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!
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.
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.
Who’s the sheriff in today’s data centre wild west? Postgres advocate Pierre Fricke looks at the risks that NoSQL will pose in years to come, while doing his best to deflate the Hadoop hype.
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.
After progressing all the way up to version 0.99, HBase 1.0 is here; a major milestone in the Apache project’s development, offering some exciting features and new APIs without sacrificing stability.
A major leap has been made for the newest version of Apache Hive, now proudly stepping up to version 1.0.0. After nine years of work, Hive can now embrace the new naming structure and all that comes with it.
Apache Hadoop, Apache Spark, Akka, Java 8 streams and Quasar: A look at the classic use cases to the newest concurrency approaches for Java developers.
A look at the pros and cons of the big data processing framework that took the industry by storm.