1 Copyright © 2012, Oracle and/or its affiliates. All ... · PDF fileOracle Big Data Appliance Releases 2.5 and 3.0 Ralf Lange Global ISV & OEM Sales

Copyright © 2012, Oracle and/or its affiliates. All rights reserved. 1

Oracle Big Data Appliance Releases 2.5 and 3.0

Ralf Lange

Global ISV & OEM Sales


Agenda

Quick Overview on BDA and its Positioning

Product Details and Updates

– Security and Encryption

– New Hadoop Versions and Components

– New NoSQL DB Features


Big Data Technology Stack

Big Data Applications

Business Analytics

Big Data Management System

Data Warehouse Data Reservoir +

Discovery Biz Intelligence +

by Industry & LoB




The Best of Both Worlds



0

1

2

3

4

5 Tooling maturity

Stringent Non-Functionals

ACID transactional requirement

Security

Variety of data formats

Data sparsity

ETL simplicity

Cost effectively store low value data

Ingestion rate

Straight Through Processing (STP)

Hadoop

Relational

The Best of Both Worlds


Oracle Big Data Management System

Oracle Big Data Management System


Oracle NoSQL

Database

Cloudera

Hadoop

Oracle R

Distribution

Big Data Appliance

Oracle Advanced

Analytics

Oracle

Database

Oracle Spatial

& Graph

Exadata

Oracle Big Data Connectors

Oracle Data Integrator


Agenda







Big Data Appliance Product Family

Starter Rack is a fully cabled and

configured for growth with 6 servers

In-Rack Expansion delivers 6 server

modular expansion block

Full Rack delivers optimal blend of

capacity and expansion options

Grow by adding rack – up to 18 racks

without additional switches


Big Data Appliance X4-2

Sun Oracle X4-2L Servers with per server:

• 2 * 8 Core Intel Xeon E5 Processors

• 64 GB Memory

• 48TB Disk space

Integrated Software (3.0):

• Oracle Linux

• Oracle Java VM

• Cloudera Distribution of Apache Hadoop (CDH) 5.0

• Cloudera Manager 5.0 and Options

• Apache Spark

• Oracle R Distribution

• Oracle NoSQL Database

All integrated software (except NoSQL DB CE) is supported as part of Premier Support for Systems and Premier Support for

Operating Systems


Two Branches

BDA 2.5 (CDH 4.6)

BDA 2.6 (CDH 4.7)

BDA 3.0 (CDH 5.0)

BDA 3.1 (CDH 5.1)

BDA 4.0 (CDH 5.2)

Upgrade Points


Agenda







Enhanced Big Data Security

Authenticate users with secure Kerberos protocol

Authorize access to data with fine grained controls

Audit activity and access with Oracle Audit Vault and Database Firewall

Encrypt data as it flows thru the system

More Info

https://stbeehive.oracle.com/content/dav/st/Big Data/Public Documents/BDA_Collateral/Big Data Appliance - Security - AV Screenshots.pptx


First Kerberos and Sentry enabled Hadoop Appliance

Founding member of Apache Sentry bringing fine fine-grained authorization to Hadoop

Bring Oracle’s security expertise and commitment to Apache Hadoop

Kerberos and Apache Sentry


Oracle Audit Vault and Database Firewall

Databases Relational Data

Hadoop Non-Relational Data

Operating Systems

Audit Vault

One Consolidated, secure repository for all audit data

Centralized platform for audit reporting, alerting and policy management


Encryption at Rest and on the Network

Only Cloudera Hadoop appliance with Pre-Configured File System and Network Encryption

Transparent to applications and at no extra cost

Encryption at

Rest

Network

Encryption


Agenda







Hadoop Technology Trends

Standardization of HDFS as the Big Data file system

Resource management opens doors to new processing

– YARN resource manager is GA, becoming the de facto standard

– Multiple processing frameworks can dynamically share resources

Processing frameworks move beyond MapReduce

– Avoid checkpoints to disk, cache data in memory

– More operators than map and reduce

– Contenders: Apache Spark (Databricks), Apache Tez (Hortonwork)


YARN Yet Another Resource Negotiator

What is it?

Benefits

Limitations

An execution-engine independent resource

management framework for Hadoop

Allows management of more than MapReduce

Management of RAM, CPU, (eventually) I/O

More complicated container model

Very few production implementations


MapReduce 2 MapReduce on YARN

What is it?

Benefits

Limitations

The MapReduce parallel processing framework

redesigned for use on YARN

Better support for multiple workload types

More complicated container model

Every job is a separate YARN executable


MapReduce 2 Launch Flow

MapReduce

Client

Resource

Manager

1. Submit MR AM Request

DataNode

And

Node Manager

Application

Master

(JobTracker)

2. Return MR Application Master

DataNode

And

Node Manager

DataNode

And

Node Manager

DataNode

And

Node Manager

DataNode

And

Node Manager

TaskTracker TaskTracker TaskTracker TaskTracker TaskTracker

3. Spawn Application Containers

4. Submit MR Job


Spark

What is it?

Benefits

Limitations

Rich Parallel-Processing with In-Memory Execution

A storage-independent, parallel-processing

framework for Big Data

Enables real-time streaming workloads

Much faster than MapReduce

Much more expressive than MapReduce

Very newly supported

Reliance on less common language (Scala)

Yet another framework to learn


In-Memory MapReduce

Spark is not “just” MapReduce with Caching

– Adopts and extends the “map/reduce” paradigm

Spark provides

– Fast, rich parallel –processing framework

– Interactive shells (Scala and Python)

– Real-time Streaming capabilities (Java, Scala)

– Machine Learning and Graph libraries out-of-the-box

Is Spark anything new?


What is Where?

BDA 2.x

Supports CDH 4.6

Delivered all security and encryption features

BDA 3.0

Builds on the features in 2.5 and

Delivers the new Hadoop components

BDA 3.0 - Available April 22nd


Agenda







Oracle NoSQL DB Release 3.0 Enterprise Ready

Ease of Adoption

Security

Business Continuity

