I will discuss the experience at LinkedIn and elsewhere moving from batch-oriented ETL to real-time streams using Apache Kafka. I’ll talk about how the design and implementation of Kafka was driven by this goal of acting as a real-time platform for event data.
I will discuss the experience at LinkedIn and elsewhere moving from batch-oriented ETL to real-time streams using Apache Kafka. I’ll talk about how the design and implementation of Kafka was driven by this goal of acting as a real-time platform for event data.
This talk presents Apache Spark, Spark Streaming, Apache Kafka, Apache Cassandra and Akka as supporting Lambda architecture in the context of a fault tolerant, streaming big data pipeline.
This talk presents Apache Spark, Spark Streaming, Apache Kafka, Apache Cassandra and Akka as supporting Lambda architecture in the context of a fault tolerant, streaming big data pipeline. We will walk through the Fault Tolerance story with these technologies to build applications, and how to easily implement and integrate them in a Scala Akka application for real-time delivery of meaning at high velocity, in highly distributed and concurrent environments.
