Recently, we were doing some experiments with a SQL query that joins a few dimensional tables to enrich incoming records. While doing so, we were thinking of whether an implementation of the same task using the DataStream API would actually be...
How to manage your RocksDB memory size in Apache Flink
Replayable Process Functions: Time, Ordering, and Timers
This post originally appeared on the Bird Engineering account on Medium. It was reproduced here with permission from the author.
Detecting Offline Scooters with Stream Processing
Some of the most interesting challenges at Bird involve dealing...
Announcing Flink Community Packages
Introducing Ververica's redesigned training
We are excited to present our re-designed public training offering effective September 2019. The all-new training experience has been re-designed from the ground-up to meet the requirements of a best-in-class curriculum that now includes two...
How Yelp uses Flink for predicting store visits in real time
Flux capacitor, huh? Temporal Tables and Joins in Streaming SQL
Figuring out how to manage and model temporal data for effective point-in-time analysis was a longstanding battle, dating as far back as the early 80’s, that culminated with the introduction of temporal tables in the SQL standard in 2011. Up to...
Flink and Prometheus: Cloud-native monitoring of streaming applications
What are the benefits of stream processing with Apache Flink for modern application development?
This blog post is a Q&A session with Vino Yang, Senior Engineer at Tencent’s Big Data team. Below, we discuss the benefits of adopting stream processing and Apache Flink for modern application development.