SlideShare a Scribd company logo
1 of 46
Oak
the architecture of Apache Jackrabbit 3
Subsection Title
• Text
• Text
Resources
• http://jackrabbit.apache.org/oak/
• Docs
• http://jackrabbit.apache.org/oak/docs/
• Code
• https://svn.apache.org/repos/asf/jackrabbit/oak/trunk/
• https://github.com/apache/jackrabbit-oak
• Builds
• http://ci.apache.org/builders/oak-trunk/
• https://travis-ci.org/apache/jackrabbit-oak
Outline
• Tree model
• Updating the tree
• Refresh and garbage collection
• Concurrency and conflicts
• Interlude: Implementations
• Replicas and sharding
• Access control
• Comparing revisions
• Commit hooks
• Observers
• Search
• Big picture
Tree model
a d
b c
Paths as identifiers
/
/a
/a/b
/a/c
/d
a d
b c
Paths as identifiers
/
/a
/a/b
/a/c
/d
Updating the tree
?
r1 r2
HEAD
r1: /d r2: /d
r1: /a/c
r2: /a/c
Refresh and garbage collection
refresh
garbage
Concurrency and conflicts
r1 r2br2a
r1
r2b
r2a
r3
merge
Conflict handling strategies
a. Fully serialized commits
• fail on conflict, no concurrent updates
b. Partially serialized commits
• fail on conflict, concurrent conflict-free updates
c. Partial merge logic
• conflict markers, manual conflict resolution
d. Full merge logic
• conflicting changes may be lost
Interlude: implementations
MicroKernel/NodeStore
• Implementation of the tree/revision model
Responsible for
Clustering
Sharding
Caching
Conflict handling
etc.
Not responsible for
Type validation
Access control
Search
Versioning
etc.
Current implementations
DocumentMK TarMK (SegmentMK)
Persistence backends MongoDB, JDBC (WIP) Local FS (tar files)
Conflict handling Partial serialization Full serialization
Clustering MongoDB clustering Simple failover
Sharding MongoDB sharding N/A
Single-node performance Moderate High
Key use cases Large deployments (>1TB),
concurrent writes
Small/medium deployments,
mostly read
Replicas and sharding
master copy full replica cache
Replicas and caches
by path by level by hash
Sharding strategies
with caching
Access control
Accessible paths
/
/a/b
/d
Existentialism
• All (syntactically valid) paths can be traversed
• But the identified node might not exist
• For example:
root.getChildNode(“a”).exists() -> false
root.getChildNode(“a”).getChildNode(“b”).exists() -> true!
• Implemented as a decorator over the MK
Comparing revisions
What changed?
Content diff
• Tells what changed between two content trees
• Cornerstone of most higher-level functionality
• validation
• indexing
• observation
• etc.
r1
r2b
r2a
r3
Examples
r1 -> r3
“a” modified
“b” removed
“d” modified
“e” added
r1 -> r2a
“a” modified
“b” removed
r1 -> r2b
“d” modified
“e” added
Commit hooks
If this changed, commit this instead
Commit hooks
• Based on given before and after states, a hook can:
• fail the commit, or
• pass the commit unmodified, or
• pass the commit with modifications
• Key plugin mechanism in Oak
• All configured hooks are applied in sequence
• Used for much higher level functionality
• Often implemented using a content diff
Examples
• All kinds of validation
• node types, access control, references, etc.
• Trigger-like functionality
• autocreated content, default values, etc.
• In-content index updates
• etc.
Types of hooks
CommitHook Editor Validator
Content diff Optional Always Always
Can modify commit Yes Yes No
Programming
model
Simple Callbacks Callbacks
Performance
impact
High Medium Low
Observers
Observers
• Based on given before and after states, an observer can:
• observe what changed in the content tree
• Invoked after the commit, unlike commit hooks
• Always asynchronous for changes from other cluster
nodes
• Depending on backend, can be synchronous for
changes on the local cluster node
• Often implemented using a content diff
Examples
• JCR Observation
• External index updates
• Cache invalidation
• Logging
• etc.
Search
SELECT
WHERE x=y
/a//*
Parser
Parser
Parser
Index
Index
Index
Parser Index
Query engine
Query processing steps
1. Parsing
a. Select matching parser
b. Parse the query string
2. Execution
a. Estimate cost per index
b. Select index with the least cost estimate
c. Execute the query against the index
3. Post-processing
a. Filter results on access control and additional constraints
b. Apply sorting, grouping, faceting, etc.
Index implementations
• Property index
• Reference index
• Lucene index
• in-content
• local file system
• Solr index
• embedded
• external
Big picture
MicroKernel
Oak Core
Oak JCR
Oak API
NodeStore API
JCR API
Plugins
Questions?

More Related Content

What's hot

Introduction to Storm
Introduction to Storm Introduction to Storm
Introduction to Storm Chandler Huang
 
Clean architectures with fast api pycones
Clean architectures with fast api   pyconesClean architectures with fast api   pycones
Clean architectures with fast api pyconesAlvaro Del Castillo
 
Apache Jackrabbit Oak - Scale your content repository to the cloud
Apache Jackrabbit Oak - Scale your content repository to the cloudApache Jackrabbit Oak - Scale your content repository to the cloud
Apache Jackrabbit Oak - Scale your content repository to the cloudRobert Munteanu
 
Rest and Sling Resolution
Rest and Sling ResolutionRest and Sling Resolution
Rest and Sling ResolutionDEEPAK KHETAWAT
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcachedJurriaan Persyn
 
AEM Sightly Deep Dive
AEM Sightly Deep DiveAEM Sightly Deep Dive
AEM Sightly Deep DiveGabriel Walt
 
RocksDB detail
RocksDB detailRocksDB detail
RocksDB detailMIJIN AN
 
AEM Sightly Template Language
AEM Sightly Template LanguageAEM Sightly Template Language
AEM Sightly Template LanguageGabriel Walt
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDBMike Dirolf
 
An introduction to MongoDB
An introduction to MongoDBAn introduction to MongoDB
An introduction to MongoDBCésar Trigo
 
A simple introduction to redis
A simple introduction to redisA simple introduction to redis
A simple introduction to redisZhichao Liang
 
Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
 
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...confluent
 
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBase
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBaseHBaseCon 2015: Taming GC Pauses for Large Java Heap in HBase
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBaseHBaseCon
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to RedisArnab Mitra
 
MongoDB - Aggregation Pipeline
MongoDB - Aggregation PipelineMongoDB - Aggregation Pipeline
MongoDB - Aggregation PipelineJason Terpko
 

What's hot (20)

Introduction to Storm
Introduction to Storm Introduction to Storm
Introduction to Storm
 
Clean architectures with fast api pycones
Clean architectures with fast api   pyconesClean architectures with fast api   pycones
Clean architectures with fast api pycones
 
Apache Jackrabbit Oak - Scale your content repository to the cloud
Apache Jackrabbit Oak - Scale your content repository to the cloudApache Jackrabbit Oak - Scale your content repository to the cloud
Apache Jackrabbit Oak - Scale your content repository to the cloud
 
Rest and Sling Resolution
Rest and Sling ResolutionRest and Sling Resolution
Rest and Sling Resolution
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcached
 
AEM Sightly Deep Dive
AEM Sightly Deep DiveAEM Sightly Deep Dive
AEM Sightly Deep Dive
 
Amazon DynamoDB 키 디자인 패턴
Amazon DynamoDB 키 디자인 패턴Amazon DynamoDB 키 디자인 패턴
Amazon DynamoDB 키 디자인 패턴
 
RocksDB detail
RocksDB detailRocksDB detail
RocksDB detail
 
AEM Sightly Template Language
AEM Sightly Template LanguageAEM Sightly Template Language
AEM Sightly Template Language
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDB
 
An introduction to MongoDB
An introduction to MongoDBAn introduction to MongoDB
An introduction to MongoDB
 
A simple introduction to redis
A simple introduction to redisA simple introduction to redis
A simple introduction to redis
 
An introduction to MongoDB
An introduction to MongoDBAn introduction to MongoDB
An introduction to MongoDB
 
Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDB
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
 
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBase
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBaseHBaseCon 2015: Taming GC Pauses for Large Java Heap in HBase
HBaseCon 2015: Taming GC Pauses for Large Java Heap in HBase
 
Apache Spark Architecture
Apache Spark ArchitectureApache Spark Architecture
Apache Spark Architecture
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
MongoDB - Aggregation Pipeline
MongoDB - Aggregation PipelineMongoDB - Aggregation Pipeline
MongoDB - Aggregation Pipeline
 

Viewers also liked

The new repository in AEM 6
The new repository in AEM 6The new repository in AEM 6
The new repository in AEM 6Jukka Zitting
 
New Repository in AEM 6 by Michael Marth
New Repository in AEM 6 by Michael MarthNew Repository in AEM 6 by Michael Marth
New Repository in AEM 6 by Michael MarthAEM HUB
 
Apache development with GitHub and Travis CI
Apache development with GitHub and Travis CIApache development with GitHub and Travis CI
Apache development with GitHub and Travis CIJukka Zitting
 
JCR, Sling or AEM? Which API should I use and when?
JCR, Sling or AEM? Which API should I use and when?JCR, Sling or AEM? Which API should I use and when?
JCR, Sling or AEM? Which API should I use and when?connectwebex
 
Rapid JCR applications development with Sling
Rapid JCR applications development with SlingRapid JCR applications development with Sling
Rapid JCR applications development with SlingBertrand Delacretaz
 
3DCG(3Dコンピュータグラフィック)をWebGLで始めよう
3DCG(3Dコンピュータグラフィック)をWebGLで始めよう3DCG(3Dコンピュータグラフィック)をWebGLで始めよう
3DCG(3Dコンピュータグラフィック)をWebGLで始めようAdvancedTechNight
 
Into the TarPit: A TarMK Deep Dive
Into the TarPit: A TarMK Deep DiveInto the TarPit: A TarMK Deep Dive
Into the TarPit: A TarMK Deep DiveMichael Dürig
 
Hivemallで始める不動産価格推定サービス
Hivemallで始める不動産価格推定サービスHivemallで始める不動産価格推定サービス
Hivemallで始める不動産価格推定サービスKentaro Yoshida
 
Cloud Native Hadoop #cwt2016
Cloud Native Hadoop #cwt2016Cloud Native Hadoop #cwt2016
Cloud Native Hadoop #cwt2016Cloudera Japan
 
D3.jsと学ぶVisualization(可視化)の世界
D3.jsと学ぶVisualization(可視化)の世界D3.jsと学ぶVisualization(可視化)の世界
D3.jsと学ぶVisualization(可視化)の世界AdvancedTechNight
 
AEM Best Practices for Component Development
AEM Best Practices for Component DevelopmentAEM Best Practices for Component Development
AEM Best Practices for Component DevelopmentGabriel Walt
 
爆速クエリエンジン”Presto”を使いたくなる話
爆速クエリエンジン”Presto”を使いたくなる話爆速クエリエンジン”Presto”を使いたくなる話
爆速クエリエンジン”Presto”を使いたくなる話Kentaro Yoshida
 
大規模データに対するデータサイエンスの進め方 #CWT2016
大規模データに対するデータサイエンスの進め方 #CWT2016大規模データに対するデータサイエンスの進め方 #CWT2016
大規模データに対するデータサイエンスの進め方 #CWT2016Cloudera Japan
 
ちょっと理解に自信がないな という皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)
ちょっと理解に自信がないなという皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)ちょっと理解に自信がないなという皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)
ちょっと理解に自信がないな という皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)hamaken
 
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料)
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料) 40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料)
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料) hamaken
 
データ分析チームの振り返り
データ分析チームの振り返りデータ分析チームの振り返り
データ分析チームの振り返りSatoshi Noto
 
Amazon Machine Learning概要
Amazon Machine Learning概要Amazon Machine Learning概要
Amazon Machine Learning概要Satoshi Noto
 

Viewers also liked (19)

The new repository in AEM 6
The new repository in AEM 6The new repository in AEM 6
The new repository in AEM 6
 
New Repository in AEM 6 by Michael Marth
New Repository in AEM 6 by Michael MarthNew Repository in AEM 6 by Michael Marth
New Repository in AEM 6 by Michael Marth
 
Introduction to JCR
Introduction to JCR Introduction to JCR
Introduction to JCR
 
JCR In 10 Minutes
JCR In 10 MinutesJCR In 10 Minutes
JCR In 10 Minutes
 
Apache development with GitHub and Travis CI
Apache development with GitHub and Travis CIApache development with GitHub and Travis CI
Apache development with GitHub and Travis CI
 
JCR, Sling or AEM? Which API should I use and when?
JCR, Sling or AEM? Which API should I use and when?JCR, Sling or AEM? Which API should I use and when?
JCR, Sling or AEM? Which API should I use and when?
 
Rapid JCR applications development with Sling
Rapid JCR applications development with SlingRapid JCR applications development with Sling
Rapid JCR applications development with Sling
 
3DCG(3Dコンピュータグラフィック)をWebGLで始めよう
3DCG(3Dコンピュータグラフィック)をWebGLで始めよう3DCG(3Dコンピュータグラフィック)をWebGLで始めよう
3DCG(3Dコンピュータグラフィック)をWebGLで始めよう
 
Into the TarPit: A TarMK Deep Dive
Into the TarPit: A TarMK Deep DiveInto the TarPit: A TarMK Deep Dive
Into the TarPit: A TarMK Deep Dive
 
Hivemallで始める不動産価格推定サービス
Hivemallで始める不動産価格推定サービスHivemallで始める不動産価格推定サービス
Hivemallで始める不動産価格推定サービス
 
Cloud Native Hadoop #cwt2016
Cloud Native Hadoop #cwt2016Cloud Native Hadoop #cwt2016
Cloud Native Hadoop #cwt2016
 
D3.jsと学ぶVisualization(可視化)の世界
D3.jsと学ぶVisualization(可視化)の世界D3.jsと学ぶVisualization(可視化)の世界
D3.jsと学ぶVisualization(可視化)の世界
 
AEM Best Practices for Component Development
AEM Best Practices for Component DevelopmentAEM Best Practices for Component Development
AEM Best Practices for Component Development
 
爆速クエリエンジン”Presto”を使いたくなる話
爆速クエリエンジン”Presto”を使いたくなる話爆速クエリエンジン”Presto”を使いたくなる話
爆速クエリエンジン”Presto”を使いたくなる話
 
大規模データに対するデータサイエンスの進め方 #CWT2016
大規模データに対するデータサイエンスの進め方 #CWT2016大規模データに対するデータサイエンスの進め方 #CWT2016
大規模データに対するデータサイエンスの進め方 #CWT2016
 
ちょっと理解に自信がないな という皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)
ちょっと理解に自信がないなという皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)ちょっと理解に自信がないなという皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)
ちょっと理解に自信がないな という皆さまに贈るHadoop/Sparkのキホン (IBM Datapalooza Tokyo 2016講演資料)
 
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料)
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料) 40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料)
40分でわかるHadoop徹底入門 (Cloudera World Tokyo 2014 講演資料)
 
データ分析チームの振り返り
データ分析チームの振り返りデータ分析チームの振り返り
データ分析チームの振り返り
 
Amazon Machine Learning概要
Amazon Machine Learning概要Amazon Machine Learning概要
Amazon Machine Learning概要
 

Similar to Oak, the architecture of Apache Jackrabbit 3

Performance and Abstractions
Performance and AbstractionsPerformance and Abstractions
Performance and AbstractionsMetosin Oy
 
Play Framework and Activator
Play Framework and ActivatorPlay Framework and Activator
Play Framework and ActivatorKevin Webber
 
Rapid API Development ArangoDB Foxx
Rapid API Development ArangoDB FoxxRapid API Development ArangoDB Foxx
Rapid API Development ArangoDB FoxxMichael Hackstein
 
High Performance Systems in Go - GopherCon 2014
High Performance Systems in Go - GopherCon 2014High Performance Systems in Go - GopherCon 2014
High Performance Systems in Go - GopherCon 2014Derek Collison
 
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014Amazon Web Services
 
Plone for Education: Bibliographies
Plone for Education: BibliographiesPlone for Education: Bibliographies
Plone for Education: BibliographiesCristopher Ewing
 
Building & Testing Scalable Rails Applications
Building & Testing Scalable Rails ApplicationsBuilding & Testing Scalable Rails Applications
Building & Testing Scalable Rails Applicationsevilmike
 
Running & Monitoring Docker at Scale
Running & Monitoring Docker at ScaleRunning & Monitoring Docker at Scale
Running & Monitoring Docker at ScaleDatadog
 
Jasig rubyon rails
Jasig rubyon railsJasig rubyon rails
Jasig rubyon rails_zaMmer_
 
Jasig rubyon rails
Jasig rubyon railsJasig rubyon rails
Jasig rubyon rails_zaMmer_
 
A Tale of 2 Systems
A Tale of 2 SystemsA Tale of 2 Systems
A Tale of 2 SystemsDavid Newman
 
Managing Changes to the Database Across the Project Life Cycle (presented by ...
Managing Changes to the Database Across the Project Life Cycle (presented by ...Managing Changes to the Database Across the Project Life Cycle (presented by ...
Managing Changes to the Database Across the Project Life Cycle (presented by ...eZ Systems
 
Managing changes to eZPublish Database
Managing changes to eZPublish DatabaseManaging changes to eZPublish Database
Managing changes to eZPublish DatabaseGaetano Giunta
 
Version control with subversion
Version control with subversionVersion control with subversion
Version control with subversionxprayc
 
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...44CON
 
44 Slides About 22 Modules
44 Slides About 22 Modules44 Slides About 22 Modules
44 Slides About 22 Modulesheyrocker
 
Git.From thorns to the stars
Git.From thorns to the starsGit.From thorns to the stars
Git.From thorns to the starsStrannik_2013
 
Rapid development with Rails
Rapid development with RailsRapid development with Rails
Rapid development with RailsYi-Ting Cheng
 
Axe-matchers gem for automated accessibility testing
Axe-matchers gem for automated accessibility testing Axe-matchers gem for automated accessibility testing
Axe-matchers gem for automated accessibility testing Charlie Morris
 

Similar to Oak, the architecture of Apache Jackrabbit 3 (20)

Upgrading to rails3
Upgrading to rails3Upgrading to rails3
Upgrading to rails3
 
Performance and Abstractions
Performance and AbstractionsPerformance and Abstractions
Performance and Abstractions
 
Play Framework and Activator
Play Framework and ActivatorPlay Framework and Activator
Play Framework and Activator
 
Rapid API Development ArangoDB Foxx
Rapid API Development ArangoDB FoxxRapid API Development ArangoDB Foxx
Rapid API Development ArangoDB Foxx
 
High Performance Systems in Go - GopherCon 2014
High Performance Systems in Go - GopherCon 2014High Performance Systems in Go - GopherCon 2014
High Performance Systems in Go - GopherCon 2014
 
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014
(APP309) Running and Monitoring Docker Containers at Scale | AWS re:Invent 2014
 
Plone for Education: Bibliographies
Plone for Education: BibliographiesPlone for Education: Bibliographies
Plone for Education: Bibliographies
 
Building & Testing Scalable Rails Applications
Building & Testing Scalable Rails ApplicationsBuilding & Testing Scalable Rails Applications
Building & Testing Scalable Rails Applications
 
Running & Monitoring Docker at Scale
Running & Monitoring Docker at ScaleRunning & Monitoring Docker at Scale
Running & Monitoring Docker at Scale
 
Jasig rubyon rails
Jasig rubyon railsJasig rubyon rails
Jasig rubyon rails
 
Jasig rubyon rails
Jasig rubyon railsJasig rubyon rails
Jasig rubyon rails
 
A Tale of 2 Systems
A Tale of 2 SystemsA Tale of 2 Systems
A Tale of 2 Systems
 
Managing Changes to the Database Across the Project Life Cycle (presented by ...
Managing Changes to the Database Across the Project Life Cycle (presented by ...Managing Changes to the Database Across the Project Life Cycle (presented by ...
Managing Changes to the Database Across the Project Life Cycle (presented by ...
 
Managing changes to eZPublish Database
Managing changes to eZPublish DatabaseManaging changes to eZPublish Database
Managing changes to eZPublish Database
 
Version control with subversion
Version control with subversionVersion control with subversion
Version control with subversion
 
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...
44CON 2014 - Pentesting NoSQL DB's Using NoSQL Exploitation Framework, Franci...
 
44 Slides About 22 Modules
44 Slides About 22 Modules44 Slides About 22 Modules
44 Slides About 22 Modules
 
Git.From thorns to the stars
Git.From thorns to the starsGit.From thorns to the stars
Git.From thorns to the stars
 
Rapid development with Rails
Rapid development with RailsRapid development with Rails
Rapid development with Rails
 
Axe-matchers gem for automated accessibility testing
Axe-matchers gem for automated accessibility testing Axe-matchers gem for automated accessibility testing
Axe-matchers gem for automated accessibility testing
 

More from Jukka Zitting

MicroKernel & NodeStore
MicroKernel & NodeStoreMicroKernel & NodeStore
MicroKernel & NodeStoreJukka Zitting
 
Open source masterclass - Life in the Apache Incubator
Open source masterclass - Life in the Apache IncubatorOpen source masterclass - Life in the Apache Incubator
Open source masterclass - Life in the Apache IncubatorJukka Zitting
 
Content extraction with apache tika
Content extraction with apache tikaContent extraction with apache tika
Content extraction with apache tikaJukka Zitting
 
Apache Jackrabbit @ Swiss Open Source Awards 2011
Apache Jackrabbit @ Swiss Open Source Awards 2011Apache Jackrabbit @ Swiss Open Source Awards 2011
Apache Jackrabbit @ Swiss Open Source Awards 2011Jukka Zitting
 
OSGifying the repository
OSGifying the repositoryOSGifying the repository
OSGifying the repositoryJukka Zitting
 
Repository performance tuning
Repository performance tuningRepository performance tuning
Repository performance tuningJukka Zitting
 
The return of the hierarchical model
The return of the hierarchical modelThe return of the hierarchical model
The return of the hierarchical modelJukka Zitting
 
Text and metadata extraction with Apache Tika
Text and metadata extraction with Apache TikaText and metadata extraction with Apache Tika
Text and metadata extraction with Apache TikaJukka Zitting
 
Mime Magic With Apache Tika
Mime Magic With Apache TikaMime Magic With Apache Tika
Mime Magic With Apache TikaJukka Zitting
 
File System On Steroids
File System On SteroidsFile System On Steroids
File System On SteroidsJukka Zitting
 
Mime Magic With Apache Tika
Mime Magic With Apache TikaMime Magic With Apache Tika
Mime Magic With Apache TikaJukka Zitting
 
Design and architecture of Jackrabbit
Design and architecture of JackrabbitDesign and architecture of Jackrabbit
Design and architecture of JackrabbitJukka Zitting
 

More from Jukka Zitting (14)

MicroKernel & NodeStore
MicroKernel & NodeStoreMicroKernel & NodeStore
MicroKernel & NodeStore
 
Open source masterclass - Life in the Apache Incubator
Open source masterclass - Life in the Apache IncubatorOpen source masterclass - Life in the Apache Incubator
Open source masterclass - Life in the Apache Incubator
 
Content extraction with apache tika
Content extraction with apache tikaContent extraction with apache tika
Content extraction with apache tika
 
Apache Jackrabbit @ Swiss Open Source Awards 2011
Apache Jackrabbit @ Swiss Open Source Awards 2011Apache Jackrabbit @ Swiss Open Source Awards 2011
Apache Jackrabbit @ Swiss Open Source Awards 2011
 
OSGifying the repository
OSGifying the repositoryOSGifying the repository
OSGifying the repository
 
Repository performance tuning
Repository performance tuningRepository performance tuning
Repository performance tuning
 
The return of the hierarchical model
The return of the hierarchical modelThe return of the hierarchical model
The return of the hierarchical model
 
Text and metadata extraction with Apache Tika
Text and metadata extraction with Apache TikaText and metadata extraction with Apache Tika
Text and metadata extraction with Apache Tika
 
Mime Magic With Apache Tika
Mime Magic With Apache TikaMime Magic With Apache Tika
Mime Magic With Apache Tika
 
NoSQL Oakland
NoSQL OaklandNoSQL Oakland
NoSQL Oakland
 
File System On Steroids
File System On SteroidsFile System On Steroids
File System On Steroids
 
Mime Magic With Apache Tika
Mime Magic With Apache TikaMime Magic With Apache Tika
Mime Magic With Apache Tika
 
Design and architecture of Jackrabbit
Design and architecture of JackrabbitDesign and architecture of Jackrabbit
Design and architecture of Jackrabbit
 
Apache Tika
Apache TikaApache Tika
Apache Tika
 

Recently uploaded

Intelligent Home Wi-Fi Solutions | ThinkPalm
Intelligent Home Wi-Fi Solutions | ThinkPalmIntelligent Home Wi-Fi Solutions | ThinkPalm
Intelligent Home Wi-Fi Solutions | ThinkPalmSujith Sukumaran
 
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...OnePlan Solutions
 
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)jennyeacort
 
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024StefanoLambiase
 
英国UN学位证,北安普顿大学毕业证书1:1制作
英国UN学位证,北安普顿大学毕业证书1:1制作英国UN学位证,北安普顿大学毕业证书1:1制作
英国UN学位证,北安普顿大学毕业证书1:1制作qr0udbr0
 
Unveiling the Future: Sylius 2.0 New Features
Unveiling the Future: Sylius 2.0 New FeaturesUnveiling the Future: Sylius 2.0 New Features
Unveiling the Future: Sylius 2.0 New FeaturesŁukasz Chruściel
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideChristina Lin
 
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...Matt Ray
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...soniya singh
 
Recruitment Management Software Benefits (Infographic)
Recruitment Management Software Benefits (Infographic)Recruitment Management Software Benefits (Infographic)
Recruitment Management Software Benefits (Infographic)Hr365.us smith
 
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样umasea
 
What is Advanced Excel and what are some best practices for designing and cre...
What is Advanced Excel and what are some best practices for designing and cre...What is Advanced Excel and what are some best practices for designing and cre...
What is Advanced Excel and what are some best practices for designing and cre...Technogeeks
 
How to Track Employee Performance A Comprehensive Guide.pdf
How to Track Employee Performance A Comprehensive Guide.pdfHow to Track Employee Performance A Comprehensive Guide.pdf
How to Track Employee Performance A Comprehensive Guide.pdfLivetecs LLC
 
What is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWhat is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWave PLM
 
MYjobs Presentation Django-based project
MYjobs Presentation Django-based projectMYjobs Presentation Django-based project
MYjobs Presentation Django-based projectAnoyGreter
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio, Inc.
 
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte Germany
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte GermanySuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte Germany
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte GermanyChristoph Pohl
 
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsUnveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsAhmed Mohamed
 
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdf
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdfGOING AOT WITH GRAALVM – DEVOXX GREECE.pdf
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdfAlina Yurenko
 
Xen Safety Embedded OSS Summit April 2024 v4.pdf
Xen Safety Embedded OSS Summit April 2024 v4.pdfXen Safety Embedded OSS Summit April 2024 v4.pdf
Xen Safety Embedded OSS Summit April 2024 v4.pdfStefano Stabellini
 

Recently uploaded (20)

Intelligent Home Wi-Fi Solutions | ThinkPalm
Intelligent Home Wi-Fi Solutions | ThinkPalmIntelligent Home Wi-Fi Solutions | ThinkPalm
Intelligent Home Wi-Fi Solutions | ThinkPalm
 
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...
Maximizing Efficiency and Profitability with OnePlan’s Professional Service A...
 
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)
Call Us🔝>༒+91-9711147426⇛Call In girls karol bagh (Delhi)
 
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
 
英国UN学位证,北安普顿大学毕业证书1:1制作
英国UN学位证,北安普顿大学毕业证书1:1制作英国UN学位证,北安普顿大学毕业证书1:1制作
英国UN学位证,北安普顿大学毕业证书1:1制作
 
Unveiling the Future: Sylius 2.0 New Features
Unveiling the Future: Sylius 2.0 New FeaturesUnveiling the Future: Sylius 2.0 New Features
Unveiling the Future: Sylius 2.0 New Features
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
 
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...
Open Source Summit NA 2024: Open Source Cloud Costs - OpenCost's Impact on En...
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
 
Recruitment Management Software Benefits (Infographic)
Recruitment Management Software Benefits (Infographic)Recruitment Management Software Benefits (Infographic)
Recruitment Management Software Benefits (Infographic)
 
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样
办理学位证(UQ文凭证书)昆士兰大学毕业证成绩单原版一模一样
 
What is Advanced Excel and what are some best practices for designing and cre...
What is Advanced Excel and what are some best practices for designing and cre...What is Advanced Excel and what are some best practices for designing and cre...
What is Advanced Excel and what are some best practices for designing and cre...
 
How to Track Employee Performance A Comprehensive Guide.pdf
How to Track Employee Performance A Comprehensive Guide.pdfHow to Track Employee Performance A Comprehensive Guide.pdf
How to Track Employee Performance A Comprehensive Guide.pdf
 
What is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWhat is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need It
 
MYjobs Presentation Django-based project
MYjobs Presentation Django-based projectMYjobs Presentation Django-based project
MYjobs Presentation Django-based project
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
 
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte Germany
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte GermanySuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte Germany
SuccessFactors 1H 2024 Release - Sneak-Peek by Deloitte Germany
 
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsUnveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML Diagrams
 
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdf
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdfGOING AOT WITH GRAALVM – DEVOXX GREECE.pdf
GOING AOT WITH GRAALVM – DEVOXX GREECE.pdf
 
Xen Safety Embedded OSS Summit April 2024 v4.pdf
Xen Safety Embedded OSS Summit April 2024 v4.pdfXen Safety Embedded OSS Summit April 2024 v4.pdf
Xen Safety Embedded OSS Summit April 2024 v4.pdf
 

Oak, the architecture of Apache Jackrabbit 3