SlideShare a Scribd company logo

C* Summit 2013: The World's Next Top Data Model by Patrick McFadin

You know you need Cassandra for it's uptime and scaling, but what about that data model? Let's bridge that gap and get you building your game changing app. We'll break down topics like storing objects and indexing for fast retrieval. You will see by understanding a few things about Cassandra internals, you can put your data model in the spotlight. The goal of this talk is to get you comfortable working with data in Cassandra throughout the application lifecycle. What are you waiting for? The cameras are waiting!

1 of 29
Download to read offline
#CASSANDRA13
Patrick McFadin | Solution Architect, DataStax
The World's Next Top Data Model
#CASSANDRA13
The saga continues!
★ Data model is dead, long live the
data model.
★ Bridging from Relational to Cassandra
★ Become a Super
Modeler
★ Core data modeling techniques
using CQL
#CASSANDRA13
Because I love talking about this
Just to recap...
#CASSANDRA13
Why does this matter?
* Cassandra lives closer to your users or applications
* Not a hammer for all use case nails
* Proper use case, proper model...
* Get it wrong and...
#CASSANDRA13
When to use Cassandra*
* Need to be in more than one datacenter. active-active
* Scaling from 0 to, uh, well... we’re not really sure.
* Need as close to 100% uptime as possible.
* Getting these from any other solution would just be mega $
and...
*nutshell version. These are all ORs not ANDs
#CASSANDRA13
You get the data
model right!

Recommended

More Related Content

What's hot

Cassandra overview
Cassandra overviewCassandra overview
Cassandra overviewSean Murphy
 
PostgreSQL Database Slides
PostgreSQL Database SlidesPostgreSQL Database Slides
PostgreSQL Database Slidesmetsarin
 
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...DataStax Academy
 
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)Jean-François Gagné
 
Storing time series data with Apache Cassandra
Storing time series data with Apache CassandraStoring time series data with Apache Cassandra
Storing time series data with Apache CassandraPatrick McFadin
 
Streaming Operational Data with MariaDB MaxScale
Streaming Operational Data with MariaDB MaxScaleStreaming Operational Data with MariaDB MaxScale
Streaming Operational Data with MariaDB MaxScaleMariaDB plc
 
Understanding Data Partitioning and Replication in Apache Cassandra
Understanding Data Partitioning and Replication in Apache CassandraUnderstanding Data Partitioning and Replication in Apache Cassandra
Understanding Data Partitioning and Replication in Apache CassandraDataStax
 
Pgday bdr 천정대
Pgday bdr 천정대Pgday bdr 천정대
Pgday bdr 천정대PgDay.Seoul
 
Introduction to PostgreSQL
Introduction to PostgreSQLIntroduction to PostgreSQL
Introduction to PostgreSQLJoel Brewer
 
MariaDB 10.11 key features overview for DBAs
MariaDB 10.11 key features overview for DBAsMariaDB 10.11 key features overview for DBAs
MariaDB 10.11 key features overview for DBAsFederico Razzoli
 
Solving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsSolving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsAlexander Korotkov
 
How to Manage Scale-Out Environments with MariaDB MaxScale
How to Manage Scale-Out Environments with MariaDB MaxScaleHow to Manage Scale-Out Environments with MariaDB MaxScale
How to Manage Scale-Out Environments with MariaDB MaxScaleMariaDB plc
 
Wide Column Store NoSQL vs SQL Data Modeling
Wide Column Store NoSQL vs SQL Data ModelingWide Column Store NoSQL vs SQL Data Modeling
Wide Column Store NoSQL vs SQL Data ModelingScyllaDB
 
C* Summit 2013: How Not to Use Cassandra by Axel Liljencrantz
C* Summit 2013: How Not to Use Cassandra by Axel LiljencrantzC* Summit 2013: How Not to Use Cassandra by Axel Liljencrantz
C* Summit 2013: How Not to Use Cassandra by Axel LiljencrantzDataStax Academy
 
Cassandra an overview
Cassandra an overviewCassandra an overview
Cassandra an overviewPritamKathar
 
Materialized Views and Secondary Indexes in Scylla: They Are finally here!
Materialized Views and Secondary Indexes in Scylla: They Are finally here!Materialized Views and Secondary Indexes in Scylla: They Are finally here!
Materialized Views and Secondary Indexes in Scylla: They Are finally here!ScyllaDB
 

What's hot (20)

Cassandra overview
Cassandra overviewCassandra overview
Cassandra overview
 
PostgreSQL Database Slides
PostgreSQL Database SlidesPostgreSQL Database Slides
PostgreSQL Database Slides
 
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...
Apache Cassandra and DataStax Enterprise Explained with Peter Halliday at Wil...
 
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)
MySQL Parallel Replication: All the 5.7 and 8.0 Details (LOGICAL_CLOCK)
 
Storing time series data with Apache Cassandra
Storing time series data with Apache CassandraStoring time series data with Apache Cassandra
Storing time series data with Apache Cassandra
 
SQL
SQLSQL
SQL
 
Streaming Operational Data with MariaDB MaxScale
Streaming Operational Data with MariaDB MaxScaleStreaming Operational Data with MariaDB MaxScale
Streaming Operational Data with MariaDB MaxScale
 
Basic sql Commands
Basic sql CommandsBasic sql Commands
Basic sql Commands
 
Understanding Data Partitioning and Replication in Apache Cassandra
Understanding Data Partitioning and Replication in Apache CassandraUnderstanding Data Partitioning and Replication in Apache Cassandra
Understanding Data Partitioning and Replication in Apache Cassandra
 
Pgday bdr 천정대
Pgday bdr 천정대Pgday bdr 천정대
Pgday bdr 천정대
 
Introduction to PostgreSQL
Introduction to PostgreSQLIntroduction to PostgreSQL
Introduction to PostgreSQL
 
MariaDB 10.11 key features overview for DBAs
MariaDB 10.11 key features overview for DBAsMariaDB 10.11 key features overview for DBAs
MariaDB 10.11 key features overview for DBAs
 
Solving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsSolving PostgreSQL wicked problems
Solving PostgreSQL wicked problems
 
How to Manage Scale-Out Environments with MariaDB MaxScale
How to Manage Scale-Out Environments with MariaDB MaxScaleHow to Manage Scale-Out Environments with MariaDB MaxScale
How to Manage Scale-Out Environments with MariaDB MaxScale
 
Mysql
MysqlMysql
Mysql
 
Wide Column Store NoSQL vs SQL Data Modeling
Wide Column Store NoSQL vs SQL Data ModelingWide Column Store NoSQL vs SQL Data Modeling
Wide Column Store NoSQL vs SQL Data Modeling
 
NoSQL databases
NoSQL databasesNoSQL databases
NoSQL databases
 
C* Summit 2013: How Not to Use Cassandra by Axel Liljencrantz
C* Summit 2013: How Not to Use Cassandra by Axel LiljencrantzC* Summit 2013: How Not to Use Cassandra by Axel Liljencrantz
C* Summit 2013: How Not to Use Cassandra by Axel Liljencrantz
 
Cassandra an overview
Cassandra an overviewCassandra an overview
Cassandra an overview
 
Materialized Views and Secondary Indexes in Scylla: They Are finally here!
Materialized Views and Secondary Indexes in Scylla: They Are finally here!Materialized Views and Secondary Indexes in Scylla: They Are finally here!
Materialized Views and Secondary Indexes in Scylla: They Are finally here!
 

Similar to C* Summit 2013: The World's Next Top Data Model by Patrick McFadin

The world's next top data model
The world's next top data modelThe world's next top data model
The world's next top data modelPatrick McFadin
 
Cassandra Community Webinar | The World's Next Top Data Model
Cassandra Community Webinar | The World's Next Top Data ModelCassandra Community Webinar | The World's Next Top Data Model
Cassandra Community Webinar | The World's Next Top Data ModelDataStax
 
Meetup cassandra for_java_cql
Meetup cassandra for_java_cqlMeetup cassandra for_java_cql
Meetup cassandra for_java_cqlzznate
 
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)Richard Low
 
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark DataStax Academy
 
Suicide Risk Prediction Using Social Media and Cassandra
Suicide Risk Prediction Using Social Media and CassandraSuicide Risk Prediction Using Social Media and Cassandra
Suicide Risk Prediction Using Social Media and CassandraKen Krugler
 
Time series with Apache Cassandra - Long version
Time series with Apache Cassandra - Long versionTime series with Apache Cassandra - Long version
Time series with Apache Cassandra - Long versionPatrick McFadin
 
Time series with apache cassandra strata
Time series with apache cassandra   strataTime series with apache cassandra   strata
Time series with apache cassandra strataPatrick McFadin
 
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...it-people
 
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandra
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable CassandraCassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandra
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandraaaronmorton
 
The Last Pickle: Repeatable, Scalable, Reliable, Observable: Cassandra
The Last Pickle: Repeatable, Scalable, Reliable, Observable: CassandraThe Last Pickle: Repeatable, Scalable, Reliable, Observable: Cassandra
The Last Pickle: Repeatable, Scalable, Reliable, Observable: CassandraDataStax Academy
 
Network Automation: Ansible 102
Network Automation: Ansible 102Network Automation: Ansible 102
Network Automation: Ansible 102APNIC
 
Most important "trick" of performance instrumentation
Most important "trick" of performance instrumentationMost important "trick" of performance instrumentation
Most important "trick" of performance instrumentationCary Millsap
 
DNN Database Tips & Tricks
DNN Database Tips & TricksDNN Database Tips & Tricks
DNN Database Tips & TricksWill Strohl
 
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...Codemotion
 
Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)zznate
 
Cassandra Data Modeling
Cassandra Data ModelingCassandra Data Modeling
Cassandra Data ModelingBen Knear
 
Updates from Cassandra Summit 2016 & SASI Indexes
Updates from Cassandra Summit 2016 & SASI IndexesUpdates from Cassandra Summit 2016 & SASI Indexes
Updates from Cassandra Summit 2016 & SASI IndexesJim Hatcher
 
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...DataStax Academy
 
Introduction to cassandra 2014
Introduction to cassandra 2014Introduction to cassandra 2014
Introduction to cassandra 2014Patrick McFadin
 

Similar to C* Summit 2013: The World's Next Top Data Model by Patrick McFadin (20)

The world's next top data model
The world's next top data modelThe world's next top data model
The world's next top data model
 
Cassandra Community Webinar | The World's Next Top Data Model
Cassandra Community Webinar | The World's Next Top Data ModelCassandra Community Webinar | The World's Next Top Data Model
Cassandra Community Webinar | The World's Next Top Data Model
 
Meetup cassandra for_java_cql
Meetup cassandra for_java_cqlMeetup cassandra for_java_cql
Meetup cassandra for_java_cql
 
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)
Mixing Batch and Real-time: Cassandra with Shark (Cassandra Europe 2013)
 
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark
C* Summit EU 2013: Mixing Batch and Real-Time: Cassandra with Shark
 
Suicide Risk Prediction Using Social Media and Cassandra
Suicide Risk Prediction Using Social Media and CassandraSuicide Risk Prediction Using Social Media and Cassandra
Suicide Risk Prediction Using Social Media and Cassandra
 
Time series with Apache Cassandra - Long version
Time series with Apache Cassandra - Long versionTime series with Apache Cassandra - Long version
Time series with Apache Cassandra - Long version
 
Time series with apache cassandra strata
Time series with apache cassandra   strataTime series with apache cassandra   strata
Time series with apache cassandra strata
 
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...
Jonathan Ellis "Apache Cassandra 2.0 and 2.1". Выступление на Cassandra conf ...
 
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandra
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable CassandraCassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandra
Cassandra SF 2015 - Repeatable, Scalable, Reliable, Observable Cassandra
 
The Last Pickle: Repeatable, Scalable, Reliable, Observable: Cassandra
The Last Pickle: Repeatable, Scalable, Reliable, Observable: CassandraThe Last Pickle: Repeatable, Scalable, Reliable, Observable: Cassandra
The Last Pickle: Repeatable, Scalable, Reliable, Observable: Cassandra
 
Network Automation: Ansible 102
Network Automation: Ansible 102Network Automation: Ansible 102
Network Automation: Ansible 102
 
Most important "trick" of performance instrumentation
Most important "trick" of performance instrumentationMost important "trick" of performance instrumentation
Most important "trick" of performance instrumentation
 
DNN Database Tips & Tricks
DNN Database Tips & TricksDNN Database Tips & Tricks
DNN Database Tips & Tricks
 
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...
Perchè potresti aver bisogno di un database NoSQL anche se non sei Google o F...
 
Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)
 
Cassandra Data Modeling
Cassandra Data ModelingCassandra Data Modeling
Cassandra Data Modeling
 
Updates from Cassandra Summit 2016 & SASI Indexes
Updates from Cassandra Summit 2016 & SASI IndexesUpdates from Cassandra Summit 2016 & SASI Indexes
Updates from Cassandra Summit 2016 & SASI Indexes
 
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...
Cassandra Community Webinar | Getting Started with Apache Cassandra with Patr...
 
Introduction to cassandra 2014
Introduction to cassandra 2014Introduction to cassandra 2014
Introduction to cassandra 2014
 

More from DataStax Academy

Forrester CXNYC 2017 - Delivering great real-time cx is a true craft
Forrester CXNYC 2017 - Delivering great real-time cx is a true craftForrester CXNYC 2017 - Delivering great real-time cx is a true craft
Forrester CXNYC 2017 - Delivering great real-time cx is a true craftDataStax Academy
 
Introduction to DataStax Enterprise Graph Database
Introduction to DataStax Enterprise Graph DatabaseIntroduction to DataStax Enterprise Graph Database
Introduction to DataStax Enterprise Graph DatabaseDataStax Academy
 
Introduction to DataStax Enterprise Advanced Replication with Apache Cassandra
Introduction to DataStax Enterprise Advanced Replication with Apache CassandraIntroduction to DataStax Enterprise Advanced Replication with Apache Cassandra
Introduction to DataStax Enterprise Advanced Replication with Apache CassandraDataStax Academy
 
Cassandra on Docker @ Walmart Labs
Cassandra on Docker @ Walmart LabsCassandra on Docker @ Walmart Labs
Cassandra on Docker @ Walmart LabsDataStax Academy
 
Cassandra 3.0 Data Modeling
Cassandra 3.0 Data ModelingCassandra 3.0 Data Modeling
Cassandra 3.0 Data ModelingDataStax Academy
 
Cassandra Adoption on Cisco UCS & Open stack
Cassandra Adoption on Cisco UCS & Open stackCassandra Adoption on Cisco UCS & Open stack
Cassandra Adoption on Cisco UCS & Open stackDataStax Academy
 
Data Modeling for Apache Cassandra
Data Modeling for Apache CassandraData Modeling for Apache Cassandra
Data Modeling for Apache CassandraDataStax Academy
 
Production Ready Cassandra
Production Ready CassandraProduction Ready Cassandra
Production Ready CassandraDataStax Academy
 
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & Python
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & PythonCassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & Python
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & PythonDataStax Academy
 
Cassandra @ Sony: The good, the bad, and the ugly part 1
Cassandra @ Sony: The good, the bad, and the ugly part 1Cassandra @ Sony: The good, the bad, and the ugly part 1
Cassandra @ Sony: The good, the bad, and the ugly part 1DataStax Academy
 
Cassandra @ Sony: The good, the bad, and the ugly part 2
Cassandra @ Sony: The good, the bad, and the ugly part 2Cassandra @ Sony: The good, the bad, and the ugly part 2
Cassandra @ Sony: The good, the bad, and the ugly part 2DataStax Academy
 
Standing Up Your First Cluster
Standing Up Your First ClusterStanding Up Your First Cluster
Standing Up Your First ClusterDataStax Academy
 
Real Time Analytics with Dse
Real Time Analytics with DseReal Time Analytics with Dse
Real Time Analytics with DseDataStax Academy
 
Introduction to Data Modeling with Apache Cassandra
Introduction to Data Modeling with Apache CassandraIntroduction to Data Modeling with Apache Cassandra
Introduction to Data Modeling with Apache CassandraDataStax Academy
 
Enabling Search in your Cassandra Application with DataStax Enterprise
Enabling Search in your Cassandra Application with DataStax EnterpriseEnabling Search in your Cassandra Application with DataStax Enterprise
Enabling Search in your Cassandra Application with DataStax EnterpriseDataStax Academy
 
Advanced Data Modeling with Apache Cassandra
Advanced Data Modeling with Apache CassandraAdvanced Data Modeling with Apache Cassandra
Advanced Data Modeling with Apache CassandraDataStax Academy
 

More from DataStax Academy (20)

Forrester CXNYC 2017 - Delivering great real-time cx is a true craft
Forrester CXNYC 2017 - Delivering great real-time cx is a true craftForrester CXNYC 2017 - Delivering great real-time cx is a true craft
Forrester CXNYC 2017 - Delivering great real-time cx is a true craft
 
Introduction to DataStax Enterprise Graph Database
Introduction to DataStax Enterprise Graph DatabaseIntroduction to DataStax Enterprise Graph Database
Introduction to DataStax Enterprise Graph Database
 
Introduction to DataStax Enterprise Advanced Replication with Apache Cassandra
Introduction to DataStax Enterprise Advanced Replication with Apache CassandraIntroduction to DataStax Enterprise Advanced Replication with Apache Cassandra
Introduction to DataStax Enterprise Advanced Replication with Apache Cassandra
 
Cassandra on Docker @ Walmart Labs
Cassandra on Docker @ Walmart LabsCassandra on Docker @ Walmart Labs
Cassandra on Docker @ Walmart Labs
 
Cassandra 3.0 Data Modeling
Cassandra 3.0 Data ModelingCassandra 3.0 Data Modeling
Cassandra 3.0 Data Modeling
 
Cassandra Adoption on Cisco UCS & Open stack
Cassandra Adoption on Cisco UCS & Open stackCassandra Adoption on Cisco UCS & Open stack
Cassandra Adoption on Cisco UCS & Open stack
 
Data Modeling for Apache Cassandra
Data Modeling for Apache CassandraData Modeling for Apache Cassandra
Data Modeling for Apache Cassandra
 
Coursera Cassandra Driver
Coursera Cassandra DriverCoursera Cassandra Driver
Coursera Cassandra Driver
 
Production Ready Cassandra
Production Ready CassandraProduction Ready Cassandra
Production Ready Cassandra
 
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & Python
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & PythonCassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & Python
Cassandra @ Netflix: Monitoring C* at Scale, Gossip and Tickler & Python
 
Cassandra @ Sony: The good, the bad, and the ugly part 1
Cassandra @ Sony: The good, the bad, and the ugly part 1Cassandra @ Sony: The good, the bad, and the ugly part 1
Cassandra @ Sony: The good, the bad, and the ugly part 1
 
Cassandra @ Sony: The good, the bad, and the ugly part 2
Cassandra @ Sony: The good, the bad, and the ugly part 2Cassandra @ Sony: The good, the bad, and the ugly part 2
Cassandra @ Sony: The good, the bad, and the ugly part 2
 
Standing Up Your First Cluster
Standing Up Your First ClusterStanding Up Your First Cluster
Standing Up Your First Cluster
 
Real Time Analytics with Dse
Real Time Analytics with DseReal Time Analytics with Dse
Real Time Analytics with Dse
 
Introduction to Data Modeling with Apache Cassandra
Introduction to Data Modeling with Apache CassandraIntroduction to Data Modeling with Apache Cassandra
Introduction to Data Modeling with Apache Cassandra
 
Cassandra Core Concepts
Cassandra Core ConceptsCassandra Core Concepts
Cassandra Core Concepts
 
Enabling Search in your Cassandra Application with DataStax Enterprise
Enabling Search in your Cassandra Application with DataStax EnterpriseEnabling Search in your Cassandra Application with DataStax Enterprise
Enabling Search in your Cassandra Application with DataStax Enterprise
 
Bad Habits Die Hard
Bad Habits Die Hard Bad Habits Die Hard
Bad Habits Die Hard
 
Advanced Data Modeling with Apache Cassandra
Advanced Data Modeling with Apache CassandraAdvanced Data Modeling with Apache Cassandra
Advanced Data Modeling with Apache Cassandra
 
Advanced Cassandra
Advanced CassandraAdvanced Cassandra
Advanced Cassandra
 

Recently uploaded

Pragmatic UI testing with Compose Semantics.pdf
Pragmatic UI testing with Compose Semantics.pdfPragmatic UI testing with Compose Semantics.pdf
Pragmatic UI testing with Compose Semantics.pdfinfogdgmi
 
"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura RochniakFwdays
 
Building Bridges: Merging RPA Processes, UiPath Apps, and Data Service to bu...
Building Bridges:  Merging RPA Processes, UiPath Apps, and Data Service to bu...Building Bridges:  Merging RPA Processes, UiPath Apps, and Data Service to bu...
Building Bridges: Merging RPA Processes, UiPath Apps, and Data Service to bu...DianaGray10
 
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Product School
 
Enterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewEnterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewAshraf Fouad
 
LF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIELF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIEDanBrown980551
 
"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys VasylievFwdays
 
How AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxHow AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxInfosec
 
Revolutionizing The Banking Industry: The Monzo Way by CPO, Monzo
Revolutionizing The Banking Industry: The Monzo Way by CPO, MonzoRevolutionizing The Banking Industry: The Monzo Way by CPO, Monzo
Revolutionizing The Banking Industry: The Monzo Way by CPO, MonzoProduct School
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfMostafa Higazy
 
Confoo 2024 Gettings started with OpenAI and data science
Confoo 2024 Gettings started with OpenAI and data scienceConfoo 2024 Gettings started with OpenAI and data science
Confoo 2024 Gettings started with OpenAI and data scienceSusan Ibach
 
Building Products That Think- Bhaskaran Srinivasan & Ashish Gupta
Building Products That Think- Bhaskaran Srinivasan & Ashish GuptaBuilding Products That Think- Bhaskaran Srinivasan & Ashish Gupta
Building Products That Think- Bhaskaran Srinivasan & Ashish GuptaISPMAIndia
 
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24Umar Saif
 
IT Nation Evolve event 2024 - Quarter 1
IT Nation Evolve event 2024  - Quarter 1IT Nation Evolve event 2024  - Quarter 1
IT Nation Evolve event 2024 - Quarter 1Inbay UK
 
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, GoogleISPMAIndia
 
How we think about an advisor tech stack
How we think about an advisor tech stackHow we think about an advisor tech stack
How we think about an advisor tech stackSummit
 
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...DianaGray10
 
Launching New Products In Companies Where It Matters Most by Product Director...
Launching New Products In Companies Where It Matters Most by Product Director...Launching New Products In Companies Where It Matters Most by Product Director...
Launching New Products In Companies Where It Matters Most by Product Director...Product School
 
From Challenger to Champion: How SpiraPlan Outperforms JIRA+Plugins
From Challenger to Champion: How SpiraPlan Outperforms JIRA+PluginsFrom Challenger to Champion: How SpiraPlan Outperforms JIRA+Plugins
From Challenger to Champion: How SpiraPlan Outperforms JIRA+PluginsInflectra
 
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdf
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdfIntroducing the New FME Community Webinar - Feb 21, 2024 (2).pdf
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdfSafe Software
 

Recently uploaded (20)

Pragmatic UI testing with Compose Semantics.pdf
Pragmatic UI testing with Compose Semantics.pdfPragmatic UI testing with Compose Semantics.pdf
Pragmatic UI testing with Compose Semantics.pdf
 
"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak
 
Building Bridges: Merging RPA Processes, UiPath Apps, and Data Service to bu...
Building Bridges:  Merging RPA Processes, UiPath Apps, and Data Service to bu...Building Bridges:  Merging RPA Processes, UiPath Apps, and Data Service to bu...
Building Bridges: Merging RPA Processes, UiPath Apps, and Data Service to bu...
 
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
 
Enterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewEnterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book Review
 
LF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIELF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIE
 
"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev
 
How AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxHow AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptx
 
Revolutionizing The Banking Industry: The Monzo Way by CPO, Monzo
Revolutionizing The Banking Industry: The Monzo Way by CPO, MonzoRevolutionizing The Banking Industry: The Monzo Way by CPO, Monzo
Revolutionizing The Banking Industry: The Monzo Way by CPO, Monzo
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdf
 
Confoo 2024 Gettings started with OpenAI and data science
Confoo 2024 Gettings started with OpenAI and data scienceConfoo 2024 Gettings started with OpenAI and data science
Confoo 2024 Gettings started with OpenAI and data science
 
Building Products That Think- Bhaskaran Srinivasan & Ashish Gupta
Building Products That Think- Bhaskaran Srinivasan & Ashish GuptaBuilding Products That Think- Bhaskaran Srinivasan & Ashish Gupta
Building Products That Think- Bhaskaran Srinivasan & Ashish Gupta
 
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24
Progress Report: Ministry of IT under Dr. Umar Saif Aug 23-Feb'24
 
IT Nation Evolve event 2024 - Quarter 1
IT Nation Evolve event 2024  - Quarter 1IT Nation Evolve event 2024  - Quarter 1
IT Nation Evolve event 2024 - Quarter 1
 
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google
"The Transformative Power of AI and Open Challenges" by Dr. Manish Gupta, Google
 
How we think about an advisor tech stack
How we think about an advisor tech stackHow we think about an advisor tech stack
How we think about an advisor tech stack
 
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
 
Launching New Products In Companies Where It Matters Most by Product Director...
Launching New Products In Companies Where It Matters Most by Product Director...Launching New Products In Companies Where It Matters Most by Product Director...
Launching New Products In Companies Where It Matters Most by Product Director...
 
From Challenger to Champion: How SpiraPlan Outperforms JIRA+Plugins
From Challenger to Champion: How SpiraPlan Outperforms JIRA+PluginsFrom Challenger to Champion: How SpiraPlan Outperforms JIRA+Plugins
From Challenger to Champion: How SpiraPlan Outperforms JIRA+Plugins
 
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdf
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdfIntroducing the New FME Community Webinar - Feb 21, 2024 (2).pdf
Introducing the New FME Community Webinar - Feb 21, 2024 (2).pdf
 

C* Summit 2013: The World's Next Top Data Model by Patrick McFadin

  • 1. #CASSANDRA13 Patrick McFadin | Solution Architect, DataStax The World's Next Top Data Model
  • 2. #CASSANDRA13 The saga continues! ★ Data model is dead, long live the data model. ★ Bridging from Relational to Cassandra ★ Become a Super Modeler ★ Core data modeling techniques using CQL
  • 3. #CASSANDRA13 Because I love talking about this Just to recap...
  • 4. #CASSANDRA13 Why does this matter? * Cassandra lives closer to your users or applications * Not a hammer for all use case nails * Proper use case, proper model... * Get it wrong and...
  • 5. #CASSANDRA13 When to use Cassandra* * Need to be in more than one datacenter. active-active * Scaling from 0 to, uh, well... we’re not really sure. * Need as close to 100% uptime as possible. * Getting these from any other solution would just be mega $ and... *nutshell version. These are all ORs not ANDs
  • 6. #CASSANDRA13 You get the data model right!
  • 7. #CASSANDRA13 So let’s do that * Four real world examples * Use case, what they were avoiding and model to accomplish * You may think this is you, but it isn’t. I hear these all the time. * All examples are in CQL3
  • 8. #CASSANDRA13 But wait you say CQL doesn’t do dynamic wide rows!
  • 9. #CASSANDRA13 Yes it can! * CQL does wide rows the same way you did them in Thrift * No really * Read this blog post http://www.datastax.com/dev/blog/does-cql-support-dynamic-columns-wide-rows ...or just trust me and I’ll show you how
  • 10. #CASSANDRA13 Customers giving you money is a good reason for uptime Shopping Cart Data Model
  • 11. #CASSANDRA13 Shopping cart use case * Store shopping cart data reliably * Minimize (or eliminate) downtime. Multi-dc * Scale for the “Cyber Monday” problem * Every minute off-line is lost $$ * Online shoppers want speed! The bad
  • 12. #CASSANDRA13 Shopping cart data model * Each customer can have one or more shopping carts * De-normalize data for fast access * Shopping cart == One partition (Row Level Isolation) * Each item a new column
  • 13. #CASSANDRA13 Shopping cart data model CREATE TABLE user ( ! username varchar, ! firstname varchar, ! lastname varchar, ! shopping_carts set<varchar>, ! PRIMARY KEY (username) ); CREATE TABLE shopping_cart ( ! username varchar, ! cart_name text ! item_id int, ! item_name varchar, description varchar, ! price float, ! item_detail map<varchar,varchar> ! PRIMARY KEY ((username,cart_name),item_id) ); INSERT INTO shopping_cart (username,cart_name,item_id,item_name,description,price,item_detail) VALUES ('pmcfadin','Gadgets I want',8675309,'Garmin 910XT','Multisport training watch',349.99, {'Related':'Timex sports watch', 'Volume Discount':'10'}); INSERT INTO shopping_cart (username,cart_name,item_id,item_name,description,price,item_detail) VALUES ('pmcfadin','Gadgets I want',9748575,'Polaris Foot Pod','Bluetooth Smart foot pod',64.00 {'Related':'Timex foot pod', 'Volume Discount':'25'}); One partition (storage row) of data Item details. Flexible for whatev Partition row key for one users cart Creates partition row key
  • 14. #CASSANDRA13 Watching users, making decisions. Freaky, but cool. User Activity Tracking
  • 15. #CASSANDRA13 User activity use case * React to user input in real time * Support for multiple application pods * Scale for speed * Losing interactions is costly * Waiting for batch(hadoop) is to long The bad
  • 16. #CASSANDRA13 User activity data model * Interaction points stored per user in short table * Long term interaction stored in similar table with date partition * Process long term later using batch * Reverse time series to get last N items
  • 17. #CASSANDRA13 User activity data model CREATE TABLE user_activity ( ! username varchar, ! interaction_time timeuuid, ! activity_code varchar, ! detail varchar, ! PRIMARY KEY (username, interaction_time) ) WITH CLUSTERING ORDER BY (interaction_time DESC); CREATE TABLE user_activity_history ( ! username varchar, ! interaction_date varchar, ! interaction_time timeuuid, ! activity_code varchar, ! detail varchar, ! PRIMARY KEY ((username,interaction_date),interaction_time) ); INSERT INTO user_activity (username,interaction_time,activity_code,detail) VALUES ('pmcfadin',0D1454E0-D202-11E2-8B8B-0800200C9A66,'100','Normal login') USING TTL 2592000; INSERT INTO user_activity_history (username,interaction_date,interaction_time,activity_code,detail) VALUES ('pmcfadin','20130605',0D1454E0- D202-11E2-8B8B-0800200C9A66,'100','Normal login'); Reverse order based on timestamp Expire after 30 days
  • 18. #CASSANDRA13 Data model usage username | interaction_time | detail | activity_code ----------+--------------------------------------+------------------------------------------+------------------ pmcfadin | 9ccc9df0-d076-11e2-923e-5d8390e664ec | Entered shopping area: Jewelry | 301 pmcfadin | 9c652990-d076-11e2-923e-5d8390e664ec | Created shopping cart: Anniversary gifts | 202 pmcfadin | 1b5cef90-d076-11e2-923e-5d8390e664ec | Deleted shopping cart: Gadgets I want | 205 pmcfadin | 1b0e5a60-d076-11e2-923e-5d8390e664ec | Opened shopping cart: Gadgets I want | 201 pmcfadin | 1b0be960-d076-11e2-923e-5d8390e664ec | Normal login | 100 select * from user_activity limit 5; Maybe put a sale item for flowers too?
  • 19. #CASSANDRA13 Machines generate logs at a furious pace. Be ready. Log collection/aggregation
  • 20. #CASSANDRA13 Log collection use case * Collect log data at high speed * Cassandra near where logs are generated. Multi-datacenter * Dice data for various uses. Dashboard. Lookup. Etc. * The scale needed for RDBMS is cost prohibitive * Batch analysis of logs too late for some use cases The bad
  • 21. #CASSANDRA13 Log collection data model * Use Flume to collect and fan out data to various tables * Tables for lookup based on source and time * Tables for dashboard with aggregation and summation
  • 22. #CASSANDRA13 Log collection data model CREATE TABLE log_lookup ( ! source varchar, ! date_to_minute varchar, ! timestamp timeuuid, ! raw_log blob, ! PRIMARY KEY ((source,date_to_minute),timestamp) ); CREATE TABLE login_success ( ! source varchar, ! date_to_minute varchar, ! successful_logins counter, ! PRIMARY KEY (source,date_to_minute) ) WITH CLUSTERING ORDER BY (date_to_minute DESC); CREATE TABLE login_failure ( ! source varchar, ! date_to_minute varchar, ! failed_logins counter, ! PRIMARY KEY (source,date_to_minute) ) WITH CLUSTERING ORDER BY (date_to_minute DESC); Consider storing raw logs as GZIP
  • 23. #CASSANDRA13 Log dashboard 0 25 50 75 100 10:01 10:03 10:05 10:07 10:09 10:11 10:13 10:15 10:17 10:19 Sucessful Logins Failed Logins SELECT date_to_minute,successful_logins FROM login_success LIMIT 20; SELECT date_to_minute,failed_logins FROM login_failure LIMIT 20;
  • 24. #CASSANDRA13 Because mistaks mistakes happen User Form Versioning
  • 25. #CASSANDRA13 Form versioning use case * Store every possible version efficiently * Scale to any number of users * Commit/Rollback functionality on a form * In RDBMS, many relations that need complicated join * Needs to be in cloud and local data center The bad
  • 26. #CASSANDRA13 Form version data model * Each user has a form * Each form needs versioning * Separate table to store live version * Exclusive lock on a form
  • 27. #CASSANDRA13 Form version data model CREATE TABLE working_version ( ! username varchar, ! form_id int, ! version_number int, ! locked_by varchar, ! form_attributes map<varchar,varchar> ! PRIMARY KEY ((username, form_id), version_number) ) WITH CLUSTERING ORDER BY (version_number DESC); INSERT INTO working_version (username, form_id, version_number, locked_by, form_attributes) VALUES ('pmcfadin',1138,1,'', {'FirstName<text>':'First Name: ', 'LastName<text>':'Last Name: ', 'EmailAddress<text>':'Email Address: ', 'Newsletter<radio>':'Y,N'}); UPDATE working_version SET locked_by = 'pmcfadin' WHERE username = 'pmcfadin' AND form_id = 1138 AND version_number = 1; INSERT INTO working_version (username, form_id, version_number, locked_by, form_attributes) VALUES ('pmcfadin',1138,2,null, {'FirstName<text>':'First Name: ', 'LastName<text>':'Last Name: ', 'EmailAddress<text>':'Email Address: ', 'Newsletter<checkbox>':'Y'}); 1. Insert first version 2. Lock for one user 3. Insert new version. Release lock
  • 28. #CASSANDRA13 That’s it! “Mind what you have learned. Save you it can.” - Yoda. Master Data Modeler
  • 29. #CASSANDRA13 Your data model is next! * Try out a few things * See what works * All else fails, engage an expert in the community * Want more? Follow me on twitter: @PatrickMcFadin