Apache Hive Vectorization

Apache Hive Vectorization was introduced newly in Apache Hive to improve query performance. By default, the Apache Hive query execution engine processes one row of a table at a time. The one row of data goes through all the operators in the query before the next row is processed, resulting in very inefficient CPU usage. In vectorized query execution, … read the rest

Apache Hive Cheat Sheet

Apache Hive Cheat Sheet is a summary of all functions and syntax for big data engineers and developers reference. It is divided into 5 parts.

Apache Hive Cheat Sheet – Query Syntax

Apache Hive Cheat Sheet – Metadata

Apache Hive Cheat Sheet – Query Compatibility

Apache Hive Cheat Sheet – Command Line

Apache Hive Cheat Sheet – Shell &  CLI

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Apache Hive CLI vs Beeline

Apache Hive development has shifted from the original Hive server (HiveServer1) to the new server (HiveServer2), and hence users and developers need to move to the new access tool. However, there’s more to this process than simply switching the executable name from “hive” to “beeline”.  Apache Hive was a heavyweight command-line tool that accepted the command and runs … read the rest

Apache Sqoop Introduction

In this article, Apache Sqoop Introduction, we will primarily discuss why this tool exists. Apache sqoop is part of Hadoop Core project or part of Hadoop Ecosystem project.

Bigdata tools which we use for transferring data between Hadoop and relational database servers is what we call Sqoop. Sqoop primarily stands for Sql for Hadoop.

In addition, there are … read the rest

Beginners Impala Tutorial

The Beginners Impala Tutorial covers key concepts of in-memory computation technology called Impala. It is developed by Cloudera. MapReduce based frameworks like Hive is slow due to excessive I/O operations. Cloudera offers a separate tool and that tool is what we call Apache Impala. This Beginners Impala Tutorial will cover the whole concept of Cloudera Impala and how this Massive … read the rest

Hadoop 3.0 Interview Question

Hadoop 3.0 or Bigdata jobs are in demand and in Hadoop 3.0 Interview Question article covers almost all the important topic including the reference link to other tutorials.

Hadoop 3.0 Interview Question

Hadoop 3.0 New Features Questions

What are the new features in Hadoop 3.0?

  1. Java 8 (jdk 1.8) as runtime for Hadoop 3.0
  2. Erasure Encoding for to reduce storage cost
  3. YARN Timeline Service
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Compare Unix Kernel Shells

This short article talks and compare UNIX kernel shells, which many technical folks are confused of. The Unix operating system used a shell program called the Bourne Shell. Then, slowly, many other shell kernel were developed for different flavors of UNIX operating system. The following is some brief information about different shells:

  • sh—Bourne shell
  • csh—C shell
  • ksh
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Hadoop 3.0 GPU

Hadoop 3.0 GPU : Hadoop is still behind high performance capacity due to CPUs’ limited parallelism, though. GPU (Graphical Processing Unit) accelerated computing involves the use of a GPU together with a CPU to accelerate applications to data processing on GPU cluster toward higher efficiency. However, GPU cluster has low level data storage capacity

Leveraged Hadoop 3.0 GPU Computing

MapReduce … read the rest