Category Archives: Use Case

How Cigna Tuned Its Spark Streaming App for Real-time Processing with Apache Kafka

Categories: Kafka Spark Use Case

Explore the configuration changes that Cigna’s Big Data Analytics team has made to optimize the performance of its real-time architecture.

Real-time stream processing with Apache Kafka as a backbone provides many benefits. For example, this architectural pattern can handle massive, organic data growth via the dynamic addition of streaming sources such as mobile devices, web servers, system logs, and wearable device data (aka, “Internet of Things”). Kafka can also help capture data in real-time and enable the proactive analysis of that data through Spark Streaming.

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How-to: Build a Complex Event Processing App on Apache Spark and Drools

Categories: HBase How-to Kafka Spark Use Case

Combining CDH with a business execution engine can serve as a solid foundation for complex event processing on big data.

Event processing involves tracking and analyzing streams of data from events to support better insight and decision making. With the recent explosion in data volume and diversity of data sources, this goal can be quite challenging for architects to achieve.

Complex event processing (CEP) is a type of event processing that combines data from multiple sources to identify patterns and complex relationships across various events.

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Using Apache Spark for Massively Parallel NLP at TripAdvisor

Categories: Guest Spark Use Case

Thanks to Jeff Palmucci, Director of Machine Learning at TripAdvisor, for permission to republish the following (originally appeared in TripAdvisor’s Engineering/Operations blog).

Here at TripAdvisor we have a lot of reviews, several hundred million according to the last announcement. I work with machine learning, and one thing we love in machine learning is putting lots of data to use.

I’ve been working on an interesting problem lately and I’d like to tell you about it.

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How Apache Spark, Scala, and Functional Programming Made Hard Problems Easy at Barclays

Categories: Guest Spark Use Case

Thanks to Barclays employees Sam Savage, VP Data Science, and Harry Powell, Head of Advanced Analytics, for the guest post below about the Barclays use case for Apache Spark and its Scala API.

At Barclays, our team recently built an application called Insights Engine to execute an arbitrary number N of near-arbitrary SQL-like queries and execute them in a way that can scale with increasing N.

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Designing Fraud-Detection Architecture That Works Like Your Brain Does

Categories: Flume HBase Kafka Spark Use Case

To design effective fraud-detection architecture, look no further than the human brain (with some help from Spark Streaming and Apache Kafka).

At its core, fraud detection is about detection whether people are behaving “as they should,” otherwise known as catching anomalies in a stream of events. This goal is reflected in diverse applications such as detecting credit-card fraud, flagging patients who are doctor shopping to obtain a supply of prescription drugs,

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