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Altiscale Big Data-as-a- Service Paul Tibaldi RSD & Ajay Jha SA

Hadoop Hadoop & Spark meetup - Altiscale

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AltiscaleBig Data-as-a-ServicePaul Tibaldi RSD & Ajay Jha SA

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• Market Background• Who is Altiscale?• Why are we different/better?• Hadoop Admin• Apache Hadoop Stack • Platform/Access/Demo• Q/A

Big Data As A Service

Market Background

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Interest in Big Data is growing fast

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Big Data in The Cloud is Accelerating

On-Premises

32%

Cloud Only

23%

Cloud Plus On-Premises

29%

Source: “Hadoop Expansion Boosts Cloud and Unsupported On-Premises Deployments,” Merv Adrian, Nick Huedecker, 3 September 2015

But the journey has dangers

Gartner: 70% of independent Big Data implementations will fail to meet revenue and cost objectives, through 2018.

Who is Altiscale?

Altiscale Data Cloud GA in 2014

Financed by top-tier technology investors

Recognized innovator in Hadoop-as-a-Service

About Altiscale

About Altiscale

Led by experienced, renowned Hadoop team from Yahoo!• Raymie Stata, CEO. Former Yahoo! CTO,

well-known advocate of Apache Software Foundation

• David Chaiken, CTO. Former Yahoo! Chief Architect

Built and managed by veterans of Big Data, SaaS, and enterprise software• From Google, Netflix, LinkedIn, VMware, Oracle, and Yahoo!

40,000 nodes500 PB1,000 users$ billions at stake

Raymie Stata, CEO David Chaiken, CTO Ricardo JenezVP of Engineering

Charles Wimmer Head of Operations

Big data built for speed

Fast time to value—days not months

Easier, faster scalability—with elastic scaling

Operations support—so your jobs get done

Lower TCO—for fast investment payback

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Unmatched Security

Altiscale is the only provider that delivers integrated security

encompassing its Big Data platform offering

Complete best of breed

Big Data is complex.It gets more complicated as you scale.

Big Data-as-a-Service

The Altiscale Data Cloud Core

Altiscale Data Cloud is 100% based on Apache open source.

Our current Altiscale Data Cloud 4.0 release is composed of the following Apache components and versions:

• Apache Hadoop 2.7.1 • Apache Spark 1.5* • Apache Hive (& HCatalog) 1.2 • Apache Tez 0.7.0 • Apache Pig 0.15.1• Apache Oozie 4.2.0 • Apache Flume 1.5.2 • Avro 1.7.4 • JDK/JRE 7 (Sun/Oracle version) • HttpFS

In addition to the above, we also support the three latest versions of Spark to our customers. That allows our customers the options of a conservative approach as well as a the option to work with the “bleeding edge” fast moving Spark community.

Concurrency with Apache Versioning

Hire an expert to take care of the cluster

• Hardware setup and Cluster installation

• Address hardware failure

• Upgrade Hadoop stack

• Tuning config parameters

• yarn-site.xml ex : yarn.nodemanager.resource.memory-mb

• mapred-site.xml ex : mapreduce.task.io.sort.mb

• hdfs-site.xml ex : dfs.blocksize

Hadoop Administration

Accessing the cloud

Spark example

• Build Spark code laptop using maven

• Build the jar and copy over Altiscale’s workbench (Gateway) node.

• Launch Spark job on YARN.

• Monitor using Resource Manager

Quick Spark Demo

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Thank You!