Cloud Native Apache Pulsar Development 101 with Python
summary
Shows how to get a standalone cluster in docker, install the Python client and set JSON/Avro schemas for typed messages, produce and consume with message keys, and run serverless processing via Functions and Connectors. Demonstrates protocol handlers for MQTT, Kafka and WebSockets and querying tiered topic data with Pulsar SQL (Presto/Trino), Flink and Spark. A live websocket-driven sentiment-analysis function via WebSockets sends input to a topic, processes it and returns results, and examples scale from one Docker node up to petabyte deployments across thousands of machines.
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chapters (16)
- 0:00Introduction
- 1:29What is Apache Pulsar
- 3:56Pulsar architecture
- 6:24Messaging models
- 8:09Message structure
- 9:13Python functions
- 11:21Kubernetes Function Mesh
- 12:26Pulsar SQL and Presto
- 13:49Spark and Flink
- 15:57Setting up a Python Pulsar development environment
- 17:19Python message production
- 19:48Presto SQL queries
- 21:10Sentiment analysis function
- 22:55Flink real-time processing
- 25:41Python message consumption
- 26:22Community resources
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