SlideShare ist ein Scribd-Unternehmen logo
1 von 14
End-to-end Analytics
          with Apache Cassandra




C*                                #cassandra12
Basics
     • CFIF/CFOF/CFRR/CFRW
     • BulkOutputFormat
     • Input locality (identical to HDFS)
     • Wide row, 2I, composite support
     • Pig, Hive, Mahout, Sqoop, Oozie, DSE
       Analytics

C*                                  #cassandra12
Why Cassandra?

     • Excellent Hadoop capabilities built-in
     • Multi-datacenter support, load isolation
     • Operationally, order of magnitude simpler
     • DSE Analytics is all-in-one, simpler still
     • Review your requirements, do homework
C*                                       #cassandra12
Use Cases

     • Trends, recommendations, reporting, etc.
     • Detect and fix problems in data
     • New realtime (or analytic) query pattern?
      • Backpopulate new CF with historical data

C*                                    #cassandra12
Data Model
     • Consider growth patterns and analytic
       query patterns for your data
      • One-off inquiry or regular processing?
      • Fast growing, want only small slices?
     • Consider active/archive CFs
     • Secondary indexes for small inputs
C*                                      #cassandra12
Miscellaneous Tips


     • Don’t forget about tombstones
     • BOP to enable range slices (Rows with
       keys ‘A*’ to ‘F*’)




C*                                     #cassandra12
Cassandra + Oozie
     • Workflows: cohesive, nestable, scheduled
     • Web UI, CLI, web service
     • Cassandra properties in oozie job
       properties, and workflow.xml
     • Writing out to Cassandra:
       mapreduce.fileoutputcommitter.marksuccessfuljobs to false


     • DSE Analytics works with Oozie 3.2.1+
C*                                                            #cassandra12
Cassandra + Pig
     • Data with validators
      • Pig tuples (address.name, address.value)
     • Data with default validator
      • Bag of key, value pairs (tuples)
      • Unmarshal with Pygmalion
        • Select by regex (eg ‘1369*’, ‘link*’)
C*                                      #cassandra12
Cassandra + Pig
     • Output to Cassandra
      • Can output directly with (key, (name,
         value), (name, value)...) format
      • For tabular data, format output with
         Pygmalion’s ToCassandraBag
      • Use BulkOutputFormat (C* 1.1)
C*                                          #cassandra12
Cassandra + Pig
     • Composite column support (C* 1.0.9+)
     • Counter support (C* 1.0.9+)
     • Secondary Index support for relatively
       small slices (C* 1.1+)
     • Wide row support (C* 1.1+)
     • Composite key support (C* 1.1.3+)
C*                                     #cassandra12
Cassandra + Hadoop X
     • Example: Cassandra + CDH3
      • Start with Cassandra ring
      • Add NN, JT, Oozie server
      • TaskTracker, DataNode on each node
      • Jobs/launching point have Cassandra info
      • Segregate out analytics with virtual DC
C*                                     #cassandra12
Current/Future Work


     • Cassandra core Hive support (outside of
       Brisk) (CASSANDRA-4131)




C*                                     #cassandra12
For More Information


     • Follow @CassandraHadoop on Twitter
     • http://wiki.apache.org/cassandra/
       HadoopSupport




C*                                  #cassandra12
Questions?




C*                #cassandra12

Weitere ähnliche Inhalte

Was ist angesagt?

Hadoop Hive Talk At IIT-Delhi
Hadoop Hive Talk At IIT-DelhiHadoop Hive Talk At IIT-Delhi
Hadoop Hive Talk At IIT-DelhiJoydeep Sen Sarma
 
The Meta of Hadoop - COMAD 2012
The Meta of Hadoop - COMAD 2012The Meta of Hadoop - COMAD 2012
The Meta of Hadoop - COMAD 2012Joydeep Sen Sarma
 
Cloudera Impala + PostgreSQL
Cloudera Impala + PostgreSQLCloudera Impala + PostgreSQL
Cloudera Impala + PostgreSQLliuknag
 
Amebaサービスのログ解析基盤
Amebaサービスのログ解析基盤Amebaサービスのログ解析基盤
Amebaサービスのログ解析基盤Toshihiro Suzuki
 
How Adobe Does 2 Million Records Per Second Using Apache Spark!
How Adobe Does 2 Million Records Per Second Using Apache Spark!How Adobe Does 2 Million Records Per Second Using Apache Spark!
How Adobe Does 2 Million Records Per Second Using Apache Spark!Databricks
 
Partners in Crime: Cassandra Analytics and ETL with Hadoop
Partners in Crime: Cassandra Analytics and ETL with HadoopPartners in Crime: Cassandra Analytics and ETL with Hadoop
Partners in Crime: Cassandra Analytics and ETL with HadoopStu Hood
 
Migrating structured data between Hadoop and RDBMS
Migrating structured data between Hadoop and RDBMSMigrating structured data between Hadoop and RDBMS
Migrating structured data between Hadoop and RDBMSBouquet
 
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)Adam Kawa
 
Hadoop Pig: MapReduce the easy way!
Hadoop Pig: MapReduce the easy way!Hadoop Pig: MapReduce the easy way!
Hadoop Pig: MapReduce the easy way!Nathan Bijnens
 
Qubole @ AWS Meetup Bangalore - July 2015
Qubole @ AWS Meetup Bangalore - July 2015Qubole @ AWS Meetup Bangalore - July 2015
Qubole @ AWS Meetup Bangalore - July 2015Joydeep Sen Sarma
 
Hd insight essentials quick view
Hd insight essentials quick viewHd insight essentials quick view
Hd insight essentials quick viewRajesh Nadipalli
 
introduction to data processing using Hadoop and Pig
introduction to data processing using Hadoop and Pigintroduction to data processing using Hadoop and Pig
introduction to data processing using Hadoop and PigRicardo Varela
 
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
 

Was ist angesagt? (20)

Nextag talk
Nextag talkNextag talk
Nextag talk
 
Hadoop Hive Talk At IIT-Delhi
Hadoop Hive Talk At IIT-DelhiHadoop Hive Talk At IIT-Delhi
Hadoop Hive Talk At IIT-Delhi
 
מיכאל
מיכאלמיכאל
מיכאל
 
Hadoop sqoop
Hadoop sqoop Hadoop sqoop
Hadoop sqoop
 
Hadoop overview
Hadoop overviewHadoop overview
Hadoop overview
 
The Meta of Hadoop - COMAD 2012
The Meta of Hadoop - COMAD 2012The Meta of Hadoop - COMAD 2012
The Meta of Hadoop - COMAD 2012
 
Cloudera Impala + PostgreSQL
Cloudera Impala + PostgreSQLCloudera Impala + PostgreSQL
Cloudera Impala + PostgreSQL
 
Amebaサービスのログ解析基盤
Amebaサービスのログ解析基盤Amebaサービスのログ解析基盤
Amebaサービスのログ解析基盤
 
Apache drill
Apache drillApache drill
Apache drill
 
How Adobe Does 2 Million Records Per Second Using Apache Spark!
How Adobe Does 2 Million Records Per Second Using Apache Spark!How Adobe Does 2 Million Records Per Second Using Apache Spark!
How Adobe Does 2 Million Records Per Second Using Apache Spark!
 
Partners in Crime: Cassandra Analytics and ETL with Hadoop
Partners in Crime: Cassandra Analytics and ETL with HadoopPartners in Crime: Cassandra Analytics and ETL with Hadoop
Partners in Crime: Cassandra Analytics and ETL with Hadoop
 
Migrating structured data between Hadoop and RDBMS
Migrating structured data between Hadoop and RDBMSMigrating structured data between Hadoop and RDBMS
Migrating structured data between Hadoop and RDBMS
 
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)
Hadoop Operations Powered By ... Hadoop (Hadoop Summit 2014 Amsterdam)
 
Hadoop Pig: MapReduce the easy way!
Hadoop Pig: MapReduce the easy way!Hadoop Pig: MapReduce the easy way!
Hadoop Pig: MapReduce the easy way!
 
Qubole @ AWS Meetup Bangalore - July 2015
Qubole @ AWS Meetup Bangalore - July 2015Qubole @ AWS Meetup Bangalore - July 2015
Qubole @ AWS Meetup Bangalore - July 2015
 
Hd insight essentials quick view
Hd insight essentials quick viewHd insight essentials quick view
Hd insight essentials quick view
 
Hadoop and Distributed Computing
Hadoop and Distributed ComputingHadoop and Distributed Computing
Hadoop and Distributed Computing
 
Hadoop
HadoopHadoop
Hadoop
 
introduction to data processing using Hadoop and Pig
introduction to data processing using Hadoop and Pigintroduction to data processing using Hadoop and Pig
introduction to data processing using Hadoop and Pig
 
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
 

Andere mochten auch

Plagger はじめよう
Plagger はじめようPlagger はじめよう
Plagger はじめようSeacolor
 
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping Study
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping StudyFriends Don't Let Friends Clap on One and Three: a Backbeat Clapping Study
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping StudyEthan Hein
 
ISUCONの勝ち方 YAPC::Asia Tokyo 2015
ISUCONの勝ち方 YAPC::Asia Tokyo 2015ISUCONの勝ち方 YAPC::Asia Tokyo 2015
ISUCONの勝ち方 YAPC::Asia Tokyo 2015Masahiro Nagano
 
Enduring CSS
Enduring CSSEnduring CSS
Enduring CSSTakazudo
 
120 Awesome Marketing Stats, Charts and Graphs
120 Awesome Marketing Stats, Charts and Graphs120 Awesome Marketing Stats, Charts and Graphs
120 Awesome Marketing Stats, Charts and GraphsHubSpot
 

Andere mochten auch (9)

Plagger はじめよう
Plagger はじめようPlagger はじめよう
Plagger はじめよう
 
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping Study
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping StudyFriends Don't Let Friends Clap on One and Three: a Backbeat Clapping Study
Friends Don't Let Friends Clap on One and Three: a Backbeat Clapping Study
 
Build Your Brand and Build Your Business
Build Your Brand and Build Your BusinessBuild Your Brand and Build Your Business
Build Your Brand and Build Your Business
 
ISUCONの勝ち方 YAPC::Asia Tokyo 2015
ISUCONの勝ち方 YAPC::Asia Tokyo 2015ISUCONの勝ち方 YAPC::Asia Tokyo 2015
ISUCONの勝ち方 YAPC::Asia Tokyo 2015
 
Design process
Design processDesign process
Design process
 
El Lenguaje Fotografico
El Lenguaje FotograficoEl Lenguaje Fotografico
El Lenguaje Fotografico
 
Enduring CSS
Enduring CSSEnduring CSS
Enduring CSS
 
120 Awesome Marketing Stats, Charts and Graphs
120 Awesome Marketing Stats, Charts and Graphs120 Awesome Marketing Stats, Charts and Graphs
120 Awesome Marketing Stats, Charts and Graphs
 
DISPLAY LUMAscape
DISPLAY LUMAscapeDISPLAY LUMAscape
DISPLAY LUMAscape
 

Ähnlich wie End-to-end Analytics with Apache Cassandra

PySpark Cassandra - Amsterdam Spark Meetup
PySpark Cassandra - Amsterdam Spark MeetupPySpark Cassandra - Amsterdam Spark Meetup
PySpark Cassandra - Amsterdam Spark MeetupFrens Jan Rumph
 
Introduction to Real-Time Analytics with Cassandra and Hadoop
Introduction to Real-Time Analytics with Cassandra and HadoopIntroduction to Real-Time Analytics with Cassandra and Hadoop
Introduction to Real-Time Analytics with Cassandra and HadoopPatricia Gorla
 
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetup
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetupDataStax - Analytics on Apache Cassandra - Paris Tech Talks meetup
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetupVictor Coustenoble
 
Deep Dive into Cassandra
Deep Dive into CassandraDeep Dive into Cassandra
Deep Dive into CassandraBrent Theisen
 
NoSQL Intro with cassandra
NoSQL Intro with cassandraNoSQL Intro with cassandra
NoSQL Intro with cassandraBrian Enochson
 
Spark + Cassandra = Real Time Analytics on Operational Data
Spark + Cassandra = Real Time Analytics on Operational DataSpark + Cassandra = Real Time Analytics on Operational Data
Spark + Cassandra = Real Time Analytics on Operational DataVictor Coustenoble
 
Apache Cassandra introduction
Apache Cassandra introductionApache Cassandra introduction
Apache Cassandra introductionfardinjamshidi
 
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-..."Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...hamidsamadi
 
Spring one2gx2010 spring-nonrelational_data
Spring one2gx2010 spring-nonrelational_dataSpring one2gx2010 spring-nonrelational_data
Spring one2gx2010 spring-nonrelational_dataRoger Xia
 
Spark cassandra integration, theory and practice
Spark cassandra integration, theory and practiceSpark cassandra integration, theory and practice
Spark cassandra integration, theory and practiceDuyhai Doan
 
Hindsight is 20/20: MySQL to Cassandra
Hindsight is 20/20: MySQL to CassandraHindsight is 20/20: MySQL to Cassandra
Hindsight is 20/20: MySQL to CassandraMichael Kjellman
 
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael Kjellman
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael KjellmanC* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael Kjellman
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael KjellmanDataStax Academy
 
Munich March 2015 - Cassandra + Spark Overview
Munich March 2015 -  Cassandra + Spark OverviewMunich March 2015 -  Cassandra + Spark Overview
Munich March 2015 - Cassandra + Spark OverviewChristopher Batey
 
Cassandra integrations
Cassandra integrationsCassandra integrations
Cassandra integrationsT Jake Luciani
 
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan Ott
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan OttTrivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan Ott
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan OttTrivadis
 
BI, Reporting and Analytics on Apache Cassandra
BI, Reporting and Analytics on Apache CassandraBI, Reporting and Analytics on Apache Cassandra
BI, Reporting and Analytics on Apache CassandraVictor Coustenoble
 
Developing with Cassandra
Developing with CassandraDeveloping with Cassandra
Developing with CassandraSperasoft
 

Ähnlich wie End-to-end Analytics with Apache Cassandra (20)

PySpark Cassandra - Amsterdam Spark Meetup
PySpark Cassandra - Amsterdam Spark MeetupPySpark Cassandra - Amsterdam Spark Meetup
PySpark Cassandra - Amsterdam Spark Meetup
 
Introduction to Real-Time Analytics with Cassandra and Hadoop
Introduction to Real-Time Analytics with Cassandra and HadoopIntroduction to Real-Time Analytics with Cassandra and Hadoop
Introduction to Real-Time Analytics with Cassandra and Hadoop
 
Cassandra & Spark for IoT
Cassandra & Spark for IoTCassandra & Spark for IoT
Cassandra & Spark for IoT
 
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetup
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetupDataStax - Analytics on Apache Cassandra - Paris Tech Talks meetup
DataStax - Analytics on Apache Cassandra - Paris Tech Talks meetup
 
Deep Dive into Cassandra
Deep Dive into CassandraDeep Dive into Cassandra
Deep Dive into Cassandra
 
NoSQL Intro with cassandra
NoSQL Intro with cassandraNoSQL Intro with cassandra
NoSQL Intro with cassandra
 
Spark + Cassandra = Real Time Analytics on Operational Data
Spark + Cassandra = Real Time Analytics on Operational DataSpark + Cassandra = Real Time Analytics on Operational Data
Spark + Cassandra = Real Time Analytics on Operational Data
 
Cassandra 2.0 (Introduction)
Cassandra 2.0 (Introduction)Cassandra 2.0 (Introduction)
Cassandra 2.0 (Introduction)
 
Apache Cassandra introduction
Apache Cassandra introductionApache Cassandra introduction
Apache Cassandra introduction
 
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-..."Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...
"Real-time data processing with Spark & Cassandra", jDays 2015 Speaker: "Duy-...
 
Spark Introduction
Spark IntroductionSpark Introduction
Spark Introduction
 
Spring one2gx2010 spring-nonrelational_data
Spring one2gx2010 spring-nonrelational_dataSpring one2gx2010 spring-nonrelational_data
Spring one2gx2010 spring-nonrelational_data
 
Spark cassandra integration, theory and practice
Spark cassandra integration, theory and practiceSpark cassandra integration, theory and practice
Spark cassandra integration, theory and practice
 
Hindsight is 20/20: MySQL to Cassandra
Hindsight is 20/20: MySQL to CassandraHindsight is 20/20: MySQL to Cassandra
Hindsight is 20/20: MySQL to Cassandra
 
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael Kjellman
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael KjellmanC* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael Kjellman
C* Summit 2013 - Hindsight is 20/20. MySQL to Cassandra by Michael Kjellman
 
Munich March 2015 - Cassandra + Spark Overview
Munich March 2015 -  Cassandra + Spark OverviewMunich March 2015 -  Cassandra + Spark Overview
Munich March 2015 - Cassandra + Spark Overview
 
Cassandra integrations
Cassandra integrationsCassandra integrations
Cassandra integrations
 
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan Ott
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan OttTrivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan Ott
Trivadis TechEvent 2016 Big Data Cassandra, wieso brauche ich das? by Jan Ott
 
BI, Reporting and Analytics on Apache Cassandra
BI, Reporting and Analytics on Apache CassandraBI, Reporting and Analytics on Apache Cassandra
BI, Reporting and Analytics on Apache Cassandra
 
Developing with Cassandra
Developing with CassandraDeveloping with Cassandra
Developing with Cassandra
 

Mehr von Jeremy Hanna

Göteborg Distributed: Eventual Consistency in Apache Cassandra
Göteborg Distributed: Eventual Consistency in Apache CassandraGöteborg Distributed: Eventual Consistency in Apache Cassandra
Göteborg Distributed: Eventual Consistency in Apache CassandraJeremy Hanna
 
Apache Cassandra in the Real World
Apache Cassandra in the Real WorldApache Cassandra in the Real World
Apache Cassandra in the Real WorldJeremy Hanna
 
Apache Cassandra in the Real World
Apache Cassandra in the Real WorldApache Cassandra in the Real World
Apache Cassandra in the Real WorldJeremy Hanna
 
Modern Cassandra for Developers
Modern Cassandra for DevelopersModern Cassandra for Developers
Modern Cassandra for DevelopersJeremy Hanna
 
Troubleshooting Cassandra
Troubleshooting CassandraTroubleshooting Cassandra
Troubleshooting CassandraJeremy Hanna
 
Cassandra + Hadoop: Analisi Batch con Apache Cassandra
Cassandra + Hadoop: Analisi Batch con Apache CassandraCassandra + Hadoop: Analisi Batch con Apache Cassandra
Cassandra + Hadoop: Analisi Batch con Apache CassandraJeremy Hanna
 
Cassandra + Hadoop @ApacheCon
Cassandra + Hadoop @ApacheCon Cassandra + Hadoop @ApacheCon
Cassandra + Hadoop @ApacheCon Jeremy Hanna
 

Mehr von Jeremy Hanna (9)

Göteborg Distributed: Eventual Consistency in Apache Cassandra
Göteborg Distributed: Eventual Consistency in Apache CassandraGöteborg Distributed: Eventual Consistency in Apache Cassandra
Göteborg Distributed: Eventual Consistency in Apache Cassandra
 
Apache Cassandra in the Real World
Apache Cassandra in the Real WorldApache Cassandra in the Real World
Apache Cassandra in the Real World
 
Apache Cassandra in the Real World
Apache Cassandra in the Real WorldApache Cassandra in the Real World
Apache Cassandra in the Real World
 
Modern Cassandra for Developers
Modern Cassandra for DevelopersModern Cassandra for Developers
Modern Cassandra for Developers
 
Troubleshooting Cassandra
Troubleshooting CassandraTroubleshooting Cassandra
Troubleshooting Cassandra
 
Cassandra + Hadoop: Analisi Batch con Apache Cassandra
Cassandra + Hadoop: Analisi Batch con Apache CassandraCassandra + Hadoop: Analisi Batch con Apache Cassandra
Cassandra + Hadoop: Analisi Batch con Apache Cassandra
 
Cassandra eu
Cassandra euCassandra eu
Cassandra eu
 
Cassandra + Hadoop @ApacheCon
Cassandra + Hadoop @ApacheCon Cassandra + Hadoop @ApacheCon
Cassandra + Hadoop @ApacheCon
 
Cassandra+Hadoop
Cassandra+HadoopCassandra+Hadoop
Cassandra+Hadoop
 

Kürzlich hochgeladen

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 

Kürzlich hochgeladen (20)

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 

End-to-end Analytics with Apache Cassandra

  • 1. End-to-end Analytics with Apache Cassandra C* #cassandra12
  • 2. Basics • CFIF/CFOF/CFRR/CFRW • BulkOutputFormat • Input locality (identical to HDFS) • Wide row, 2I, composite support • Pig, Hive, Mahout, Sqoop, Oozie, DSE Analytics C* #cassandra12
  • 3. Why Cassandra? • Excellent Hadoop capabilities built-in • Multi-datacenter support, load isolation • Operationally, order of magnitude simpler • DSE Analytics is all-in-one, simpler still • Review your requirements, do homework C* #cassandra12
  • 4. Use Cases • Trends, recommendations, reporting, etc. • Detect and fix problems in data • New realtime (or analytic) query pattern? • Backpopulate new CF with historical data C* #cassandra12
  • 5. Data Model • Consider growth patterns and analytic query patterns for your data • One-off inquiry or regular processing? • Fast growing, want only small slices? • Consider active/archive CFs • Secondary indexes for small inputs C* #cassandra12
  • 6. Miscellaneous Tips • Don’t forget about tombstones • BOP to enable range slices (Rows with keys ‘A*’ to ‘F*’) C* #cassandra12
  • 7. Cassandra + Oozie • Workflows: cohesive, nestable, scheduled • Web UI, CLI, web service • Cassandra properties in oozie job properties, and workflow.xml • Writing out to Cassandra: mapreduce.fileoutputcommitter.marksuccessfuljobs to false • DSE Analytics works with Oozie 3.2.1+ C* #cassandra12
  • 8. Cassandra + Pig • Data with validators • Pig tuples (address.name, address.value) • Data with default validator • Bag of key, value pairs (tuples) • Unmarshal with Pygmalion • Select by regex (eg ‘1369*’, ‘link*’) C* #cassandra12
  • 9. Cassandra + Pig • Output to Cassandra • Can output directly with (key, (name, value), (name, value)...) format • For tabular data, format output with Pygmalion’s ToCassandraBag • Use BulkOutputFormat (C* 1.1) C* #cassandra12
  • 10. Cassandra + Pig • Composite column support (C* 1.0.9+) • Counter support (C* 1.0.9+) • Secondary Index support for relatively small slices (C* 1.1+) • Wide row support (C* 1.1+) • Composite key support (C* 1.1.3+) C* #cassandra12
  • 11. Cassandra + Hadoop X • Example: Cassandra + CDH3 • Start with Cassandra ring • Add NN, JT, Oozie server • TaskTracker, DataNode on each node • Jobs/launching point have Cassandra info • Segregate out analytics with virtual DC C* #cassandra12
  • 12. Current/Future Work • Cassandra core Hive support (outside of Brisk) (CASSANDRA-4131) C* #cassandra12
  • 13. For More Information • Follow @CassandraHadoop on Twitter • http://wiki.apache.org/cassandra/ HadoopSupport C* #cassandra12
  • 14. Questions? C* #cassandra12

Hinweis der Redaktion

  1. \n
  2. wide row, 2I and composite key support in 1.1.\ncomposite column support in 1.0.9+\nwide row support is in both pig and hive\n
  3. \n
  4. So I have all this data...\nAll the normal use cases for Hadoop, plus some interesting use cases that are specific to things like Cassandra.\n
  5. If you are going to seriously use Cassandra with Hadoop, your analytic query patterns also have to be considered.\nFor active/archive CFs, denormalize by query - same as with RT query patterns\nYou can have lots of CFs, so no worries there\n
  6. \n
  7. OOZIE-477: hardcoded goodness if don’t want to use Oozie 3.2.1 (tiny patch)\n
  8. \n
  9. \n
  10. \n
  11. Dachis Group: in production with Cassandra + CDH3 going on 18 months.\nLaunching point may be a server from which you test or submit jobs. On that node, just put the Cassandra information in the default Hadoop conf (mapred-site.xml).\nFor tuning, just realize that Cassandra and Hadoop will share each node’s resources, but that you can scale one with the other. Both require memory, CPU, and IO.\n
  12. \n
  13. \n
  14. \n