Author Archives: Gwen Shapira

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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Deploying Apache Kafka: A Practical FAQ

Categories: CDH Kafka

This post contains answers to common questions about deploying and configuring Apache Kafka as part of a Cloudera-powered enterprise data hub.

Cloudera added support for Apache Kafka, the open standard for streaming data, in February 2015 after its brief incubation period in Cloudera Labs. Apache Kafka now is an integrated part of CDH, manageable via Cloudera Manager, and we are witnessing rapid adoption of Kafka across our customer base.

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How-to: Do Real-Time Log Analytics with Apache Kafka, Cloudera Search, and Hue

Categories: Data Ingestion How-to Hue Kafka Search

Cloudera recently announced formal support for Apache Kafka. This simple use case illustrates how to make web log analysis, powered in part by Kafka, one of your first steps in a pervasive analytics journey.

If you are not looking at your company’s operational logs, then you are at a competitive disadvantage in your industry. Web server logs, application logs, and system logs are all valuable sources of operational intelligence,

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5 Pitfalls of Benchmarking Big Data Systems

Categories: Hadoop Performance

Benchmarking Big Data systems is nontrivial. Avoid these traps!

Here at Cloudera, we know how hard it is to get reliable performance benchmarking results. Benchmarking matters because one of the defining characteristics of Big Data systems is the ability to process large datasets faster. “How large” and “how fast” drive technology choices, purchasing decisions, and cluster operations. Even with the best intentions, performance benchmarking is fraught with pitfalls—easy to get numbers,

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Flafka: Apache Flume Meets Apache Kafka for Event Processing

Categories: Flume Kafka

The new integration between Flume and Kafka offers sub-second-latency event processing without the need for dedicated infrastructure.

In this previous post you learned some Apache Kafka basics and explored a scenario for using Kafka in an online application. This post takes you a step further and highlights the integration of Kafka with Apache Hadoop, demonstrating both a basic ingestion capability as well as how different open-source components can be easily combined to create a near-real time stream processing workflow using Kafka,

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