Fusion in Action
Search, analytics, and big data with Lucidworks Fusion
Guy Sperry
  • ISBN 9781617295652
  • 425 pages (estimated)
  • printed in black & white

A great book for anybody wanting to set up a search engine using Fusion solution.

Julien Pohie
Lucidworks Fusion makes short work of large-scale analytics. Blending the powerful capabilities of best-in-class tools like the Apache Solr search engine and the Apache Spark data clustering framework, Fusion provides a lean, mature data search and analytics platform that expertly combines search and AI. In Fusion in Action, expert Guy Sperry shows you how to get the most from your data by building Fusion-based analytics solutions.

Lucidworks is providing all MEAP readers of Fusion in Action with an extended free trial edition of Fusion 4, so you can practice as you learn using the latest version of the software.
Table of Contents detailed table of contents

1 Meet Fusion

1.1.1 Search is the most powerful method of data interaction

1.1.2 Scale and data growth

1.1.3 Integrated data platforms

1.2 Fusion Overview

1.2.1 Built on an open-source foundation

1.2.2 Fusion Core Services

1.2.3 REST API

1.2.4 Security

1.3 When Fusion is the answer

1.3.2 Fusion for insight

1.3.3 Big data processing with Fusion

1.3.4 Analyze data with Fusion SQL

1.3.5 Fusion for data at scale

1.3.6 When Fusion isn’t the answer

1.4 Summary

2 Build your first search application

2.1 Search application overview

2.1.1 Components of a simple search application

2.1.2 Sample data for prototyping

2.2 Fusion APIs

2.2.1 Apps API

2.2.2 The Connectors Datasources API

2.2.3 The Connectors Jobs API

2.2.4 The Query Pipelines API

2.3 Create a search app with App Studio

2.3.1 Build a new search app UI

2.3.2 Use your search app

2.4 Summary

3 Fusion’s Search Features

3.2 Creating a document search solution

3.2.1 Components of a document search application

3.2.2 Download sample documents

3.2.3 Create a Fusion app to store documents and search features

3.2.4 Create a local filesystem datasource to index files

3.2.5 Import and index documents with an index job

3.3 Deliver search features with query pipelines

3.3.1 Pipeline concepts

3.3.2 Create a query pipeline

3.3.3 Configuring a query profile

3.4 Testing configurations with the Query Workbench

3.4.1 Launching the Query Workbench

3.4.2 Testing your changes outside the workbench

3.4.3 Comparing changes

3.5 Highlighting and content fragments

3.5.1 Content fragments

3.5.2 Highlighting search terms

3.6.1 Inverted Index

3.6.2 What are facets?

3.6.3 Field facets

3.7 Navigating results with filter queries

3.7.1 Filter queries for navigation

3.7.2 Filter queries for security and convenience

3.8 Incorporating features in your search application

3.8.1 Configure features for your ebooks search app

3.8.2 Experience your implemented features

3.9 Summary

4 Integrate your data with connectors and pipelines

4.1 Data integration overview

4.2 Ingest diverse data formats with parsers

4.2.1 Apache Tika parser stage

4.3 Built-in connectors

4.3.1 Other available connectors

4.4 Site search with the Web connector

4.4.1 Create a site search app

4.4.2 Keep data fresh with job triggers and schedules

4.5 Building a data app with the JDBC connector

4.5.1 The JDBC connector

4.5.2 Install a JDBC database

4.5.3 Create a JDBC Fusion app

4.5.4 Testing configurations with the index workbench

4.5.5 Index Job

4.6 ETL with index pipelines

4.6.1 Integrating external data at index time with the REST query index stage

4.6.2 Schema and datatypes

4.6.3 Range facets

4.6.4 Completing your data app

4.7 Summary

5 Additional Search Concepts/Features

5.1 Typeahead searching (autocomplete)

5.1.1 Why typeahead is an important feature

5.1.2 Implementing typeahead in Fusion

5.1.3 Implementing typeahead in App Studio

5.2 The JavaScript pipeline stage

5.2.1 Under the covers of the JavaScript pipeline stage

5.2.2 Integrating data at query time using the JavaScript pipeline stage

5.3 Digging deeper into App Studio

5.3.1 App Studio services, processors, and filters

5.3.2 Creating details pages in App Studio

5.4 Get users there faster with landing pages

5.5 Summary

6 Data analytics

7 Accessing data with Fusion SQL

8 Fusion’s NoSQL database features

9 Taking search to the next level with Fusion AI

10 Using Spark to process your data

11 Security

Appendixes

Appendix A: Preparing your environment

A.1 Setting up your environment

A.1.1 Hardware requirements

A.1.2 Operating systems

A.1.3 Terminal

A.1.4 Software prerequisites

A.2 Getting Fusion up and running

A.2.1 Download and start Fusion

A.2.2 Login and activate Fusion

A.2.3 Registering your copy of Fusion

A.2.4 License activation

A.2.5 The Fusion Quickstart

A.2.6 Stopping Fusion

A.2.7 Checking Fusion status

Appendix B: Query Pipeline Stages

B.1 Query pipeline stages

Appendix C: Datasource connectors

C.1 Fusion data connectors

C.2 Fusion custom connector framework

About the Technology

Fusion is a production-grade analytics platform built by Lucidworks on a foundation of the open source tools Apache Solr and Apache Spark. Designed to maximize your productivity, Fusion is easy to set up and configure, saving you valuable time and resources. Fusion can process vast amounts of data, offering business-ready features to search, analyze, and report. You’ll find built-in machine learning for relevance tuning and query intent as well as a full SQL engine and additional security. Fusion in Action covers the current Fusion 4 release, and it’s written so that you can learn this powerful platform using the free trial edition provided by Lucidworks.

About the book

Fusion in Action teaches you to build a full-featured data analytics pipeline, including document and data search and distributed data clustering. You’ll learn foundational search engine concepts, methods for efficient data interaction, and essential Fusion features, all explained in the author’s friendly, straightforward style. In the hands-on projects, you’ll use Fusion as an insight engine with analytics dashboards, and as a database, accessing application data via NoSQL and SQL methods. You’ll dive deep into aggregating data in Fusion and experience the power of search as you integrate and transform data from diverse sources using Fusion’s connectors and pipelines. With the valuable skills you’ll learn from this practical, easy-to-digest guide, you’ll implement solutions that give your customers the best, most relevant data results possible!

What's inside

  • Overview of Fusion and its core services
  • Building a search application
  • Fusion APIs including connectors and query pipelines
  • Creating a document search solution
  • Testing configurations with the query workbench
  • Navigating results with filter queries
  • Incorporating features in your search applications

About the reader

Intended for those familiar with the basics of SQL, JavaScript, XML, and JSON.

About the author

Guy Sperry is an independent consultant, implementing content management and search-related business solutions for state and local government for more than eighteen years. He’s been a member of the Lucidworks Customer Advisory Board since it was created.

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