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HuffingtonPost CTO to speak on Enterprise MySQL: Heavy-Traffic Management on Aug. 11 at the NYC MySQL Group http://www.meetup.com/mysqlnyc/calendar/10930810/

How to delete table from mysql

Although there are many open source CMSes available, we're going to focus on those that are based upon PHP. The following CMSes are thus PHP-based, and use a MySQL database. The advantages of using such a CMS include portability, support and a large developer base with frequent updates and improvements. We will discuss the following four CMSes: Drupal - a free open source content management system written in PHP and distributed under the GNU General Public License Joomla - an open source content management system platform for publishing content as a Model-view-controller (MVC) web application framework PHPNuke - a web-based automated news publishing and content management system based on PHP and MySQL Wordpress - an open source CMS, often used as a blog publishing application, and is the most popular blog software in use today

Php tricks blog is all about to gather knowledge on PHP-Mysql and all the related topics to it. Free download Tutorial and snippets on php and mysql. Our Motto is to Share Knowledge and Get Knowledge.

Product announcements have raised questions Oracle and OpenOffice.org don't want to answer. Here's what we know. By Eric Lai Eric has provided us with a comprehensive set of questions surrounding the Oracle aquisition of Sun.  The key issues he focuses on concern the future of OpenOffice, MYSQL and something called Oracle Cloud Office.  Unfortunately his efforts resulted in only a handful of tentative answers.  Which leads me to believe that over a year of negotiations and planning at Oracle has left them up in the air and undecided. Time to go through the questions.  I'm going to use the Diigo highlight and comments overlay of Eric's article to do this.

"Apparently confirming last year's report, Screven said that Sun had been working on Oracle Cloud Office 'for some time.'" Sun reorganized internally in February of 2008, transferring the StarOffice/OOo resources under a newly-minted Cloud Computing division.That seems likely to be the point when Sun got serious about the cloud-based rewrite of OOo. So around two years into the effort?

http://www.manageit.me ---The greatest minds in IT in 50+ presentations : top industry-leaders: Creator of MySQL Michael "Monty" Widenius, Internet Celebrity Gary Vaynerchuk, Co-Creator of PHP & Zend CTO Zeev Suraski, Richard Sheridan, CEO of Menlo Innovations & Pioneer of Agile eXtreme Programmi...

"Google's Cloud Platform has long featured Cloud SQL, a zero-maintenance MySQL database that's hosted on Google's cloud platform. What it didn't offer was an API to easily manage these databases without having to use Google's admin interface. Today, however, Google is launching the Cloud SQL API. This new REST API will allow developers to programmatically manage their database instances and open a number of new use cases for Cloud SQL. The API, which Google still deems to be experimental, will allow developers to create their own workflows to easily create and delete instances, restart them and restore them from backup. They will also be able to use it to important and export their databases to and from Google Cloud Storage. For developers, this means using Google's cloud database is now quite a bit easier, especially if they need to regularly manage multiple databases for their customers. Google's launch partner for this API is OrangeScape, which uses it to power parts of KiSSFLOW, its Google Apps workflow SaaS service. "

Excellent Hadoop/Hive explanation.  Hat tip to Matt Asay for the link.  I eft a comment on Matt's blog questioning the consequences of the Oracle vs. Google Android lawsuit, and the possible enforcement of the Java API copyright claim against Hadoop/Hive.  Based on this explanation of Hadoop/Hive, i'm wondering if Oracle is making a move to claim the entire era of Big Data Cloud Computing?  To understand why, it's first necessary to read Matt the Hadoople's explanation.   kill shot excerpt: "You've built your Hadoop job, and have successfully processed the data. You've generated some structured output, and that resides on HDFS. Naturally you want to run some reports, so you load your data into a MySQL or an Oracle database. Problem is, the data is large. In fact it's so large that when you try to run a query against the table you've just created, your database begins to cry. If you listen to its sobs, you'll probably hear "I was built to process Megabytes, maybe Gigabytes of data. Not Terabytes. Not Perabytes. That's not my job. I was built in the 80's and 90's, back when floppy drives were used. Just leave me alone". "This is where Hive comes to the rescue. Hive lets you run an SQL statement against structured data stored on HDFS. When you issue an SQL query, it parses it, and translates it into a Java Map/Reduce job, which is then executed on your data. Although Hive does some optimizations, in general it just goes record by record against all your data. This means that it's relatively slow - a typical Hive query takes 5 or 10 minutes to complete, depending on how much data you have. However, that's what makes it effective. Unlike a relational database, you don't waste time on query optimization, adding indexes, etc. Instead, what keeps the processing time down is the fact that the query is run on all machines in your Hadoop cluster, and the scalability is taken care of for you." "Hive is extremely useful in data-warehousing kind of scenarios. You would

Good Chart comparing four types of Data Stores: Key-Value, Tabular/Columnar, Document Store, Relational excerpt: The bottleneck is no longer around performance or the cost of computing - it's about quickly getting the information to thousands, or hundreds of thousands, of nodes trying to act as one computer delivering a service. Google and IBM both have written about the data center as a computer, and Facebook says it thinks of adding hardware at the rack level rather than at the server level. But the current means of storing and accessing data have not made this leap from a single server to a rack - let alone an entire data center. As programmers attempt this leap, they face several difficulties, which include working with existing software and programming languages and figuring out what problems and bottlenecks the new services built on these monolithic computer platforms will encounter. Plus, the IT world doesn't all move at once, which means plenty of jobs and workloads will continue with the old way of doing things - that is, relational databases such as Oracle's offerings and the open source MySQL, which Oracle now has a stake in thanks to its purchase of Sun. The result is not a steady movement to non-relational databases or other methods of storing data, but a back-and-forth as programmers and businesses figure out what kind of architecture they need and what problems they want to solve. For a closer look at the issue and a bunch of charts detailing how the landscape is currently laid out, analyst Matt Sarrel, has penned a report over at GigaOM Pro (sub. req'd.) on the NoSQL movement called "NoSQL Databases - Providing Extreme Scale and Flexibility."