Recently, I worked on a project to consume Kafka message and ingest into Hive using Spark Structure Streaming. I mainly used python for most of the work with data pipeline construction, and this project is not exception.

Everything moved smoothly at the beginning when launching first Spark Structure Streaming to read simple message in raw text format from Kafka cluster. The problem was rising when I tried to parse the real Kafka message serialized in Avro format.

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To quickly launch spark and kafka for local development, docker would be the top choice as of its flexibily and isolated environment. This save lot of time for manually installing bunch of packages as well as conflicting issues.

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Apache Kafka is a distributed streaming platform. It is used for building real-time data pipelines and streaming apps. It is horizontally scalable, fault tolerant, wicked fast, and runs in production in thousands of companies.

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