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Fusion 3 Overview Webinar


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

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Fusion 3 Overview Webinar

  1. 1. Data:
  2. 2. Search is broken.
  3. 3. User expectations changed. 1
  4. 4. 2 Legacy search approaches don’t scale and don’t perform.
  5. 5. Understanding users and their data is too slow and too complicated. 3
  6. 6. Next Gen Results. No PHd. Required.
  7. 7. • 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
  8. 8. Simplified App Dev
  9. 9. • 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
  10. 10. Best in class open source
  11. 11. • 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
  12. 12. 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
  13. 13. Index Workbench Parsers as 1st class citizens Change data before it causes problems View/configure pipeline changes
  14. 14. Query Workbench
  15. 15. 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
  16. 16. 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
  17. 17. A SQL Engine Unlike Any Other
  18. 18. 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
  19. 19. 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
  20. 20. 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
  21. 21. Resources • Download Fusion 3.0: • Contact Us: • Fusion documentation: • Webinar recording will be available at • Tableau Public Web Data Connector: