programminglanguage:sql

Attackers are turning MySQL servers into DDoS bots

▻http://www.net-security.org/malware_news.php?id=3134

Someone has been compromising MySQL servers around the world and using them to mount DDoS attacks. The latest targets of these attacks are an (unnamed) US hosting provider and a Chinese IP address.

Most of the servers affected in this campaign are located in India, China, Brazil and the Netherlands, but others can be found around the globe.

Uses variant of #Chikdos Trojan
• SQL injection to install malicious user-defined function (UDF) on target server, then loaded into SQL and executed
• UDF acts as downloader and compromise server to get remote access
• UDF downloads two variants of Chikdos trojan from 2 compromised sites.

#DDoS
#SQL_injection
#trojan #malware

You’re never going to find a data scientist with that ad - TechRepublic
▻http://www.techrepublic.com/article/youre-never-going-to-find-a-data-scientist-with-that-ad

“Admit it,” [Christi Eubanks, Gartner analyst] writes, “You and/or the recruiter took a bunch of LinkedIn posts and genetically engineered your perfect, beautiful quant baby with skills you didn’t even know you needed.”

And so the job spec asks for an MS or PhD (with an MBA, preferred!) that knows every business intelligence program ever invented, hacks NoSQL databases in her spare time, and also loves PowerPoint.

This leads Eubanks to conclude: “Data scientists are related to, but not the same as statisticians, who are not all versed in web analytics, which is not SEM, though all of the above can probably handle some SQL, and none would pick .ppt as their favorite medium. There are three or four different experts rolled into this one position, but none of them are going to apply for this job.”

Far better, she argues, following her colleague Svetlana Sicular, to stop searching for unicorns and instead let someone with potential grow into the job. According to Sicular, the best data scientists will be those that know the right questions to ask. Learning the tools (like Hadoop) that help answer the questions is a secondary problem.

Phinx
▻http://phinx.org

Phinx allows developers to alter and manipulate databases in a clear and concise way. It avoids the use of writing SQL by hand and instead offers a powerful #api for creating migrations using #php code.

▻http://docs.phinx.org/en/latest/configuration.html

Phinx currently supports the following database adapters natively: #mysql, PostgreSQL, #sqlite, SQL Server

Grosso merdo c’est l’API SQL de #SPIP ^^

For data scientists, the big money is in open source - TechRepublic
▻http://www.techrepublic.com/blog/big-data-analytics/data-scientists-can-find-big-money-in-open-source/#ftag=RSS56d97e7

As O’Reilly’s 2013 Data Science Salary Survey suggests, “ the field of big data has ushered in the arrival of new, complex tools that relatively few people understand or have even heard of. ” Knowing those tools is what yields such outsized salaries.

But which tools a data scientist masters turns out to have a large, material impact on her earning power.

The top data tool by far is SQL, which isn’t surprising: data analysis has been around long before we gave it a sexy “data science” label, and accessing data through SQL has long been the standard for data analysis. This isn’t changing overnight.

http://tr1.cbsistatic.com/hub/i/r/2014/01/21/222504a7-17c3-407a-9f55-0769874e055b/resize/620x485/oreilly%201.jpg

But once we move beyond SQL, it’s telling just how much of the most widely used Big Data tools are open source: R, Python, Hadoop and more. More interestingly, however, is the bifurcation between what O’Reilly calls “the Hadoop group”(orange) and the “SQL/Excel group” (blue):

http://tr1.cbsistatic.com/hub/i/r/2014/01/21/691b4c15-86f9-4d29-b785-786ab20b577b/resize/620x485/oreilly%202.jpg

Et dans le bloc Hadoop, les data scientists ont tendance à connaître plus d’outils, donc à être mieux payés. En plus, avec Hadoop, ils peuvent évoluer vers des données vraiment grosses.

Jay Cabrales – Yochanans Vision EP (2013)
▻http://chewbone.rickshide.com/2013/11/06/jay-cabrales-yochanans-vision-ep-2013

Jay Cabrales – Yochanans Vision EP (2013)Progressive House | OLD SQL Recordings (OLDSQL144)320 kbps | MP3 | single | 2013-09-01 | 00:33:22 | 76.56 MbUploaded: ul.to, u22023982.letitbit.net, bitshare.com, dfiles.ru, turbobit.net Source: ▻http://www.freshremix.org/house/50302-jay-cabrales-yochanans-vision-ep-2013.html

#Forums #Warez

VirtualPG: VirtualPG
▻https://www.gaia-gis.it/fossil/virtualpg/index

VirtualPG is a loadable dynamic #extension to both #sqlite and SpatiaLite. Its intended scope is supporting direct SQL access to #postgresql and PostGIS own tables, so to make any possible kind of data exchange between these two popular open source Spatial DBMSes as straightforward and simple as possible.

Testing for SQL Injection (OWASP-DV-005) - OWASP
▻https://www.owasp.org/index.php/Testing_for_SQL_Injection_(OWASP-DV-005)

Documentation exhaustive sur les techniques d’injection SQL (OWASP = The Open Web Application Security Project)

#sql #injection #documentation #attaque #owasp

Are NoSQL and Big Data Just Hype? Interview with SQL Creator, Monty Widenius
▻http://www.dzone.com/articles/are-nosql-and-big-data-just

The expert in the database area, Monty Widenius, talks in his interview about the current and future state of SQL, NoSQL and Big Data. And his answers were somewhat surprising.

Source: dzone.com - fresh links for developers

Vizzuality/cartodb - GitHub
►https://github.com/Vizzuality/cartodb

With CartoDB, you can upload your geospatial data (Shapefiles, GeoJSON, etc) using a web form and then make it public or private. After it is uploaded, you can visualize it in a table or on a map, search it using SQL, and apply map styles using CartoCSS. You can even access it using the CartoDB Maps API and SQL API, or export it to a file.

Un truc qui fait penser à Tilemill. Un jour j’aurai le temps de m’intéresser à tout ça en détail, un jour...

#map #tiles #server #opensource #gis

Coding Horror: A Visual Explanation of SQL Joins
►http://www.codinghorror.com/blog/archives/000976.html

#database #programming #sql #joins #join #mysql