Faster Batch Processing with Cloudera 5.7: Hive-on-Spark is ready for production

Speakers: Santosh Kumar, Rui Li 
Date & Time: 5/03/2016 @ 10AM PT / 1PM ET

It’s no secret that Apache Spark is becoming the successor to MapReduce for data processing in Hadoop. With it’s easy development, flexible API, and performance benefits, Spark is a powerful data processing engine that has quickly gained popularity within the community. On the other hand Hive continues to be the most widely used data warehouse/ETL engine with large scale adoption across enterprises. Therefore, it’s imperative to enable Spark as the underlying execution engine for Hive to seamlessly allow existing and future Hive workloads to leverage the advantages of Spark.

With the recent release of Cloudera 5.7, we have delivered on this goal by adding support for Hive-on-Spark. Data engineers and ETL developers can now transition from MR to Spark for their Hive workloads seamlessly thereby benefitting from the advantages of Spark without any disruption on their end.

Join Santosh Kumar, Senior Product Manager at Cloudera, and Rui Li, Apache Hive committer and engineer at Intel, as we discuss:

  • An Introduction to Spark and its advantages over MR

  • An introduction of Hive-on-Spark: Goals and Design Principles

  • Migrating to HoS and a live demo

  • Configuring and tuning for batch workloads

  • What’s next for both tools

This will be a technical webinar with time at the end for a live Q&A

Multi-Tenant Operations with Cloudera 5.7: Meeting your SLAs with Cloudera Manager

Speakers: Matt Schumpert, Phill Radley
Date & Time: 5/10/2016 @ 10AM PT / 1PM ET

One of the benefits of Apache Hadoop is the ability to power multiple workloads, across many different users and departments, all within a single, shared cluster. This capability dramatically opens up data access across the business for more insights and a lower total cost of ownership. This also means that all of these users are fighting over the same resources, all with their own SLAs and priorities to meet. How can an administrator ensure that everyone has what they need to get the best results from Hadoop?

Cloudera Manager makes Hadoop (and its resource management) easy to manage and, with the recent release of Cloudera 5.7, we have added new features to provide better visibility for multi-tenant operations.

Join Matt Schumpert, Director of Product Management at Cloudera, and Phill Radley, Chief Data Architect at British Telecom, as we discuss:

  • Hadoop resource management with Cloudera Manager and what’s new with 5.7

  • Capacity planning and resource showback for multi-tenant environments

  • Live demo of new Cluster Utilization Reporting

  • Real-world use cases

  • What’s next for Cloudera Manager

This will be a technical webinar with time at the end for a live Q&A

Optimized Data Management with Cloudera 5.7: Understanding data value with Cloudera Navigator

Speakers: Mark Donsky
Date & Time: 5/17/2016 @ 10AM PT / 1PM ET

Across all industries, organizations are embracing the promise of Apache Hadoop to store and analyze data of all types, at larger volumes than ever before possible. But to tap into the true value of this data, organizations need to manage this data and its subsequent metadata to understand its context, see how it’s changing, and take actions on it.

Cloudera Navigator is the only integrated data management and governance for Hadoop and is designed to do exactly this. With Cloudera 5.7, we have further expanded the capabilities in Cloudera Navigator to make it even easier to understand your data and maintain metadata consistency as it moves through Hadoop.

Join Mark Donsky, Director of Product Management, as he discusses:

  • A brief overview of Cloudera Navigator and data management in Hadoop

  • What’s new in 5.7, including business lineage, managed metadata, and enhanced data discovery

  • A live demo and real-world use cases

  • What’s next for Cloudera Navigator

This will be a technical webinar with time at the end for a live Q&A


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