Fluid - Kubernetes Native Distributed Dataset Orchestrator and Accelerator
Explore Fluid, a Kubernetes-native solution for optimizing big data and AI applications. Learn about its architecture, features, and how it enhances performance in cloud environments.
Heterogeneous Multi-Cluster Full Mesh Communication Practice
高性能异构多Kubernetes集群网络通信方案：结合主机路由和vxlan隧道技术，实现第二层和第三层网络的高效连接，支持大数据业务跨集群访问。
Scala - The Unpredicted Lingua Franca for Data Science
Explore how Scala has become a key language for data science, offering distributed computing capabilities and integrating seamlessly with big data technologies like Apache Spark.
The Future of Scala Performance on Big Data
Explore Scala's performance improvements for big data, including new benchmarks and optimizations for datacenter workloads. Learn about advancements in Scala's efficiency for large-scale data processing.
Build a Recommender System in Apache Spark and Integrate It Using Akka
Learn to build and integrate a recommender system using Apache Spark and Akka HTTP. Discover the components of recommender systems and implement one with machine learning techniques in a practical, hands-on session.
Distributed Real Time Stream Processing - Why and How
Explore state-of-art distributed streaming frameworks, their differences, trade-offs, and use-cases. Learn how to choose between Spark Streaming, Storm, Samza, and Flink for your specific streaming needs.
Beyond Shuffling - Scaling Apache Spark
Scaling Apache Spark: best practices for large datasets, performance optimization, and efficient data processing techniques. Covers counters, key/value operations, caching, and functional transformations with Datasets.
The Future of Scala Performance on Big Data
Explore Scala's performance in big data, new benchmarks, and optimizations for datacenter computing. Gain insights into Apache Spark and real-world workload improvements.
Postcapitalism
Exploring how open-source software disrupts capitalism, examining economic transitions, and discussing strategies for companies to remain relevant in a world of free software.
Distributed Real-Time Stream Processing - Why and How
Explore state-of-the-art open-source distributed streaming frameworks, their trade-offs, use-cases, and selection criteria. Learn about Spark Streaming, Storm, Samza, and Flink for modern data processing challenges.
Scala - The Unpredicted Lingua Franca for Data Science
Explore Scala's emergence as a key language for data science, covering its features, integration with Spark, and advantages over traditional options like Python and R.
Swave - A Fresh Reactive Streams Implementation
Explore Swave, a high-performance Reactive Streams implementation for Scala. Learn its design, features, and advantages over existing solutions for asynchronous stream processing.
Scala and the JVM as a Big Data Platform - Lessons from Apache Spark
Explore Scala's advantages for Big Data, focusing on Apache Spark. Learn about JVM optimizations and Spark's Tungsten project for improved performance in data processing.
Data in Motion - Streaming Static Data Efficiently in Akka Persistence
Explore efficient streaming of static data in Akka Persistence, focusing on architecture, implementation, and performance tuning for distributed systems and enterprise applications.
Connecting Reactive Applications with Fast Data Using Reactive Streams
Explore integrating Spark Streaming with reactive applications using Reactive Streams. Learn about Spark's streaming model, back pressure support, and see a demo of a fully integrated reactive system.
Build a Recommender System in Apache Spark and Integrate it Using Akka
Learn to build and integrate a recommender system using Apache Spark and Akka HTTP. Discover the basics of machine learning and how to implement it in your applications for personalized recommendations.
Stream Away with Scala
Explore functional programming concepts for streaming data processing, focusing on real-time robot control using Scala. Learn about Potassium framework, Akka actors, and data visualization with React and Scala.js.
Fault Tolerance in Distributed Systems - A Case Study in Apache Spark
Explore fault tolerance in distributed systems through Apache Spark, examining design principles, challenges, and lessons for building robust systems and understanding their limitations.
Learn You Akka Streams for Great Good
Learn essential and advanced Akka Streams features through live coding and demos. Covers materialized values, cyclic graphs, and practical applications in Scala for efficient stream processing.
Akka Streams for High Throughput Data Processing
Explore high-throughput data processing with Akka Streams, comparing it to Akka Actors. Learn best practices, optimization techniques, and when to switch to Streams for improved performance in large-scale data transfer systems.
Analyzing Pwned Passwords with Apache Spark
Learn to analyze large datasets of compromised passwords using Apache Spark, exploring data processing techniques and security implications in this Scala Days conference talk.