Description
Apache Spark has introduced a powerful engine for distributed data processing, providing unmatched capabilities to handle petabytes of data across multiple servers. Its capabilities and performance unseated other technologies in the Hadoop world, but while Spark provides a lot of power, it also comes with a high maintenance cost, which is why we now see innovations to simplify the Spark infrastructure. Kubernetes on its right, offers a simplified way to manage infrastructure and applications. Kubernetes provides a practical approach to isolated workloads, limiting the use of resources, deploying on-demand and scaling as needed. Yaron Haviv will explain how to work with Kubernetes to build a single workflow with Spark based data preparation and ML tasks. Participants will learn how running Spark with Kubernetes enables users to unify analytics and data science on a single cloud-native architecture and eliminate the overhead of an extra big data cluster managed by different tools. About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: https://databricks.c…
Description from YouTube. Full content on the video page.
More from Databricks
NewsHow adidas Uses Databricks to Build Better Products
Adidas uses Databricks' lakehouse platform to centralize all its data—from product to football-related insights—enabling faster analytics across the organization. The company's Genie analytics tool helps analysts spend less time processing data and more time on strategic questions, ultimately supporting better product development.
NewsDatabricks for Good x MapAid: Creating a Searchable Database for Groundwater Discovery
MapAid is using Databricks to build an AI groundwater mapping system called Well Mapper that processes water documents to identify accurate well-drilling locations in Ethiopia, improving on the current 30% success rate. The system analyzes 400 well logs in half a second instead of four weeks, with potential to double Ethiopia's food supply through improved irrigation.
NewsHow Databricks Genie Automates Data Workflows with Genie Ontology and Scheduled Tasks
Databricks Genie enables ontology by default for business context and adds document/PDF uploads, direct Unity Catalog queries, and team collaboration features in chat. Scheduled tasks automate recurring workflows with embedded visualizations and PDF outputs accessible across web, desktop, and mobile platforms.
NewsGenie One Beginner's Guide: Explore Data & Automate Tasks
Genie One helps subject matter experts avoid repetitive questions by using business ontology to understand your data and run real-time queries that generate instant answers and shareable reports. The tool can also automate monitoring with conditional alerts that only notify you when specific business thresholds are met.
TutorialsHow to Schedule Automated Meeting Prep in Genie One
Genie One allows users to connect multiple data sources like Databricks tables and Google Calendar, then create analyses through natural language prompts to prepare for customer meetings. The platform can schedule these analyses to run automatically on a recurring basis and deliver results via email or mobile app.
TutorialsHow to Build Custom Skills in Genie One in Minutes
Genie 1 can populate business report templates by analyzing their format and running SQL queries against organizational data. Users can save these report workflows as reusable skills that execute with a single slash command, enabling automation of recurring reports.