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I'm in the process of migrating an ACID-based monolith to an event-based microservice architecture. In the monolith potentially large files are stored in a database and I want to share this information (including the file content) with the microservices.

My approach would be to split the file into numbered blocks and send several messages (e.g. 1 FileCreatedMessage with metadata and an id followed by n FileContentMessage containing the block and its sequence number). On the receiving side messages may not arrive in order. Therefore I'd store the blocks from messages, order and join them and store the result.

Is there any approach which allows me to stream the data through Kafka with one message or another approach without the overhead of implementing the spliting, order and join logic for several messages?

I noticed Kafka Streams. It seems to solve different problems than this one.

Kalle Richter
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2 Answers2

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Kafka is not the right approach for sending the large files. First, you need to ensure that chunks of one message will come to the same partition, so that they will be processed by the one instance of the consumer. The weak point here is that your consumer may fail in the middle loosing the chunks, it gathered. If you store the chunks in some storage (database) until all of them arrive, then you will need the separate process to assemble them. Your will also need to think about what happens if you loose a chunk or have an error during the processing of the chunk. We were thinking about this question in our company and decided not to send files through Kafka at all, keep them in storage and send the reference to them inside the message.

This article summarizes pros and cons.

Kafka streams will not help you here as it is the framework, which contains high level constructs for working with streams, but it just works over Kafka.

Katya Gorshkova
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I try not to use Kafka to hold large file content. Instead, I store the file on a distributed file system (usually HDFS, but there are other good ones) and then put the URI into the Kafka message along with any other meta data I need. You do need to be careful of replication times within the distributed file system if processing your Kafka topic on a distributed streaming execution platform (e.g. Storm or Flink). There may be instances where the Kafka message is processed before the DFS can replicate the file for access by the local system, but that's easier to solve than the problems caused by storing large file content in Kafka.

Chris Gerken
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