Recap of Hadoop News for February

Recap of Hadoop News for February

News on Hadoop- February 2016

Hadoop News 2016

Hadoop has turned 10, but it still has a long way to go in terms of enterprise adoption. February 3, 2016. 

At the 10th birthday of Hadoop, which is fast becoming everyone’s favorite big data technology – is gearing up for enterprise wide adoption. According to Forrester Wave: Big Data Hadoop Distributions, Q1 2016, within a span of 2 years, 100% of the large enterprises will adopt Hadoop or other Hadoop technologies like Apache Spark.

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Work on Hands on Projects in Big Data and Hadoop

MapR claims the first innovative patent on opensource Hadoop. February 5, 2016.

Hadoop is open source, but there are several Hadoop vendors in the market, who create enterprise relevant extension son Hadoop to make it more compatible for enterprise adoption. MapR’s Sr. Vice President of product management, Anil Gadre, said that there is a lot of scope for foundational innovation in any open source framework. This helps customers gain a competitive edge.

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Looker develops new layout which supports all Hadoop SQL dialects. February 9, 2016.

When Apache Hive 1.2 was launched last May, it supported the SQL Union functionality that is important for querying in Hadoop. After that every new version that was released like Spark MLib, Impala Project all supported the Hadoop SQL dialects. Looker allows for larger dialects in the Hadoop ecosystem to support business intelligence.

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Hortonworks reports more than 100% increase in revenue for the fiscal year 2015. February 11, 2016.

The popular Hadoop vendor – Hortonworks has reported an annual increase in revenue of up to 165%. While this is all good, their expenses still outweigh the sales revenue. The Hadoop vendor is still young and is rapidly growing. While their costs are more extensive than their revenue, their executive estimate that in the Q4 of 2016, after adjusting EBITDA, they will break even.

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Hadoop enters its 3rd Phase of Maturity. February 16, 2016. 

In the 10 years that Hadoop has been a part of the Big Data community, it has undergone several changes and modifications to suit the current Big Data need. Currently Hadoop is in the phase of Hadoop enterprise adoption where it is accessible to all business units.

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Hadoop is becoming more entrenched in Banking and Government sectors. February 19, 2016. 

A Research and Markets report – “World Hadoop Market, Opportunities and Forecasts, 2014 – 2021” – states that not only is the Big Data and Hadoop market on the rise, but it is actually getting deeply entrenched into critical industries like banking and the government. This report also predicts that by 2021, the global Hadoop market’s revenue will rise to $84.6 bn.

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Spring Technologies all set to make Hadoop workflows and YARN easier to work with. February 21, 2016.

Springone2GX is designed to keep the developers up-to-date on the latest big data technologies and upgrades. With the adoption of Spring cloud technology for Apache Hadoop, workflows with MapReduce, Hive and Pig is set to become much easier and Spring will provide portability across Cloudera, Hortonworks and MapR distributions.

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Yahoo bares it out in the open with their CaffeOnSpark Deep Learning framework for Hadoop. February 24, 2016. 

Yahoo has open sourced some of its key Artificial Intelligence technologies. Last year, Yahoo built a library called CaffeOnSpark which is to perform the popular AI of deep learning on the vast data present in their Hadoop file systems. CaffeOnSpark is written primarily in C++ and was developed to take advantage of Apache Spark which can perform certain computations faster than Hadoop.

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For the complete list of big data companies and their salaries- CLICK HERE



Work on hands on projects on Big Data and Hadoop with Industry Professionals

Relevant Projects

Data Mining Project on Yelp Dataset using Hadoop Hive
Use the Hadoop ecosystem to glean valuable insights from the Yelp dataset. You will be analyzing the different patterns that can be found in the Yelp data set, to come up with various approaches in solving a business problem.

Create A Data Pipeline Based On Messaging Using PySpark And Hive - Covid-19 Analysis
In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.

Real-Time Log Processing in Kafka for Streaming Architecture
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.

Implementing Slow Changing Dimensions in a Data Warehouse using Hive and Spark
Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.

Data processing with Spark SQL
In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.

Spark Project-Analysis and Visualization on Yelp Dataset
The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.

Data Warehouse Design for E-commerce Environments
In this hive project, you will design a data warehouse for e-commerce environments.

Analysing Big Data with Twitter Sentiments using Spark Streaming
In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

Finding Unique URL's using Hadoop Hive
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.

Yelp Data Processing Using Spark And Hive Part 1
In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.