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In short: on context, (streaming) (big) data & information architecture.

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Connect Kafka to HDFS

Recently I’ve been playing with the Kafka Connect HDFS Connector as a means to get data from Kafka to HDFS. It’s a Kafka connector provided by the Confluent folks, and it’s a important part of their streaming data platform offering. You can’t call it ETL these days, but you can refer to it as building scalable ETL Pipelines.

Some history maybe? The Confluent platform already included Camus as a means to get data out of Kafka onto HDFS. It does the job, I can confirm. But what used to be LinkedIn’s Camus is being phased out and replaced by Goblin, the universal data ingestion framework for Hadoop. And since the release of Apache Kafka, there is Kafka Connect.

So why is this such an important part of a streaming data platform? At least 2 reasons come to mind: integration and analytics.

Kafka connectors enable the integration of existing enterprise datasources with Kafka, thus exposing existing systems as event data streams. It replaces all what has previously been integrated using custom ETL flows based on some technique of change data capture. The second kind of integration allows to offload Kafka events to other systems. The Kafka Connect HDFS Connector for example offloads Kafka events to HDFS. It can be a means to provide a backup, to archive historical data or to expose a copy of a stream of data in a more traditional (filesystem-like, batch processing) way.

Unless your Kafka cluster is set to have unlimited log retention, data will be removed from it eventually. A full archive will often be required however when you explore or mine your data and create analytic jobs. Often those jobs don’t produce any meaningful results unless you already have some history of data available to run them on.

Kafka is an essential part of a streaming data platform, but it is not such a platform on its own. A true platform also requires tools to ingest and offload data, and an easily accessible, filesystem-like access to the entire data archive. That’s often HDFS, used to bootstrap your analytics jobs with, to mine and query, to use with 3rd party tools etc.

In short: the Kafka Connect HDFS Connector is an essential part of a streaming data platform, and as such it’s provided by Confluent as a part of its core platform. It’s an implementation of a Kafka Connector that serves the enterprise integration of a streaming data platform, but it’s also an internal component of the platform that enables offloading Kafka data to HDFS.

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