Apache Flink - Learn Data Science with Travis

Apache-Flink

Apache Flink is an open-source, distributed stream processing framework designed for high-performance, scalable data processing. It excels in handling both stateful and stateless computations over unbounded and bounded data streams, making it suitable for real-time analytics and event-driven applications. Flink’s architecture supports low-latency processing and fault tolerance, allowing it to efficiently manage massive volumes of data across clusters. With its expressive APIs, including DataStream and DataSet, Flink enables developers to build complex data processing pipelines that can ingest, process, and output data seamlessly. Its growing popularity is evident in its adoption by major companies for large-scale data analytics.

Flink Checkpointing and Recovery

Towards Data Science

Apache Flink is a popular real-time data processing framework. It’s gaining more and more popularity thanks to its low-latency processing at extremely high throughput in a fault-tolerant manner…

Apache Flink Series 1 — What is Apache Flink

Analytics Vidhya

In this post, I will try to explain what is Apache Flink, what is used for, and features of Apache Flink. Before pass the “use cases for Apache Flink”, let me point to the what does the stateful…

Apache Flink Series 4 — DataStream API

Analytics Vidhya

When we look at the Flink as a software, Flink is built as layered system. And one of the layer is DataStream API which places top of Runtime Layer. close()= is an finalization method. It is called…

An Introduction to Stream Processing with Apache Flink

Towards Data Science

An Introduction to Stream Processing with Apache Flink

Building a realtime dashboard with Flink: The Backend

Towards Data Science

With the demand for “realtime” low latency data growing more data scientists will likely have to become familiar with streams. One good place to start is Apache Flink. Flink is a distributed…

Running Apache Flink with RocksDB on Azure Kubernetes Service

Towards Data Science

Recently I was looking into how to deploy an Apache Flink cluster that uses RocksDB as the backend state and found a lack of detailed documentation on the subject. I was able to piece together how to…...

Real-time Twitch chat sentiment analysis with Apache Flink

Towards Data Science

Real-Time Twitch Chat Sentiment Analysis with Apache Flink Learn how to empower creators by real-time sentiment analysis with Apache Flink to decipher audience emotions to steer content for viewer sa...

The Foundations for Building an Apache Flink Application

Analytics Vidhya

Our monolith solution does not cope with the increased load of incoming data, and thus it has to evolve. This is the time for the next generation of our product. Stream processing is the new data…

How I Dockerized Apache Flink, Kafka, and PostgreSQL for Real-Time Data Streaming

Towards Data Science

Integrating pyFlink, Kafka, and PostgreSQL using Docker Get your pyFlink applications ready using docker — author generated image using https://www.dall-efree.com/ Why Read This? * Real-World Insight...

Apache Flume

Towards Data Science

Trickle-feed unstructured data into HDFS using Apache Flume

Apache Thrift

Software Architecture with C plus plus

Apache Thrift is an interface description language and binary communication protocol. It is used as an RPC method that allows creating distributed and scalable services built in a variety of languages...

Complex Event Processing with Flink on realtime Twitter data

Towards Data Science

Recently, I decided to look into Flink’s Complex Event Processing library (CEP) and see what it was capable of. I found it surprisingly easy to use and I can envision many possible use cases. What is…...