Book Image

Learning Hunk

By : Dmitry Anoshin, Sergey Sheypak
Book Image

Learning Hunk

By: Dmitry Anoshin, Sergey Sheypak

Overview of this book

Hunk is the big data analytics platform that lets you rapidly explore, analyse, and visualize data in Hadoop and NoSQL data stores. It provides a single, fluid user experience, designed to show you insights from your big data without the need for specialized skills, fixed schemas, or months of development. Hunk goes beyond typical data analysis methods and gives you the power to rapidly detect patterns and find anomalies across petabytes of raw data. This book focuses on exploring, analysing, and visualizing big data in Hadoop and NoSQL data stores with this powerful full-featured big data analytics platform. You will begin by learning the Hunk architecture and Hunk Virtual Index before moving on to how to easily analyze and visualize data using Splunk Search Language (SPL). Next you will meet Hunk Apps which can easy integrate with NoSQL data stores such as MongoDB or Sqqrl. You will also discover Hunk knowledge objects, build a semantic layer on top of Hadoop, and explore data using the friendly user-interface of Hunk Pivot. You will connect MongoDB and explore data in the data store. Finally, you will go through report acceleration techniques and analyze data in the AWS Cloud.
Table of Contents (14 chapters)

Chapter 4. Adding Speed to Reports

One of the attributes of big data analytics is its velocity. In the modern world of information technology, speed is one of the crucial factors of any successful organization because even delays measured in seconds can cost money. Big data must move at extremely high velocities no matter how much we scale or what workloads our store must handle. The data handling hoops of Hadoop or NoSQL solutions put a serious drag on performance. That's why Hunk has a powerful feature that can speed up analytics and help immediately derive business insight from a vast amount of data.

In this chapter, we will learn about the report acceleration technique of Hunk, create new virtual indexes, and compare the performance of the same search with and without acceleration.