Lucidworks CTO and Apache Solr committer Grant Ingersoll shows what’s new and improved in Fusion 3.

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

3. Search is broken.

4. User expectations changed.
1

5. 2
Legacy search approaches
don’t scale and don’t
perform.

6. Understanding users and their
data is too slow and too
complicated.
3

8. Next Gen Results.
No PHd. Required.

9. • 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

10. Simplified App Dev

11. • 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

12. Best in class open source

13. • 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

14. 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 Spark
Cluster
Manager
RESTAPI
Admin UI
Lucidworks
View
LOGS FILE WEB DATABASE CLOUD
HDFS(Optional)
Core Services
• • •
ETL and Query Pipelines
Recommenders/Signals
NLP
Machine Learning
Alerting and Messaging
Security
Connectors
Scheduling

16. Index
Workbench
Parsers as 1st class
citizens
Change data before it
causes problems
View/configure pipeline
changes

17. Query
Workbench

18. 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

19. 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

20. A SQL Engine Unlike Any Other

21. 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

22. 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

23. 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

25. 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