SlideShare une entreprise Scribd logo

AWS Customer Presentation - eHarmony

•
•
Amazon Web Services
Amazon Web Services

Ben Hardy, Senior Software Engineer, eHarmony talks about their use of AWS to power their matching algorithms

FormationTechnologie
1  sur  12
Matchmaking in the Cloud A study on Amazon EC2, Elastic MapReduce and Apache Hadoop at eHarmony Ben Hardy - Sr. Software Engineer
About eHarmony ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Business use case ,[object Object]
Scorer ,[object Object],[object Object],[object Object]
Challenges to meet ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How Hadoop solved our problem ,[object Object],[object Object],[object Object],[object Object]
Architecture Overview Hadoop Data Warehouse Local Store unload s3put EC2 S3 s3get start verify get job status shutdown User and Match data Cluster control Score Data store
How AWS solved our problem ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
AWS Elastic MapReduce BETA ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Simplified Job Control ,[object Object],[object Object],[object Object],Jar and Config on S3 and Job status queried via REST interface #{ELASTIC_MR_UTIL} --create --name #{JOB_NAME} --num-instances #{NUM_INSTANCES} --instance-type #{INSTANCE_TYPE} --key_pair #{KEY_PAIR_NAME} --log-uri #{SCORER_LOG_BUCKET_URL} --jar #{SCORER_JAR_S3_PATH} --main-class #{MR_JAVA_PACKAGE}.join.JoinJob --arg -xconf --arg #{MASTER_CONF_DIR}/join-config.xml --jar #{SCORER_JAR_S3_PATH} --main-class #{MR_JAVA_PACKAGE}.scorer.ScorerJob --arg -xconf --arg #{MASTER_CONF_DIR}/scorer-config.xml --jar #{SCORER_JAR_S3_PATH} --main-class #{MR_JAVA_PACKAGE}.combiner.CombinerJob --arg -xconf --arg #{MASTER_CONF_DIR}/combiner-config-#{TARGET_ENV}.xml
AWS Management Console Elastic MapReduce BETA
Points of caution Elastic MapReduce BETA ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Recommandé

Azure DocumentDB en Dev@Nights
Azure DocumentDB en Dev@NightsAzure DocumentDB en Dev@Nights
Azure DocumentDB en Dev@NightsMatias Quaranta
 
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...Amazon Web Services
 
Azure Web Scalability
Azure Web ScalabilityAzure Web Scalability
Azure Web ScalabilityMatias Quaranta
 
Build Data Lakes & Analytics on AWS: Patterns & Best Practices
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesBuild Data Lakes & Analytics on AWS: Patterns & Best Practices
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
 
Big Data - Part IV
Big Data - Part IVBig Data - Part IV
Big Data - Part IVThanuja Seneviratne
 
Minería de Datos en Sql Server 2008
Minería de Datos en Sql Server 2008Minería de Datos en Sql Server 2008
Minería de Datos en Sql Server 2008Eduardo Castro
 
Building Data Lakes with Apache Airflow
Building Data Lakes with Apache AirflowBuilding Data Lakes with Apache Airflow
Building Data Lakes with Apache AirflowGary Stafford
 
Big Data - Part I
Big Data - Part IBig Data - Part I
Big Data - Part IThanuja Seneviratne
 

Recommandé

Azure DocumentDB en Dev@Nights
Azure DocumentDB en Dev@NightsAzure DocumentDB en Dev@Nights
Azure DocumentDB en Dev@NightsMatias Quaranta
 
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...
(BDT306) Mission-Critical Stream Processing with Amazon EMR and Amazon Kinesi...Amazon Web Services
 
Azure Web Scalability
Azure Web ScalabilityAzure Web Scalability
Azure Web ScalabilityMatias Quaranta
 
Build Data Lakes & Analytics on AWS: Patterns & Best Practices
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesBuild Data Lakes & Analytics on AWS: Patterns & Best Practices
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
 
Big Data - Part IV
Big Data - Part IVBig Data - Part IV
Big Data - Part IVThanuja Seneviratne
 
Minería de Datos en Sql Server 2008
Minería de Datos en Sql Server 2008Minería de Datos en Sql Server 2008
Minería de Datos en Sql Server 2008Eduardo Castro
 
Building Data Lakes with Apache Airflow
Building Data Lakes with Apache AirflowBuilding Data Lakes with Apache Airflow
Building Data Lakes with Apache AirflowGary Stafford
 
Big Data - Part I
Big Data - Part IBig Data - Part I
Big Data - Part IThanuja Seneviratne
 
AWS_ac_ra_loganalysis_11
AWS_ac_ra_loganalysis_11AWS_ac_ra_loganalysis_11
AWS_ac_ra_loganalysis_11Kashif .T Ibrahim
 
Big Data - Part II
Big Data - Part IIBig Data - Part II
Big Data - Part IIThanuja Seneviratne
 
Big Data - Part III
Big Data - Part IIIBig Data - Part III
Big Data - Part IIIThanuja Seneviratne
 
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...Chuan-Yen Chiang
 
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Amazon Web Services
 
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_DataPeter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_DataTriNimbus
 
Treasure Data From MySQL to Redshift
Treasure Data From MySQL to RedshiftTreasure Data From MySQL to Redshift
Treasure Data From MySQL to RedshiftTreasure Data, Inc.
 
Operationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at StarbucksOperationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at StarbucksDatabricks
 
Amazon Web Services (Database)
Amazon Web Services (Database)Amazon Web Services (Database)
Amazon Web Services (Database)Nishant Bhardwaj
 
App development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebaseApp development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebasePankaj Rai
 
Prakash_Wagle_Resume
Prakash_Wagle_ResumePrakash_Wagle_Resume
Prakash_Wagle_ResumePrakash Wagle
 
Big Data on the Cloud
Big Data on the CloudBig Data on the Cloud
Big Data on the CloudSercan Karaoglu
 
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...Amazon Web Services
 
Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...Amazon Web Services
 
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...Yann Cluchey
 
AWS Summit Milan - Data Analysis
AWS Summit Milan - Data AnalysisAWS Summit Milan - Data Analysis
AWS Summit Milan - Data AnalysisAmazon Web Services
 
AWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution ShowcaseAWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution ShowcaseAmazon Web Services
 
Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15Akash Kant
 
What's next for Big Data? -- Apache Spark
What's next for Big Data? -- Apache SparkWhat's next for Big Data? -- Apache Spark
What's next for Big Data? -- Apache SparkTUMRA | Big Data Science - Gain a competitive advantage through Big Data & Data Science
 
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...Rukmani Gopalan
 
presentation
presentationpresentation
presentationcheesebot234
 
Hdfs high availability
Hdfs high availabilityHdfs high availability
Hdfs high availabilityHadoop User Group
 

Contenu connexe

Tendances

Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...Chuan-Yen Chiang
 
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Amazon Web Services
 
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_DataPeter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_DataTriNimbus
 
Treasure Data From MySQL to Redshift
Treasure Data From MySQL to RedshiftTreasure Data From MySQL to Redshift
Treasure Data From MySQL to RedshiftTreasure Data, Inc.
 
Operationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at StarbucksOperationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at StarbucksDatabricks
 
Amazon Web Services (Database)
Amazon Web Services (Database)Amazon Web Services (Database)
Amazon Web Services (Database)Nishant Bhardwaj
 
App development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebaseApp development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebasePankaj Rai
 
Prakash_Wagle_Resume
Prakash_Wagle_ResumePrakash_Wagle_Resume
Prakash_Wagle_ResumePrakash Wagle
 
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...Amazon Web Services
 
Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...Amazon Web Services
 
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...Yann Cluchey
 
AWS Summit Milan - Data Analysis
AWS Summit Milan - Data AnalysisAWS Summit Milan - Data Analysis
AWS Summit Milan - Data AnalysisAmazon Web Services
 
AWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution ShowcaseAWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution ShowcaseAmazon Web Services
 
Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15Akash Kant
 
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...Rukmani Gopalan
 

Tendances (20)

AWS_ac_ra_loganalysis_11
AWS_ac_ra_loganalysis_11AWS_ac_ra_loganalysis_11
AWS_ac_ra_loganalysis_11
 
Big Data - Part II
Big Data - Part IIBig Data - Part II
Big Data - Part II
 
Big Data - Part III
Big Data - Part IIIBig Data - Part III
Big Data - Part III
 
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
Hands on experience in real-time data process with AWS Kinesis, Firehose, S3 ...
 
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
 
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_DataPeter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
Peter_Smith_PhD_ACL_10000_Foot_View_of_Big_Data
 
Treasure Data From MySQL to Redshift
Treasure Data From MySQL to RedshiftTreasure Data From MySQL to Redshift
Treasure Data From MySQL to Redshift
 
Operationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at StarbucksOperationalizing Machine Learning at Scale at Starbucks
Operationalizing Machine Learning at Scale at Starbucks
 
Amazon Web Services (Database)
Amazon Web Services (Database)Amazon Web Services (Database)
Amazon Web Services (Database)
 
App development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebaseApp development with constraint layout, kotlin & firebase
App development with constraint layout, kotlin & firebase
 
Prakash_Wagle_Resume
Prakash_Wagle_ResumePrakash_Wagle_Resume
Prakash_Wagle_Resume
 
Big Data on the Cloud
Big Data on the CloudBig Data on the Cloud
Big Data on the Cloud
 
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
AWS re:Invent 2016: Predicting Customer Churn with Amazon Machine Learning (M...
 
Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...Design for Scale - Building Real Time, High Performing Marketing Technology p...
Design for Scale - Building Real Time, High Performing Marketing Technology p...
 
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
GOTO Aarhus 2014: Making Enterprise Data Available in Real Time with elastics...
 
AWS Summit Milan - Data Analysis
AWS Summit Milan - Data AnalysisAWS Summit Milan - Data Analysis
AWS Summit Milan - Data Analysis
 
AWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution ShowcaseAWS Webcast - Tableau Big Data Solution Showcase
AWS Webcast - Tableau Big Data Solution Showcase
 
Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15Cassandra REST API with Pagination TEAM 15
Cassandra REST API with Pagination TEAM 15
 
What's next for Big Data? -- Apache Spark
What's next for Big Data? -- Apache SparkWhat's next for Big Data? -- Apache Spark
What's next for Big Data? -- Apache Spark
 
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
Sql Bits 2020 - Designing Performant and Scalable Data Lakes using Azure Data...
 

En vedette

Karmasphere hadoop-productivity-tools
Karmasphere hadoop-productivity-toolsKarmasphere hadoop-productivity-tools
Karmasphere hadoop-productivity-toolsHadoop User Group
 
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...Hadoop User Group
 
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduce
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReducePublic Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduce
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduceHadoop User Group
 
Bay Area HUG Feb 2011 Intro
Bay Area HUG Feb 2011 IntroBay Area HUG Feb 2011 Intro
Bay Area HUG Feb 2011 IntroOwen O'Malley
 
Next Generation MapReduce
Next Generation MapReduceNext Generation MapReduce
Next Generation MapReduceOwen O'Malley
 
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...Hadoop User Group
 
Next Generation Hadoop Operations
Next Generation Hadoop OperationsNext Generation Hadoop Operations
Next Generation Hadoop OperationsOwen O'Malley
 
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...Hadoop User Group
 
Hadoop, Hbase and Hive- Bay area Hadoop User Group
Hadoop, Hbase and Hive- Bay area Hadoop User GroupHadoop, Hbase and Hive- Bay area Hadoop User Group
Hadoop, Hbase and Hive- Bay area Hadoop User GroupHadoop User Group
 
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector Yahoo Developer Network
 
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...Yahoo Developer Network
 
Yahoo! Mail antispam - Bay area Hadoop user group
Yahoo! Mail antispam - Bay area Hadoop user groupYahoo! Mail antispam - Bay area Hadoop user group
Yahoo! Mail antispam - Bay area Hadoop user groupHadoop User Group
 

En vedette (20)

presentation
presentationpresentation
presentation
 
Hdfs high availability
Hdfs high availabilityHdfs high availability
Hdfs high availability
 
Cascalog internal dsl_preso
Cascalog internal dsl_presoCascalog internal dsl_preso
Cascalog internal dsl_preso
 
Karmasphere hadoop-productivity-tools
Karmasphere hadoop-productivity-toolsKarmasphere hadoop-productivity-tools
Karmasphere hadoop-productivity-tools
 
Common crawlpresentation
Common crawlpresentationCommon crawlpresentation
Common crawlpresentation
 
Pig at Linkedin
Pig at LinkedinPig at Linkedin
Pig at Linkedin
 
Data Science of Love
Data Science of LoveData Science of Love
Data Science of Love
 
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...
Yahoo! Hadoop User Group - May Meetup - Extraordinarily rapid and robust data...
 
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduce
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReducePublic Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduce
Public Terabyte Dataset Project: Web crawling with Amazon Elastic MapReduce
 
January 2011 HUG: Howl Presentation
January 2011 HUG: Howl PresentationJanuary 2011 HUG: Howl Presentation
January 2011 HUG: Howl Presentation
 
January 2011 HUG: Pig Presentation
January 2011 HUG: Pig PresentationJanuary 2011 HUG: Pig Presentation
January 2011 HUG: Pig Presentation
 
Bay Area HUG Feb 2011 Intro
Bay Area HUG Feb 2011 IntroBay Area HUG Feb 2011 Intro
Bay Area HUG Feb 2011 Intro
 
Next Generation MapReduce
Next Generation MapReduceNext Generation MapReduce
Next Generation MapReduce
 
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...
Yahoo! Hadoop User Group - May 2010 Meetup - Apache Hadoop Release Plans for ...
 
Next Generation Hadoop Operations
Next Generation Hadoop OperationsNext Generation Hadoop Operations
Next Generation Hadoop Operations
 
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...
Yahoo! Hadoop User Group - May Meetup - HBase and Pig: The Hadoop ecosystem a...
 
Hadoop, Hbase and Hive- Bay area Hadoop User Group
Hadoop, Hbase and Hive- Bay area Hadoop User GroupHadoop, Hbase and Hive- Bay area Hadoop User Group
Hadoop, Hbase and Hive- Bay area Hadoop User Group
 
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector
August 2016 HUG: Open Source Big Data Ingest with StreamSets Data Collector
 
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...
August 2016 HUG: Better together: Fast Data with Apache Spark™ and Apache Ign...
 
Yahoo! Mail antispam - Bay area Hadoop user group
Yahoo! Mail antispam - Bay area Hadoop user groupYahoo! Mail antispam - Bay area Hadoop user group
Yahoo! Mail antispam - Bay area Hadoop user group
 

Similaire à AWS Customer Presentation - eHarmony

B3 - Business intelligence apps on aws
B3 - Business intelligence apps on awsB3 - Business intelligence apps on aws
B3 - Business intelligence apps on awsAmazon Web Services
 
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...Yahoo Developer Network
 
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Amazon Web Services
 
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Amazon Web Services
 
Hw09 Matchmaking In The Cloud
Hw09 Matchmaking In The CloudHw09 Matchmaking In The Cloud
Hw09 Matchmaking In The CloudCloudera, Inc.
 
Build Data Lakes and Analytics on AWS
Build Data Lakes and Analytics on AWS Build Data Lakes and Analytics on AWS
Build Data Lakes and Analytics on AWS Amazon Web Services
 
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹Amazon Web Services
 
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017Amazon Web Services
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon RedshiftAmazon Web Services
 
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWS
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWSAWS Summit Stockholm 2014 – B4 – Business intelligence on AWS
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWSAmazon Web Services
 
AWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapAWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapIan Massingham
 
AWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapAWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapAdrian Hornsby
 
Hong Kong AWS Summit 2017 - Keynote
Hong Kong AWS Summit 2017 - KeynoteHong Kong AWS Summit 2017 - Keynote
Hong Kong AWS Summit 2017 - KeynoteAmazon Web Services
 
Architetture serverless e pattern avanzati per AWS Lambda
Architetture serverless e pattern avanzati per AWS LambdaArchitetture serverless e pattern avanzati per AWS Lambda
Architetture serverless e pattern avanzati per AWS LambdaAmazon Web Services
 
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...Amazon Web Services
 
Getting Started with Big Data and HPC in the Cloud - August 2015
Getting Started with Big Data and HPC in the Cloud - August 2015Getting Started with Big Data and HPC in the Cloud - August 2015
Getting Started with Big Data and HPC in the Cloud - August 2015Amazon Web Services
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon RedshiftAmazon Web Services
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon RedshiftAmazon Web Services
 
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...Amazon Web Services
 

Similaire à AWS Customer Presentation - eHarmony (20)

B3 - Business intelligence apps on aws
B3 - Business intelligence apps on awsB3 - Business intelligence apps on aws
B3 - Business intelligence apps on aws
 
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...
Apache Hadoop India Summit 2011 talk "Making Hadoop Enterprise Ready with Am...
 
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
 
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
Understanding AWS Managed Database and Analytics Services | AWS Public Sector...
 
Hw09 Matchmaking In The Cloud
Hw09 Matchmaking In The CloudHw09 Matchmaking In The Cloud
Hw09 Matchmaking In The Cloud
 
Build Data Lakes and Analytics on AWS
Build Data Lakes and Analytics on AWS Build Data Lakes and Analytics on AWS
Build Data Lakes and Analytics on AWS
 
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹
透過 Amazon Redshift 打造數據分析服務及 Amazon Redshift 新功能案例介紹
 
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon Redshift
 
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWS
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWSAWS Summit Stockholm 2014 – B4 – Business intelligence on AWS
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWS
 
AWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapAWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:Cap
 
AWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:CapAWS re:Invent 2016 Day 1 Keynote re:Cap
AWS re:Invent 2016 Day 1 Keynote re:Cap
 
Hong Kong AWS Summit 2017 - Keynote
Hong Kong AWS Summit 2017 - KeynoteHong Kong AWS Summit 2017 - Keynote
Hong Kong AWS Summit 2017 - Keynote
 
Azure for ug
Azure for ugAzure for ug
Azure for ug
 
Architetture serverless e pattern avanzati per AWS Lambda
Architetture serverless e pattern avanzati per AWS LambdaArchitetture serverless e pattern avanzati per AWS Lambda
Architetture serverless e pattern avanzati per AWS Lambda
 
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...
AWS November Webinar Series - Advanced Analytics with Amazon Redshift and the...
 
Getting Started with Big Data and HPC in the Cloud - August 2015
Getting Started with Big Data and HPC in the Cloud - August 2015Getting Started with Big Data and HPC in the Cloud - August 2015
Getting Started with Big Data and HPC in the Cloud - August 2015
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon Redshift
 
Getting Started with Amazon Redshift
Getting Started with Amazon RedshiftGetting Started with Amazon Redshift
Getting Started with Amazon Redshift
 
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...
 

Plus de Amazon Web Services

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
 
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
 
Esegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateEsegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateAmazon Web Services
 
Costruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSCostruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSAmazon Web Services
 
Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
 
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
 
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
 
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsMicrosoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
 
Database Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareDatabase Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareAmazon Web Services
 
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSCrea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
 
API moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAPI moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAmazon Web Services
 
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareDatabase Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
 
Tools for building your MVP on AWS
Tools for building your MVP on AWSTools for building your MVP on AWS
Tools for building your MVP on AWSAmazon Web Services
 
How to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckHow to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckAmazon Web Services
 
Building a web application without servers
Building a web application without serversBuilding a web application without servers
Building a web application without serversAmazon Web Services
 
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
 
Introduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceIntroduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceAmazon Web Services
 

Plus de Amazon Web Services (20)

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
 
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
 
Esegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateEsegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS Fargate
 
Costruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSCostruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWS
 
Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot
 
Open banking as a service
Open banking as a serviceOpen banking as a service
Open banking as a service
 
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
 
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
 
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsMicrosoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
 
Computer Vision con AWS
Computer Vision con AWSComputer Vision con AWS
Computer Vision con AWS
 
Database Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareDatabase Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatare
 
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSCrea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
 
API moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAPI moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e web
 
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareDatabase Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
 
Tools for building your MVP on AWS
Tools for building your MVP on AWSTools for building your MVP on AWS
Tools for building your MVP on AWS
 
How to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckHow to Build a Winning Pitch Deck
How to Build a Winning Pitch Deck
 
Building a web application without servers
Building a web application without serversBuilding a web application without servers
Building a web application without servers
 
Fundraising Essentials
Fundraising EssentialsFundraising Essentials
Fundraising Essentials
 
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
 
Introduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceIntroduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container Service
 

Dernier

Textual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSTextual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSMae Pangan
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...JojoEDelaCruz
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxAnupkumar Sharma
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfVanessa Camilleri
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptxmary850239
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management systemChristalin Nelson
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEaurabinda banchhor
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfErwinPantujan2
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management SystemChristalin Nelson
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Celine George
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptxmary850239
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxVanesaIglesias10
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...Postal Advocate Inc.
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONHumphrey A Beña
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataBabyAnnMotar
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmStan Meyer
 

Dernier (20)

Textual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSTextual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHS
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdf
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptxYOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management system
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSE
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management System
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptx
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped data
 
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptxINCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and Film
 

AWS Customer Presentation - eHarmony

  • 1. Matchmaking in the Cloud A study on Amazon EC2, Elastic MapReduce and Apache Hadoop at eHarmony Ben Hardy - Sr. Software Engineer
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7. Architecture Overview Hadoop Data Warehouse Local Store unload s3put EC2 S3 s3get start verify get job status shutdown User and Match data Cluster control Score Data store
  • 8.
  • 9.
  • 10.
  • 11. AWS Management Console Elastic MapReduce BETA
  • 12.

Notes de l'éditeur

  1. Here are some facts and figures on us 2% of US Marriages
  2. Db joins etc, models are CPU and IO intensive and need to be tested, in offline system we can take advantage of aggregate data without constraining our online system
  3. Getting our data to and from EC2 is definitely non-trivial Steps 1,2,6, and 7 are outside the cloud
  4. EMR simplifies the process and scripting for us by consolidating the allocation, hadoop configuration and process control of the jobs
  5. Lots of steps before EMR. No fun. Lots of possible points of failure. No need to copy job to master, or even touch the master in any way. Uses Amazon’s elastic-mapreduce.rb utility script.
  6. Status of job flow Status of steps in each job flow
  7. Design for failure