Upwork’s latest skills index has a bunch of surprises for the hungry freelance market. It’s time to brush off your Hadoop skills and revisit your science textbooks. We take a look at what skills you should highlight on your resume, from machine learning skills to data security certifications.
Big data was born on the back of Apache Hadoop. Today, we take a look at the latest version of this open source framework for distributed computing, Hadoop 3.2! Highlights include powerful new features and deep learning applications.
When the readily available tools won’t cut it, build a new one! And this is exactly what LinkedIn did to natively run TensorFlow on Apache Hadoop; TonY is now open source. Let’s have a look at what’s under this framework’s hood!
Every year, Stack Overflow asks the developer community about everything from their favorite technologies to their job preferences. As always, we focus on the most popular technologies but we also skim through the most dreaded languages, libraries, frameworks and tools.
Hadoop is back! The latest version [3.0.0] of the Open Source software framework for reliable, scalable, distributed computing brings a lot of new features, including an early preview (alpha 2) of a major revision of YARN Timeline Service, shell script rewrite and more.
Twenty years ago we were just learning how to hook up the new Java language to our relational database to run queries. Five years later and the first IMDGs are starting to appear on the scene and things get faster. Another 5 years and we get NoSQL, finally we can get rid of the ORM, NoSQL works nicely with IMDGs too. Then comes Hadoop and for some bizarre reason we start to see ORM coming back – something’s wrong. What next?
In this article, Nilay Shrivastava, Business Manager at IBM Cloud, explains why we should use Hadoop-as-a-Service. He claims there are at least five benefits that should spark our interest.
LinkedIn has open sourced Dr. Elephant , a tool focused toward helping Hadoop users understand and optimize their flows which solves about 80 percent of the problems through simple diagnosis.
Spark has made some improvements over Hadoop but where are we now with this mess? John Davies will shed some light on this issue and point out the latter’s importance even as time goes by and Spark challenges its reign.
Although Facebook famously ditched Cassandra to use HBase for its messenger service, the NoSQL database remains largely overlooked. Ubeeko CEO Ghislain Mazars takes a look under the hood of HBase features.
Google have released an open source MapReduce framework for C, called MR4C, that allows developers to run native code in the Hadoop framework. Added contributions to the project are welcomed from the community.
A look at the pros and cons of the big data processing framework that took the industry by storm.