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April , 2007
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Importing a CSV Text File into Oracle 10G XE by Jayaram Krishnaswamy The present article looks at importing a Comma Separated Value (CSV) file, used commonly in exporting MS Excel files, into an Oracle 10G XE table. CSV files are very popular and frequently used data transformation formats since legacy data are usually of this type. In recent times XML formatted data has replaced them. However, there is a whole lot of legacy data that needs to be loaded on to more recent databases. Hence, every database vendor provides a program to accomplish this conversion. Also programs exist which takes a CSV file and convert it into an XML file. Perhaps this is another route one can take in data conversions for legacy data.
Click here for the
article. Data Profiling and Automated Cleansing Using Oracle Warehouse Builder 10g Release 2 by Mark Rittman
Most organizations build a data warehouse to provide an integrated, reliable, and consistent “single version of the truth.” Data is usually sourced from a number of systems and has to be extracted, cleansed, and integrated before being made available for users to query. The quality of the data loaded into the data warehouse is often variable, however, and for that reason, historically the process of profiling your source data has been a time-consuming, manual process that has required either lots of experience with SQL*Plus or the purchase of an expensive third-party tool. With the release of Oracle Warehouse Builder 10g Release 2, however, the ability to profile your data is built into the tool and no knowledge of SQL*Plus is required. Furthermore, the data profiles that you build using Oracle Warehouse Builder can be used to generate automatic corrections to your data. In this article, you’ll learn all the nuances of this important new feature. Click here for the article.
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Table Spaces And Locking Levels, Part 3 In Part 1, I described a database and three types of table spaces that can be defined within a database. In Part 2, I discussed how page-level locking is handled in those different types of table spaces. You might want to review those columns before reading this one (see Resources). In this article, we'll look at how DSNZPARMs are used to control the maximum number of locks we may acquire, the length of time we'll wait for a lock, and other system-level issues. We will also explore timeouts, lock escalation vs. lock upgrades, and deadlocks. And, we'll find out how an index-only job can time out even though we don't get locks on indexes.
Click here
for the article.
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In A Nutshell
Interested in learning more tips and techniques for SQL Server? "In A Nutshell"
is what you are looking for. Kevin Kline,
author of O'Reilly's "SQL in a Nutshell" and "Transact-SQL Programming" and President of The Professional Association for SQL Server,
offers tips, techniques and much more. Updated numerous times a week,
there is always valuable material to be had!
Click
here
to see what Kevin is up to in the SQL Server world.
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| Understanding the MySQL Falcon Transaction Storage Engine – Part 1 If you’ve been using MySQL for any time at all, you know that a unique advantage afforded MySQL users is the ability to use multiple storage engines to manage the underlying data stored on the server. This efficient and modular architecture provides large performance and manageability benefits for those wishing to specifically target a particular application need – such as data warehousing, transaction processing, high availability situations, etc. – while enjoying the advantage of utilizing a set of interfaces and services that are independent of any one storage engine. The MySQL server supplies engines that are internally developed, provided by third-party software vendors, and also allows a user to build their own storage engine if they desire. Some of MySQL’s engines support transaction processing and some do not. The current production engines in MySQL 5.0 that support transaction management are NDB/Cluster, InnoDB (supplied by Oracle), and the solidDB engine (supplied by Solid Information Technology). MySQL has also just introduced a new transactional storage engine – code named Falcon – that is currently available in an alpha release. Falcon is a next-generation transactional management engine designed to run on all popular hardware/architecture platforms, but it is especially designed to take advantage of the large memory caches available in 64-bit environments. Falcon is a natural fit for modern businesses and always online applications that need lightening-fast transaction performance and rock-solid data reliability. In this first in a series of short articles on the Falcon engine, let’s take a look at how Falcon has been architected and see how it differs from some of the other popular MySQL storage engines. Click here to see this article.
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If you are asked to estimate the effort, duration and cost for a major piece of work, you should spend a little time in preparation before jumping right in. Spending a little time in preparation can save you a lot of re-work time. Consider the following techniques before you begin the estimating process. Click here for more information on preparing estimates for large projects.
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| Webcasts
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Interactive Crossword
Puzzle: "Name that Dog"
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