracle manages passwords and how "thinking like a hacker" can help you to better protect your databases from potential password theft.