Stream processing and Apache Flink Best Practices, Use Cases and more

Flux capacitor, huh? Temporal Tables and Joins in Streaming SQL

May 08, 2019

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...

What's new in Flink 1.8.0?

April 11, 2019

This post originally appeared on the Apache Flink blog. It was reproduced here under the Apache License, Version 2.0.

The Apache Flink community is pleased to announce Apache Flink 1.8.0. The latest release includes more than 420 resolved issues...

Flink and Prometheus: Cloud-native monitoring of streaming applications

March 13, 2019

This post originally appeared on the Apache Flink blog. It was reproduced here under the Apache License, Version 2.0.

This blog post describes how developers can leverage Apache Flink’s built-in metrics system together with Prometheus to observe...

What are the benefits of stream processing with Apache Flink for modern application development?

March 05, 2019

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.

Flink Forward Session Preview: Elastic Data Processing with Apache Flink and Apache Pulsar

February 28, 2019

Excited for Flink Forward San Francisco 2019? As one of the 30+ conference speakers, I want to give a sneak preview of my upcoming Flink Forward talk: Elastic Data Processing with Apache Flink and Apache Pulsar.

Monitoring Apache Flink Applications 101

February 27, 2019

This post originally appeared on the Apache Flink blog. It was reproduced here under the Apache License, Version 2.0.

batch processing, stream processing, Apache Flink,

Batch as a Special Case of Streaming and Alibaba's contribution of Blink

February 19, 2019

Authors: Stephan Ewen, Fabian Hueske & Xiaowei Jiang

This post originally appeared on the Apache Flink blog. It was reproduced here under the Apache License, Version 2.0.

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3 important performance factors for stateful functions and operators in Flink

February 15, 2019

This post focuses on the 3 factors developers should keep in mind when assessing the performance of a function or operator that uses Flink’s Keyed State in a stateful streaming application.

Smart Systems IoT Use Case with open source Kafka, Flink & CrateDB

February 12, 2019

The Smart Systems IoT Use Case

IoT systems use data and artificial intelligence (AI) to monitor, control, or predict the behavior of internet-connected devices. They are the basis for new smart factories, smart cities, and smart vehicle fleets...

MATCH_RECOGNIZE: where Flink SQL and Complex Event Processing meet.

January 29, 2019

With the unavoidable and ever-growing presence of sensors and smart devices, Complex Event Processing (CEP) is fast becoming a critical paradigm for enterprises to keep ahead of the curve and turn real-time, potentially infinite data streams into...

Ververica Blog

Category: apache-flink

Flux capacitor, huh? Temporal Tables and Joins in Streaming SQL

What's new in Flink 1.8.0?

Flink and Prometheus: Cloud-native monitoring of streaming applications

What are the benefits of stream processing with Apache Flink for modern application development?

Flink Forward Session Preview: Elastic Data Processing with Apache Flink and Apache Pulsar

Monitoring Apache Flink Applications 101

Batch as a Special Case of Streaming and Alibaba's contribution of Blink

3 important performance factors for stateful functions and operators in Flink

Smart Systems IoT Use Case with open source Kafka, Flink & CrateDB

The Smart Systems IoT Use Case

MATCH_RECOGNIZE: where Flink SQL and Complex Event Processing meet.

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