Loading video...

Video Failed to Load

Go Home

๐Ÿ› Use the #IntelliJIDEA debugger to debug streams and visualize what is going on in Java Stream operations using โ€œTrace Current Stream Chainโ€ in the Debug tool window. ๐Ÿž #IntelliJIDEATips

40,329 views โ€ข 2 years ago โ€ขvia X (Twitter)

6 Comments

schrepfler's profile picture
schrepfler2 years ago

Nice! Any plans to cover Reactor streams or similar (Akka, etc.)?

01010101 Human Bot's profile picture
01010101 Human Bot2 years ago

๐Ÿ˜๐Ÿ˜๐Ÿ˜

Deeeee's profile picture
Deeeee2 years ago

Does IntelliJ still have the community version?

Thulasi's profile picture
Thulasi2 years ago

Thatโ€™s something Iโ€™ve been looking for to simplify one of the current requirementโ€™s testing!

Jonathan's profile picture
Jonathan2 years ago

Witch version is this functionality available ?

Hemant's profile picture
Hemant2 years ago

This is cool๐Ÿ‘. Didn't know about this.

Related Videos

Building real-time data pipelines and stream processing is one of the best-paid skills in the market. โ€‹ Apache Kafka and Flink are the industry standards, but they are Java-based and have a Python wrapper. โ€‹ If you are a Python developer, there is an open-source alternative! โ€‹ Watch this video. It's a full tutorial solving a real-world problem using the Quix Streams library. โ€‹ Quix Streams is all Python, and it's open-source! โ€‹ The video shows you how to process GitHub's Firehose API, a constant stream of raw activity. You can use this stream to identify real-time trends with code, issues, and the popularity of public repositories. โ€‹ Here is what the video covers: โ€‹ โ€ข How to tap into the GitHub Firehose API using Python and server-sent events (SSE) โ€‹ โ€ข How to efficiently stream that data into Kafka โ€‹ โ€ข How to optimize Kafka producer settings like batch size and compression for maximum throughput โ€‹ A few other notes about Quix Streams: โ€‹ โ€ข You don't need to know any Java โ€ข It has a dead-simple API โ€ข It integrates seamlessly with your Python stack โ€ข It's designed for parallel processing at high velocity โ€‹ You can use Quix Streams to build complete stream processing pipelines in Python, including feature engineering, pre-computations, inference, and real-time machine learning. โ€‹ Thanks to the Quix team for collaborating with me on this post.

Santiago

89,230 views โ€ข 1 year ago