#apache-flink

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#stream-processing

Real-time stream processing with Flink now at your fingertips

The Powered By Ververica program integrates advanced stream processing technology to enhance real-time data capabilities for tech partners.

Event Time Processing with Flink and Beam - Power of Real time Analytics | HackerNoon

Apache Flink enables robust real-time data processing through effectively addressing the elements of what, where, when, and how in the pipeline.

Real-time stream processing with Flink now at your fingertips

The Powered By Ververica program integrates advanced stream processing technology to enhance real-time data capabilities for tech partners.

Event Time Processing with Flink and Beam - Power of Real time Analytics | HackerNoon

Apache Flink enables robust real-time data processing through effectively addressing the elements of what, where, when, and how in the pipeline.
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How to Implement Real-Time Credit Card Fraud Detection With Apache Flink on AWS | HackerNoon

Real-time fraud detection using Apache Flink on AWS is crucial for financial institutions to prevent credit card fraud efficiently.

Three-year-old Apache Flink flaw now under active attack

Apache Flink CVE-2020-17519 allows unauthorized reading of local files, exploited in the wild, prompting urgent patches and checks for compromises.

Confluent Cloud for Apache Flink is Now Generally Available with AI Features

Confluent Cloud for Apache Flink offers fully managed real-time data processing across major cloud platforms.

Yelp Overhauls Its Streaming Architecture with Apache Beam and Apache Flink

Yelp revamped data streaming architecture with Apache Beam and Apache Flink for unified solution.

Checkpoint in the Flink Streaming Job

Checkpoints in Apache Flink ensure the resiliency and fault tolerance of streaming data applications.
Checkpoints allow for the consistent snapshotting of the state of the application, enabling recovery in case of failures.
Flink provides options for storing checkpoints, including in-memory checkpoints and RocksDB.
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