Apache Spot (incubating) and Cloudera on AWS in 60 Minutes

Categories: CDH Cloud Cloudera Director

For the Apache Spot novice or for quick evaluation of a Cybersecurity solution on Cloudera Enterprise Data Hub (EDH) without the arduous tasks of manual installation, we’ve created a rapid deployment of Apache Spot on Amazon Web Services (AWS) using Cloudera Director.

You will immediately see how you can isolate and identify suspicious activities from the Apache Spot UI using the sample data provided in the deployment at cloud scale.

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What’s New in Cloudera Director 2.7?

Categories: Cloudera Director

Cloudera Director 2.7 introduces support for LDAP authentication, improved Java 8 support, and instance template level normalization configuration. Continuing improvements have been made to the AWS plugin.

Cloudera Director helps you deploy, scale, and manage Cloudera clusters in AWS, Azure, or Google Cloud Platform. Its enterprise-grade features deliver a mechanism for establishing production-ready clusters in the cloud for big-data workloads and applications in a simple, reliable, automated fashion.

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Deploy Cloudera EDH Clusters Like a Boss Revamped – Part 2

Categories: CDH Hadoop HDFS

In Part 1: Infrastructure Considerations in this three part revamped series on deploying clusters like a boss, we provided a general explanation for how nodes are classified, disk layout configurations and network topologies to think about when deploying your clusters.

In this Part 2: Service and Role Layouts segment of the series, we take a step higher up the stack looking at the various services and roles that make up your Cloudera Enterprise deployment.

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Large-Scale Health Data Analytics with OHDSI

Categories: CDH Data Science

Data analytics is increasingly being brought to bear to treat human disease, but as more and more health data is stored in computer databases, one significant challenge is how to perform analyses across these disparate databases. In this post I take a look at the Observational Health Data Sciences and Informatics (or OHDSI, pronounced “Odyssey”) program that was formed to address this challenge, and which today accounts for 1.26 billion patient records collectively stored across 64 databases in 17 countries.

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Faster Performance for Selective Queries

Categories: CDH Impala

One of the principal features used in analytic databases is table partitioning. This feature is so frequently used because of its ability to significantly reduce query latency by allowing the execution engine to skip reading data that is not necessary for the query. For example, consider a table of events partitioned on the event time using calendar day granularity. If the table contained 2 years of events and a user wanted to find the events for a given 7-day window,

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