Tag Archives: Training

Docker is the New QuickStart Option for Apache Hadoop and Cloudera

Categories: CDH Ops and DevOps QuickStart VM Testing

Now there’s an even quicker “QuickStart” option for getting hands-on with the Apache Hadoop ecosystem and Cloudera’s platform: a new Docker image.

docker-logoYou might already be familiar with Cloudera’s popular QuickStart VM, a virtual image containing our distributed data processing platform. Originally intended as a demo environment, the QuickStart VM quickly evolved over time into quite a useful general-purpose environment for developers, customers,

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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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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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New Cloudera Search Training: Learn Powerful Techniques for Full-Text Search on an EDH

Categories: Search Training

Cloudera Search combines the speed of Apache Solr with the scalability of CDH. Our newest training course covers this exciting technology in depth, from indexing to user interfaces, and is ideal for developers, analysts, and engineers who want to learn how to effectively search both structured and unstructured data at scale.

Despite being nearly 10 years old, Apache Hadoop already has an interesting history. Some of you may know that it was inspired by the Google File System and MapReduce papers,

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Text Mining with Impala

Categories: Guest Impala Use Case

Thanks to Torsten Kilias and Alexander Löser of the Beuth University of Applied Sciences in Berlin for the following guest post about their INDREX project and its integration with Impala for integrated management of textual and relational data.

Textual data is a core source of information in the enterprise. Example demands arise from sales departments (monitor and identify leads), human resources (identify professionals with capabilities in ‘xyz’), market research (campaign monitoring from the social web),

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