How To Get Lifetime FREE Cloud Platform For Students and Developers

Oracle has a Lifetime FREE Cloud Platform For Big Data Practice . OCI or Oracle Cloud Infrastructure is made a Lifetime Free edition for Building , Testing deploying any sample apps for Free. This includes Two Compute Virtual Mchine 1/8 OCPU and 1 GB memory each ,  SSD & Object Storage , Load Balancer etc. You can use these AS LONG AS YOU WANT - there in Absolutely NO TIME LIMITATION. On Top of this , you can also Add A Trial Version of Other Oracle Cloud Services for 30 Days.

List of Kafka Commands Cheatsheet

List of Kafka Commands Cheatsheet. In this post we will explore the common kafka commands , kafka consumer group command , kafka command line , kafka consumer command , kafka console consumer command, kafka console producer command .

MuseNet – Music Created by Artificial Intelligence !

MuseNet by OpenAI is a 72-Layer Deep Neural Network program that can generate music. It can incorporate different instruments - piano, drums, bass, guitaras etc. as well as various genre of music – country , jazz , rock etc. You feed MuseNet with notes from various artists or bands .Subsequently it learns , understands and generates or tries to generate music of a similar genre .

Google Cloud GCP Tutorial

Google Cloud GCP Tutorial (Being Updated)

PySpark Tutorial

PySpark Tutorial

How To Troubleshoot Docker - Best Practices ?

In this post, we will explore - How To Troubleshoot Docker Applications - Best Practices. We present below some of the step by step process to manage Docker applications that will negate any possible issues.  

How to use Broadcast Variable in Spark ?

In this post , we will see - How to use Broadcast Variable in Spark . Broadcast variables can be tricky if the concepts behind are not clearly understood. This creates errors while using any Broadcast variables down the line. Broadcast variables are used to implement map-side join, i.e. a join using a map. e.g.. Lookup tables or data are distributed across nodes in a Distributed cluster using broadcast . And they are then used inside map (to do the join implicitly).

Dataframe Operation Examples in PySpark

Dataframe Operation Examples in PySpark.

Python Flavours - CPython, Cython, Jython, IronPython, PyPy Differences

In this post, Let's understand the different implementations of Python available. Python Flavours -

• CPython
• Cython
• Jython
• IronPython
• PyPy

Python Instance, Static & Class Method Differences

In this post, we will try to understand Python Instance, Static & Class Method Differences.

Python Read and Write File (JSON, XML, CSV, Text) - Sample Code

Python Read and Write File (JSON, XML, CSV, Text) - Sample Code. In this post , we will see - How To Read & Write Various File Formats in Python.  

Difference Between React.js (React) and React Native ?

React.js (React) vs React Native Differences: React helps to make efficient interactive UIs. You can design views for each state in the app. React Native can be used in Android and iOS projects or you can create a complete new app from scratch.

How To Code a PySpark Cassandra Application ?

This post is a Sample Code How To Code a PySpark Cassandra Application ?. It reads the data from a csv file and writes to Spark Table.  

Sample Code for Spark Cassandra Scala Application

This is a step by step sample code to Read write a Spark Cassandra Application in Scala. It shows how to Connect , Read into a Cassandra Table from a Spark Application. It uses Spark RDD Structure.

How To Read Kafka From Spark Structured Streaming ?

This post provides a very basic Sample Code - How To Read Kafka From Spark Structured Streaming.

Sample Code - Spark Structured Streaming vs Spark Streaming

This post gives Sample Code - Spark Structured Streaming vs Spark Streaming . Major differences between Spark Structured Streaming vs Spark Streaming are -

• Structured Streaming works on Dataframe\Datasets whereas Spark Streaming works on RDDs
• Structured Streaming doesn't work on Micro-batch format(like Spark Streaming does). Rather each data stream row is processed and updated into the unbounded result table. So Structured Streaming is more Real-Time from that aspect.