As you may already realise, Kafka is not just a fancy message bus, or a pipe for big data. It’s an event streaming platform! If this is news to you, I’ll wait here whilst you read this or watch this…
Let’s imagine we have XML data on a queue in IBM MQ, and we want to ingest it into Kafka to then use downstream, perhaps in an application or maybe to stream to a NoSQL store like MongoDB.
We saw in the first post how to hack together an ingestion pipeline for XML into Kafka using a source such as curl piped through xq to wrangle the XML and stream it into Kafka using kafkacat, optionally using ksqlDB to apply and register a schema for it.
The second one showed the use of any Kafka Connect source connector plus the kafka-connect-transform-xml Single Message Transformation. Now we’re going to take a look at a source connector from the community that can also be used to ingest XML data into Kafka.
We previously looked at the background to getting XML into Kafka, and potentially how [not] to do it. Now let’s look at the proper way to build a streaming ingestion pipeline for XML into Kafka, using Kafka Connect.
If you’re unfamiliar with Kafka Connect, check out this quick intro to Kafka Connect here. Kafka Connect’s excellent plugable architecture means that we can pair any source connector to read XML from wherever we have it (for example, a flat file, or a MQ, or anywhere else), with a Single Message Transform to transform the XML into a payload with a schema, and finally a converter to serialise the data in a form that we would like to use such as Avro or Protobuf.
When I set out to learn Go one of the aims I had in mind was to write a version of this little Python utility which accompanies a blog I wrote recently about understanding and diagnosing problems with Kafka advertised listeners. Having successfully got Producer, Consumer, and AdminClient API examples working, it is now time to turn to that task.
Having written my first Kafka producer in Go, and even added error handling to it, the next step was to write a consumer. It follows closely the pattern of Producer code I finished up with previously, using the channel-based approach for the Consumer:
I looked last time at the very bare basics of writing a Kafka producer using Go. It worked, but only with everything lined up and pointing the right way. There was no error handling of any sorts. Let’s see about fixing this now.
With the first leg of my journey with Go done (starting from a very rudimentary base), the next step for me was to bring it into my current area of interest and work - Apache Kafka.
I’ve been poking around recently with capturing Wi-Fi packet data and streaming it into Apache Kafka, from where I’m processing and analysing it. Kafka itself is rock-solid - because I’m using ☁️Confluent Cloud and someone else worries about provisioning it, scaling it, and keeping it running for me. But whilst Kafka works just great, my side of the setup—tshark running on a Raspberry Pi—is less than stable. For whatever reason it sometimes stalls and I have to restart the Raspberry Pi and restart the capture process.
My name’s Robin, and I’m a Developer Advocate. What that means in part is that I build a ton of demos, and Docker Compose is my jam. I love using Docker Compose for the same reasons that many people do:
Spin up and tear down fully-functioning multi-component environments with ease. No bespoke builds, no cloning of VMs to preserve "that magic state where everything works"
Repeatability. It’s the same each time.
Portability. I can point someone at a docker-compose.yml that I’ve written and they can run the same on their machine with the same results almost guaranteed.
A short & sweet blog post to help people Googling for this error, and me next time I encounter it.
The scenario: trying to create a connector in Kafka Connect (running in distributed mode, one worker) failed with the curl response
HTTP/1.1 500 Internal Server Error
Date: Fri, 29 Nov 2019 14:33:53 GMT
Content-Type: application/json
Content-Length: 48
Server: Jetty(9.4.18.v20190429)
{"error_code":500,"message":"Request timed out"}