rmoff’s random ramblings

✨ Data Engineering, Kafka, and other random geekery 🤓

Streaming Wi-Fi trace data from Raspberry Pi to Apache Kafka with Confluent Cloud

Wi-fi is now ubiquitous in most populated areas, and the way the devices communicate leaves a lot of 'digital exhaust'. Usually a computer will have a Wi-Fi device that’s configured to connect to a given network, but often these devices can be configured instead to pick up the background Wi-Fi chatter of surrounding devices. There are good reasons—and bad—for doing this. Just like taking apart equipment to understand how it works teaches us things, so being able to dissect and examine protocol traffic lets us learn about this.

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Kafka Connect JDBC Sink - setting the key field name

I wanted to get some data from a Kafka topic:

ksql> PRINT PERSON_STATS FROM BEGINNING;
Key format: KAFKA (STRING)
Value format: AVRO
rowtime: 2/25/20 1:12:51 PM UTC, key: robin, value: {"PERSON": "robin",
 "LOCATION_CHANGES":1, "UNIQUE_LOCATIONS": 1}

into Postgres, so did the easy thing and used Kafka Connect with the JDBC Sink connector.

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Adventures in the Cloud, Part 94: ECS

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.

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Primitive Keys in ksqlDB

ksqlDB 0.7 will add support for message keys as primitive data types beyond just STRING (which is all we’ve had to date). That means that Kafka messages are going to be much easier to work with, and require less wrangling to get into the form in which you need them. Take an example of a database table that you’ve ingested into a Kafka topic, and want to join to a stream of events. Previously you’d have had to take the Kafka topic into which the table had been ingested and run a ksqlDB processor to re-key the messages such that ksqlDB could join on them. Friends, I am here to tell you that this is no longer needed!

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Fantastical / Mac Calendar not showing Google Shared Calendar

Very simple to fix: go to https://calendar.google.com/calendar/syncselect and select the calendars that you want. Click save.

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Notes on getting data into InfluxDB from Kafka with Kafka Connect

You can download the InfluxDB connector for Kafka Connect here. Documentation for it is here.

When a message from your source Kafka topic is written to InfluxDB the InfluxDB values are set thus:

Timestamp is taken from the Kafka message timestamp (which is either set by your producer, or the time at which it was received by the broker)
Tag(s) are taken from the tags field in the message. This field must be a map type - see below
Value fields are taken from the rest of the message, and must be numeric or boolean
Measurement name can be specified as a field of the message, or hardcoded in the connector config.

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Kafka Connect and Schemas

Here’s a fun one that Kafka Connect can sometimes throw out:

java.lang.ClassCastException: 
java.util.HashMap cannot be cast to org.apache.kafka.connect.data.Struct

HashMap? Struct? HUH?

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Monitoring Sonos with ksqlDB, InfluxDB, and Grafana

I’m quite a fan of Sonos audio equipment but recently had some trouble with some of the devices glitching and even cutting out whilst playing. Under the covers Sonos stuff is running Linux (of course) and exposes some diagnostics through a rudimentary frontend that you can access at http://<sonos player IP>:1400/support/review: Whilst this gives you the current state, you can’t get historical data on it. It felt like the problems were happening "all the time", but were they actually?

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UnsupportedClassVersionError: `<x>` has been compiled by a more recent version of the Java Runtime

This article is just for Googlers and my future self encountering this error. Recently I was building a Docker image from the ksqlDB code base, and whilst it built successfully the ksqlDB server process in the Docker container when instantiated failed with a UnsupportedClassVersionError:

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Changing the Logging Level for Kafka Connect Dynamically

Logs are magical things. They tell us what an application is doing—or not doing. They help us debug problems. As it happens, they also underpin the entire philosophy of Apache Kafka, but that’s a story for another day. Today we’re talking about logs written by Kafka Connect, and how we can change the amount of detail written. By default, Kafka Connect will write logs at INFO and above. So when it starts up, the settings that it’s using, and any WARN or ERROR messages along the way - a missing configuration, a broken connector, and so on.

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How to win [or at least not suck] at the conference abstract submission game

Just over a year ago, I put together the crudely-titled "Quick Thoughts on Not Writing a Crap Abstract" after reviewing a few dozen conference abstracts. This time around I’ve had the honour of being on a conference programme committee and with it the pleasure of reading 250+ abstracts—from which I have some more snarky words of wisdom to impart on the matter. Remind me…how does this conference game work? Before we really get into it, let’s recap how this whole game works, because plenty of people are new to conference speaking.

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Exploring ksqlDB window start time

Prompted by a question on StackOverflow I had a bit of a dig into how windows behave in ksqlDB, specifically with regards to their start time. This article shows also how to create test data in ksqlDB and create data to be handled with a timestamp in the past. For a general background to windowing in ksqlDB see the excellent docs. The nice thing about recent releases of ksqlDB/KSQL is that you can create and populate streams directly with CREATE STREAM and INSERT INTO respectively.

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Streaming messages from RabbitMQ into Kafka with Kafka Connect

This was prompted by a question on StackOverflow to which I thought the answer would be straightforward, but turned out not to be so. And then I got a bit carried away and ended up with a nice example of how you can handle schema-less data coming from a system such as RabbitMQ and apply a schema to it. Note This same pattern for ingesting bytes and applying a schema will work with other connectors such as MQTT What?

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Analysing network behaviour with ksqlDB and MongoDB

In this post I want to build on my previous one and show another use of the Syslog data that I’m capturing. Instead of looking for SSH attacks, I’m going to analyse the behaviour of my networking components. Note You can find all the code to run this on GitHub. Getting Syslog data into Kafka As before, let’s create ourselves a syslog connector in ksqlDB: CREATE SOURCE CONNECTOR SOURCE_SYSLOG_UDP_01 WITH ( 'tasks.

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Detecting and Analysing SSH Attacks with ksqlDB

I’ve written previously about ingesting Syslog into Kafka and using KSQL to analyse it. I want to revisit the subject since it’s nearly two years since I wrote about it and some things have changed since then. ksqlDB now includes the ability to define connectors from within it, which makes setting things up loads easier. You can find the full rig to run this on GitHub. Create and configure the Syslog connector To start with, create a source connector:

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Copy MongoDB collections from remote to local instance

This is revisiting the blog I wrote a while back, which showed using mongodump and mongorestore to copy a MongoDB database from one machine (a Unifi CloudKey) to another. This time instead of a manual lift and shift, I wanted a simple way to automate the update of the target with changes made on the source. The source is as before, Unifi’s CloudKey, which runs MongoDB to store its data about the network - devices, access points, events, and so on.

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Kafka Connect - Request timed out

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"}

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Using tcpdump With Docker

I was doing some troubleshooting between two services recently and wanting to poke around to see what was happening in the REST calls between them. Normally I’d reach for tcpdump to do this but imagine my horror when I saw:

root@ksqldb-server:/# tcpdump
bash: tcpdump: command not found

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Common mistakes made when configuring multiple Kafka Connect workers

Kafka Connect can be deployed in two modes: Standalone or Distributed. You can learn more about them in my Kafka Summit London 2019 talk. I usually recommend Distributed for several reasons: It can scale It is fault-tolerant It can be run on a single node sandbox or a multi-node production environment It is the same configuration method however you run it I usually find that Standalone is appropriate when:

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Streaming data from SQL Server to Kafka to Snowflake ❄️ with Kafka Connect

Snowflake is the data warehouse built for the cloud, so let’s get all ☁️ cloudy and stream some data from Kafka running in Confluent Cloud to Snowflake! What I’m showing also works just as well for an on-premises Kafka cluster. I’m using SQL Server as an example data source, with Debezium to capture and stream and changes from it into Kafka. I’m assuming that you’ve signed up for Confluent Cloud and Snowflake and are the proud owner of credentials for both.

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Robin Moffatt

Robin Moffatt is a Principal DevEx Engineer at Decodable. He likes writing about himself in the third person, eating good breakfasts, and drinking good beer.