From d2a44fbe75f3fcbc635f5b630bf2fdd7767fa8fc Mon Sep 17 00:00:00 2001 From: Krishna Chaiatanya Date: Mon, 16 Sep 2024 18:45:20 +0530 Subject: [PATCH] Update flink@o6GQ3-8DgDtHzdX6yeg1w.md (#7115) * Update spark@UljuqA89_SlCSDWWMD_C_.md * Update src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md * Update flink@o6GQ3-8DgDtHzdX6yeg1w.md --------- Co-authored-by: Arik Chakma --- src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md b/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md index 8309479d1..03a06864b 100644 --- a/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md +++ b/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md @@ -1,8 +1,9 @@ # Flink -Apache Flink is a distributed stream processing framework that is used to process large amounts of data in real-time. It is designed to be highly scalable and fault-tolerant. Flink is built on top of the Apache Kafka messaging system and is used to process data streams in real-time. +Apache Flink is an open-source stream processing framework designed for real-time and batch data processing with low latency and high throughput. It supports event time processing, fault tolerance, and stateful operations, making it ideal for applications like real-time analytics, fraud detection, and event-driven systems. Flink is highly scalable, integrates with various data systems, and is widely used in industries for large-scale, real-time data processing tasks. Visit the following resources to learn more: - [@article@Apache Flink Documentation](https://flink.apache.org/) - [@feed@Explore top posts about Apache Flink](https://app.daily.dev/tags/apache-flink?ref=roadmapsh) +-[@reference@Apache Flink Tutorialpoint](https://www.tutorialspoint.com/apache_flink/apache_flink_introduction.htm)