taming the big data tsunami using intel architecture

Taming the Big Data Tsunami using Intel® Architecture

DATS004

Clive D’Souza, Solutions Architect, Intel Corporation Dhruv Bansal, Chief Science Officer, Infochimps

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Agenda

•  What is Big Data? •  Why does Big Data matter? •  How can Intel®

Architecture help •  Summary

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Big Data Tsunami Between the birth of the world and 2003, there were five Exabyte of information created. We now create five Exabyte every two days

Eric Schmidt

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Exp

onen

tial

Gro

wth Content Depots – Massive/

Unstructured

Traditional Unstructured

Traditional Structured Data

Enterprise Hosting Services

Lin

ear

Gro

wth

Source: IDC, 2011 Worldwide Enterprise Storage Systems 2011–2015 Forecast Update. Worldwide Enterprise Storage Consumption Capacity Shipped by Model, 2006–2015 (PB)

2.7 Zetabytes of data in 2012, 15 billion connected devices by 2015 !!!

Over 24 Petabytes Data processed by Google* every day in 2011

Four billion Pieces of content shared on Facebook* every day by July 2011

250 Million Tweets per day in October 2011

5.5 million Legitimate emails sent every second in 2011

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Big Data — Traits

Unstructured datasets whose Volume, Variety and Velocity is beyond the ability of typical database

software tools to capture, store, manage and analyze†

Volume

Variety Velocity

Value

Big Data Decrees •  Speed is everything! •  Use diverse data •  Data never gets stale •  Data growth will be

exponential •  Big Data is real •  Transformational to business Core Tenants

†Big data: The next frontier for innovation, competition, and productivity”, McKinsey Global Institute

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Big Data — Flow

Data Ingestion

Data Aggregation

Data Curation

Data - Query Enabled

Data Analytics

Compute/Network/IO/Storage-Intensive

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Agenda



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Our Problem – Which 5K?

Image used with permission from Author

•  Don’t know the future value of today’s data

•  We cannot connect the dots we do not yet have

•  The old collect, winnow, dissemble model fails spectacularly in the Big Data world

The “5K” is different for everybody!

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Intelligent 5K = Big Money!

Source: Mckinsey, 2011

Manufacturing • Up to 50 percent decrease in product development, assembly costs

• Up to seven percent reduction in working capital Europe public sector

administration • €250 billion value per year

• ~0.5 percent annual productivity growth

US health care • $300 billion value per year

• ~0.7 percent annual productivity growth

Global personal location data • $100 billion+ revenue for service providers

• Up to $700 billion value to end users

US retail • 60+ percent increase in net margin possible

• 0.5-1.0 percent annual productivity growth

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Big Data in play by

Infochimps*

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Growing Pains… •  IT growth outpaced by Big

Data growth •  Unparalleled data complexity •  Need for speed – race to the

bottom! •  Workload management •  Data access, data silos, data

quality, data security •  Shortage of data scientists •  New domain – not easy to

implement

Big Data solutions will transform IT

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Big Data Means More Than Hadoop*

About Infochimps* www.infochimps.com

[Many people’s] understanding of “Hadoop” is like my understanding of “tango”: I know the word, I know one when I see one, but I can’t dance for ***.

Jeffrey Eisenberg

•  Multi-language •  Databases •  Web •  Realtime

•  Java* •  I/O-bound •  Batch, map/reduce,

historical

Ecosystem Hadoop*

Big Data hardware needs more than I/O

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Sensors

Rich Media

System Logs

Mobile Web Logs

CRM

POS

ERM

Public Data

Internal DBs & Appliances

Documents

Full Data Stack Overview

Hadoop* (Batch/Historical

Analytics)

Data Storage (Analytic DBs and

filesystem)

Stream Processing (Real-Time Analytics)

Data Integration

(ETL and streaming)

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Hadoop*

Bulk/Large-Scale Processing Engine

Full Data Stack

Hbase* or

HDFS* Primary Analytics Datastore

Mongo* or MySQL*

Reporting Aggregates

Streaming Sources

Database Sources Sqoop*

Bulk Load Structured Datastores like SQL

Elasticsearch* Search Engine and API

Flume* Collect and Process Streaming or Fast-Changing Data

DataViz*

Tableau* LogiXML* Custom App etc.

Web Servers Local Disk Statistical

Packages

SAS*, R*, Stata*, etc.

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Demonstration When are two time series correlated?

AAPL

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Demonstration

Source Data: •  Web traffic logs (Wikipedia, 3 mos.) •  S&P 500* Stock Prices

Q: Traffic to which Wikipedia* articles is correlated with the price of AAPL?

AAPL

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Demonstration

AAPL

Tentative Answer: Traffic to articles about music, television, and video games are directly correlated with AAPL’s stock price.

Bonus: Also Jack Dorsey, CEO of Square!

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Full Data Stack

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Agenda



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Intelligent Data Center

Compute WWW

VPN or LAN

Virtualized Servers

Dedicated Servers

“Centralized” Storage

Premium Storage

High-Capacity Storage

Low-Latency, Proximity Storage

HDD

Edge/M2M

HPC & Decision Support

IT/Web/Application Development

Infrastructures

IOPS/TB Optimized

$/TB Optimized

Unified Network

NVM

SSD

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Intel® Xeon® Processor = Heart of the Intelligent Data Center •  Integrated PCI Express* Gen 3.0 •  Intel® Hyper-Threading

Technology, two Threads/Core •  Shared Last Level Cache, 2.5 MB/

Core •  Higher memory bandwidth with

DDR3 •  Integrated Memory Controller •  PCIe Non-Transparent Bridge •  Asynchronous DRAM self-refresh

(ADR) •  Intel® QuickData Technology

Direct Memory Access

Intel® Xeon® powers Big Data compute

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Intelligent Storage Optimizations

De-duplication

Intelligent Tiering Thin Provisioning

Real Time Compression

BEFORE AFTER DE-DUPLICATION

APPLI 1

APPLI 2

APPLI 3

TRADITIONAL ALLOCATION THIN PROVISIONING ALLOCATED BUT FREE

USED

ALLOCATED BUT FREE

USED

USED

ALLOCATED BUT FREE

APPLI 1 APPLI 2 APPLI 3

SYSTEM-WIDE CAPACITY RESERVED

Up to 80% data reduction2 95% smaller backup1

Up to 80% reduction in disk expenses3

1 IBM storage simulcast, November 9, 2011 2 BM storage simulcast, November 9, 2011 3 Dell “Fluid Data Storage: Driving Flexibility in the Data Center”, February 2011 4 Intel IT study “Solving Intel IT’s Data Storage Growth Challenges

Up to 25% reduction in annual storage CapEx

growth4

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New Memory Hierarchies — Non-Volatile Memory

CPU Processing

Tim

elin

e

CPU Processing

SW 10µs

NVM 65µs IO

Processing

Time spent by application in CPU vs. IO

Application

•  Enhanced Performance -  Sequential R/W: 2.0/1.0 GB/s -  Random R/W: 180/75 KIOPS -  Latency R/W: 65/65µs

•  High Endurance 25nm HET MLC -  10x drive writes/day for five years -  30x endurance over standard MLC

due to improved write amplitude and NAND management

Intel® Solid-State Drive 910 Series

Reduction of software latency dramatically increases

application IOPS as NVM latency decreases

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Intel Ethernet Controller

Intel QPI 1

Intel QPI 2 CORE 1 CORE 2

CORE 3 CORE 4

CORE 5 CORE 6

CORE 7 CORE 8

Intel Xeon® Processor E5-2600

CACHE IOC

PCI Express*

DMA Write directly To “IO allocated” LLC

Rx Packet

No Memory

Transactions

Core Reads Data 2

1

LLC Data to Core 3

Intel® Integrated IO Technology

Intel QPI - Intel QuickPath* Interconnect

Intel Ethernet Controller

Intel QPI 1

Intel QPI 2

CORE 1 CORE 2

CORE 3 CORE 4

CORE 5 CORE 6

CORE 7 CORE 8

Intel Xeon Processor E5-2600

CACHE

PCI Express*

Outbound Flow (Tx)

Tx P

acke

t

Core creates buffer for I/O device to read, putting data in cache (cache line allocated)

1

I/O request read of I/O data

2

Data to I/O 3

No Memory

Transactions

Intel Data Direct I/O Technology (Intel DDIO)

Inbound Flow (Rx)

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10GbE Completes the Job Faster

Economies of scale realized with 10GbE

4X Improvement

Performance comparison using best submitted/published 2-socket server results on the SPECfp*_rate_base2006 benchmark as of 6 March 2012.

Software and workloads used in performance tests may have been optimized for performance only on Intel® microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance. Configuration: Source: Intel internal measurements of average time for an I/O device read to local system memory under idle conditions comparing Intel® Xeon® processor E5-2600 product family (230ns) vs. Intel Xeon processor 5500 series (340ns). See notes in backup for configuration details.

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Up to four channels DDR3 1600 MHz memory

Up to eight cores Up to 20 MB cache

Integrated PCI Express* 3.0 Up to 40 lanes per socket

Platform and Software Optimizations

1 Performance comparison using best submitted/published 2-socket server results on the SPECfp*_rate_base2006 benchmark as of 6 March 2012. 2 Source: Intel internal measurements of average time for an I/O device read to local system memory under idle conditions comparing Intel® Xeon® processor E5-2600 product family (230ns) vs.. Intel Xeon processor 5500 series (340ns). See notes in backup for configuration details

•  Up to 80% Performance Boost vs. Prior Generation1

–  Intel® Advanced Vector Extensions (Intel® AVX) - Reduce Compute Time

–  Intel® Turbo Boost Technology — Increased Performance2 •  Hadoop* Optimizations from Intel

–  Built on Open Source Releases –  Custom Tuning for Data Types and Scaling Approaches

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Intel® Intelligent Storage Acceleration Library (Intel® ISA-L)

Intel ISA-L enables OEMs to obtain more performance from Intel® CPUs

0

1

2

3

4

Normalized to Existing Open Source Solutions

AVX Multi-buffer Hashing Functions (Baseline case is without Intel ISA-L)

Note: For more information go to http://www.intel.com/performance

Algorithmic Library to address key Storage market segment needs •  Optimized for Intel® Architecture •  Enhances efficiency, data integrity,

security/encryption Benefits of using Intel® ISA-L •  Allows maximum utilization of additional

cores •  Faster time to market (TTM)/less

resources than developing in-house •  Allows Intel to develop optimizations

using new architectural enhancements that promote faster TTM

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A Fresh Look at Intel® Virtualization Technology (Intel® VT) Intel® Virtualization Technology

Intel VT for IA-32 and Intel 64 (Intel VT-x) HW support for

isolated execution

Intel VT for Directed I/O

(Intel VT-d) HW support for

isolated I/O

VMM

VM2 VM1

Traditional Server VMM •  Isolate development and

production environment •  Technology demonstrators New Cloud Security Model •  Isolation of workloads in

multi-tenant cloud •  Memory monitoring for

malware detection •  Device Isolation for protection

against DMA attacks

Hardware Provides Stronger Isolation of VMs

Intel® Virtualization Technology for IA-32, Intel® 64 and Intel® Architecture (Intel® VT-x)

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Intel® Trusted Execution Technology (Intel® TXT)

Internet

Compliance Hardware support for compliance reporting enhances auditability of cloud environment

Trusted Launch Verified platform integrity reduces malware threat

Trusted Pools Control VMs based on platform trust to better protect data

Intel® TXT •  Enables isolation and tamper

detection in boot process •  Complements runtime

protections •  Hardware based trust provides

verification useful in compliance

•  Trust status usable by security and policy applications to control workloads

Hardens and Helps Control the Platform

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Data Protection with Intel® AES-NI

Internet Intranet

Data in Motion Secure transactions used pervasively in ecommerce, banking, etc.

Data in Process Most enterprise and cloud applications offer encryption options to secure information and protect confidentiality

Intel® AES-NI •  Special math functions built

in the processor accelerate processing of crypto algorithms like AES

•  Includes 7 new instructions •  Makes enabled encryption

software faster and stronger

Efficient Ways to Use Encryption for Data Protection

Intel® AES New Instructions (Intel® AES-NI)

Data at Rest Full disk encryption software protects data while saving to disk

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Agenda



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Big Data rEvolution

Collecting Connecting

Predicting

From To

Analyzing

From To

From To Structured Unstructured

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Summary

Intel® Architecture is foundational to finding “Your 5K”

•  Big Data Phenomenon is Real

•  Analytics based on Hadoop* will be the norm

•  Compute, Network & Storage will converge for Big Data Solutions

Compute Intel® Xeon® Processor

Storage NVM, Tiered, JBOD 10GbE Network

Network

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Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance

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Legal Disclaimer •  Intel® Hyper-Threading Technology (Intel® HT Technology) is available on select Intel® Core™ processors. Requires

an Intel® HT Technology-enabled system. Consult your PC manufacturer. Performance will vary depending on the specific hardware and software used. For more information including details on which processors support Intel HT Technology, visit http://www.intel.com/info/hyperthreading.

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•  Intel® Virtualization Technology (Intel® VT) requires a computer system with an enabled Intel® processor, BIOS, and virtual machine monitor (VMM). Functionality, performance or other benefits will vary depending on hardware and software configurations. Software applications may not be compatible with all operating systems. Consult your PC manufacturer. For more information, visit http://www.intel.com/go/virtualization

•  Intel® Turbo Boost Technology requires a system with Intel Turbo Boost Technology. Intel Turbo Boost Technology and Intel Turbo Boost Technology 2.0 are only available on select Intel® processors. Consult your PC manufacturer. Performance varies depending on hardware, software, and system configuration. For more information, visit http://www.intel.com/go/turbo

•  Intel® AES-NI requires a computer system with an AES-NI enabled processor, as well as non-Intel software to execute the instructions in the correct sequence. AES-NI is available on select Intel® processors. For availability, consult your reseller or system manufacturer. For more information, see Intel® Advanced Encryption Standard Instructions (AES-NI)

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Rev. 5/4/12