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Reynold Xin
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Reynold Xin oversees technical contributions to Apache Spark at Databricks, including DataFrames and Project Tungsten. He led Spark’s 2014 Daytona GraySort contest, setting a world record with 30x higher per-node efficiency than Hadoop. Previously, as a PhD student at UC Berkeley AMPLab, his work focused on scalable data processing; he authored highly cited papers in SIGMOD 2011, 2013, and 2015 and won the Best Demo Award at VLDB 2011 and SIGMOD 2012.
Bio from: Databricks DATA + AI Summit 2023
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Reynold Xin, Co-founder and Chief Architect, Databricks shares the latest innovation coming out of the Apache Spark™ open source project including a preview of the anticipated release of Spark 4.0
Speakers: Reynold Xin, Co-founder and Chief Architect, Databricks Tareef Kawaf, President, Posit Sofware, PBC
Reynold Xin explains the evolution of Apache Spark™, outlining several historical challenges and how the Spark community worked to make improvements, including the addition of PySpark.
Speaker: Reynold Xin, Co-founder and Chief Architect at Databricks
Databricks Co-founder and Chief Architect, Reynold Xin, on the evolution of Apache Spark™ and what's next, including Spark Connect and a preview of Apache Spark™ 4.0
Speaker: Reynold Xin, Co-founder and Chief Architect, Databricks
Reynold Xin, Co-founder and Chief Architect at Databricks, presented during Data + AI Summit 2024 on Databricks SQL and its advancements and how to drive performance improvements with the Databricks Data Intelligence Platform.
Speakers: Reynold Xin, Co-founder and Chief Architect, Databricks Pearl Ubaru, Technical Product Engineer, Databricks
Main Points and Key Takeaways (AI-generated summary)
Introduction of Databricks SQL: - Databricks SQL was announced four years ago and has become the fastest-growing product in Databricks history. - Over 7,000 customers, including Shell, AT&T, and Adobe, use Databricks SQL for data warehousing.
Evolution from Data Warehouses to Lakehouses: - Traditional data architectures involved separate data warehouses (for business intelligence) and data lakes (for machine learning and AI). - The lakehouse concept combines the best aspects of data warehouses and data lakes into a single package, addressing issues of governance, storage formats, and data silos.
Technological Foundations: - To support the lakehouse, Databricks developed Delta Lake (storage layer) and Unity Catalog (governance layer). - Over time, lakehouses have been recognized as the future of data architecture.
Core Data Warehousing Capabilities: - Databricks SQL has evolved to support essential data warehousing functionalities like full SQL support, materialized views, and role-based access control. - Integration with major BI tools like Tableau, Power BI, and Looker is available out-of-the-box, reducing migration costs.
Price Performance: - Databricks SQL offers significant improvements in price performance, which is crucial given the high costs associated with data warehouses. - Databricks SQL scales more efficiently compared to traditional data warehouses, which struggle with larger data sets.
Incorporation of AI Systems: - Databricks has integrated AI systems at every layer of their engine, improving performance significantly. - AI systems automate data clustering, query optimization, and predictive indexing, enhancing efficiency and speed.
Benchmarks and Performance Improvements: - Databricks SQL has seen dramatic improvements, with some benchmarks showing a 60% increase in speed compared to 2022. - Real-world benchmarks indicate that Databricks SQL can handle high concurrency loads with consistent low latency.
User Experience Enhancements: - Significant efforts have been made to improve the user experience, making Databricks SQL more accessible to analysts and business users, not just data scientists and engineers. - New features include visual data lineage, simplified error messages, and AI-driven recommendations for error fixes.
AI and SQL Integration: - Databricks SQL now supports AI functions and vector searches, allowing users to perform advanced analysis and query optimizations with ease. - The platform enables seamless integration with AI models, which can be published and accessed through the Unity Catalog.
Conclusion: - Databricks SQL has transformed into a comprehensive data warehousing solution that is powerful, cost-effective, and user-friendly. - The lakehouse approach is presented as a superior alternative to traditional data warehouses, offering better performance and lower costs.
Speakers: - Alexander Booth, Asst Director of Research & Development, Texas Rangers - Ali Ghodsi, Co-Founder and CEO, Databricks - Bilal Aslam, Sr. Director of Product Management, Databricks - Darshana Sivakumar, Staff Product Manager, Databricks - Hannes Mühleisen, Creator of DuckDB, DuckDB Labs - Matei Zaharia, Chief Technology Officer and Co-Founder, Databricks - Reynold Xin, Chief Architect and Co-Founder, Databricks - Ryan Blue, CEO, Tabular - Tareef Kawaf, President, Posit Software, PBC - Yejin Choi, Sr Research Director Commonsense AI, AI2, University of Washington - Zeashan Pappa, Staff Product Manager, Databricks
About Databricks Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Conde Nast, Rivian, and Shell, and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data… Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc
Databricks Data + AI Summit 2024 Keynote Day 1
Experts, researchers and open source contributors — from Databricks and across the data and AI community gathered in San Francisco June 10 - 13, 2024 to discuss the latest technologies in data management, data warehousing, data governance, generative AI for the enterprise, and data in the era of AI.
Hear from Databricks Co-founder and CEO Ali Ghodsi on building generative AI applications, putting your data to work, and how data + AI leads to data intelligence.
Plus a fireside chat between Ali Ghodsi and Nvidia Co-founder and CEO, Jensen Huang, on the expanded partnership between Nvidia and Databricks to accelerate enterprise data for the era of generative AI
Product announcements in the video include: - Databricks Data Intelligence Platform - Native support for NVIDIA GPU acceleration on the Databricks Data Intelligence Platform - Databricks open source model DBRX available as an NVIDIA NIM microservice - Shutterstock Image AI powered by Databricks - Databricks AI/BI - Databricks LakeFlow - Databricks Mosaic AI - Mosaic AI Agent Framework - Mosaic AI Agent Evaluation - Mosaic AI Tools Catalog - Mosaic AI Model Training - Mosaic AI Gateway
In this keynote hear from: - Ali Ghodsi, Co-founder and CEO, Databricks (1:45) - Brian Ames, General Motors (29:55) - Patrick Wendall, Co-founder and VP of Engineering, Databricks (38:00) - Jackie Brosamer, Head of AI, Data and Analytics, Block (1:14:42) - Fei Fei Li, Professor, Stanford University and Denning Co-Director, Stanford Institute for Human-Centered AI (1:23:15) - Jensen Huang, Co-founder and CEO of NVIDIA with Ali Ghodsi, Co-founder and CEO of Databricks (1:42:27) - Reynold Xin, Co-founder and Chief Architect, Databricks (2:07:43) - Ken Wong, Senior Director, Product Management, Databricks (2:31:15) - Ali Ghodsi, Co-founder and CEO, Databricks (2:48:16)
0:00 Open 6:08 Ali Ghodsi & Marc Andreessen 32:06 Reynold Xin 48:09 Michael Armbrust 1:00:00 Matei Zaharia & Panel 1:27:10 Hannes Muhleisen 01:37:43 Harrison Chase 01:49:15 Lin Qiao 02:05:03 Jitendra Malik 02:21:15 Arsalan & Eric Schmidt
0:00 Opener 01:18- Ali Ghodsi, Databricks 06:53 - Satya Nadella, Microsoft 15:50 Ali Ghodsi, Databricks 20:40 Larry Feinsmith, JP Morgan Chase 41:09 Ali Ghodsi, Databricks 45:07 Matei Zaharia, Databricks 52:31 Weston Hutchins, Databricks 58:36 Ali Ghodsi, Databricks 1:02:05 Naveen Rao, MosaicML 1:12:15 Patrick Wendell, Databricks 1:27:57 Kasey Uhlenhuth, Databricks 1:39:18 Sai Pradhan Ravuru, Jetblue 01:47 Ali Ghodsi, Databricks 1:49:20 Reynold Xin, Databricks 2:05:07 Ali Ghodsi, Databricks 2:09:26 Matei Zaharia, Databricks 2:17:24 Caryl Yuhas, Databricks 2:24:12 Zaheera Valani, Databricks 2:39:55 Wassym Bensaid, Rivian
Join the Day 1 keynote to hear from Databricks co-founders - and original creators of Apache Spark and Delta Lake - Ali Ghodsi, Matei Zaharia, and Reynold Xin on how Databricks and the open source community is taking on the biggest challenges in data. The talks will address the latest updates on the Apache Spark and Delta Lake projects, the evolution of data lakehouse architecture, and how companies like Adobe and Amgen are using lakehouse architecture to advance their data goals.
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Data + AI Summit Keynote talks from Reynold Xin and Karthik Ramasamy
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Day 1 Morning Keynote | Data + AI Summit 2022 Welcome & "Destination Lakehouse" | Ali Ghodsi Apache Spark Community Update | Reynold Xin Streaming Lakehouse | Karthik Ramasamy Delta Lake | Michael Armbrust How Adobe migrated to a unified and open data Lakehouse to deliver personalization at unprecedented scale | Dave Weinstein Data Governance and Sharing on Lakehouse |Matei Zaharia Analytics Engineering and the Great Convergence | Tristan Handy Data Warehousing | Shant Hovespian Unlocking the power of data, AI & analytics: Amgen’s journey to the Lakehouse | Kerby Johnson
Get insights on how to launch a successful lakehouse architecture in Rise of the Data Lakehouse by Bill Inmon, the father of the data warehouse. Download the ebook: https://dbricks.co/3ER9Y0K
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Reynold Xin is a technical co-founder and Chief Architect at Databricks. He's also a co-creator and the top contributor to the Apache Spark project. In this casual conversation with Drew Banin, co-founder and Chief Product Officer at dbt Labs, the two will be discussing the data infrastructure trends they find most interesting. Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com. The Analytics Engineering Podcast is brought to you by dbt Labs.