SlideShare uma empresa Scribd logo
1 de 26
Baixar para ler offline
(ATS4-PLAT05) Accelrys Catalog:
    A Search Index for AEP
                                       Ton van Daelen
          Sr. Director, Platform Product Management
                          ton.vandaelen@accelrys.com
The information on the roadmap and future software development efforts are
intended to outline general product direction and should not be relied on in making
a purchasing decision.
Outline

•   Search use cases
•   Deployment architecture
•   Solr search index
•   Search syntax
•   Administration
•   Demo
    – Pro client UI
    – Web UI
    – Admin UI
Accelrys Catalog Vision

                         Search from Pro Client                                                                         Administer
                         Examples that use the ‘Http Connector’ component                                            Generate index
                         PilotScript referencing ‘rsplit()’                                                        Update frequency
   Pro Client –
 Pers Productivity
                         Protocols using MAO data




                                                                                           Admin
                                                                  Catalog
                                                                                            Search              Canned reports
                                                                                    Generate index                Security issues
                                                                                  Update frequency                   Bad design
                                                                                                             Bad documentation

                                                                Xml         log
                     Search from Web Port
                     Recent protocols
                     Popular protocols
                     Protocols searching ‘Corporate
   Web User          Database”
                                                                                                   Next steps:
                                                                                                   • Mail Users
                                                                                                   • Post report
The Size of the Challenge

• 10-100 Pro client users
• 50-1000 Web users
• 1-10 servers

• -> 5000+ protocols to be managed
Admin Use Cases …

• Bad design practices. Find protocols that:
   –   have shortcuts as copies
   –   have saved checkpoints
   –   store passwords
   –   have components that are owner access only
   –   don’t have top level parameters (Web Port)
   –   have component with absolute file paths


• Bad documentation practices. Find protocols that:
   – don’t have help text (or default help)
   – have components with missing captions
More Admin Use Cases

• General queries. Find protocols:
   – with components that are deprecated (ad hoc / report)
   – not run in n days
   – not changed in n days
   – by client type (pro client, web port, web service, Notebook,
     Isentris, …)
   – with components with GUID x
   – with SQL components with specific DSN
Introduction to Text Searching

• Unstructured or
  minimally-
  structured searches
   – Think “Google”
   – Keyword-based,
     non-relational; wide
     range of user input
   – Based on lookups
     using pre-built word
     (token) indexes
Introduction to Text Searching (cont’d)

• Strategies to make searches more effective
   – Stop word removal: and, the, by, for, of, …
   – Stemming: startedstart, clusterscluster, etc.
   – Synonym aliasing: oncology=cancer, MB=megabyte, etc.
     (supported but only minimally implemented; extensible)
   – Language-specific document and query processing (support for
     Asian languages)
Apache Solr

• Open source text search server
• Part of Apache Software
  Foundation
• Uses and extends Lucene Java
  search library
• Hosted by a web application
  server
• http://lucene.apache.org/solr/
Solr: Under the Hood…
• Schema
   – XML specification of document fields and their types
   – Specifies how fields are tokenized and processed for indexing
• Solr config file
   – XML specification of query and result set processing rules
   – E.g. field weights
• Optional auxiliary files
   – Stop words, synonyms, protected words (unstemmed)
• Host application container
   – For AEP this is Tomcat
Tokenization and Filtering
• Tokenization options in Solr
    –   Break on whitespace
    –   Break on all non-letter characters
    –   Break on case changes (for CamelCaseTokenization)
    –   Break on character set changes (alphanum/ideographic/katakana)
• Additional filters
    – Lowercase filter: converts all characters to lowercase
    – CJK bigram filter: outputs adjacent character pairs for Asian languages
    – Stem filter: applies stemming rules (many language-specific variants)
• Field indexing and query processing use same tokenization
    – Better search results may be obtained by using slightly different analysis for indexing
      versus querying
• See http://wiki.apache.org/solr/AnalyzersTokenizersTokenFilters
Customizing Solr
Mapping XMLDB to Solr Documents
• XML Database = Component/Protocol Database
• For each item in XMLDB, an indexing protocol
   –   reads the item from the database
   –   creates data record properties corresponding to Solr fields
   –   joins in statistics from usage log
   –   converts the data record to a JSON “document”
   –   POSTs the document to Apache/Tomcat/Solr via HTTP
• Weighting
   – Protocol name and description have higher weight
   – Proximity has higher weight
Some Catalog Fields (defined in schema)

 •   name: protocol or component name
 •   path: location in XMLDB
 •   type: “component” or “protocol”
 •   parameters: names of parameters
 •   author: user who created protocol/component
 •   modifieddate: data protocol/component last changed
 •   runcount: number of times protocol has been run
 •   lastrun: date protocol was last run
 •   uses: list of components used by protocol
 •   alltext: composite field for keyword search
Administration

• Configure servers
• Specify update interval
• Manual rebuild
Configuring Accelrys Catalog

• Configuration (admin portal)
   – AEP servers to index
   – Indexing schedule
• Note
   –   Indexer runs as scheduled service
   –   Indexing takes ~1 to 3 minutes per 1000 XMLDB items
   –   Two index copies; users can continue search while index is rebuilt
   –   Tomcat and Solr automatically installed and launched with Apache
Limitations

• Usage info can be incorrect because log file doesn’t store
  full protocol path (“Protocol 1” !)
• No indexing at runtime – it can take a day before index is
  updated
Demo
Example Queries

• MAO type:"Component“
   – Any components referencing ‘MAO’
• uses:"Xml Reader" -author:Accelrys
   – Components/protocols that have an xml reader and are not
     authored by Accelrys
• lastrun:[*TO NOW-6MONTH]
   – Last run at least six months prior
• runcount:0
   – Never been run
Summary

• Accelrys Catalog is powerful search technology built into
  AEP
• Become a beta tester (beta-2)
• Plan for 9.0 upgrade now

• (ATS4-PLAT10) Planning your deployment for a 64 bit
  world

Mais conteúdo relacionado

Mais procurados

NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices SessionNZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
Michael Noel
 
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
Michael Noel
 
End-to-end Data Governance with Apache Avro and Atlas
End-to-end Data Governance with Apache Avro and AtlasEnd-to-end Data Governance with Apache Avro and Atlas
End-to-end Data Governance with Apache Avro and Atlas
DataWorks Summit
 
Google appenginejava.ppt
Google appenginejava.pptGoogle appenginejava.ppt
Google appenginejava.ppt
Young Alista
 
Motivation for multithreaded architectures
Motivation for multithreaded architecturesMotivation for multithreaded architectures
Motivation for multithreaded architectures
Young Alista
 
Using Oracle Database with Amazon Web Services
Using Oracle Database with Amazon Web ServicesUsing Oracle Database with Amazon Web Services
Using Oracle Database with Amazon Web Services
guest484c12
 

Mais procurados (20)

NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices SessionNZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
 
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
Sharing the Point South America 2013 (STPSA) - Ultimate SharePoint Infrastruc...
 
(ATS6-PLAT09) Deploying Applications on load balanced AEP servers for high av...
(ATS6-PLAT09) Deploying Applications on load balanced AEP servers for high av...(ATS6-PLAT09) Deploying Applications on load balanced AEP servers for high av...
(ATS6-PLAT09) Deploying Applications on load balanced AEP servers for high av...
 
SharePoint 2013 Performance Analysis - Robi Vončina
SharePoint 2013 Performance Analysis - Robi VončinaSharePoint 2013 Performance Analysis - Robi Vončina
SharePoint 2013 Performance Analysis - Robi Vončina
 
End-to-end Data Governance with Apache Avro and Atlas
End-to-end Data Governance with Apache Avro and AtlasEnd-to-end Data Governance with Apache Avro and Atlas
End-to-end Data Governance with Apache Avro and Atlas
 
SharePoint Saturday St. Louis 2014: What SharePoint Admins need to know about...
SharePoint Saturday St. Louis 2014: What SharePoint Admins need to know about...SharePoint Saturday St. Louis 2014: What SharePoint Admins need to know about...
SharePoint Saturday St. Louis 2014: What SharePoint Admins need to know about...
 
Google appenginejava.ppt
Google appenginejava.pptGoogle appenginejava.ppt
Google appenginejava.ppt
 
Cara v3 8 major new features
Cara v3 8 major new featuresCara v3 8 major new features
Cara v3 8 major new features
 
Valerii Moisieienko Apache hbase workshop
Valerii Moisieienko	Apache hbase workshopValerii Moisieienko	Apache hbase workshop
Valerii Moisieienko Apache hbase workshop
 
Timeline Service v.2 (Hadoop Summit 2016)
Timeline Service v.2 (Hadoop Summit 2016)Timeline Service v.2 (Hadoop Summit 2016)
Timeline Service v.2 (Hadoop Summit 2016)
 
Motivation for multithreaded architectures
Motivation for multithreaded architecturesMotivation for multithreaded architectures
Motivation for multithreaded architectures
 
Roman Ugolnikov Migrationа and sourcecontrol for your db
Roman Ugolnikov Migrationа and sourcecontrol for your dbRoman Ugolnikov Migrationа and sourcecontrol for your db
Roman Ugolnikov Migrationа and sourcecontrol for your db
 
Column encoding
Column encodingColumn encoding
Column encoding
 
Evolutionary database design
Evolutionary database designEvolutionary database design
Evolutionary database design
 
Using Oracle Database with Amazon Web Services
Using Oracle Database with Amazon Web ServicesUsing Oracle Database with Amazon Web Services
Using Oracle Database with Amazon Web Services
 
Apache Spark Streaming
Apache Spark StreamingApache Spark Streaming
Apache Spark Streaming
 
Timeline Service Next Gen (YARN-2928): YARN BOF @ Hadoop Summit 2015
Timeline Service Next Gen (YARN-2928): YARN BOF @ Hadoop Summit 2015Timeline Service Next Gen (YARN-2928): YARN BOF @ Hadoop Summit 2015
Timeline Service Next Gen (YARN-2928): YARN BOF @ Hadoop Summit 2015
 
Kent State University Libraries Develops a New System for Resource Selection
Kent State University Libraries Develops a New System for Resource SelectionKent State University Libraries Develops a New System for Resource Selection
Kent State University Libraries Develops a New System for Resource Selection
 
Antelope: A Web service for publishing Life Cycle Assessment models and resul...
Antelope: A Web service for publishing Life Cycle Assessment models and resul...Antelope: A Web service for publishing Life Cycle Assessment models and resul...
Antelope: A Web service for publishing Life Cycle Assessment models and resul...
 
Autoconfig r12
Autoconfig r12Autoconfig r12
Autoconfig r12
 

Destaque

(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
BIOVIA
 
Assessing Galaxy's ability to express scientific workflows in bioinformatics
Assessing Galaxy's ability to express scientific workflows in bioinformaticsAssessing Galaxy's ability to express scientific workflows in bioinformatics
Assessing Galaxy's ability to express scientific workflows in bioinformatics
Peter van Heusden
 

Destaque (8)

(ATS3-APP08) Top 10 things every Symyx Notebook by Accelrys Administrator sho...
(ATS3-APP08) Top 10 things every Symyx Notebook by Accelrys Administrator sho...(ATS3-APP08) Top 10 things every Symyx Notebook by Accelrys Administrator sho...
(ATS3-APP08) Top 10 things every Symyx Notebook by Accelrys Administrator sho...
 
(ATS6-APP08) ADQM Solution Deployment
(ATS6-APP08) ADQM Solution Deployment(ATS6-APP08) ADQM Solution Deployment
(ATS6-APP08) ADQM Solution Deployment
 
(ATS4-DEV02) Accelrys Query Service: Technology and Tools
(ATS4-DEV02) Accelrys Query Service: Technology and Tools(ATS4-DEV02) Accelrys Query Service: Technology and Tools
(ATS4-DEV02) Accelrys Query Service: Technology and Tools
 
(ATS4-DEV08) Building Widgets for the Symyx Notebook Home Page
(ATS4-DEV08) Building Widgets for the Symyx Notebook Home Page(ATS4-DEV08) Building Widgets for the Symyx Notebook Home Page
(ATS4-DEV08) Building Widgets for the Symyx Notebook Home Page
 
(ATS4-APP09)Tips and tricks for Managing Symyx Notebook Server Performance
(ATS4-APP09)Tips and tricks for Managing Symyx Notebook Server Performance(ATS4-APP09)Tips and tricks for Managing Symyx Notebook Server Performance
(ATS4-APP09)Tips and tricks for Managing Symyx Notebook Server Performance
 
(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
(ATS6-APP07) Configuration of Accelrys ELN to Clone to the Latest Template Ve...
 
Assessing Galaxy's ability to express scientific workflows in bioinformatics
Assessing Galaxy's ability to express scientific workflows in bioinformaticsAssessing Galaxy's ability to express scientific workflows in bioinformatics
Assessing Galaxy's ability to express scientific workflows in bioinformatics
 
(ATS3-PLAT06) Handling “Big Data” with Pipeline Pilot (MapReduce/NoSQL)
(ATS3-PLAT06) Handling “Big Data” with Pipeline Pilot (MapReduce/NoSQL)(ATS3-PLAT06) Handling “Big Data” with Pipeline Pilot (MapReduce/NoSQL)
(ATS3-PLAT06) Handling “Big Data” with Pipeline Pilot (MapReduce/NoSQL)
 

Semelhante a (ATS4-PLAT05) Accelrys Catalog: A Search Index for AEP

Architectures, Frameworks and Infrastructure
Architectures, Frameworks and InfrastructureArchitectures, Frameworks and Infrastructure
Architectures, Frameworks and Infrastructure
harendra_pathak
 
Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)
Petter Skodvin-Hvammen
 
(BDT317) Building A Data Lake On AWS
(BDT317) Building A Data Lake On AWS(BDT317) Building A Data Lake On AWS
(BDT317) Building A Data Lake On AWS
Amazon Web Services
 
OOW09 Ebs Tuning Final
OOW09 Ebs Tuning FinalOOW09 Ebs Tuning Final
OOW09 Ebs Tuning Final
jucaab
 
Share point 2010 performance and capacity planning best practices
Share point 2010 performance and capacity planning best practicesShare point 2010 performance and capacity planning best practices
Share point 2010 performance and capacity planning best practices
Eric Shupps
 
An architecture for federated data discovery and lineage over on-prem datasou...
An architecture for federated data discovery and lineage over on-prem datasou...An architecture for federated data discovery and lineage over on-prem datasou...
An architecture for federated data discovery and lineage over on-prem datasou...
DataWorks Summit
 

Semelhante a (ATS4-PLAT05) Accelrys Catalog: A Search Index for AEP (20)

Architectures, Frameworks and Infrastructure
Architectures, Frameworks and InfrastructureArchitectures, Frameworks and Infrastructure
Architectures, Frameworks and Infrastructure
 
(ATS3-DEV04) Introduction to Pipeline Pilot Protocol Development for Developers
(ATS3-DEV04) Introduction to Pipeline Pilot Protocol Development for Developers(ATS3-DEV04) Introduction to Pipeline Pilot Protocol Development for Developers
(ATS3-DEV04) Introduction to Pipeline Pilot Protocol Development for Developers
 
Microservices
MicroservicesMicroservices
Microservices
 
Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)
 
Summer training oracle
Summer training   oracle Summer training   oracle
Summer training oracle
 
(BDT317) Building A Data Lake On AWS
(BDT317) Building A Data Lake On AWS(BDT317) Building A Data Lake On AWS
(BDT317) Building A Data Lake On AWS
 
Service quality monitoring system architecture
Service quality monitoring system architectureService quality monitoring system architecture
Service quality monitoring system architecture
 
Summer training oracle
Summer training   oracle Summer training   oracle
Summer training oracle
 
IBM Cloud Day January 2021 Data Lake Deep Dive
IBM Cloud Day January 2021 Data Lake Deep DiveIBM Cloud Day January 2021 Data Lake Deep Dive
IBM Cloud Day January 2021 Data Lake Deep Dive
 
OOW09 Ebs Tuning Final
OOW09 Ebs Tuning FinalOOW09 Ebs Tuning Final
OOW09 Ebs Tuning Final
 
What's New in IBM Streams V4.1
What's New in IBM Streams V4.1What's New in IBM Streams V4.1
What's New in IBM Streams V4.1
 
Serverless spark
Serverless sparkServerless spark
Serverless spark
 
Technology behind-real-time-log-analytics
Technology behind-real-time-log-analytics Technology behind-real-time-log-analytics
Technology behind-real-time-log-analytics
 
Introduction to Apache Apex
Introduction to Apache ApexIntroduction to Apache Apex
Introduction to Apache Apex
 
VA Smalltalk Update
VA Smalltalk UpdateVA Smalltalk Update
VA Smalltalk Update
 
Share point 2010 performance and capacity planning best practices
Share point 2010 performance and capacity planning best practicesShare point 2010 performance and capacity planning best practices
Share point 2010 performance and capacity planning best practices
 
AWS March 2016 Webinar Series Building Your Data Lake on AWS
AWS March 2016 Webinar Series Building Your Data Lake on AWS AWS March 2016 Webinar Series Building Your Data Lake on AWS
AWS March 2016 Webinar Series Building Your Data Lake on AWS
 
Centralized Logging System Using ELK Stack
Centralized Logging System Using ELK StackCentralized Logging System Using ELK Stack
Centralized Logging System Using ELK Stack
 
Internals of Presto Service
Internals of Presto ServiceInternals of Presto Service
Internals of Presto Service
 
An architecture for federated data discovery and lineage over on-prem datasou...
An architecture for federated data discovery and lineage over on-prem datasou...An architecture for federated data discovery and lineage over on-prem datasou...
An architecture for federated data discovery and lineage over on-prem datasou...
 

Mais de BIOVIA

(ATS6-PLAT03) What's behind Discngine collections
(ATS6-PLAT03) What's behind Discngine collections(ATS6-PLAT03) What's behind Discngine collections
(ATS6-PLAT03) What's behind Discngine collections
BIOVIA
 
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
BIOVIA
 

Mais de BIOVIA (20)

ScienceCloud: Collaborative Workflows in Biologics R&D
ScienceCloud: Collaborative Workflows in Biologics R&DScienceCloud: Collaborative Workflows in Biologics R&D
ScienceCloud: Collaborative Workflows in Biologics R&D
 
(ATS6-PLAT03) What's behind Discngine collections
(ATS6-PLAT03) What's behind Discngine collections(ATS6-PLAT03) What's behind Discngine collections
(ATS6-PLAT03) What's behind Discngine collections
 
(ATS6-PLAT06) Maximizing AEP Performance
(ATS6-PLAT06) Maximizing AEP Performance(ATS6-PLAT06) Maximizing AEP Performance
(ATS6-PLAT06) Maximizing AEP Performance
 
(ATS6-PLAT05) Security enhancements in AEP 9
(ATS6-PLAT05) Security enhancements in AEP 9(ATS6-PLAT05) Security enhancements in AEP 9
(ATS6-PLAT05) Security enhancements in AEP 9
 
(ATS6-PLAT01) Chemistry Harmonization: Bringing together the Direct 9 and Pip...
(ATS6-PLAT01) Chemistry Harmonization: Bringing together the Direct 9 and Pip...(ATS6-PLAT01) Chemistry Harmonization: Bringing together the Direct 9 and Pip...
(ATS6-PLAT01) Chemistry Harmonization: Bringing together the Direct 9 and Pip...
 
(ATS6-GS04) Performance Analysis of Accelrys Enterprise Platform 9.0 on IBM’s...
(ATS6-GS04) Performance Analysis of Accelrys Enterprise Platform 9.0 on IBM’s...(ATS6-GS04) Performance Analysis of Accelrys Enterprise Platform 9.0 on IBM’s...
(ATS6-GS04) Performance Analysis of Accelrys Enterprise Platform 9.0 on IBM’s...
 
(ATS6-GS02) Integrating Contur and HEOS
(ATS6-GS02) Integrating Contur and HEOS(ATS6-GS02) Integrating Contur and HEOS
(ATS6-GS02) Integrating Contur and HEOS
 
(ATS6-GS01) Welcome
(ATS6-GS01) Welcome (ATS6-GS01) Welcome
(ATS6-GS01) Welcome
 
(ATS6-DEV09) Deep Dive into REST and SOAP Integration for Protocol Authors
(ATS6-DEV09) Deep Dive into REST and SOAP Integration for Protocol Authors(ATS6-DEV09) Deep Dive into REST and SOAP Integration for Protocol Authors
(ATS6-DEV09) Deep Dive into REST and SOAP Integration for Protocol Authors
 
(ATS6-DEV08) Integrating Contur ELN with other systems using a RESTful API
(ATS6-DEV08) Integrating Contur ELN with other systems using a RESTful API(ATS6-DEV08) Integrating Contur ELN with other systems using a RESTful API
(ATS6-DEV08) Integrating Contur ELN with other systems using a RESTful API
 
(ATS6-DEV07) Building widgets for ELN home page
(ATS6-DEV07) Building widgets for ELN home page(ATS6-DEV07) Building widgets for ELN home page
(ATS6-DEV07) Building widgets for ELN home page
 
(ATS6-DEV05) Building Interactive Web Applications with the Reporting Collection
(ATS6-DEV05) Building Interactive Web Applications with the Reporting Collection(ATS6-DEV05) Building Interactive Web Applications with the Reporting Collection
(ATS6-DEV05) Building Interactive Web Applications with the Reporting Collection
 
(ATS6-DEV04) Building Web MashUp applications that include Accelrys Applicati...
(ATS6-DEV04) Building Web MashUp applications that include Accelrys Applicati...(ATS6-DEV04) Building Web MashUp applications that include Accelrys Applicati...
(ATS6-DEV04) Building Web MashUp applications that include Accelrys Applicati...
 
(ATS6-DEV03) Building an Enterprise Web Solution with AEP
(ATS6-DEV03) Building an Enterprise Web Solution with AEP(ATS6-DEV03) Building an Enterprise Web Solution with AEP
(ATS6-DEV03) Building an Enterprise Web Solution with AEP
 
(ATS6-DEV02) Web Application Strategies
(ATS6-DEV02) Web Application Strategies(ATS6-DEV02) Web Application Strategies
(ATS6-DEV02) Web Application Strategies
 
(ATS6-APP09) ELN configuration management with ADM
(ATS6-APP09) ELN configuration management with ADM(ATS6-APP09) ELN configuration management with ADM
(ATS6-APP09) ELN configuration management with ADM
 
(ATS6-APP06) Accelrys LIMS and Accelrys ELN integration
(ATS6-APP06) Accelrys LIMS and Accelrys ELN integration    (ATS6-APP06) Accelrys LIMS and Accelrys ELN integration
(ATS6-APP06) Accelrys LIMS and Accelrys ELN integration
 
(ATS6-APP05) Deploying Contur ELN to large organizations
(ATS6-APP05) Deploying Contur ELN to large organizations(ATS6-APP05) Deploying Contur ELN to large organizations
(ATS6-APP05) Deploying Contur ELN to large organizations
 
(ATS6-APP04) Flexible Data Capture for Improved Laboratory Ergonomics
(ATS6-APP04) Flexible Data Capture for Improved Laboratory Ergonomics(ATS6-APP04) Flexible Data Capture for Improved Laboratory Ergonomics
(ATS6-APP04) Flexible Data Capture for Improved Laboratory Ergonomics
 
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
(ATS6-APP03) Thomson Rueters Content used in Acclrys Pipeline Pilot
 

Último

Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 

(ATS4-PLAT05) Accelrys Catalog: A Search Index for AEP

  • 1. (ATS4-PLAT05) Accelrys Catalog: A Search Index for AEP Ton van Daelen Sr. Director, Platform Product Management ton.vandaelen@accelrys.com
  • 2. The information on the roadmap and future software development efforts are intended to outline general product direction and should not be relied on in making a purchasing decision.
  • 3. Outline • Search use cases • Deployment architecture • Solr search index • Search syntax • Administration • Demo – Pro client UI – Web UI – Admin UI
  • 4. Accelrys Catalog Vision Search from Pro Client Administer Examples that use the ‘Http Connector’ component Generate index PilotScript referencing ‘rsplit()’ Update frequency Pro Client – Pers Productivity Protocols using MAO data Admin Catalog Search Canned reports Generate index Security issues Update frequency Bad design Bad documentation Xml log Search from Web Port Recent protocols Popular protocols Protocols searching ‘Corporate Web User Database” Next steps: • Mail Users • Post report
  • 5. The Size of the Challenge • 10-100 Pro client users • 50-1000 Web users • 1-10 servers • -> 5000+ protocols to be managed
  • 6. Admin Use Cases … • Bad design practices. Find protocols that: – have shortcuts as copies – have saved checkpoints – store passwords – have components that are owner access only – don’t have top level parameters (Web Port) – have component with absolute file paths • Bad documentation practices. Find protocols that: – don’t have help text (or default help) – have components with missing captions
  • 7. More Admin Use Cases • General queries. Find protocols: – with components that are deprecated (ad hoc / report) – not run in n days – not changed in n days – by client type (pro client, web port, web service, Notebook, Isentris, …) – with components with GUID x – with SQL components with specific DSN
  • 8. Introduction to Text Searching • Unstructured or minimally- structured searches – Think “Google” – Keyword-based, non-relational; wide range of user input – Based on lookups using pre-built word (token) indexes
  • 9. Introduction to Text Searching (cont’d) • Strategies to make searches more effective – Stop word removal: and, the, by, for, of, … – Stemming: startedstart, clusterscluster, etc. – Synonym aliasing: oncology=cancer, MB=megabyte, etc. (supported but only minimally implemented; extensible) – Language-specific document and query processing (support for Asian languages)
  • 10. Apache Solr • Open source text search server • Part of Apache Software Foundation • Uses and extends Lucene Java search library • Hosted by a web application server • http://lucene.apache.org/solr/
  • 11. Solr: Under the Hood… • Schema – XML specification of document fields and their types – Specifies how fields are tokenized and processed for indexing • Solr config file – XML specification of query and result set processing rules – E.g. field weights • Optional auxiliary files – Stop words, synonyms, protected words (unstemmed) • Host application container – For AEP this is Tomcat
  • 12. Tokenization and Filtering • Tokenization options in Solr – Break on whitespace – Break on all non-letter characters – Break on case changes (for CamelCaseTokenization) – Break on character set changes (alphanum/ideographic/katakana) • Additional filters – Lowercase filter: converts all characters to lowercase – CJK bigram filter: outputs adjacent character pairs for Asian languages – Stem filter: applies stemming rules (many language-specific variants) • Field indexing and query processing use same tokenization – Better search results may be obtained by using slightly different analysis for indexing versus querying • See http://wiki.apache.org/solr/AnalyzersTokenizersTokenFilters
  • 14. Mapping XMLDB to Solr Documents • XML Database = Component/Protocol Database • For each item in XMLDB, an indexing protocol – reads the item from the database – creates data record properties corresponding to Solr fields – joins in statistics from usage log – converts the data record to a JSON “document” – POSTs the document to Apache/Tomcat/Solr via HTTP • Weighting – Protocol name and description have higher weight – Proximity has higher weight
  • 15. Some Catalog Fields (defined in schema) • name: protocol or component name • path: location in XMLDB • type: “component” or “protocol” • parameters: names of parameters • author: user who created protocol/component • modifieddate: data protocol/component last changed • runcount: number of times protocol has been run • lastrun: date protocol was last run • uses: list of components used by protocol • alltext: composite field for keyword search
  • 16. Administration • Configure servers • Specify update interval • Manual rebuild
  • 17. Configuring Accelrys Catalog • Configuration (admin portal) – AEP servers to index – Indexing schedule • Note – Indexer runs as scheduled service – Indexing takes ~1 to 3 minutes per 1000 XMLDB items – Two index copies; users can continue search while index is rebuilt – Tomcat and Solr automatically installed and launched with Apache
  • 18. Limitations • Usage info can be incorrect because log file doesn’t store full protocol path (“Protocol 1” !) • No indexing at runtime – it can take a day before index is updated
  • 19. Demo
  • 20.
  • 21. Example Queries • MAO type:"Component“ – Any components referencing ‘MAO’ • uses:"Xml Reader" -author:Accelrys – Components/protocols that have an xml reader and are not authored by Accelrys • lastrun:[*TO NOW-6MONTH] – Last run at least six months prior • runcount:0 – Never been run
  • 22.
  • 23.
  • 24.
  • 25.
  • 26. Summary • Accelrys Catalog is powerful search technology built into AEP • Become a beta tester (beta-2) • Plan for 9.0 upgrade now • (ATS4-PLAT10) Planning your deployment for a 64 bit world