In the following blog posts we study the topic of Distributed Deep Learning, or rather, how to parallelize gradient descent using data parallel methods. We start by laying out the theory, while supplying you with some intuition into the techniques we applied. At the end of this blog post, we conduct some experiments to evaluate how different optimization schemes perform in identical situations.

Topic: this post is about a simple implementation with examples of IPython custom magic functions for running SQL in Apache Spark usin

I have been wanting to test Apache Kafka for sometime now and finally got around to it! In this blog post I give a very short introduction on what is Kafka, installation & configuration of Kafka cluster and finally benchmarking few near real-world scenarios on OpenStack VM's

Topic: This post is about performance optimizations introduced in Apache Spark 2.0, in particular whole-stage cod

Hello,

Last week I've investigated how does OAuth2 protocol works and developed a Proof of Concept (PoC) in Java. In this post I would like to show you how effortlessly develop simple client-server application using OAuth 2.0 standard for authorization of protected resources placed on a server.

Before we start developing our first secured web application with OAuth2 let's understand how it works.

What is it and how does it work?

Topic: In this post, you will find an example of how to build and deploy a basic artificial neural network scoring engine using PL/SQL.

Topic: In this short post you can find examples of how to use IPython/Jupyter notebooks for running SQL on Oracle.

Topic: In this post you will find a short discussion and pointers to the code of a few sample scripts that I have written using Linux BPF/bcc and uprobes for

Introduction

In the part 2 of 'Integrating Hadoop and Elasticsearch' blogpost series we look at bridging Apache Spark and Elasticsearch. I assume that you have access to Hadoop and Elasticsearch clusters and you are faced with the challenge of bridging these two distributed systems. As spark code can be written in scala, python and java, we look at the setup, configuration and code snippets across all these three languages both in batch and interactively.

Topic: in this post you can find examples of how to get started with using IPython/Jupyter notebooks for querying Apache Impala.