SlideShare a Scribd company logo
1 of 28
Large Data Volume
 100s of TBs to 10s of PBs
 Large scale processing and analytics at
unprecedented low cost (hardware and
software)
New Economics
 Distributed Parallel Processing
Frameworks
 Easy to Scale on commodity hardware
 MapReduce-style programming models
New
Technologies
 Unstructured
 Weak relational schema
 Text, Images, Videos, Logs
Non-Traditional data
Types
 Sensors
 Devices
 Traditional applications
 Web Servers
 Public data
New Data Sources
 How popular is my product?
 What is the best ad to serve?
 Is this a fraudulent transaction?
New Questions & New
Insights
4
5
6
var logentries =
from line in logs
where !line.StartsWith("#")
select new LogEntry(line);
var user =
from access in logentries
where access.user.EndsWith(@"sen")
select access;
var accesses =
from access in user
group access by access.page into pages
select new UserPageCount(“sen", pages.Key, pages.Count());
var htmAccesses =
from access in accesses
where access.page.EndsWith(".htm")
orderby access.count descending
select access;
LINQ query transformed into
computation graph
Input
Compute
Compute and
resort
Compute and
resort
Output
2
1
3
4 5
Processing
vertices
Edges
(files)
Inputs
Outputs
Processing
vertices
Edges
(files)
Inputs
Outputs
Free Compute Resources
Application that
calls LINQ to HPC
APIs
HPC Head Node
DSC
Submit LINQ to
HPC Job
1
1
The LINQ to HPC job also
starts a set of parametric
sweep tasks across the rest
of the nodes as DVH
2b
A LINQ to HPC job
starts 1 basic task
assigning a node as the
DGM
2a
2a
LINQ to HPC Vertices
read and write files
3b
Graph Manager starts/stops
Vertices
3a
HPC Compute Nodes
3a
3b
2b
Graph Manager
Vertex Host
Vertices read and write
files
3b
Graph Manager starts/stops
Dryad Vertices
3a
HPC Compute Nodes
3a
3b
Graph Manager
Vertex Host
Vertices in logical
computation graph
• Graph manager starts vertices on Vertex
Hosts
• Preferentially schedules vertices near input
files
When input is already on cluster, can make local
IO the common case
Application that
calls LINQ to HPC
APIs
HPC Head Node
DSC
Publish to share:
1. binaries for LINQ to HPC job
2. XML description of LINQ to
HPC graph
1
1
DVH loads binaries for this LINQ to HPC
job from share, executes them according
to commands from DGM
DGM reads XML description of graph from
share, calls DSC to locate files referenced in
XML
2a
3b
3a
HPC Compute Nodes
3a
3b
2b
LINQ to HPC Graph
Manager
LINQ to HPC Vertex
Host
The LINQ to HPC job also
starts a set of parametric
sweep tasks across the rest
of the nodes as DVH
2b
A LINQ to HPC job
starts 1 basic task
assigning a node as the
DGM
2a
DSC NODE ADD sen-cn1 /TEMPPATH:c:DryadHpcTemp /DATAPATH:c:DryadHpcData /SERVICE:sen-hn
using System;
using System.Linq;
using Microsoft.Hpc.Linq;
namespace MyProgram {
class Program {
static void Main(string[] args) {
var config = new HpcLinqConfiguration(“MyHpcClusterHeadNode”);
var context = new HpcLinqContext(config);
var lengths = context.FromDsc<LineRecord>("MyTextData")
.Select(r => r.Line.Length);
Console.WriteLine("The maximum line length is {0}", lengths.Max());
}
}
}
HPC provisioning, management,
etc.
MPI SOA
LINQ to HPC
runtime
Windows
Server
Azure*
Distributed runtimes
Cluster and cloud services
Platform
DSC (Distributed
Storage Catalog)
Bind individual NTFS shares
together to support the LINQ to
HPC distributed runtime
Programming models LINQ to HPC NEW
* Future support planned
Microsoft Big Data End-to-End
Sensors
Devices
Apps
Bots
Crawlers
Data Marts
SSAS
ERP
CRM
LOB
HPC Server
SQL EDW
S S
RS
Data & Compute
Intensive HPC App
Interactive Reports
Performance Scorecard
PowerPivot
Embedded BI Apps
Hadoop
Integration Services
Integration Services
microsoft.com/learning/en/us/exam.aspx?ID=70-690
www.microsoft.com/teched www.microsoft.com/learning
http://microsoft.com/technet http://microsoft.com/msdn
http://northamerica.msteched.com
Analyzing Large Volumes of Diverse Data with New Analytics Approaches
Analyzing Large Volumes of Diverse Data with New Analytics Approaches
Analyzing Large Volumes of Diverse Data with New Analytics Approaches

More Related Content

What's hot

Stateful Distributed Stream Processing
Stateful Distributed Stream ProcessingStateful Distributed Stream Processing
Stateful Distributed Stream ProcessingGyula Fóra
 
InfluxDB Live Product Training
InfluxDB Live Product TrainingInfluxDB Live Product Training
InfluxDB Live Product TrainingInfluxData
 
Changing landscapes in data integration - Kafka Connect for near real-time da...
Changing landscapes in data integration - Kafka Connect for near real-time da...Changing landscapes in data integration - Kafka Connect for near real-time da...
Changing landscapes in data integration - Kafka Connect for near real-time da...HostedbyConfluent
 
InfluxEnterprise Architecture Patterns by Tim Hall & Sam Dillard
InfluxEnterprise Architecture Patterns by Tim Hall & Sam DillardInfluxEnterprise Architecture Patterns by Tim Hall & Sam Dillard
InfluxEnterprise Architecture Patterns by Tim Hall & Sam DillardInfluxData
 
Baymeetup-FlinkResearch
Baymeetup-FlinkResearchBaymeetup-FlinkResearch
Baymeetup-FlinkResearchFoo Sounds
 
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...Flink Forward
 
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...Flink Forward
 
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar Aasen
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar AasenContainer Monitoring Best Practices Using AWS and InfluxData by Gunnar Aasen
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar AasenInfluxData
 
Streaming in the Wild with Apache Flink
Streaming in the Wild with Apache FlinkStreaming in the Wild with Apache Flink
Streaming in the Wild with Apache FlinkKostas Tzoumas
 
Assaf Araki – Real Time Analytics at Scale
Assaf Araki – Real Time Analytics at ScaleAssaf Araki – Real Time Analytics at Scale
Assaf Araki – Real Time Analytics at ScaleFlink Forward
 
Jim Dowling – Interactive Flink analytics with HopsWorks and Zeppelin
Jim Dowling – Interactive Flink analytics with HopsWorks and ZeppelinJim Dowling – Interactive Flink analytics with HopsWorks and Zeppelin
Jim Dowling – Interactive Flink analytics with HopsWorks and ZeppelinFlink Forward
 
Principles in Data Stream Processing | Matthias J Sax, Confluent
Principles in Data Stream Processing | Matthias J Sax, ConfluentPrinciples in Data Stream Processing | Matthias J Sax, Confluent
Principles in Data Stream Processing | Matthias J Sax, ConfluentHostedbyConfluent
 
How Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + HotstarHow Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + HotstarHostedbyConfluent
 
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...HostedbyConfluent
 
Apache Flink and what it is used for
Apache Flink and what it is used forApache Flink and what it is used for
Apache Flink and what it is used forAljoscha Krettek
 
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?Flink Forward
 
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...Flink Forward
 
Change Data Capture - Scale by the Bay 2019
Change Data Capture - Scale by the Bay 2019Change Data Capture - Scale by the Bay 2019
Change Data Capture - Scale by the Bay 2019Petr Zapletal
 

What's hot (20)

Stateful Distributed Stream Processing
Stateful Distributed Stream ProcessingStateful Distributed Stream Processing
Stateful Distributed Stream Processing
 
InfluxDB Live Product Training
InfluxDB Live Product TrainingInfluxDB Live Product Training
InfluxDB Live Product Training
 
Changing landscapes in data integration - Kafka Connect for near real-time da...
Changing landscapes in data integration - Kafka Connect for near real-time da...Changing landscapes in data integration - Kafka Connect for near real-time da...
Changing landscapes in data integration - Kafka Connect for near real-time da...
 
InfluxEnterprise Architecture Patterns by Tim Hall & Sam Dillard
InfluxEnterprise Architecture Patterns by Tim Hall & Sam DillardInfluxEnterprise Architecture Patterns by Tim Hall & Sam Dillard
InfluxEnterprise Architecture Patterns by Tim Hall & Sam Dillard
 
Baymeetup-FlinkResearch
Baymeetup-FlinkResearchBaymeetup-FlinkResearch
Baymeetup-FlinkResearch
 
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...
Virtual Flink Forward 2020: Production-Ready Flink and Hive Integration - wha...
 
Flink Streaming
Flink StreamingFlink Streaming
Flink Streaming
 
Self-Service Analytics on Hadoop: Lessons Learned
Self-Service Analytics on Hadoop: Lessons LearnedSelf-Service Analytics on Hadoop: Lessons Learned
Self-Service Analytics on Hadoop: Lessons Learned
 
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...
Flink Forward Berlin 2017 Keynote: Ferd Scheepers - Taking away customer fric...
 
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar Aasen
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar AasenContainer Monitoring Best Practices Using AWS and InfluxData by Gunnar Aasen
Container Monitoring Best Practices Using AWS and InfluxData by Gunnar Aasen
 
Streaming in the Wild with Apache Flink
Streaming in the Wild with Apache FlinkStreaming in the Wild with Apache Flink
Streaming in the Wild with Apache Flink
 
Assaf Araki – Real Time Analytics at Scale
Assaf Araki – Real Time Analytics at ScaleAssaf Araki – Real Time Analytics at Scale
Assaf Araki – Real Time Analytics at Scale
 
Jim Dowling – Interactive Flink analytics with HopsWorks and Zeppelin
Jim Dowling – Interactive Flink analytics with HopsWorks and ZeppelinJim Dowling – Interactive Flink analytics with HopsWorks and Zeppelin
Jim Dowling – Interactive Flink analytics with HopsWorks and Zeppelin
 
Principles in Data Stream Processing | Matthias J Sax, Confluent
Principles in Data Stream Processing | Matthias J Sax, ConfluentPrinciples in Data Stream Processing | Matthias J Sax, Confluent
Principles in Data Stream Processing | Matthias J Sax, Confluent
 
How Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + HotstarHow Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
 
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...
Safer Commutes & Streaming Data | George Padavick, Ohio Department of Transpo...
 
Apache Flink and what it is used for
Apache Flink and what it is used forApache Flink and what it is used for
Apache Flink and what it is used for
 
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?
Vyacheslav Zholudev – Flink, a Convenient Abstraction Layer for Yarn?
 
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...
Flink Forward San Francisco 2019: Massive Scale Data Processing at Netflix us...
 
Change Data Capture - Scale by the Bay 2019
Change Data Capture - Scale by the Bay 2019Change Data Capture - Scale by the Bay 2019
Change Data Capture - Scale by the Bay 2019
 

Viewers also liked

HybridAzureCloud
HybridAzureCloudHybridAzureCloud
HybridAzureCloudChris Condo
 
破「Windows azureでhpc 」わんくま大阪2013年12月
破「Windows azureでhpc 」わんくま大阪2013年12月破「Windows azureでhpc 」わんくま大阪2013年12月
破「Windows azureでhpc 」わんくま大阪2013年12月幸智 Yukinori 黒田 Kuroda
 
Microsoft Azure in HPC scenarios
Microsoft Azure in HPC scenariosMicrosoft Azure in HPC scenarios
Microsoft Azure in HPC scenariosmictc
 
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場幸智 Yukinori 黒田 Kuroda
 
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)Windows Azureでスーパーコンピューティング︕(DCおめでとう版)
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)幸智 Yukinori 黒田 Kuroda
 
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...Osamu Masutani
 
JPSPSLT-「WindowsAzure 最新事情」2014年2月版
JPSPSLT-「WindowsAzure 最新事情」2014年2月版JPSPSLT-「WindowsAzure 最新事情」2014年2月版
JPSPSLT-「WindowsAzure 最新事情」2014年2月版幸智 Yukinori 黒田 Kuroda
 
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用幸智 Yukinori 黒田 Kuroda
 
Taking High Performance Computing to the Cloud: Windows HPC and
Taking High Performance Computing to the Cloud: Windows HPC and Taking High Performance Computing to the Cloud: Windows HPC and
Taking High Performance Computing to the Cloud: Windows HPC and Saptak Sen
 
Windows Server ActiveDirectory のフォルダアクセス権設定のコツ
Windows Server ActiveDirectory のフォルダアクセス権設定のコツWindows Server ActiveDirectory のフォルダアクセス権設定のコツ
Windows Server ActiveDirectory のフォルダアクセス権設定のコツ幸智 Yukinori 黒田 Kuroda
 
Windows HPC Server 講習会 第1回 導入編 1/2
Windows HPC Server 講習会 第1回 導入編 1/2Windows HPC Server 講習会 第1回 導入編 1/2
Windows HPC Server 講習会 第1回 導入編 1/2Osamu Masutani
 
Windows HPC Server 講習会 第2回 開発編
Windows HPC Server 講習会 第2回 開発編Windows HPC Server 講習会 第2回 開発編
Windows HPC Server 講習会 第2回 開発編Osamu Masutani
 
Power BI チュートリアル 導入・初級編
Power BI チュートリアル 導入・初級編Power BI チュートリアル 導入・初級編
Power BI チュートリアル 導入・初級編Osamu Masutani
 

Viewers also liked (17)

HybridAzureCloud
HybridAzureCloudHybridAzureCloud
HybridAzureCloud
 
破「Windows azureでhpc 」わんくま大阪2013年12月
破「Windows azureでhpc 」わんくま大阪2013年12月破「Windows azureでhpc 」わんくま大阪2013年12月
破「Windows azureでhpc 」わんくま大阪2013年12月
 
Microsoft Azure in HPC scenarios
Microsoft Azure in HPC scenariosMicrosoft Azure in HPC scenarios
Microsoft Azure in HPC scenarios
 
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場
「Windows Azure でスーパーコンピューティング!」for Microsoft MVP camp 2014 大阪会場
 
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)Windows Azureでスーパーコンピューティング︕(DCおめでとう版)
Windows Azureでスーパーコンピューティング︕(DCおめでとう版)
 
「Windows Azureで HPC 」 for JAZUG 2013年9月
「Windows Azureで HPC 」 for JAZUG 2013年9月「Windows Azureで HPC 」 for JAZUG 2013年9月
「Windows Azureで HPC 」 for JAZUG 2013年9月
 
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...
A Sensing Coverage Analysis of a Route Control Method for Vehicular Crowd Sen...
 
JPSPSLT-「WindowsAzure 最新事情」2014年2月版
JPSPSLT-「WindowsAzure 最新事情」2014年2月版JPSPSLT-「WindowsAzure 最新事情」2014年2月版
JPSPSLT-「WindowsAzure 最新事情」2014年2月版
 
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用
20130601わんくま「序hpcクラスターを作ろう!まずはオンプレで」公開用
 
Taxi Fare Deep Dive
Taxi Fare Deep DiveTaxi Fare Deep Dive
Taxi Fare Deep Dive
 
Taking High Performance Computing to the Cloud: Windows HPC and
Taking High Performance Computing to the Cloud: Windows HPC and Taking High Performance Computing to the Cloud: Windows HPC and
Taking High Performance Computing to the Cloud: Windows HPC and
 
Windows Server ActiveDirectory のフォルダアクセス権設定のコツ
Windows Server ActiveDirectory のフォルダアクセス権設定のコツWindows Server ActiveDirectory のフォルダアクセス権設定のコツ
Windows Server ActiveDirectory のフォルダアクセス権設定のコツ
 
Windows HPC Server 講習会 第1回 導入編 1/2
Windows HPC Server 講習会 第1回 導入編 1/2Windows HPC Server 講習会 第1回 導入編 1/2
Windows HPC Server 講習会 第1回 導入編 1/2
 
Windows HPC Server 講習会 第2回 開発編
Windows HPC Server 講習会 第2回 開発編Windows HPC Server 講習会 第2回 開発編
Windows HPC Server 講習会 第2回 開発編
 
HPC Market Update from IDC
HPC Market Update from IDCHPC Market Update from IDC
HPC Market Update from IDC
 
Life sciences Predictions 2016
Life sciences Predictions 2016Life sciences Predictions 2016
Life sciences Predictions 2016
 
Power BI チュートリアル 導入・初級編
Power BI チュートリアル 導入・初級編Power BI チュートリアル 導入・初級編
Power BI チュートリアル 導入・初級編
 

Similar to Analyzing Large Volumes of Diverse Data with New Analytics Approaches

SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...butest
 
SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...butest
 
Managing and Deploying High Performance Computing Clusters using Windows HPC ...
Managing and Deploying High Performance Computing Clusters using Windows HPC ...Managing and Deploying High Performance Computing Clusters using Windows HPC ...
Managing and Deploying High Performance Computing Clusters using Windows HPC ...Saptak Sen
 
The Download: Tech Talks by the HPCC Systems Community, Episode 11
The Download: Tech Talks by the HPCC Systems Community, Episode 11The Download: Tech Talks by the HPCC Systems Community, Episode 11
The Download: Tech Talks by the HPCC Systems Community, Episode 11HPCC Systems
 
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...Robert Metzger
 
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...confluent
 
Apache Kafka® and the Data Mesh
Apache Kafka® and the Data MeshApache Kafka® and the Data Mesh
Apache Kafka® and the Data MeshConfluentInc1
 
Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia
Deep learning and streaming in Apache Spark 2.2 by Matei ZahariaDeep learning and streaming in Apache Spark 2.2 by Matei Zaharia
Deep learning and streaming in Apache Spark 2.2 by Matei ZahariaGoDataDriven
 
Clusters (Distributed computing)
Clusters (Distributed computing)Clusters (Distributed computing)
Clusters (Distributed computing)Sri Prasanna
 
HIPAS UCP HSP Openstack Sascha Oehl
HIPAS UCP HSP Openstack Sascha OehlHIPAS UCP HSP Openstack Sascha Oehl
HIPAS UCP HSP Openstack Sascha OehlSascha Oehl
 
Overview of VS2010 and .NET 4.0
Overview of VS2010 and .NET 4.0Overview of VS2010 and .NET 4.0
Overview of VS2010 and .NET 4.0Bruce Johnson
 
What's New in .Net 4.5
What's New in .Net 4.5What's New in .Net 4.5
What's New in .Net 4.5Malam Team
 
Google Cloud Computing on Google Developer 2008 Day
Google Cloud Computing on Google Developer 2008 DayGoogle Cloud Computing on Google Developer 2008 Day
Google Cloud Computing on Google Developer 2008 Dayprogrammermag
 
Red Hat Enterprise Linux: The web performance leader
Red Hat Enterprise Linux: The web performance leaderRed Hat Enterprise Linux: The web performance leader
Red Hat Enterprise Linux: The web performance leaderJoanne El Chah
 
Webinar: Unlock the Power of Streaming Data with Kinetica and Confluent
Webinar: Unlock the Power of Streaming Data with Kinetica and ConfluentWebinar: Unlock the Power of Streaming Data with Kinetica and Confluent
Webinar: Unlock the Power of Streaming Data with Kinetica and ConfluentKinetica
 
The Never Landing Stream with HTAP and Streaming
The Never Landing Stream with HTAP and StreamingThe Never Landing Stream with HTAP and Streaming
The Never Landing Stream with HTAP and StreamingTimothy Spann
 
MACHBASE_NEO
MACHBASE_NEOMACHBASE_NEO
MACHBASE_NEOMACHBASE
 
Leveraging Mainframe Data for Modern Analytics
Leveraging Mainframe Data for Modern AnalyticsLeveraging Mainframe Data for Modern Analytics
Leveraging Mainframe Data for Modern Analyticsconfluent
 

Similar to Analyzing Large Volumes of Diverse Data with New Analytics Approaches (20)

SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...
 
SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...SVR17: Data-Intensive Computing on Windows HPC Server with the ...
SVR17: Data-Intensive Computing on Windows HPC Server with the ...
 
Managing and Deploying High Performance Computing Clusters using Windows HPC ...
Managing and Deploying High Performance Computing Clusters using Windows HPC ...Managing and Deploying High Performance Computing Clusters using Windows HPC ...
Managing and Deploying High Performance Computing Clusters using Windows HPC ...
 
Xavient - DiP
Xavient - DiPXavient - DiP
Xavient - DiP
 
The Download: Tech Talks by the HPCC Systems Community, Episode 11
The Download: Tech Talks by the HPCC Systems Community, Episode 11The Download: Tech Talks by the HPCC Systems Community, Episode 11
The Download: Tech Talks by the HPCC Systems Community, Episode 11
 
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
Apache Flink Meetup Munich (November 2015): Flink Overview, Architecture, Int...
 
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
 
Apache Kafka® and the Data Mesh
Apache Kafka® and the Data MeshApache Kafka® and the Data Mesh
Apache Kafka® and the Data Mesh
 
Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia
Deep learning and streaming in Apache Spark 2.2 by Matei ZahariaDeep learning and streaming in Apache Spark 2.2 by Matei Zaharia
Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia
 
Clusters (Distributed computing)
Clusters (Distributed computing)Clusters (Distributed computing)
Clusters (Distributed computing)
 
HIPAS UCP HSP Openstack Sascha Oehl
HIPAS UCP HSP Openstack Sascha OehlHIPAS UCP HSP Openstack Sascha Oehl
HIPAS UCP HSP Openstack Sascha Oehl
 
Overview of VS2010 and .NET 4.0
Overview of VS2010 and .NET 4.0Overview of VS2010 and .NET 4.0
Overview of VS2010 and .NET 4.0
 
What's New in .Net 4.5
What's New in .Net 4.5What's New in .Net 4.5
What's New in .Net 4.5
 
Google Cloud Computing on Google Developer 2008 Day
Google Cloud Computing on Google Developer 2008 DayGoogle Cloud Computing on Google Developer 2008 Day
Google Cloud Computing on Google Developer 2008 Day
 
Red Hat Enterprise Linux: The web performance leader
Red Hat Enterprise Linux: The web performance leaderRed Hat Enterprise Linux: The web performance leader
Red Hat Enterprise Linux: The web performance leader
 
Webinar: Unlock the Power of Streaming Data with Kinetica and Confluent
Webinar: Unlock the Power of Streaming Data with Kinetica and ConfluentWebinar: Unlock the Power of Streaming Data with Kinetica and Confluent
Webinar: Unlock the Power of Streaming Data with Kinetica and Confluent
 
The Never Landing Stream with HTAP and Streaming
The Never Landing Stream with HTAP and StreamingThe Never Landing Stream with HTAP and Streaming
The Never Landing Stream with HTAP and Streaming
 
MACHBASE_NEO
MACHBASE_NEOMACHBASE_NEO
MACHBASE_NEO
 
Big Data , Big Problem?
Big Data , Big Problem?Big Data , Big Problem?
Big Data , Big Problem?
 
Leveraging Mainframe Data for Modern Analytics
Leveraging Mainframe Data for Modern AnalyticsLeveraging Mainframe Data for Modern Analytics
Leveraging Mainframe Data for Modern Analytics
 

More from Saptak Sen

Apache Spark with Hortonworks Data Platform - Seattle Meetup
Apache Spark with Hortonworks Data Platform - Seattle MeetupApache Spark with Hortonworks Data Platform - Seattle Meetup
Apache Spark with Hortonworks Data Platform - Seattle MeetupSaptak Sen
 
Introduction to Apache NiFi - Seattle Scalability Meetup
Introduction to Apache NiFi - Seattle Scalability MeetupIntroduction to Apache NiFi - Seattle Scalability Meetup
Introduction to Apache NiFi - Seattle Scalability MeetupSaptak Sen
 
Data Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataData Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataSaptak Sen
 
Do You Have Big Data? (Most Likely!)
Do You Have Big Data? (Most Likely!)Do You Have Big Data? (Most Likely!)
Do You Have Big Data? (Most Likely!)Saptak Sen
 
Predictive Analytics with Microsoft Big Data
Predictive Analytics with Microsoft Big DataPredictive Analytics with Microsoft Big Data
Predictive Analytics with Microsoft Big DataSaptak Sen
 
Data Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataData Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataSaptak Sen
 
Apache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitApache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitSaptak Sen
 

More from Saptak Sen (7)

Apache Spark with Hortonworks Data Platform - Seattle Meetup
Apache Spark with Hortonworks Data Platform - Seattle MeetupApache Spark with Hortonworks Data Platform - Seattle Meetup
Apache Spark with Hortonworks Data Platform - Seattle Meetup
 
Introduction to Apache NiFi - Seattle Scalability Meetup
Introduction to Apache NiFi - Seattle Scalability MeetupIntroduction to Apache NiFi - Seattle Scalability Meetup
Introduction to Apache NiFi - Seattle Scalability Meetup
 
Data Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataData Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your Data
 
Do You Have Big Data? (Most Likely!)
Do You Have Big Data? (Most Likely!)Do You Have Big Data? (Most Likely!)
Do You Have Big Data? (Most Likely!)
 
Predictive Analytics with Microsoft Big Data
Predictive Analytics with Microsoft Big DataPredictive Analytics with Microsoft Big Data
Predictive Analytics with Microsoft Big Data
 
Data Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your DataData Management in Microsoft HDInsight: How to Move and Store Your Data
Data Management in Microsoft HDInsight: How to Move and Store Your Data
 
Apache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitApache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop Summit
 

Recently uploaded

The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...soniya singh
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVshikhaohhpro
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 
Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)OPEN KNOWLEDGE GmbH
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfkalichargn70th171
 
What is Binary Language? Computer Number Systems
What is Binary Language?  Computer Number SystemsWhat is Binary Language?  Computer Number Systems
What is Binary Language? Computer Number SystemsJheuzeDellosa
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio, Inc.
 
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfThe Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfkalichargn70th171
 
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASEBATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASEOrtus Solutions, Corp
 
DNT_Corporate presentation know about us
DNT_Corporate presentation know about usDNT_Corporate presentation know about us
DNT_Corporate presentation know about usDynamic Netsoft
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityNeo4j
 
TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providermohitmore19
 
why an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfwhy an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfjoe51371421
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataBradBedford3
 
Professional Resume Template for Software Developers
Professional Resume Template for Software DevelopersProfessional Resume Template for Software Developers
Professional Resume Template for Software DevelopersVinodh Ram
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackVICTOR MAESTRE RAMIREZ
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdfWave PLM
 
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...stazi3110
 

Recently uploaded (20)

The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTV
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 
Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
 
What is Binary Language? Computer Number Systems
What is Binary Language?  Computer Number SystemsWhat is Binary Language?  Computer Number Systems
What is Binary Language? Computer Number Systems
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
 
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfThe Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
 
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASEBATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
 
DNT_Corporate presentation know about us
DNT_Corporate presentation know about usDNT_Corporate presentation know about us
DNT_Corporate presentation know about us
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
 
TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service provider
 
why an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfwhy an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdf
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
 
Professional Resume Template for Software Developers
Professional Resume Template for Software DevelopersProfessional Resume Template for Software Developers
Professional Resume Template for Software Developers
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStack
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf
 
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
 

Analyzing Large Volumes of Diverse Data with New Analytics Approaches

  • 1.
  • 2.
  • 3.
  • 4. Large Data Volume  100s of TBs to 10s of PBs  Large scale processing and analytics at unprecedented low cost (hardware and software) New Economics  Distributed Parallel Processing Frameworks  Easy to Scale on commodity hardware  MapReduce-style programming models New Technologies  Unstructured  Weak relational schema  Text, Images, Videos, Logs Non-Traditional data Types  Sensors  Devices  Traditional applications  Web Servers  Public data New Data Sources  How popular is my product?  What is the best ad to serve?  Is this a fraudulent transaction? New Questions & New Insights 4
  • 5. 5
  • 6. 6
  • 7.
  • 8. var logentries = from line in logs where !line.StartsWith("#") select new LogEntry(line); var user = from access in logentries where access.user.EndsWith(@"sen") select access; var accesses = from access in user group access by access.page into pages select new UserPageCount(“sen", pages.Key, pages.Count()); var htmAccesses = from access in accesses where access.page.EndsWith(".htm") orderby access.count descending select access; LINQ query transformed into computation graph Input Compute Compute and resort Compute and resort Output 2 1 3 4 5
  • 11. Application that calls LINQ to HPC APIs HPC Head Node DSC Submit LINQ to HPC Job 1 1 The LINQ to HPC job also starts a set of parametric sweep tasks across the rest of the nodes as DVH 2b A LINQ to HPC job starts 1 basic task assigning a node as the DGM 2a 2a LINQ to HPC Vertices read and write files 3b Graph Manager starts/stops Vertices 3a HPC Compute Nodes 3a 3b 2b Graph Manager Vertex Host
  • 12. Vertices read and write files 3b Graph Manager starts/stops Dryad Vertices 3a HPC Compute Nodes 3a 3b Graph Manager Vertex Host Vertices in logical computation graph • Graph manager starts vertices on Vertex Hosts • Preferentially schedules vertices near input files When input is already on cluster, can make local IO the common case
  • 13. Application that calls LINQ to HPC APIs HPC Head Node DSC Publish to share: 1. binaries for LINQ to HPC job 2. XML description of LINQ to HPC graph 1 1 DVH loads binaries for this LINQ to HPC job from share, executes them according to commands from DGM DGM reads XML description of graph from share, calls DSC to locate files referenced in XML 2a 3b 3a HPC Compute Nodes 3a 3b 2b LINQ to HPC Graph Manager LINQ to HPC Vertex Host The LINQ to HPC job also starts a set of parametric sweep tasks across the rest of the nodes as DVH 2b A LINQ to HPC job starts 1 basic task assigning a node as the DGM 2a
  • 14. DSC NODE ADD sen-cn1 /TEMPPATH:c:DryadHpcTemp /DATAPATH:c:DryadHpcData /SERVICE:sen-hn
  • 15.
  • 16.
  • 17. using System; using System.Linq; using Microsoft.Hpc.Linq; namespace MyProgram { class Program { static void Main(string[] args) { var config = new HpcLinqConfiguration(“MyHpcClusterHeadNode”); var context = new HpcLinqContext(config); var lengths = context.FromDsc<LineRecord>("MyTextData") .Select(r => r.Line.Length); Console.WriteLine("The maximum line length is {0}", lengths.Max()); } } }
  • 18.
  • 19.
  • 20. HPC provisioning, management, etc. MPI SOA LINQ to HPC runtime Windows Server Azure* Distributed runtimes Cluster and cloud services Platform DSC (Distributed Storage Catalog) Bind individual NTFS shares together to support the LINQ to HPC distributed runtime Programming models LINQ to HPC NEW * Future support planned
  • 21.
  • 22.
  • 23. Microsoft Big Data End-to-End Sensors Devices Apps Bots Crawlers Data Marts SSAS ERP CRM LOB HPC Server SQL EDW S S RS Data & Compute Intensive HPC App Interactive Reports Performance Scorecard PowerPivot Embedded BI Apps Hadoop Integration Services Integration Services