Ahorra un 25 % (o incluso más) en tus costes de Kafka | Acepta el reto del ahorro con Kafka de Confluent
September is the start of the fall conference season. Between Strata + Hadoop World New York and ApacheCon: Big Data Europe, there is plenty to keep us busy learning.
Conferences can provide too many choices, and finding the most relevant and most exciting sessions can be a challenge. So I reviewed the Strata conference agenda and picked some of my favorites related to Apache Kafka and stream processing.
In addition to all of the Strata sessions, there is the NYC Kafka meetup. You will not want miss Jay Kreps‘ talk about Stream Processing – trust me on this one. Gwen Shapira will present “When Bad Things Happen to Good Kafka Clusters” – war stories from using Kafka in production and how to avoid the same mistakes.
Drop by to meet the Confluent team and chat about Apache Kafka, stream processing, and other geeky topics. Meet Jay Kreps and pick up a free signed copy of his book, I Heart Logs, on Wednesday, September 30 at 12:45pm. And for those of you that only care about Kafka swag, the booth will be stocked with stickers and t-shirts.
Going at at the same time as Strata NYC, ApacheCon: Big Data Europe is taking place in Budapest, Hungary, from Sep 28-30. This is a great opportunity to catch up with the Big Data and Apache Kafka open source communities, particularly for European users. If you are going to Apache: Big Data, here are our recommendations:
Looking forward to meeting you at the conferences!
This blog post demonstrates using Tableflow to easily transform Kafka topics into queryable Iceberg tables. It uses UK Environment Agency sensor data as a data source, and shows how to use Tableflow with standard SQL to explore and understand the data.
The guide covers Kafka consumer offsets, the challenges with manual control, and the improvements introduced by KIP-1094. Key enhancements include tracking the next offset and leader epoch accurately. This ensures consistent data processing, better reliability, and performance.