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)

Introducing Pivot


A data model is a semantic layer that makes Hunk a powerful analytical tool for business users. Pivot is a user-friendly interface where anyone can create complex multidimensional reports or interactive dashboards that can be distributed across colleagues.

Let's explore the Pivot UI. Click on Pivot, select the Unicorn Fashion Digital Analytics data model, and Pivot UI will come up:

Pivot UI consists of the following main elements:

Pivot element

Definition

Filters (1)

This is used to cut down the result count for the object. There are restrictions in addition to those that might be applied via constraints or other means in the object's definition. All Pivots are filtered by time range. We can optionally add one or more filters by attribute.

Split Rows (2)

This splits out the Pivot results by row. For example, we could use this element to configure a page view object to display a row for each month of the past year, thus breaking out the page view count by month.

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