Tag Archives: demo

Progress Report: Hive-on-Spark Nears Production Readiness

Categories: Cloudera Labs Hive Spark

Contributors from Intel, Cloudera, and the rest of the community have been making strong progress on the Hive-on-Spark initiative. This post provides an update.

[Editor’s note (April 20, 2016): Hive-on-Spark is now GA/shipping starting in CDH 5.7.]

Since its inception about one year ago, the community initiative to make Apache Spark a data processing engine for Apache Hive (HIVE-7292) has attracted widespread interest from developers around the world and gone through phases of rapid development,

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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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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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How-to: Prepare Unstructured Data in Impala for Analysis

Categories: How-to Impala

Learn how to build an Impala table around data that comes from non-Impala, or even non-SQL, sources.

As data pipelines start to include more aspects such as NoSQL or loosely specified schemas, you might encounter situations where you have data files (particularly in Apache Parquet format) where you do not know the precise table definition. This tutorial shows how you can build an Impala table around data that comes from non-Impala or even non-SQL sources,

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New in CDH 5.4: Sensitive Data Redaction

Categories: CDH Cloudera Manager Platform Security & Cybersecurity

The best data protection strategy is to remove sensitive information from everyplace it’s not needed.

Have you ever wondered what sort of “sensitive” information might wind up in Apache Hadoop log files? For example, if you’re storing credit card numbers inside HDFS, might they ever “leak” into a log file outside of HDFS? What about SQL queries? If you have a query like select * from table where creditcard = ‘1234-5678-9012-3456’,

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