This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
The document contains code snippets for configuring Spring Batch jobs and steps using Java configuration. It defines beans for a tasklet step, item readers, item processors, item writers, and more. It also includes code for configuring the database schema for metadata tables and running jobs from the command line.
The document contains code snippets for configuring Spring Batch jobs and steps using Java configuration. It defines beans for a tasklet step, item readers, item processors, item writers, and more. It also includes code for configuring the database schema for metadata tables and running jobs from the command line.