Category Archives: Hadoop

Cloudera Enterprise 5.11 is Now Available

Categories: CDH Cloud Cloudera Manager Cloudera Navigator Hadoop

Cloudera Enterprise 5.11 is Now Available

Cloudera is pleased to announce that Cloudera Enterprise 5.11 is now generally available (GA). The highlights of this release include lineage support for Apache Spark, Apache Kudu security integration, embedded data discovery for self-service BI, and new cloud capabilities for Microsoft ADLS and Amazon S3.

As usual, there are also a number of quality enhancements, bug fixes, and other improvements across the stack. Here is a partial list of what’s included (see the Release Notes for a full list):

  • Core Platform and Cloud
    • Amazon S3 Consistency: S3Guard ensures that operations on Amazon S3 are immediately visible to other clients,

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Blacklisting in Apache Spark

Categories: Hadoop Spark

At Cloudera, we’re always working to provide our customers and the Apache Spark community with the most robust, most reliable software possible. This article describes some recent engineering work on [SPARK-8425] that is available in CDH 5.10 and CDH5.11, as well as in upstream Apache Spark starting with the 2.2 release.

The work pertains to the Blacklist Tracker mechanism in Spark’s scheduler. This was the subject of a recent Spark Summit talk,

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How-to: Log Analytics with Solr, Spark, OpenTSDB and Grafana

Categories: Hadoop How-to Search Spark

Organizations analyze logs for a variety of reasons.  Some typical use cases include predicting server failures, analyzing customer behavior, and fighting cybercrime.  However, one of the most overlooked use cases is to help companies write better software.  In this digital age, most companies write applications, be it for its employees or external users.  The cost of faulty software can be severe, ranging from customer churn to a complete firm’s demise, as was the case with Knight Capital in 2012.

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Offheap Read-Path in Production – The Alibaba story

Categories: Hadoop HBase Performance Use Case

This article is syndicated with permission from the Apache HBase blog and highlights a collaboration between our partners at Intel and Alibaba engineering in time for “Singles Day“, the biggest shopping day on the net. For more on HBase, mark your calendars! On June 12th, 2017 the Apache HBase community will be hosting their annual HBaseCon.

Introduction

HBase is the core storage system in Alibaba’s Search Infrastructure.

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How To Set Up a Shared Amazon RDS as Your Hive Metastore

Categories: Cloud Hadoop Hive How-to Impala Spark Use Case

Before CDH 5.10, every CDH cluster had to have its own Apache Hive Metastore (HMS) backend database. This model is ideal for clusters where each cluster contains the data locally along with the metadata. In the cloud, however, many CDH clusters run directly on a shared object store (like Amazon S3), making it possible for the data to live across multiple clusters and beyond any cluster’s lifespan. In this scenario clusters need to regenerate and coordinate metadata for the underlying shared data individually.

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