Operationalizing Machine Learning with SparkML on YARN
By May 2016, SparkML had emerged as a practical and scalable way to build and deploy machine learning pipelines directly on distributed infrastructure — and ...
Recent Posts
Beyond YARN: Evolving Alternatives for Distributed Data Processing and Storage
By April 2016, YARN had already become the cornerstone of resource management in the Hadoop ecosystem — powering everything from MapReduce to Spark, Hive, an...
Error Handling and Recovery with Akka Actors: Scalable Resilience Inspired by Erlang
As of April 2016, the need for scalable and resilient systems has made actor-based concurrency more relevant than ever. In the JVM world, Akka brings this mo...
Transactional Memory and Functional Programming: Scalable Concurrency in Haskell and Beyond
As of April 2016, building concurrent systems is no longer optional — it’s a necessity. Whether you’re writing backend services, data processing pipelines, o...
Apache Oozie and YARN: Building Scalable, Reproducible DAG-Based Data Workflows
As of March 2016, Apache Oozie remains one of the foundational workflow engines in the Hadoop ecosystem. Designed for orchestrating complex, multi-stage data...