Data: https://www-odi.nhtsa.dot.gov/downloads/

Search is broken.

` `User expectations changed.

1

2

Legacy search approaches don’t scale and don’t

perform.

Understanding users and their data is too slow and too

complicated.

3

Next Gen Results. No PHd. Required.

• Machine Driven: Signals aggregation learn and automatically tune relevancy and drive recommendations out of the box.

• Rules when you need them: Point-and-click query pipeline configuration and rules module allow fine-grained control of results.

• Science, not guessing: Experiment management and bandits do the heavy lifting of systematically testing new ideas

Simplified App Dev

• Over 50 connectors and a robust parsing framework to seamlessly ingest all your data

• Powerful pipeline stages: Customize fields, stages, synonyms, boosts, facets, and dozens of other powerful search stages.

• Point and click Indexing configuration and iterative simulation of results for full control over your ETL process

• Your security model enforced end-to-end from ingest to search across your different datasources

Best in class open source

• 24/7/365 Customer Success: Support and advice for all of your search and machine learning problems

• Backed by the team that makes Solr

• Enables you to attract and grow top talent in your organization

Best in class open source

Fusion Architecture

SECURITY BUILT-IN

Shards Shards

Apache Solr

Apache Zookeeper

ZK 1

Leader Election

Load Balancing

ZK N

Shared Config Management

Worker Worker

Apache SparkCluster

Manager

RE

ST A

PI

Admin UI

Lucidworks View

LOGS FILE WEB DATABASE CLOUD

HD

FS

(Op

tio

nal

)

Core Services

• • •

ETL and Query Pipelines

Recommenders/Signals

NLP

Machine Learning

Alerting and Messaging

Security

Connectors

Scheduling

Index Workbench

Parsers as 1st class citizens

Change data before it causes problems

View/configure pipeline changes

Query Workbench

Powered by Solr 6.3 and Spark 1.6.3• Support for Machine Learning Models

• Additional Kerberos support

• New Query time joins

•New SQL/Streaming features and operators

•Better support for high cardinality field faceting

• Improved Memory Mgmt and Perf.

• Query Planner Optimizations

• Faster null-safe joins and columnar caching performance

• ML Pipeline Persistance

• SQL queries on flat files

But Wait, There’s More!

• PySpark, Notebook support (Zeppelin, Jupyter)

• Clickstream Boosting Out of the Box

• Numerous Performance Improvements

• Streaming document support and better large/archival doc support

• Faster, more scalable aggregations

• Distributed Index Pipelines

• Content-based Recommendations Pipeline

• More connectivity at Query Time via the Query REST/RPC Stage

A SQL Engine Unlike Any Other

Basic Features

• Connect to any Spark Data Source for cross data source joins

• Standard connectivity with ODBC/JDBC so all your existing SQL tools work

• Leverages both Spark and Solr SQL for intelligent query planning and optimizations

Fusion Only Features

• Full Solr syntax for search and streaming expressions available means leveraging:

• Solr Query Syntax for the ultimate sort function

• Graph Traversals for complex relationships

• Machine Learning scoring functions built-in

• First class support for text, numerics, spatial and custom data types

• The Fusion Catalog makes it easy to create views and enforce data governance

• Create views for common scenarios and to increase performance of high-usage queries

• Overlay Fusion security for total control of data assets

Searching for Pretty Pictures

• Harness the power of Fusion with existing Business Intelligence tools and Data Science Notebooks

• Tableau Public, Desktop, etc. all work with Fusion 3

• Works with Apache Zeppelin, Jupyter/iPython and others

Resources

• Download Fusion 3.0: https://lucidworks.com/download/

• Contact Us: https://lucidworks.com/company/contact/

• Fusion documentation: https://doc.lucidworks.com/index.html

• Webinar recording will be available at http://lucidworks.com

• Tableau Public Web Data Connector: https://github.com/lucidworks/tableau-fusion-wdc