fusion 3 overview webinar
Post on 16-Feb-2017
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• 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
• 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
• 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
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
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
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