Explore the world of streaming data platforms and Clojure in this 51-minute Devoxx conference talk. Dive into live coding demonstrations showcasing the creation of a Streaming Data Platform using Clojure, Apache Kafka, and Apache Cassandra. Learn about high availability, real-time stream processing, and linear scalability while discovering how to handle large volumes of log data. Gain insights into the power of Clojure's REPL for idea exploration and the JVM's capabilities in delivering scalable systems. Examine the characteristics and concerns of streaming data platforms, including data durability and partitioning. Investigate case studies and delve into the intricacies of Kafka and Cassandra, addressing their potential challenges. Get an overview of Clojure, its project structure, and how it interacts with data without object models. Explore system namespaces, keys, and the Kafka namespace while learning about partitions and data manipulation in this comprehensive talk on modern data processing techniques.
Overview
Syllabus
Introduction
What are streaming data platforms
Performance art
First computers
Loading screens
Ripples
Characteristics of Streaming Data Platforms
Data Durability
Streaming Data Platform Concerns
Case Study
Streaming Data Platform
Closure
Kafka
Partitions
Problems with Kafka
Cassandra
Cassandra Problems
Clojure Overview
What is Closure
Play
Clojure Projects
Cursive
Playing with data
No object models
System namespace
System keys
Kafka namespace
Kafka partitions
Taught by
Devoxx
Related Courses
-
Applying the Lambda Architecture with Spark, Kafka, and Cassandra
-
Streaming Big Data with Spark Streaming, Scala, and Spark 3!
-
Realtime Data Streaming - End-to-End Data Engineering Project
-
Apache Kafka Event Streaming Platform for .NET Developers
-
Apache Kafka and KSQL in Action - Let's Build a Streaming Data Pipeline
-
Apache Kafka and KSQL in Action - Let’s Build a Streaming Data Pipeline
