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Scala In Demand Technologies Built On Scala

Knowledge Hut

In late 2013, Cloudera, the largest Hadoop vendor supported the idea of replacing MapReduce with Apache Spark. Spark effectively provides an alternative for Hadoop’s two stage MapReduce model. Apache Spark Apache Spark can be considered as the replacement of MapReduce.

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The Evolution of Table Formats

Monte Carlo

Let’s revisit how several of those key table formats have emerged and developed over time: Apache Avro : Developed as part of the Hadoop project and released in 2009, Apache Avro provides efficient data serialization with a schema-based structure.

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5 Reasons why Java professionals should learn Hadoop

ProjectPro

According to the Industry Analytics Report, hadoop professionals get 250% salary hike. If you are a java developer, you might have already heard about the excitement revolving around big data hadoop. There are 132 Hadoop Java developer jobs currently open in London, as per cwjobs.co.uk

Java 52
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Hadoop- The Next Big Thing in India

ProjectPro

Big Data Hadoop skills are most sought after as there is no open source framework that can deal with petabytes of data generated by organizations the way hadoop does. 2014 was the year people realized the capability of transforming big data to valuable information and the power of Hadoop in impeding it. The talent pool is huge.”

Hadoop 52
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What are the Pre-requisites to learn Hadoop?

ProjectPro

Hadoop has now been around for quite some time. But this question has always been present as to whether it is beneficial to learn Hadoop, the career prospects in this field and what are the pre-requisites to learn Hadoop? between 2013 - 2020. So many people have told you that Hadoop is the hottest technology right now.

Hadoop 52
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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

Evolution of Open Table Formats Here’s a timeline that outlines the key moments in the evolution of open table formats: 2008 - Apache Hive and Hive Table Format Facebook introduced Apache Hive as one of the first table formats as part of its data warehousing infrastructure, built on top of Hadoop.

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5 Reasons Why ETL Professionals Should Learn Hadoop

ProjectPro

Hadoop’s significance in data warehousing is progressing rapidly as a transitory platform for extract, transform, and load (ETL) processing. Mention about ETL and eyes glaze over Hadoop as a logical platform for data preparation and transformation as it allows them to manage huge volume, variety, and velocity of data flawlessly.

Hadoop 52