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Cloudata is a new open source implementation of Google's BigTable paper. It can be found on Github here. It appears to be the project of a Korean developer named YKKwon.

As noted at MyNoSQL, there are only a couple commits and it's not clear how serious this project is. But it will be of interest to big data, MapReduce and BigTable buffs.

Looking for some projects to brush-up on your development skills in the coming week? Here are three interesting tutorials that might do the trick: one on sanitizing input, one on MapReduce and one on Scala.

Plus a bonus tutorial for those looking for something a little more offbeat.

Have you been wanting to learn Hadoop, but have no idea how to get started? Carlo Scarioni has a basic Hadoop tutorial that covers installing Hadoop, creating a Hadoop Distributed File System (HDFS), moving files into HDFS, and creating a simple Hadoop application. The tutorial also introduces the basic concepts of Map Reduce.

It doesn't, however, get into distributing the application, which is the main point of using Hadoop in the first place. Scarioni leaves that to a future tutorial. But if you want to get your feet wet with Hadoop and/or Map Reduce, this seems like a pretty good place to start.

Yelp has a few nifty features on its network that gives it that special sauce. It's what you see with most world-class social networks where features provide context and allow for discovery. It make it simple to use the service with such features as review highlights, autocomplete, spelling suggestion and top searches.

"People Who Viewed this Also Viewed..." is one of its popular features. It shows you photos by other people who also have similar viewing habits.

Take the King Burrito page on Yelp. It is a favorite Mexican spot in North Portland, Oregon. The food rocks. On Yelp, the sidebar shows what visitors to the King Burrito page are also viewing.

It's the earliest of days of smartphone cloud computing. But it 's time has arrived as demonstrated by a group of researcher who have showed how smartphones can be used to create a self-contained cloud computing network.

Using smartphones to create a cloud computing infrastructure is a bit quizzical. Each smart phone has a fraction of the processing power of a remote server. But there are advantages to a mobile device oriented network. Data does not have to travel to remote servers in a data center. Overall, the research demonstrates the advances we should expect as smartphone-based cloud computing networks begin emerging as an alternative to traditional data centers.

According to MIT Technology Review, the researchers developed using "misco, a version of MapReduce that can be handled by a "server farm" comprised of 20-odd Nokia N95 smartphones."

Amazon announced today that it is bridging two of its web computing services, EC2 and S3, with Hadoop, an open-source project that brings the same distributed data processing power as Google's MapReduce. In fact, it is calling the new service Amazon Elastic MapReduce. The new service will allow its EC2 customers to perform distributed MapReduce queries on enormous datasets stored in S3, paying only for the computation time they need.