SlideShare ist ein Scribd-Unternehmen logo
1 von 21
Downloaden Sie, um offline zu lesen
Cassandra Data Access in Java
eBuddy use of Cassandra
XMS
● User Data Service
● User Discovery Service
● Persistent Session Store
● Message History
● Location-based Discovery
Cassandra in
eBuddy Messaging Platform
● Current size of data
● 1,4 TiB total (replication of 3x); 467 GiB actual data
● 12 million sessions (11 million users plus groups)
● Almost a billion rows in one column family
(inverse social graph)
Some Statistics
Data Access - Overview
Design Objectives
● Data Source Agnostic
● Testable
● Thread Safe
● Strong Typing
● Supports “transactions”, i.e. units of work in batch
● Efficient Mapping to Application Domain Model
● Follows Familiar Patterns (e.g. Spring JDBC Template)
Data Access in Layers
“Operations” Layer
Writing
● Use Generic Typing
● Has Interface
(for testability, etc.)
● Handles Exceptions
Reading
● Use Mappers
Serializers
● Constructed with serializers that convert to types needed
by data access layer
Reading
Data Access Layer
Data Access Object
● Data Access Object (DAO) is singleton
● Transforms from data model to domain model
● Operations object configured with serializers to convert
from data model to domain model
● Defines the mappers for read operations
Next Steps
CQL3
DataStax:
"We believe that CQL3 is a simpler and overall better API for Cassandra
than the thrift API is. Therefore, new projects/applications are encouraged
to use CQL3"
At eBuddy, we are still using the Thrift API and the Java Hector library.
We are currently looking at CQL3 and whether we want to use it going
forward and whether we will "upgrade" existing code.
Structured Data
● Object Mapping Frameworks
● Mapped vs. Embedded Objects
● Nested Properties ("path" access)
Object Mapping Frameworks
● Simple mapper frameworks with (some) JPA support
● Hector Object Mapper
● Kundera
● Firebrand (not JPA)
● has most features,
e.g supports both embedded and mapped object graphs
https://github.com/impetus-opensource/Kundera
http://github.com/hector-client/hector
http://firebrandocm.org
Hierarchical Properties
● Use DynamicComposites to model keys that have a
variable number of components
put(“accounts|msn|x.y.z|sign_in”, “0”);
put(“accounts|msn|x.y.z|key”, “value”);
get(“accounts”) --> retrieved as a map:
{"accounts":
{ "msn":
{ "x.y.z":
{ "sign_in": "0",
"key": "value" } } } }
● Use a slice query to retrieve properties using partial path:
Questions?
XMS
Unlimited messaging.
Better. Free.
We're Hiring!
Download XMS now:

Weitere ähnliche Inhalte

Was ist angesagt?

Exploring MongoDB & Elasticsearch: Better Together
Exploring MongoDB & Elasticsearch: Better TogetherExploring MongoDB & Elasticsearch: Better Together
Exploring MongoDB & Elasticsearch: Better TogetherObjectRocket
 
A head start on cloud native event driven applications - bigdatadays
A head start on cloud native event driven applications - bigdatadaysA head start on cloud native event driven applications - bigdatadays
A head start on cloud native event driven applications - bigdatadaysSriskandarajah Suhothayan
 
Overhauling a database engine in 2 months
Overhauling a database engine in 2 monthsOverhauling a database engine in 2 months
Overhauling a database engine in 2 monthsMax Neunhöffer
 
Multi-model databases and node.js
Multi-model databases and node.jsMulti-model databases and node.js
Multi-model databases and node.jsMax Neunhöffer
 
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...Sriskandarajah Suhothayan
 
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...In-Memory Computing Summit
 
Electron, databases, and RxDB
Electron, databases, and RxDBElectron, databases, and RxDB
Electron, databases, and RxDBBen Gotow
 
Webtech Conference: NoSQL and Web scalability
Webtech Conference: NoSQL and Web scalabilityWebtech Conference: NoSQL and Web scalability
Webtech Conference: NoSQL and Web scalabilityLuca Bonmassar
 
Log analysis using elk
Log analysis using elkLog analysis using elk
Log analysis using elkRushika Shah
 
Accelerating Delivery of Data Products - The EBSCO Way
Accelerating Delivery of Data Products - The EBSCO WayAccelerating Delivery of Data Products - The EBSCO Way
Accelerating Delivery of Data Products - The EBSCO WayMongoDB
 
FOXX - a Javascript application framework on top of ArangoDB
FOXX - a Javascript application framework on top of ArangoDBFOXX - a Javascript application framework on top of ArangoDB
FOXX - a Javascript application framework on top of ArangoDBArangoDB Database
 
The CIOs Guide to NoSQL
The CIOs Guide to NoSQLThe CIOs Guide to NoSQL
The CIOs Guide to NoSQLDATAVERSITY
 
Backbone using Extensible Database APIs over HTTP
Backbone using Extensible Database APIs over HTTPBackbone using Extensible Database APIs over HTTP
Backbone using Extensible Database APIs over HTTPMax Neunhöffer
 
Data platform architecture principles - ieee infrastructure 2020
Data platform architecture principles - ieee infrastructure 2020Data platform architecture principles - ieee infrastructure 2020
Data platform architecture principles - ieee infrastructure 2020Julien Le Dem
 
Scaling ArangoDB on Mesosphere DCOS
Scaling ArangoDB on Mesosphere DCOSScaling ArangoDB on Mesosphere DCOS
Scaling ArangoDB on Mesosphere DCOSMax Neunhöffer
 
Db presentation google_megastore
Db presentation google_megastoreDb presentation google_megastore
Db presentation google_megastoreAlanoud Alqoufi
 

Was ist angesagt? (20)

Exploring MongoDB & Elasticsearch: Better Together
Exploring MongoDB & Elasticsearch: Better TogetherExploring MongoDB & Elasticsearch: Better Together
Exploring MongoDB & Elasticsearch: Better Together
 
A head start on cloud native event driven applications - bigdatadays
A head start on cloud native event driven applications - bigdatadaysA head start on cloud native event driven applications - bigdatadays
A head start on cloud native event driven applications - bigdatadays
 
Overhauling a database engine in 2 months
Overhauling a database engine in 2 monthsOverhauling a database engine in 2 months
Overhauling a database engine in 2 months
 
Oslo bekk2014
Oslo bekk2014Oslo bekk2014
Oslo bekk2014
 
Stream Processing with Ballerina
Stream Processing with BallerinaStream Processing with Ballerina
Stream Processing with Ballerina
 
Multi-model databases and node.js
Multi-model databases and node.jsMulti-model databases and node.js
Multi-model databases and node.js
 
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...
WSO2 Stream Processor: Graphical Editor, HTTP & Message Trace Analytics and m...
 
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...
IMC Summit 2016 Breakout - William Bain - Implementing Extensible Data Struct...
 
Electron, databases, and RxDB
Electron, databases, and RxDBElectron, databases, and RxDB
Electron, databases, and RxDB
 
Webtech Conference: NoSQL and Web scalability
Webtech Conference: NoSQL and Web scalabilityWebtech Conference: NoSQL and Web scalability
Webtech Conference: NoSQL and Web scalability
 
Log analysis using elk
Log analysis using elkLog analysis using elk
Log analysis using elk
 
Accelerating Delivery of Data Products - The EBSCO Way
Accelerating Delivery of Data Products - The EBSCO WayAccelerating Delivery of Data Products - The EBSCO Way
Accelerating Delivery of Data Products - The EBSCO Way
 
FOXX - a Javascript application framework on top of ArangoDB
FOXX - a Javascript application framework on top of ArangoDBFOXX - a Javascript application framework on top of ArangoDB
FOXX - a Javascript application framework on top of ArangoDB
 
The CIOs Guide to NoSQL
The CIOs Guide to NoSQLThe CIOs Guide to NoSQL
The CIOs Guide to NoSQL
 
Backbone using Extensible Database APIs over HTTP
Backbone using Extensible Database APIs over HTTPBackbone using Extensible Database APIs over HTTP
Backbone using Extensible Database APIs over HTTP
 
NoSQL for SQL Users
NoSQL for SQL UsersNoSQL for SQL Users
NoSQL for SQL Users
 
Data platform architecture principles - ieee infrastructure 2020
Data platform architecture principles - ieee infrastructure 2020Data platform architecture principles - ieee infrastructure 2020
Data platform architecture principles - ieee infrastructure 2020
 
Document Database
Document DatabaseDocument Database
Document Database
 
Scaling ArangoDB on Mesosphere DCOS
Scaling ArangoDB on Mesosphere DCOSScaling ArangoDB on Mesosphere DCOS
Scaling ArangoDB on Mesosphere DCOS
 
Db presentation google_megastore
Db presentation google_megastoreDb presentation google_megastore
Db presentation google_megastore
 

Andere mochten auch

Meetup cassandra for_java_cql
Meetup cassandra for_java_cqlMeetup cassandra for_java_cql
Meetup cassandra for_java_cqlzznate
 
Retention and upsale in using customer data
Retention and upsale in using customer dataRetention and upsale in using customer data
Retention and upsale in using customer dataGideon Cohen
 
שירות כמנוע צמיחה ורווחיות
שירות כמנוע צמיחה ורווחיותשירות כמנוע צמיחה ורווחיות
שירות כמנוע צמיחה ורווחיותGideon Cohen
 
Integrating Voice Of Customers with Customer Success
Integrating Voice Of Customers with Customer SuccessIntegrating Voice Of Customers with Customer Success
Integrating Voice Of Customers with Customer SuccessGideon Cohen
 
B2B - Measuring Customer Satisfaction - Comverse ltd
B2B - Measuring Customer Satisfaction - Comverse ltdB2B - Measuring Customer Satisfaction - Comverse ltd
B2B - Measuring Customer Satisfaction - Comverse ltdGideon Cohen
 
Voice of Customers programs in B2B
Voice of Customers programs in B2BVoice of Customers programs in B2B
Voice of Customers programs in B2BGideon Cohen
 
Model assure media pembelajaran
Model assure media pembelajaranModel assure media pembelajaran
Model assure media pembelajaranitnay cindo
 
Using puppet, foreman and git to develop and operate a large scale internet s...
Using puppet, foreman and git to develop and operate a large scale internet s...Using puppet, foreman and git to develop and operate a large scale internet s...
Using puppet, foreman and git to develop and operate a large scale internet s...techblog
 
Managing service projects in a B2B environment
Managing service projects in a B2B environmentManaging service projects in a B2B environment
Managing service projects in a B2B environmentGideon Cohen
 

Andere mochten auch (13)

Meetup cassandra for_java_cql
Meetup cassandra for_java_cqlMeetup cassandra for_java_cql
Meetup cassandra for_java_cql
 
Retention and upsale in using customer data
Retention and upsale in using customer dataRetention and upsale in using customer data
Retention and upsale in using customer data
 
C* path
C* pathC* path
C* path
 
Агман Забуровна
Агман ЗабуровнаАгман Забуровна
Агман Забуровна
 
שירות כמנוע צמיחה ורווחיות
שירות כמנוע צמיחה ורווחיותשירות כמנוע צמיחה ורווחיות
שירות כמנוע צמיחה ורווחיות
 
Агман Забуровна
Агман ЗабуровнаАгман Забуровна
Агман Забуровна
 
Integrating Voice Of Customers with Customer Success
Integrating Voice Of Customers with Customer SuccessIntegrating Voice Of Customers with Customer Success
Integrating Voice Of Customers with Customer Success
 
B2B - Measuring Customer Satisfaction - Comverse ltd
B2B - Measuring Customer Satisfaction - Comverse ltdB2B - Measuring Customer Satisfaction - Comverse ltd
B2B - Measuring Customer Satisfaction - Comverse ltd
 
Voice of Customers programs in B2B
Voice of Customers programs in B2BVoice of Customers programs in B2B
Voice of Customers programs in B2B
 
Model assure media pembelajaran
Model assure media pembelajaranModel assure media pembelajaran
Model assure media pembelajaran
 
Using puppet, foreman and git to develop and operate a large scale internet s...
Using puppet, foreman and git to develop and operate a large scale internet s...Using puppet, foreman and git to develop and operate a large scale internet s...
Using puppet, foreman and git to develop and operate a large scale internet s...
 
Managing service projects in a B2B environment
Managing service projects in a B2B environmentManaging service projects in a B2B environment
Managing service projects in a B2B environment
 
Post Usage ROI?
Post Usage ROI?Post Usage ROI?
Post Usage ROI?
 

Ähnlich wie Cassandra data access

Composable Parallel Processing in Apache Spark and Weld
Composable Parallel Processing in Apache Spark and WeldComposable Parallel Processing in Apache Spark and Weld
Composable Parallel Processing in Apache Spark and WeldDatabricks
 
Big data distributed processing: Spark introduction
Big data distributed processing: Spark introductionBig data distributed processing: Spark introduction
Big data distributed processing: Spark introductionHektor Jacynycz García
 
Cassandra meetup slides - Oct 15 Santa Monica Coloft
Cassandra meetup slides - Oct 15 Santa Monica ColoftCassandra meetup slides - Oct 15 Santa Monica Coloft
Cassandra meetup slides - Oct 15 Santa Monica ColoftJon Haddad
 
MongoDB Versatility: Scaling the MapMyFitness Platform
MongoDB Versatility: Scaling the MapMyFitness PlatformMongoDB Versatility: Scaling the MapMyFitness Platform
MongoDB Versatility: Scaling the MapMyFitness PlatformMongoDB
 
GraphFrames: DataFrame-based graphs for Apache® Spark™
GraphFrames: DataFrame-based graphs for Apache® Spark™GraphFrames: DataFrame-based graphs for Apache® Spark™
GraphFrames: DataFrame-based graphs for Apache® Spark™Databricks
 
BISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesBISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesSrinath Perera
 
Architectures, Frameworks and Infrastructure
Architectures, Frameworks and InfrastructureArchitectures, Frameworks and Infrastructure
Architectures, Frameworks and Infrastructureharendra_pathak
 
Shift: Real World Migration from MongoDB to Cassandra
Shift: Real World Migration from MongoDB to CassandraShift: Real World Migration from MongoDB to Cassandra
Shift: Real World Migration from MongoDB to CassandraDataStax
 
Summer 2017 undergraduate research powerpoint
Summer 2017 undergraduate research powerpointSummer 2017 undergraduate research powerpoint
Summer 2017 undergraduate research powerpointChristopher Dubois
 
MongoDB 4.0 새로운 기능 소개
MongoDB 4.0 새로운 기능 소개MongoDB 4.0 새로운 기능 소개
MongoDB 4.0 새로운 기능 소개Ha-Yang(White) Moon
 
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...JPoint'15 Mom, I so wish Hibernate for my NoSQL database...
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...Alexey Zinoviev
 
Kafka Streams - From the Ground Up to the Cloud
Kafka Streams - From the Ground Up to the CloudKafka Streams - From the Ground Up to the Cloud
Kafka Streams - From the Ground Up to the CloudVMware Tanzu
 
Apache Spark 101 - Demi Ben-Ari
Apache Spark 101 - Demi Ben-AriApache Spark 101 - Demi Ben-Ari
Apache Spark 101 - Demi Ben-AriDemi Ben-Ari
 
Spring data presentation
Spring data presentationSpring data presentation
Spring data presentationOleksii Usyk
 
AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned Omid Vahdaty
 
Introduction to TitanDB
Introduction to TitanDB Introduction to TitanDB
Introduction to TitanDB Knoldus Inc.
 
Otimizações de Projetos de Big Data, Dw e AI no Microsoft Azure
Otimizações de Projetos de Big Data, Dw e AI no Microsoft AzureOtimizações de Projetos de Big Data, Dw e AI no Microsoft Azure
Otimizações de Projetos de Big Data, Dw e AI no Microsoft AzureLuan Moreno Medeiros Maciel
 
PostgreSQL - Object Relational Database
PostgreSQL - Object Relational DatabasePostgreSQL - Object Relational Database
PostgreSQL - Object Relational DatabaseMubashar Iqbal
 

Ähnlich wie Cassandra data access (20)

Composable Parallel Processing in Apache Spark and Weld
Composable Parallel Processing in Apache Spark and WeldComposable Parallel Processing in Apache Spark and Weld
Composable Parallel Processing in Apache Spark and Weld
 
Big data distributed processing: Spark introduction
Big data distributed processing: Spark introductionBig data distributed processing: Spark introduction
Big data distributed processing: Spark introduction
 
Cassandra meetup slides - Oct 15 Santa Monica Coloft
Cassandra meetup slides - Oct 15 Santa Monica ColoftCassandra meetup slides - Oct 15 Santa Monica Coloft
Cassandra meetup slides - Oct 15 Santa Monica Coloft
 
MongoDB Versatility: Scaling the MapMyFitness Platform
MongoDB Versatility: Scaling the MapMyFitness PlatformMongoDB Versatility: Scaling the MapMyFitness Platform
MongoDB Versatility: Scaling the MapMyFitness Platform
 
GraphFrames: DataFrame-based graphs for Apache® Spark™
GraphFrames: DataFrame-based graphs for Apache® Spark™GraphFrames: DataFrame-based graphs for Apache® Spark™
GraphFrames: DataFrame-based graphs for Apache® Spark™
 
BISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesBISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple Spaces
 
Architectures, Frameworks and Infrastructure
Architectures, Frameworks and InfrastructureArchitectures, Frameworks and Infrastructure
Architectures, Frameworks and Infrastructure
 
Shift: Real World Migration from MongoDB to Cassandra
Shift: Real World Migration from MongoDB to CassandraShift: Real World Migration from MongoDB to Cassandra
Shift: Real World Migration from MongoDB to Cassandra
 
Summer 2017 undergraduate research powerpoint
Summer 2017 undergraduate research powerpointSummer 2017 undergraduate research powerpoint
Summer 2017 undergraduate research powerpoint
 
MongoDB 4.0 새로운 기능 소개
MongoDB 4.0 새로운 기능 소개MongoDB 4.0 새로운 기능 소개
MongoDB 4.0 새로운 기능 소개
 
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...JPoint'15 Mom, I so wish Hibernate for my NoSQL database...
JPoint'15 Mom, I so wish Hibernate for my NoSQL database...
 
Apache Spark on HDinsight Training
Apache Spark on HDinsight TrainingApache Spark on HDinsight Training
Apache Spark on HDinsight Training
 
Kafka Streams - From the Ground Up to the Cloud
Kafka Streams - From the Ground Up to the CloudKafka Streams - From the Ground Up to the Cloud
Kafka Streams - From the Ground Up to the Cloud
 
Apache Spark 101 - Demi Ben-Ari
Apache Spark 101 - Demi Ben-AriApache Spark 101 - Demi Ben-Ari
Apache Spark 101 - Demi Ben-Ari
 
Spark
SparkSpark
Spark
 
Spring data presentation
Spring data presentationSpring data presentation
Spring data presentation
 
AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned AWS Big Data Demystified #1: Big data architecture lessons learned
AWS Big Data Demystified #1: Big data architecture lessons learned
 
Introduction to TitanDB
Introduction to TitanDB Introduction to TitanDB
Introduction to TitanDB
 
Otimizações de Projetos de Big Data, Dw e AI no Microsoft Azure
Otimizações de Projetos de Big Data, Dw e AI no Microsoft AzureOtimizações de Projetos de Big Data, Dw e AI no Microsoft Azure
Otimizações de Projetos de Big Data, Dw e AI no Microsoft Azure
 
PostgreSQL - Object Relational Database
PostgreSQL - Object Relational DatabasePostgreSQL - Object Relational Database
PostgreSQL - Object Relational Database
 

Kürzlich hochgeladen

"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyAlfredo García Lavilla
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersRaghuram Pandurangan
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 

Kürzlich hochgeladen (20)

"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information Developers
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 

Cassandra data access

  • 2. eBuddy use of Cassandra
  • 3. XMS
  • 4. ● User Data Service ● User Discovery Service ● Persistent Session Store ● Message History ● Location-based Discovery Cassandra in eBuddy Messaging Platform
  • 5. ● Current size of data ● 1,4 TiB total (replication of 3x); 467 GiB actual data ● 12 million sessions (11 million users plus groups) ● Almost a billion rows in one column family (inverse social graph) Some Statistics
  • 6. Data Access - Overview
  • 7. Design Objectives ● Data Source Agnostic ● Testable ● Thread Safe ● Strong Typing ● Supports “transactions”, i.e. units of work in batch ● Efficient Mapping to Application Domain Model ● Follows Familiar Patterns (e.g. Spring JDBC Template)
  • 8. Data Access in Layers
  • 10. Writing ● Use Generic Typing ● Has Interface (for testability, etc.) ● Handles Exceptions
  • 12. Serializers ● Constructed with serializers that convert to types needed by data access layer
  • 15. Data Access Object ● Data Access Object (DAO) is singleton ● Transforms from data model to domain model ● Operations object configured with serializers to convert from data model to domain model ● Defines the mappers for read operations
  • 17. CQL3 DataStax: "We believe that CQL3 is a simpler and overall better API for Cassandra than the thrift API is. Therefore, new projects/applications are encouraged to use CQL3" At eBuddy, we are still using the Thrift API and the Java Hector library. We are currently looking at CQL3 and whether we want to use it going forward and whether we will "upgrade" existing code.
  • 18. Structured Data ● Object Mapping Frameworks ● Mapped vs. Embedded Objects ● Nested Properties ("path" access)
  • 19. Object Mapping Frameworks ● Simple mapper frameworks with (some) JPA support ● Hector Object Mapper ● Kundera ● Firebrand (not JPA) ● has most features, e.g supports both embedded and mapped object graphs https://github.com/impetus-opensource/Kundera http://github.com/hector-client/hector http://firebrandocm.org
  • 20. Hierarchical Properties ● Use DynamicComposites to model keys that have a variable number of components put(“accounts|msn|x.y.z|sign_in”, “0”); put(“accounts|msn|x.y.z|key”, “value”); get(“accounts”) --> retrieved as a map: {"accounts": { "msn": { "x.y.z": { "sign_in": "0", "key": "value" } } } } ● Use a slice query to retrieve properties using partial path: