Question from the Confluent Community Slack group:
How can I access the data in object in an array like below using ksqlDB stream
"Total": [ { "TotalType": "Standard", "TotalAmount": 15.99 }, { "TotalType": "Old Standard", "TotalAmount": 16, " STID":56 } ]
Alfred is one of my favourite productivity apps for the Mac. It’s a file indexer, a clipboard manager, a snippet expander - and that’s just scratching the surface really. I recently got a new machine without it installed and realised just how much I rely on Alfred, particularly its clipboard manager.
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.
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.
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.
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!
Very simple to fix: go to https://calendar.google.com/calendar/syncselect and select the calendars that you want. Click save.
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.
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.StructHashMap? Struct? HUH?
<x> has been compiled by a more recent version of the Java RuntimeThis 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:
