#SummitNow
Super Size Your Search
6th November 2013
Piergiorgio Lucidi (Sourcesense)
Fran Alvarez (Zaizi)
#SummitNow#SummitNow
Piergiorgio Lucidi
• Open Source ECM Specialist at Sourcesense
• Alfresco Certified Trainer / Engineer
• Alfresco Wiki Gardener / Community Star
• Alfresco forum supporter
• Global Moderator of the italian forum
• Author and Technical Reviewer at Packt
• PMC Member and Mentor at ASF
• Project Leader in the JBoss Community
#SummitNow#SummitNow
Overview
How to build and manage your search
server:
1. Scenario
2. Introducing Apache ManifoldCF
3. Zaizi Integrated Search Solution
#SummitNow#SummitNow
Scenario
An overview about the typical complex
search architecture
#SummitNow#SummitNow
Scenario - Alfresco limitations
Alfresco supports these search engines:
• Apache Lucene (embedded)
• Apache Solr (provided by Alfresco)
• needs development if other repositories
must be involved
Every other approach must be implemented
(ScheduledActions, WebScripts, etc..)
#SummitNow#SummitNow
Scenario – Embedded
Simple Search Architecture
Alfresco is the only one repository involved in the
architecture using the embedded search engine:
• the repository must take care of indexes also
managing index transactions
Indexes
Alfresco
FrontEnd
applications
Apache Lucene
#SummitNow#SummitNow
Scenario – Embedded - Cluster
Embedded
Not easy to scale out with Lucene
1. every cluster must have its own search
indexes
2. The cluster must synchronize indexes
Indexes
Alfresco
Apache Lucene
Indexes
Alfresco
Apache Lucene
JGroups
#SummitNow#SummitNow
Scenario – Simple Architecture
Simple search architecture
Alfresco is the only one repository involved in the
architecture with an external search server
1. The search server can be used for publish
contents in the front end architecture
2. The repository will stay in the logic backend
Search Engine
Indexes
Alfresco FrontEnd
applications
#SummitNow#SummitNow
Scenario – Publish with search
A search engine can be used for:
• advanced management of search indexes
• scaling out
• executing complex search on contents
• publishing contents in the FE
architecture
#SummitNow#SummitNow
Scenario – Publish with search
Publish with search architecture
Alfresco is the only one repository involved in the
architecture with an external search server
1. The search server can be used for publishing
contents in the front end architecture (HTML)
2. The repository will stay in the logic backend
Search Engine
Indexes
Alfresco FrontEnd
applications
BackEnd FrontEnd
Lucene / Solr
Indexes
#SummitNow#SummitNow
Scenario – Simple Architecture
Simple Search Architecture
Alfresco is the only one repository involved in the
architecture with an external search server
1. The search server can be used for publish
contents in the front end architecture
2. The repository will stay in the logic backend
Search Engine
Indexes
Alfresco FrontEnd
applications
#SummitNow#SummitNow
Scenario – Complex
Architecture
1. Alfresco is only one of the platforms that
must be involved in your search
architecture
2. You don’t want to increase the
development effort
3. You want just something to configure 
#SummitNow#SummitNow
Scenario – Complex
Architecture
Architecture with different ECM systems
Alfresco is one of the content platforms that must
be involved in the indexing process
Alfresco
Search Engine
Indexes
SharePoint
FileNet
CMIS
JIRA
Google Drive
DropBox
#SummitNow#SummitNow
Scenario – Complex
Architecture
Architecture with different ECM systems
Alfresco is one of the content platforms that must
be involved in the indexing process
Alfresco
Search Engine
Indexes
SharePoint
FileNet
CMIS
JIRA
Google Drive
DropBox
#SummitNow#SummitNow
Scenario – Complex
Architecture
Architecture with different ECM systems
Alfresco is one of the content platforms that must
be involved in the indexing process
Alfresco
Search Engine
Indexes
SharePoint
FileNet
CMIS
JIRA
Google Drive
DropBox
#SummitNow#SummitNow
Introducing Apache ManifoldCF
#SummitNow#SummitNow
Apache ManifoldCF - History
ManifoldCF code base was granted by MetaCarta to the
Apache Software Foundation in December 2009.
The MetaCarta effort represented more than five years of
successful development and testing in multiple, challenging
enterprise environments.
The project was graduated as Apache Top Level
Project in July 2012.
#SummitNow#SummitNow
Apache ManifoldCF – What is?
Open Source crawler
• crawling model (add, change, delete)
• schedule jobs to create indexes
• get contents from repositories
• push contents on search servers
#SummitNow#SummitNow
Apache ManifoldCF – What is?
Repository 1
Repository 3
Repository 4
Repository 2
Apache ManifoldCF
Search Server 1
Search Server 2
Search Server 3
Search Server 4
#SummitNow#SummitNow
Apache ManifoldCF – What is?
Out-Of-The-Box it is distributed as a webapp
• REST API
• Authority Service
• ACL indexes
• Crawler UI
can be embedded in any Java application
#SummitNow#SummitNow
Apache ManifoldCF – Why?
• Reliability
• Incremental
• Flexible
• Multi repositories
• Security model
• Monitoring
#SummitNow#SummitNow
ManifoldCF – Why? - Reliability
Jobs scheduling and configuration are stored in the
database to maintain the state of all the executions
Repository 1
Repository 3
Repository 4
Repository 2
Apache ManifoldCF
Search Server 1
Search Server 2
Search Server 3
Search Server 4
Pull Agent Daemon
Database
#SummitNow#SummitNow
ManifoldCF – Why? -
Incremental
get content changesets obtained from the repository API
Repository 1 Apache ManifoldCF
Pull Agent Daemon
Database
query
Complete
Changesets
#SummitNow#SummitNow
ManifoldCF – Why? - Flexible
If the repository can't supply all the changes Manifold can
discover them through crawling
Apache ManifoldCF
Pull Agent Daemon
Database
query
Incomplete
Changesets
Change Discovery
N N
#SummitNow#SummitNow
ManifoldCF – Why? – Multi repo
Jobs can retrieve contents
from the following
repositories:
• Google Drive
• Dropbox
• HDFS
• CMIS-compliant
• Alfresco
• IBM FileNet
• EMC Documentum
• Microsoft SharePoint
• OpenText LiveLink
• Autonomy Meridio
• Memex Patriarch
• Windows Share/DFS
• Generic JDBC
• Generic Filesystem
• Generic RSS and Web
#SummitNow#SummitNow
ManifoldCF – Why? – Multi repo
Jobs can ingest contents to
the following search servers:
• Apache Solr
• ElasticSearch
• OpenSearchServer
• MetaCarta GTS
#SummitNow#SummitNow
ManifoldCF – Why? - Security
Retrieve per-content ACLs
Repository 1
Repository 3
Repository 4
Repository 2
Apache ManifoldCF
Search Server 1
Search Server 2
Search Server 3
Search Server 4
Authority Service
Authority 1
Authority 2
access
tokens
#SummitNow#SummitNow
ManifoldCF – Why? - Security
Retrieve per-content ACLs
Repository 1
Repository 3
Repository 4
Repository 2
Apache ManifoldCF
Search Server 1
Search Server 2
Search Server 3
Search Server 4
Authority Service
Authority 1
Authority 2
user access tokens
user specific
search results
#SummitNow#SummitNow
ManifoldCF – Why? –
MonitoringUI Crawler allows you to:
• configure jobs and connectors
• monitor jobs execution
• monitor contents ingestion
• status reports
• document status
• queue status
• history reports
• simple history
• maximum activity
• maximum bandwidth
• result histogram
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector Output Connector
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector Output Connector
Authority Connector
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector
query to retrieve
contents
Output Connector
Authority Connector
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector
query to retrieve
contents
Output Connector
metadata mapping
content ingestion
Authority Connector
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector
query to retrieve
contents
Output Connector
metadata mapping
content ingestion
Authority Connector
retrieve content
ACEs
#SummitNow#SummitNow
ManifoldCF – Architecture
Repository Job Search Server
ACLs
Repository Connector
query to retrieve
contents
Output Connector
metadata mapping
content ingestion
Authority Connector
retrieve content
ACEs
• verbal
description
• crawling model
• scheduling
#SummitNow#SummitNow
Who is using ManifoldCF?
#SummitNow#SummitNow
ManifoldCF - Resources
The project is available at
http://manifoldcf.apache.org/
From this website you can access to
the mailing lists, documentation and
download links for binaries and
source.
#SummitNow#SummitNow
ManifoldCF – Resources - Book
ManifoldCF in Action
by Karl Wright
published by Manning
Karl is the original developer and the
principal committer of Apache
ManifoldCF
The book is available at
http://www.manning.com/wright
#SummitNow#SummitNow
Zaizi Integrated Search Solution
#SummitNow#SummitNow
Fran Alvarez
• Director of Zaizi Iberia and Lead Architect
• Alfresco Certified Engineer
• Responsible of large Alfresco
architectures
• Semantic Consultant for Sensefy
• Alfresco Meetups Organizer
#SummitNow#SummitNow
Alfresco + Solr Approach
Quite a good architecture
• Performance issues are solved
• Different architectures depending on business requirements
However…
• It does not cover some use cases or scenarios
• It does not leverage Cloud benefits or latest technologies
• With huge data volume there are other approaches
How can we solve limitations and enhance benefits?
#SummitNow#SummitNow
Alfresco + Solr Approach
• Decouples Search solution from Alfresco
• Allow to implement different Search solutions
• Allow to change Search solution without changing anything in Alfresco
• Not even a property!
• Provides an API to integrate it with Alfresco as search engine
• Even other repository vendors! E.g. Filesystem, Sharepoint,
Documentum, Filenet, Drupal…
• And preserve security permissions in the results
• Alfresco permissions are indexed and used during search
It’s included in our Semantic solution: Sensefy!
#SummitNow#SummitNow
What we’ve done in Manifold
Repository Connector:
• Alfresco Repository Connector: New implementation
• Removing dependency with Alfresco Solr API
Output connectors:
• Cloud Search Output Connector: Design & Development
• Elastic Search Output Connector: Improvements
• Solr Cloud Output Connector: Configuration for Alfresco
Authority Connector
• Alfresco Authority Connector: Design & Development
• Similar approach to Alfresco Solr
• Acl reads for Users and Groups in Alfresco
#SummitNow#SummitNow
Scenarios
Let’s see some examples
#SummitNow#SummitNow
I: Several Alfresco instances
Current Approach:
• Each Alfresco has its own Search
subsystem
• They can’t share indexes
Implications:
• Federated search is not an option
• Results can’t be merged
• If so, what resultset should be
first?
Conclusion
Results could be presented to users in
different tabs or “manually” merged.
Not the best approach
#SummitNow#SummitNow
I: Several Alfresco instances
Zaizi Approach:
• Our solution like search box
• Which manages a single index
Implications:
• All documents are driven to same
index
• Users can select results from either all
Alfresco instances or a subset
Conclusion
Search across Repositories
Could be based Elastic Search, Solr
Cloud, Amazon Cloud, etc.
#SummitNow#SummitNow
II: Alfresco + Other data providers
Current Approach:
• Alfresco has its own Search
subsystem
• Other repository may have (or not) its
own Search subsystem
Implications:
• Different data providers mean different
formats
• E.g. Filesystem does not support
CMIS
• Alfresco can’t reach external data
Conclusion
No way to merge results and present
them uniformly to end users
#SummitNow#SummitNow
II: Alfresco + Other data providers
Zaizi Approach:
• Both Alfresco and other repositories
share Search subsystem (Manifold)
Implications:
• Alfresco and other providers results
will have same format in our Solution
• They will speak ‘our’ language
• Alfresco reaches external data when
communicating with our solution
Conclusion
Results are present and accessible between
data providers
#SummitNow#SummitNow
III: Alfresco + O(TB) data
Current Approach:
• Alfresco has its own Search
subsystem
• All data is in one (or several if cluster)
Solr instance
Implications:
• Every Solr node manages the whole
index
• No chance to apply scale techniques
for indexing:
• Sharding, Replication…
Conclusion
Huge servers are required and
performance might be compromised
#SummitNow#SummitNow
III: Alfresco + O(TB) data
Zaizi Approach:
• Alfresco uses our solution
• Data is indexed in search solution which
better suits:
• Amazon Cloud, Solr Cloud, Elastic
Search…
Implications:
• Cloud Search solution manages index
• Indexing techniques can be applied
according to use cases
• Sharding, Replication
Conclusion
Search strategy can be adopted and easily
implemented with search solution which
better fits
#SummitNow#SummitNow
Apache Manifold: Other benefits
Can extract, index and map information from any other
sources
• Apache Stanbol, RedLink, any other data enricher
• Our solution will gather everything in one place
• Documents, entities…
Permissions are checked just once
• Everything is in the same place, even user authorization
capabilities
• Performance and scalability is improved
• Faceted search and other search capabilities are combined
with such permission feature
#SummitNow#SummitNow
Demo
#SummitNow#SummitNow
Conclusions
Zaizi solution allows searching and indexing in the most popular Cloud
Search solutions
• Other Search solutions can be integrated as well
Zaizi solution allows retrieving information from the most popular
repositories
• Other Data providers can be integrated too
• It solves plenty of current issues related search and indexing in
Alfresco
• Can be used outside Alfresco or even with Alfresco and any other
data repository
Zaizi solution manages permissions and security from the most popular
repositories and the latest Cloud search technologies
Fully supported by us!
#SummitNow#SummitNow
Conclusions
#SummitNow#SummitNow
What’s coming
Powerful User Interface
• Admin functions
• Wide range of facets
• UI for Share
Benchmarking
New connectors
• Filesystem authority
• RedLink repository
• Stanbol repository
Alfresco Search
Subsystem?
#SummitNow

Super Size Your Search

  • 1.
    #SummitNow Super Size YourSearch 6th November 2013 Piergiorgio Lucidi (Sourcesense) Fran Alvarez (Zaizi)
  • 2.
    #SummitNow#SummitNow Piergiorgio Lucidi • OpenSource ECM Specialist at Sourcesense • Alfresco Certified Trainer / Engineer • Alfresco Wiki Gardener / Community Star • Alfresco forum supporter • Global Moderator of the italian forum • Author and Technical Reviewer at Packt • PMC Member and Mentor at ASF • Project Leader in the JBoss Community
  • 3.
    #SummitNow#SummitNow Overview How to buildand manage your search server: 1. Scenario 2. Introducing Apache ManifoldCF 3. Zaizi Integrated Search Solution
  • 4.
    #SummitNow#SummitNow Scenario An overview aboutthe typical complex search architecture
  • 5.
    #SummitNow#SummitNow Scenario - Alfrescolimitations Alfresco supports these search engines: • Apache Lucene (embedded) • Apache Solr (provided by Alfresco) • needs development if other repositories must be involved Every other approach must be implemented (ScheduledActions, WebScripts, etc..)
  • 6.
    #SummitNow#SummitNow Scenario – Embedded SimpleSearch Architecture Alfresco is the only one repository involved in the architecture using the embedded search engine: • the repository must take care of indexes also managing index transactions Indexes Alfresco FrontEnd applications Apache Lucene
  • 7.
    #SummitNow#SummitNow Scenario – Embedded- Cluster Embedded Not easy to scale out with Lucene 1. every cluster must have its own search indexes 2. The cluster must synchronize indexes Indexes Alfresco Apache Lucene Indexes Alfresco Apache Lucene JGroups
  • 8.
    #SummitNow#SummitNow Scenario – SimpleArchitecture Simple search architecture Alfresco is the only one repository involved in the architecture with an external search server 1. The search server can be used for publish contents in the front end architecture 2. The repository will stay in the logic backend Search Engine Indexes Alfresco FrontEnd applications
  • 9.
    #SummitNow#SummitNow Scenario – Publishwith search A search engine can be used for: • advanced management of search indexes • scaling out • executing complex search on contents • publishing contents in the FE architecture
  • 10.
    #SummitNow#SummitNow Scenario – Publishwith search Publish with search architecture Alfresco is the only one repository involved in the architecture with an external search server 1. The search server can be used for publishing contents in the front end architecture (HTML) 2. The repository will stay in the logic backend Search Engine Indexes Alfresco FrontEnd applications BackEnd FrontEnd Lucene / Solr Indexes
  • 11.
    #SummitNow#SummitNow Scenario – SimpleArchitecture Simple Search Architecture Alfresco is the only one repository involved in the architecture with an external search server 1. The search server can be used for publish contents in the front end architecture 2. The repository will stay in the logic backend Search Engine Indexes Alfresco FrontEnd applications
  • 12.
    #SummitNow#SummitNow Scenario – Complex Architecture 1.Alfresco is only one of the platforms that must be involved in your search architecture 2. You don’t want to increase the development effort 3. You want just something to configure 
  • 13.
    #SummitNow#SummitNow Scenario – Complex Architecture Architecturewith different ECM systems Alfresco is one of the content platforms that must be involved in the indexing process Alfresco Search Engine Indexes SharePoint FileNet CMIS JIRA Google Drive DropBox
  • 14.
    #SummitNow#SummitNow Scenario – Complex Architecture Architecturewith different ECM systems Alfresco is one of the content platforms that must be involved in the indexing process Alfresco Search Engine Indexes SharePoint FileNet CMIS JIRA Google Drive DropBox
  • 15.
    #SummitNow#SummitNow Scenario – Complex Architecture Architecturewith different ECM systems Alfresco is one of the content platforms that must be involved in the indexing process Alfresco Search Engine Indexes SharePoint FileNet CMIS JIRA Google Drive DropBox
  • 16.
  • 17.
    #SummitNow#SummitNow Apache ManifoldCF -History ManifoldCF code base was granted by MetaCarta to the Apache Software Foundation in December 2009. The MetaCarta effort represented more than five years of successful development and testing in multiple, challenging enterprise environments. The project was graduated as Apache Top Level Project in July 2012.
  • 18.
    #SummitNow#SummitNow Apache ManifoldCF –What is? Open Source crawler • crawling model (add, change, delete) • schedule jobs to create indexes • get contents from repositories • push contents on search servers
  • 19.
    #SummitNow#SummitNow Apache ManifoldCF –What is? Repository 1 Repository 3 Repository 4 Repository 2 Apache ManifoldCF Search Server 1 Search Server 2 Search Server 3 Search Server 4
  • 20.
    #SummitNow#SummitNow Apache ManifoldCF –What is? Out-Of-The-Box it is distributed as a webapp • REST API • Authority Service • ACL indexes • Crawler UI can be embedded in any Java application
  • 21.
    #SummitNow#SummitNow Apache ManifoldCF –Why? • Reliability • Incremental • Flexible • Multi repositories • Security model • Monitoring
  • 22.
    #SummitNow#SummitNow ManifoldCF – Why?- Reliability Jobs scheduling and configuration are stored in the database to maintain the state of all the executions Repository 1 Repository 3 Repository 4 Repository 2 Apache ManifoldCF Search Server 1 Search Server 2 Search Server 3 Search Server 4 Pull Agent Daemon Database
  • 23.
    #SummitNow#SummitNow ManifoldCF – Why?- Incremental get content changesets obtained from the repository API Repository 1 Apache ManifoldCF Pull Agent Daemon Database query Complete Changesets
  • 24.
    #SummitNow#SummitNow ManifoldCF – Why?- Flexible If the repository can't supply all the changes Manifold can discover them through crawling Apache ManifoldCF Pull Agent Daemon Database query Incomplete Changesets Change Discovery N N
  • 25.
    #SummitNow#SummitNow ManifoldCF – Why?– Multi repo Jobs can retrieve contents from the following repositories: • Google Drive • Dropbox • HDFS • CMIS-compliant • Alfresco • IBM FileNet • EMC Documentum • Microsoft SharePoint • OpenText LiveLink • Autonomy Meridio • Memex Patriarch • Windows Share/DFS • Generic JDBC • Generic Filesystem • Generic RSS and Web
  • 26.
    #SummitNow#SummitNow ManifoldCF – Why?– Multi repo Jobs can ingest contents to the following search servers: • Apache Solr • ElasticSearch • OpenSearchServer • MetaCarta GTS
  • 27.
    #SummitNow#SummitNow ManifoldCF – Why?- Security Retrieve per-content ACLs Repository 1 Repository 3 Repository 4 Repository 2 Apache ManifoldCF Search Server 1 Search Server 2 Search Server 3 Search Server 4 Authority Service Authority 1 Authority 2 access tokens
  • 28.
    #SummitNow#SummitNow ManifoldCF – Why?- Security Retrieve per-content ACLs Repository 1 Repository 3 Repository 4 Repository 2 Apache ManifoldCF Search Server 1 Search Server 2 Search Server 3 Search Server 4 Authority Service Authority 1 Authority 2 user access tokens user specific search results
  • 29.
    #SummitNow#SummitNow ManifoldCF – Why?– MonitoringUI Crawler allows you to: • configure jobs and connectors • monitor jobs execution • monitor contents ingestion • status reports • document status • queue status • history reports • simple history • maximum activity • maximum bandwidth • result histogram
  • 30.
  • 31.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector
  • 32.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector Output Connector
  • 33.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector Output Connector Authority Connector
  • 34.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector query to retrieve contents Output Connector Authority Connector
  • 35.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector query to retrieve contents Output Connector metadata mapping content ingestion Authority Connector
  • 36.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector query to retrieve contents Output Connector metadata mapping content ingestion Authority Connector retrieve content ACEs
  • 37.
    #SummitNow#SummitNow ManifoldCF – Architecture RepositoryJob Search Server ACLs Repository Connector query to retrieve contents Output Connector metadata mapping content ingestion Authority Connector retrieve content ACEs • verbal description • crawling model • scheduling
  • 38.
  • 39.
    #SummitNow#SummitNow ManifoldCF - Resources Theproject is available at http://manifoldcf.apache.org/ From this website you can access to the mailing lists, documentation and download links for binaries and source.
  • 40.
    #SummitNow#SummitNow ManifoldCF – Resources- Book ManifoldCF in Action by Karl Wright published by Manning Karl is the original developer and the principal committer of Apache ManifoldCF The book is available at http://www.manning.com/wright
  • 41.
  • 42.
    #SummitNow#SummitNow Fran Alvarez • Directorof Zaizi Iberia and Lead Architect • Alfresco Certified Engineer • Responsible of large Alfresco architectures • Semantic Consultant for Sensefy • Alfresco Meetups Organizer
  • 43.
    #SummitNow#SummitNow Alfresco + SolrApproach Quite a good architecture • Performance issues are solved • Different architectures depending on business requirements However… • It does not cover some use cases or scenarios • It does not leverage Cloud benefits or latest technologies • With huge data volume there are other approaches How can we solve limitations and enhance benefits?
  • 44.
    #SummitNow#SummitNow Alfresco + SolrApproach • Decouples Search solution from Alfresco • Allow to implement different Search solutions • Allow to change Search solution without changing anything in Alfresco • Not even a property! • Provides an API to integrate it with Alfresco as search engine • Even other repository vendors! E.g. Filesystem, Sharepoint, Documentum, Filenet, Drupal… • And preserve security permissions in the results • Alfresco permissions are indexed and used during search It’s included in our Semantic solution: Sensefy!
  • 45.
    #SummitNow#SummitNow What we’ve donein Manifold Repository Connector: • Alfresco Repository Connector: New implementation • Removing dependency with Alfresco Solr API Output connectors: • Cloud Search Output Connector: Design & Development • Elastic Search Output Connector: Improvements • Solr Cloud Output Connector: Configuration for Alfresco Authority Connector • Alfresco Authority Connector: Design & Development • Similar approach to Alfresco Solr • Acl reads for Users and Groups in Alfresco
  • 46.
  • 47.
    #SummitNow#SummitNow I: Several Alfrescoinstances Current Approach: • Each Alfresco has its own Search subsystem • They can’t share indexes Implications: • Federated search is not an option • Results can’t be merged • If so, what resultset should be first? Conclusion Results could be presented to users in different tabs or “manually” merged. Not the best approach
  • 48.
    #SummitNow#SummitNow I: Several Alfrescoinstances Zaizi Approach: • Our solution like search box • Which manages a single index Implications: • All documents are driven to same index • Users can select results from either all Alfresco instances or a subset Conclusion Search across Repositories Could be based Elastic Search, Solr Cloud, Amazon Cloud, etc.
  • 49.
    #SummitNow#SummitNow II: Alfresco +Other data providers Current Approach: • Alfresco has its own Search subsystem • Other repository may have (or not) its own Search subsystem Implications: • Different data providers mean different formats • E.g. Filesystem does not support CMIS • Alfresco can’t reach external data Conclusion No way to merge results and present them uniformly to end users
  • 50.
    #SummitNow#SummitNow II: Alfresco +Other data providers Zaizi Approach: • Both Alfresco and other repositories share Search subsystem (Manifold) Implications: • Alfresco and other providers results will have same format in our Solution • They will speak ‘our’ language • Alfresco reaches external data when communicating with our solution Conclusion Results are present and accessible between data providers
  • 51.
    #SummitNow#SummitNow III: Alfresco +O(TB) data Current Approach: • Alfresco has its own Search subsystem • All data is in one (or several if cluster) Solr instance Implications: • Every Solr node manages the whole index • No chance to apply scale techniques for indexing: • Sharding, Replication… Conclusion Huge servers are required and performance might be compromised
  • 52.
    #SummitNow#SummitNow III: Alfresco +O(TB) data Zaizi Approach: • Alfresco uses our solution • Data is indexed in search solution which better suits: • Amazon Cloud, Solr Cloud, Elastic Search… Implications: • Cloud Search solution manages index • Indexing techniques can be applied according to use cases • Sharding, Replication Conclusion Search strategy can be adopted and easily implemented with search solution which better fits
  • 53.
    #SummitNow#SummitNow Apache Manifold: Otherbenefits Can extract, index and map information from any other sources • Apache Stanbol, RedLink, any other data enricher • Our solution will gather everything in one place • Documents, entities… Permissions are checked just once • Everything is in the same place, even user authorization capabilities • Performance and scalability is improved • Faceted search and other search capabilities are combined with such permission feature
  • 54.
  • 55.
    #SummitNow#SummitNow Conclusions Zaizi solution allowssearching and indexing in the most popular Cloud Search solutions • Other Search solutions can be integrated as well Zaizi solution allows retrieving information from the most popular repositories • Other Data providers can be integrated too • It solves plenty of current issues related search and indexing in Alfresco • Can be used outside Alfresco or even with Alfresco and any other data repository Zaizi solution manages permissions and security from the most popular repositories and the latest Cloud search technologies Fully supported by us!
  • 56.
  • 57.
    #SummitNow#SummitNow What’s coming Powerful UserInterface • Admin functions • Wide range of facets • UI for Share Benchmarking New connectors • Filesystem authority • RedLink repository • Stanbol repository Alfresco Search Subsystem?
  • 58.