SlideShare une entreprise Scribd logo
1  sur  17
Télécharger pour lire hors ligne
© 2015 MapR Technologies 1© 2015 MapR Technologies
Taking Your Spark To Production Scale
© 2015 MapR Technologies 2
The Journey To Production Scale
Trials,
science projects
Large
mission-critical,
operational
deployments
© 2015 MapR Technologies 2
© 2015 MapR Technologies 3
Companies with Spark & MapR in Production
GLOBAL
TELECOM
HEALTHCARE
GLOBALFINANCIAL
SERVICES
© 2015 MapR Technologies 4
Key Issues
To Plan For
3
© 2015 MapR Technologies 5
Global Managed Security Services
delivered on Hadoop
Spark Stream processing used to
first check for known threats
Data next processed on Hadoop
using MLLib and GraphX
Additional SQL querying done via
Spark SQL
Security Intelligence Operations
Delivers Lightning Fast
Analytics for Clients
Building largest Hadoop cluster
in Australia
Real-time analytics using Spark on
MapR–reducing data loading time
from hours to minutes
Leverage multi-tenancy,
high-performance and reliability
of MapR
© 2015 MapR Technologies 7
Next-Gen Genomics
Develop flexible platform to keep up with fast
changing research techniques
POSIX file access lets bio-informaticians use
existing tools with open source tools (Spark)
Graph manipulations can be done reliably and
at scale using Spark
© 2015 MapR Technologies 8
Real-Time Customer Analytics
• MapR Data Lake stores both online
and archive data
• Spark on MapR reduced ETL
processing
• NFS moved data into the cluster
seamlessly
• 1/10th Total Cost of Ownership vs.
old way
• New customer onboarding cut from
months to weeks
© 2015 MapR Technologies 9
Databricks & MapR
Strategic Partnership
(since April 2014)
Support for the
complete Spark stack
Engineering & roadmap
collaboration
Back-end support
+
© 2015 MapR Technologies 10
The Most Complete Spark Environment
Spark SQL
(SQL)
Spark
Streaming
(Streaming)
MLlib
(Machine
learning)
GraphX (Graph
computation)
Foundation For Enterprise-Grade Spark
© 2015 MapR Technologies 11
DB
Operations
Real-Time and
Actionable
Analytics
Operations + Analytics on One Hadoop Platform with SQL Access
Mobile
application
server
Customer 360
dashboard
Churn analysis Product/service
optimization and
personalization
Real-time ad
targeting
Web application
server
Data exploration
(SQL)
• User profiles and state
• User interactions
• Real-time location data
• Web and mobile session state
• Comments/rankings
© 2015 MapR Technologies 12
Spark + MapR = Ready For Production Success
World-record performance on disk
High Performance
SLA-Driven Applications
• High availability
• Data protection
• Disaster recovery
Reliability for Production
Strategic partnership with
Databricks to ensure enterprise
support for the entire stack
24/7 Best-in-class Global
Support
MapR-DB + Spark = real-time analytics
Operational Data Store
© 2015 MapR Technologies 13
Free
On-Demand Training
www.mapr.com/training
© 2015 MapR Technologies 14
Self-Service Data Exploration
Data Agility with Less IT Required
Single SQL Interface for Structured
and Semi-Structured Data
© 2015 MapR Technologies 15
MapR Introduces 3 New Spark-Based
Quick Start Solutions
Real-Time Security Log Analytics
Time Series Analytics
Genome Sequencing
© 2015 MapR Technologies 16
Get Your Tattoo In The MapR Booth!
Show off your
Kickstart My Heart skills
and enter to win
Xbox 360 & Guitar Hero
© 2015 MapR Technologies 17
Top-Ranked NoSQL
Top-Ranked Hadoop
Distribution
Top-Ranked SQL-on Hadoop
Solution

Contenu connexe

Tendances

3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data AnalyticsMapR Technologies
 
CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016Mathieu Dumoulin
 
Real World Use Cases: Hadoop and NoSQL in Production
Real World Use Cases: Hadoop and NoSQL in ProductionReal World Use Cases: Hadoop and NoSQL in Production
Real World Use Cases: Hadoop and NoSQL in ProductionCodemotion
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageMapR Technologies
 
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapR
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapRThe Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapR
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapRThe Hive
 
NoSQL Application Development with JSON and MapR-DB
NoSQL Application Development with JSON and MapR-DBNoSQL Application Development with JSON and MapR-DB
NoSQL Application Development with JSON and MapR-DBMapR Technologies
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0MapR Technologies
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR Technologies
 
MapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR Technologies
 
State of the Art Robot Predictive Maintenance with Real-time Sensor Data
State of the Art Robot Predictive Maintenance with Real-time Sensor DataState of the Art Robot Predictive Maintenance with Real-time Sensor Data
State of the Art Robot Predictive Maintenance with Real-time Sensor DataMathieu Dumoulin
 
How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications MapR Technologies
 
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...MapR Technologies
 
Common and unique use cases for Apache Hadoop
Common and unique use cases for Apache HadoopCommon and unique use cases for Apache Hadoop
Common and unique use cases for Apache HadoopBrock Noland
 
MapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR Technologies
 

Tendances (20)

3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics
 
Keys for Success from Streams to Queries
Keys for Success from Streams to QueriesKeys for Success from Streams to Queries
Keys for Success from Streams to Queries
 
CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016
 
Real World Use Cases: Hadoop and NoSQL in Production
Real World Use Cases: Hadoop and NoSQL in ProductionReal World Use Cases: Hadoop and NoSQL in Production
Real World Use Cases: Hadoop and NoSQL in Production
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
 
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapR
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapRThe Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapR
The Hive Think Tank: "Stream Processing Systems" by M.C. Srivas of MapR
 
NoSQL Application Development with JSON and MapR-DB
NoSQL Application Development with JSON and MapR-DBNoSQL Application Development with JSON and MapR-DB
NoSQL Application Development with JSON and MapR-DB
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -
 
MapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document Database
 
State of the Art Robot Predictive Maintenance with Real-time Sensor Data
State of the Art Robot Predictive Maintenance with Real-time Sensor DataState of the Art Robot Predictive Maintenance with Real-time Sensor Data
State of the Art Robot Predictive Maintenance with Real-time Sensor Data
 
How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications
 
MapR 5.2 Product Update
MapR 5.2 Product UpdateMapR 5.2 Product Update
MapR 5.2 Product Update
 
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...
Xactly: How to Build a Successful Converged Data Platform with Hadoop, Spark,...
 
Philly DB MapR Overview
Philly DB MapR OverviewPhilly DB MapR Overview
Philly DB MapR Overview
 
Log I am your father
Log I am your fatherLog I am your father
Log I am your father
 
Common and unique use cases for Apache Hadoop
Common and unique use cases for Apache HadoopCommon and unique use cases for Apache Hadoop
Common and unique use cases for Apache Hadoop
 
Big Data at your Desk with KNIME
Big Data at your Desk with KNIMEBig Data at your Desk with KNIME
Big Data at your Desk with KNIME
 
MapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community Edition
 
Deep Learning at Scale
Deep Learning at ScaleDeep Learning at Scale
Deep Learning at Scale
 

En vedette

Machine Learning with Hadoop Boston hug 2012
Machine Learning with Hadoop Boston hug 2012Machine Learning with Hadoop Boston hug 2012
Machine Learning with Hadoop Boston hug 2012MapR Technologies
 
HBase backups and performance on MapR
HBase backups and performance on MapRHBase backups and performance on MapR
HBase backups and performance on MapRlohitvijayarenu
 
Apache Drill – Hands-On SQL References
Apache Drill – Hands-On SQL ReferencesApache Drill – Hands-On SQL References
Apache Drill – Hands-On SQL ReferencesMapR Technologies
 
Practical Machine Learning: Innovations in Recommendation Workshop
Practical Machine Learning:  Innovations in Recommendation WorkshopPractical Machine Learning:  Innovations in Recommendation Workshop
Practical Machine Learning: Innovations in Recommendation WorkshopMapR Technologies
 
Intro to Apache Spark by CTO of Twingo
Intro to Apache Spark by CTO of TwingoIntro to Apache Spark by CTO of Twingo
Intro to Apache Spark by CTO of TwingoMapR Technologies
 
Real Time and Big Data – It’s About Time
Real Time and Big Data – It’s About TimeReal Time and Big Data – It’s About Time
Real Time and Big Data – It’s About TimeMapR Technologies
 
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapR
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapRHadoop benchmark: Evaluating Cloudera, Hortonworks, and MapR
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapRDouglas Bernardini
 
Intro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezIntro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezMapR Technologies
 
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッション
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッションApache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッション
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッションMapR Technologies Japan
 
Inside MapR's M7
Inside MapR's M7Inside MapR's M7
Inside MapR's M7Ted Dunning
 
Introduction to Apache HBase, MapR Tables and Security
Introduction to Apache HBase, MapR Tables and SecurityIntroduction to Apache HBase, MapR Tables and Security
Introduction to Apache HBase, MapR Tables and SecurityMapR Technologies
 
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQL
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQLHBase and Drill: How Loosely Typed SQL is Ideal for NoSQL
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQLMapR Technologies
 
Apache HBase Performance Tuning
Apache HBase Performance TuningApache HBase Performance Tuning
Apache HBase Performance TuningLars Hofhansl
 

En vedette (16)

Machine Learning with Hadoop Boston hug 2012
Machine Learning with Hadoop Boston hug 2012Machine Learning with Hadoop Boston hug 2012
Machine Learning with Hadoop Boston hug 2012
 
HBase backups and performance on MapR
HBase backups and performance on MapRHBase backups and performance on MapR
HBase backups and performance on MapR
 
Inside MapR's M7
Inside MapR's M7Inside MapR's M7
Inside MapR's M7
 
Apache Drill – Hands-On SQL References
Apache Drill – Hands-On SQL ReferencesApache Drill – Hands-On SQL References
Apache Drill – Hands-On SQL References
 
Practical Machine Learning: Innovations in Recommendation Workshop
Practical Machine Learning:  Innovations in Recommendation WorkshopPractical Machine Learning:  Innovations in Recommendation Workshop
Practical Machine Learning: Innovations in Recommendation Workshop
 
Intro to Apache Spark by CTO of Twingo
Intro to Apache Spark by CTO of TwingoIntro to Apache Spark by CTO of Twingo
Intro to Apache Spark by CTO of Twingo
 
Real Time and Big Data – It’s About Time
Real Time and Big Data – It’s About TimeReal Time and Big Data – It’s About Time
Real Time and Big Data – It’s About Time
 
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapR
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapRHadoop benchmark: Evaluating Cloudera, Hortonworks, and MapR
Hadoop benchmark: Evaluating Cloudera, Hortonworks, and MapR
 
Intro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezIntro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco Vasquez
 
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッション
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッションApache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッション
Apache Drill でたしなむ セルフサービスデータ探索 - 2014/11/06 Cloudera World Tokyo 2014 LTセッション
 
MapR & Skytree:
MapR & Skytree: MapR & Skytree:
MapR & Skytree:
 
Inside MapR's M7
Inside MapR's M7Inside MapR's M7
Inside MapR's M7
 
Introduction to Apache HBase, MapR Tables and Security
Introduction to Apache HBase, MapR Tables and SecurityIntroduction to Apache HBase, MapR Tables and Security
Introduction to Apache HBase, MapR Tables and Security
 
Apache Spark & Hadoop
Apache Spark & HadoopApache Spark & Hadoop
Apache Spark & Hadoop
 
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQL
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQLHBase and Drill: How Loosely Typed SQL is Ideal for NoSQL
HBase and Drill: How Loosely Typed SQL is Ideal for NoSQL
 
Apache HBase Performance Tuning
Apache HBase Performance TuningApache HBase Performance Tuning
Apache HBase Performance Tuning
 

Similaire à Spark & Hadoop at Production at Scale

Spark and Hadoop at Production Scale-(Anil Gadre, MapR)
Spark and Hadoop at Production Scale-(Anil Gadre, MapR)Spark and Hadoop at Production Scale-(Anil Gadre, MapR)
Spark and Hadoop at Production Scale-(Anil Gadre, MapR)Spark Summit
 
How Experian increased insights with Hadoop
How Experian increased insights with HadoopHow Experian increased insights with Hadoop
How Experian increased insights with HadoopPrecisely
 
BDTC2015 databricks-辛湜-state of spark
BDTC2015 databricks-辛湜-state of sparkBDTC2015 databricks-辛湜-state of spark
BDTC2015 databricks-辛湜-state of sparkJerry Wen
 
Integrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentIntegrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentMapR Technologies
 
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin Motgi
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin MotgiWhither the Hadoop Developer Experience, June Hadoop Meetup, Nitin Motgi
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin MotgiFelicia Haggarty
 
Hadoop and NoSQL joining forces by Dale Kim of MapR
Hadoop and NoSQL joining forces by Dale Kim of MapRHadoop and NoSQL joining forces by Dale Kim of MapR
Hadoop and NoSQL joining forces by Dale Kim of MapRData Con LA
 
Hadoop and the Future of SQL: Using BI Tools with Big Data
Hadoop and the Future of SQL: Using BI Tools with Big DataHadoop and the Future of SQL: Using BI Tools with Big Data
Hadoop and the Future of SQL: Using BI Tools with Big DataSenturus
 
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
 
Key Considerations for Putting Hadoop in Production SlideShare
Key Considerations for Putting Hadoop in Production SlideShareKey Considerations for Putting Hadoop in Production SlideShare
Key Considerations for Putting Hadoop in Production SlideShareMapR Technologies
 
Big Data LDN 2017: How to leverage the cloud for Business Solutions
Big Data LDN 2017: How to leverage the cloud for Business SolutionsBig Data LDN 2017: How to leverage the cloud for Business Solutions
Big Data LDN 2017: How to leverage the cloud for Business SolutionsMatt Stubbs
 
Meruvian - Introduction to MapR
Meruvian - Introduction to MapRMeruvian - Introduction to MapR
Meruvian - Introduction to MapRThe World Bank
 
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-Hadoop
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-HadoopHP Vertica and MapR Webinar: Building a Business Case for SQL-on-Hadoop
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-HadoopMapR Technologies
 
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017Stefan Lipp
 
Big Data & Open Source - Neil Jadhav
Big Data & Open Source - Neil JadhavBig Data & Open Source - Neil Jadhav
Big Data & Open Source - Neil JadhavSwapnil (Neil) Jadhav
 
Enabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureEnabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureMapR Technologies
 
Spark + Hadoop Perfect together
Spark + Hadoop Perfect togetherSpark + Hadoop Perfect together
Spark + Hadoop Perfect togetherIsheeta Sanghi
 
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyWebinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyDataStax
 
Scaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceScaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceeRic Choo
 
Spark and Hadoop Perfect Togeher by Arun Murthy
Spark and Hadoop Perfect Togeher by Arun MurthySpark and Hadoop Perfect Togeher by Arun Murthy
Spark and Hadoop Perfect Togeher by Arun MurthySpark Summit
 
Spark Summit EMEA - Arun Murthy's Keynote
Spark Summit EMEA - Arun Murthy's KeynoteSpark Summit EMEA - Arun Murthy's Keynote
Spark Summit EMEA - Arun Murthy's KeynoteHortonworks
 

Similaire à Spark & Hadoop at Production at Scale (20)

Spark and Hadoop at Production Scale-(Anil Gadre, MapR)
Spark and Hadoop at Production Scale-(Anil Gadre, MapR)Spark and Hadoop at Production Scale-(Anil Gadre, MapR)
Spark and Hadoop at Production Scale-(Anil Gadre, MapR)
 
How Experian increased insights with Hadoop
How Experian increased insights with HadoopHow Experian increased insights with Hadoop
How Experian increased insights with Hadoop
 
BDTC2015 databricks-辛湜-state of spark
BDTC2015 databricks-辛湜-state of sparkBDTC2015 databricks-辛湜-state of spark
BDTC2015 databricks-辛湜-state of spark
 
Integrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentIntegrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environment
 
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin Motgi
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin MotgiWhither the Hadoop Developer Experience, June Hadoop Meetup, Nitin Motgi
Whither the Hadoop Developer Experience, June Hadoop Meetup, Nitin Motgi
 
Hadoop and NoSQL joining forces by Dale Kim of MapR
Hadoop and NoSQL joining forces by Dale Kim of MapRHadoop and NoSQL joining forces by Dale Kim of MapR
Hadoop and NoSQL joining forces by Dale Kim of MapR
 
Hadoop and the Future of SQL: Using BI Tools with Big Data
Hadoop and the Future of SQL: Using BI Tools with Big DataHadoop and the Future of SQL: Using BI Tools with Big Data
Hadoop and the Future of SQL: Using BI Tools with Big Data
 
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
 
Key Considerations for Putting Hadoop in Production SlideShare
Key Considerations for Putting Hadoop in Production SlideShareKey Considerations for Putting Hadoop in Production SlideShare
Key Considerations for Putting Hadoop in Production SlideShare
 
Big Data LDN 2017: How to leverage the cloud for Business Solutions
Big Data LDN 2017: How to leverage the cloud for Business SolutionsBig Data LDN 2017: How to leverage the cloud for Business Solutions
Big Data LDN 2017: How to leverage the cloud for Business Solutions
 
Meruvian - Introduction to MapR
Meruvian - Introduction to MapRMeruvian - Introduction to MapR
Meruvian - Introduction to MapR
 
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-Hadoop
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-HadoopHP Vertica and MapR Webinar: Building a Business Case for SQL-on-Hadoop
HP Vertica and MapR Webinar: Building a Business Case for SQL-on-Hadoop
 
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017
Cloudera Big Data Integration Speedpitch at TDWI Munich June 2017
 
Big Data & Open Source - Neil Jadhav
Big Data & Open Source - Neil JadhavBig Data & Open Source - Neil Jadhav
Big Data & Open Source - Neil Jadhav
 
Enabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureEnabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data Capture
 
Spark + Hadoop Perfect together
Spark + Hadoop Perfect togetherSpark + Hadoop Perfect together
Spark + Hadoop Perfect together
 
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyWebinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
 
Scaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data ScienceScaling up with Cisco Big Data: Data + Science = Data Science
Scaling up with Cisco Big Data: Data + Science = Data Science
 
Spark and Hadoop Perfect Togeher by Arun Murthy
Spark and Hadoop Perfect Togeher by Arun MurthySpark and Hadoop Perfect Togeher by Arun Murthy
Spark and Hadoop Perfect Togeher by Arun Murthy
 
Spark Summit EMEA - Arun Murthy's Keynote
Spark Summit EMEA - Arun Murthy's KeynoteSpark Summit EMEA - Arun Murthy's Keynote
Spark Summit EMEA - Arun Murthy's Keynote
 

Plus de MapR Technologies

Converging your data landscape
Converging your data landscapeConverging your data landscape
Converging your data landscapeMapR Technologies
 
ML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationMapR Technologies
 
Self-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataSelf-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataMapR Technologies
 
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...MapR Technologies
 
ML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsMapR Technologies
 
Machine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMachine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMapR Technologies
 
Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action MapR Technologies
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsMapR Technologies
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionMapR Technologies
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformMapR Technologies
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...MapR Technologies
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareMapR Technologies
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsMapR Technologies
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Technologies
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLMapR Technologies
 
Handling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceHandling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceMapR Technologies
 
Baptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataBaptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataMapR Technologies
 
The Keys to Digital Transformation
The Keys to Digital TransformationThe Keys to Digital Transformation
The Keys to Digital TransformationMapR Technologies
 
Insight Platforms Accelerate Digital Transformation
Insight Platforms Accelerate Digital TransformationInsight Platforms Accelerate Digital Transformation
Insight Platforms Accelerate Digital TransformationMapR Technologies
 
Design Patterns for working with Fast Data
Design Patterns for working with Fast DataDesign Patterns for working with Fast Data
Design Patterns for working with Fast DataMapR Technologies
 

Plus de MapR Technologies (20)

Converging your data landscape
Converging your data landscapeConverging your data landscape
Converging your data landscape
 
ML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & Evaluation
 
Self-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataSelf-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your Data
 
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
 
ML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning Logistics
 
Machine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMachine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model Management
 
Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIs
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn Prediction
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data Platform
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in Healthcare
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and Analytics
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQL
 
Handling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceHandling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in Finance
 
Baptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataBaptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big Data
 
The Keys to Digital Transformation
The Keys to Digital TransformationThe Keys to Digital Transformation
The Keys to Digital Transformation
 
Insight Platforms Accelerate Digital Transformation
Insight Platforms Accelerate Digital TransformationInsight Platforms Accelerate Digital Transformation
Insight Platforms Accelerate Digital Transformation
 
Design Patterns for working with Fast Data
Design Patterns for working with Fast DataDesign Patterns for working with Fast Data
Design Patterns for working with Fast Data
 

Dernier

Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Adtran
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...DianaGray10
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfDaniel Santiago Silva Capera
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsSafe Software
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfJamie (Taka) Wang
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Will Schroeder
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Brian Pichman
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1DianaGray10
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...Aggregage
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.YounusS2
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8DianaGray10
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IES VE
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7DianaGray10
 

Dernier (20)

Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and Istio
 
20150722 - AGV
20150722 - AGV20150722 - AGV
20150722 - AGV
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
 
201610817 - edge part1
201610817 - edge part1201610817 - edge part1
201610817 - edge part1
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
 
20230104 - machine vision
20230104 - machine vision20230104 - machine vision
20230104 - machine vision
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
 

Spark & Hadoop at Production at Scale

  • 1. © 2015 MapR Technologies 1© 2015 MapR Technologies Taking Your Spark To Production Scale
  • 2. © 2015 MapR Technologies 2 The Journey To Production Scale Trials, science projects Large mission-critical, operational deployments © 2015 MapR Technologies 2
  • 3. © 2015 MapR Technologies 3 Companies with Spark & MapR in Production GLOBAL TELECOM HEALTHCARE GLOBALFINANCIAL SERVICES
  • 4. © 2015 MapR Technologies 4 Key Issues To Plan For 3
  • 5. © 2015 MapR Technologies 5 Global Managed Security Services delivered on Hadoop Spark Stream processing used to first check for known threats Data next processed on Hadoop using MLLib and GraphX Additional SQL querying done via Spark SQL Security Intelligence Operations
  • 6. Delivers Lightning Fast Analytics for Clients Building largest Hadoop cluster in Australia Real-time analytics using Spark on MapR–reducing data loading time from hours to minutes Leverage multi-tenancy, high-performance and reliability of MapR
  • 7. © 2015 MapR Technologies 7 Next-Gen Genomics Develop flexible platform to keep up with fast changing research techniques POSIX file access lets bio-informaticians use existing tools with open source tools (Spark) Graph manipulations can be done reliably and at scale using Spark
  • 8. © 2015 MapR Technologies 8 Real-Time Customer Analytics • MapR Data Lake stores both online and archive data • Spark on MapR reduced ETL processing • NFS moved data into the cluster seamlessly • 1/10th Total Cost of Ownership vs. old way • New customer onboarding cut from months to weeks
  • 9. © 2015 MapR Technologies 9 Databricks & MapR Strategic Partnership (since April 2014) Support for the complete Spark stack Engineering & roadmap collaboration Back-end support +
  • 10. © 2015 MapR Technologies 10 The Most Complete Spark Environment Spark SQL (SQL) Spark Streaming (Streaming) MLlib (Machine learning) GraphX (Graph computation) Foundation For Enterprise-Grade Spark
  • 11. © 2015 MapR Technologies 11 DB Operations Real-Time and Actionable Analytics Operations + Analytics on One Hadoop Platform with SQL Access Mobile application server Customer 360 dashboard Churn analysis Product/service optimization and personalization Real-time ad targeting Web application server Data exploration (SQL) • User profiles and state • User interactions • Real-time location data • Web and mobile session state • Comments/rankings
  • 12. © 2015 MapR Technologies 12 Spark + MapR = Ready For Production Success World-record performance on disk High Performance SLA-Driven Applications • High availability • Data protection • Disaster recovery Reliability for Production Strategic partnership with Databricks to ensure enterprise support for the entire stack 24/7 Best-in-class Global Support MapR-DB + Spark = real-time analytics Operational Data Store
  • 13. © 2015 MapR Technologies 13 Free On-Demand Training www.mapr.com/training
  • 14. © 2015 MapR Technologies 14 Self-Service Data Exploration Data Agility with Less IT Required Single SQL Interface for Structured and Semi-Structured Data
  • 15. © 2015 MapR Technologies 15 MapR Introduces 3 New Spark-Based Quick Start Solutions Real-Time Security Log Analytics Time Series Analytics Genome Sequencing
  • 16. © 2015 MapR Technologies 16 Get Your Tattoo In The MapR Booth! Show off your Kickstart My Heart skills and enter to win Xbox 360 & Guitar Hero
  • 17. © 2015 MapR Technologies 17 Top-Ranked NoSQL Top-Ranked Hadoop Distribution Top-Ranked SQL-on Hadoop Solution

Notes de l'éditeur

  1. JN: I’d make the arrow not absolutely vertical tilt steeply to the right
  2. http://www.thinkstockphotos.com/image/stock-photo-businessman-selecting-a-futuristic-padlock/179694007/popup?sq=Datacenter%20security/f=CPIHVX/s=Popularity
  3. http://www.thinkstockphotos.com/image/stock-photo-scientist-holding-test-tube/461208473/popup?sq=drug%20discovery/f=CPIHVX/s=Popularity a. Interested in Adam project - runs on top of Spark - for nextgen genomics - good whiteppaer - search for APche spark Adam Git hub for Adam - Notes - links to the whitepaper - AMPLab - http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-207.html Genomics realignment tool - crux - next ten gemonic medicine - allows you to much more quickly access and manage the alignment of data. b. Existing genomics pipeline - many weeks to realign - drill down augment and working through their chemical compounds - genetics can come and test their compound against the alignment c. Not the exact sections of then they cannot focus - back out and zoom back in on the right set of sequence. that process 6 weeks - geneticist - 1 day and shift it - 6 weeks to get to the change - Adam in a matter of hours - geneticists can do it themselves - whole team of HPC experts otherwise d. this is the case for almost all pharma companies - Novartis is also the same e. One tool in a bigger framework - several other use cases as well.
  4. Objectives: Razorsight's cloud-based predictive analytics software delivers insights to help communications service providers (CSPs) and media companies optimize operations and offer superior customer experiences. “As we grew as a company and big data evolved, there was a lot more data available,” explains Razorsight CTO Suren Nathan. “Today’s data has higher volumes and different structures. There are new types of devices generating data for the Internet of Things, mobile phones using broadband for apps, and VoIP.”   Challenges Razorsight’s old technology platform could not keep up with the demands and opportunities of this increasing volume of data. Storage costs were exploding and they wanted to be able to maintain performance and scalability at a lower cost. The prior platform was based on IBM Pure Data (Netezza) as a data warehouse appliance and couldn’t support high-speed data ingestion and reporting. Additionally it required having a separate database for each customer. Solution MapR came out on top for several reasons and is being used as the primary data store for online and archive data Having the flexibility of the full Spark stack as part of the Hadoop distribution was very important. Spark helps transition a large part of ETL processing 2. MapR provided production-class Hadoop with enterprise support 3. The NFS gateway was critical for easy, high-speed access. Business Impact Customers such as Virgin Mobile LA are reducing churn by tailoring campaigns to the right subscriber at the right time. Much lower TCO compared to IBM Netezza ( 1/8th the cost). Razorsight is able to also reduce on-boarding time for new customers from 4-6 months to 8-12 weeks.
  5. Spark execution engine rides on the Mesos framework and any distributed file system (in this case HDFS)
  6. Data Agility with No IT Intervention
  7. Just Thought You Might Want To Know….