SlideShare ist ein Scribd-Unternehmen logo
1 von 20
OSLO STOCKHOLM LONDON BOSTON
Improve Performance in
FAST Search for SharePoint
2010 (FS4SP)
Enda Flynn – Marketing Manager
Job Maelane - Senior Consultant
Financials
Financially stabile and secure
Profitable growth when expanding
AAA Rating (D&B)
Employees
50 + specialists and growing
Ability to attract highly qualified employees
Customers
90 +
3 continents
Search Projects
200 + FAST projects completed
Comperio | Search Matters.
Agenda
• Comperio Search Introduction
• FS4SP Architecture Overview
• Factors influencing performance
• Analyzing Feeding & Indexing
• Questions
Common Issues
• “Crawler is slow. Crawler takes too long”
• “Queries are slow”
• “Incremental indexing takes a long time”
• “Indexing fails”
FAST Search Server 2010
Summary of architectural components
Content
Search Center
Content
User Profiles
…
Property
Extraction
…
Content
retrieval
Content
processing
Query
processing
& matching
Administration
Hardware – Best Practices
CPU: 2 x 2GHz+ (Quad/six core)
Memory: 24-48 GB
Disk:
2 x 300 GB, SAS, 10K RPM (RAID 1)
CPU: 2 x 2GHz+ (Quad/six core)
Memory: 24-48 GB
Disk alternatives:
1.0 TB: 8 x 300 GB, SAS, 10K RPM (RAID10)
1.8 TB: 8 x 300 GB, SAS, 10K RPM (RAID 5)
3.6 TB: 16 x 300 GB, SAS, 10K RPM (RAID 5+0)
New: 7.2 TB: 16 x 600 GB, SAS, 10K RPM (RAID
5+0)
SAN: Configured for “database performance”
Storage Server
Admin / Processing
Server
• Index latency
– How long, on average, a document takes to index
• Documents per second
– How many documents processed and indexed per
second
• Query latency
– How quickly are the results generated from a query
• Queries per second (QPS)
– How many queries are processed per second
How is search performance measured?
• Search Administration Reports
• Crawl Rate Per Content Source
• Crawl Rate Per Type
• Crawl Processing Per Activity
• Crawl Processing Per Component
• Crawl Queue
• Query Latency
and more
• Web Analytics Reports
• Total Number of Search Queries
• Top queries
• Failed queries
• Best Bet usage
• Keywords usage
and more
FS4SP- Search Administration Reports
Analyze Ribbon
- More date range options
- Filtering search scope
- Search query text
- Export to Spreadsheet etc.
Web Analytics Web Part
- Display popular items on a site
(such as popular content, popular
search queries, or search results)
• No of documents
• Content types
• Deep or shallow refiners
• Entity extraction
• Complex queries (many terms)
• Substring search
• Lemmatisation
• Spell check
• Maximum and average document size
• And many more….
What influences performance?
Lots of things!
Resource Consumptions
CPU RAM DISK TRANS DISK SPACE NETW B/W
Content Distributor     
Document Processor     
Index Dispatcher     
Indexer 
 
 
Search Engine     
QR Server     
Admin Services     
Web Link Analysis   
 
FAST Search for SharePoint Scale out
Content
Volume
Query
Volume
Scale-out multiple
“dimensions”
Query Volume
Content Volume
Indexing freshness
Redundancy options
Search
Indexing
Performance targets*
15M Docs/node
25 QPS/node
*Depends on content and hardware specifics
Search and Indexing
Crawling and Content
Processing
Query and Result
Processing
Back-end with extreme and flexible scale out options
FS4SP – Medium Deployment
FAST Search for SharePoint 2010 Farm
FAST-ADM-1
Admin
Content Distributor 1
Web Analyzer
12 Docprocs+
FAST-FSTIDX-11
Index (Search)
12 Docprocs+
FAST-FSTIDX-12
Index (Search)
12 Docprocs+
FAST-FSTIDX-21
(Index) Search
QR Server
FAST-FSTIDX-22
(Index) Search
QR Server
FAST-ADM-2
Content Distributor 2
Web Analyzer
12 Docprocs+
(Enterprise Crawler)
FAST-FSTIDX-13
Index (Search)
12 Docprocs+
FAST-FSTIDX-23
(Index) Search
QR Server
SP2010 Farm
SQL 2008 Cluster
WFE
Query SSA
WFE
Query SSA
SP Crawl
People Crawl
SP Crawl
People Crawl
Crawl DB
Search Admin DB
FS4SP – Large Deployment
SP2010 Farm
FAST Search for SharePoint 2010 Farm
SQL 2008 Cluster
WFE
Query SSA
WFE
Query SSA
SP Crawl
People Crawl
SP Crawl
People Crawl
Crawl DB
Search Admin DB
SP Crawl
FAST-ADM-1
Admin
ConfigServer
Spelltuner
SamAdmin
Content Distributor 1
Web Analyzer
12 Docprocs+
FAST-FSTIDX-11
Index (Search)
12 Docprocs+
FAST-FSTIDX-12
Index (Search)
12 Docprocs+
FAST-FSTIDX-21
(Index) Search
QR Server
FAST-FSTIDX-22
(Index) Search
QR Server
FAST-ADM-2
Content Distributor 2
Web Analyzer
12 Docprocs+
FAST-FSTIDX-13
Index (Search)
12 Docprocs+
FAST-FSTIDX-23
(Index) Search
QR Server
FAST-FSTIDX-14
Index (Search)
12 Docprocs+
FAST-FSTIDX-15
Index (Search)
12 Docprocs+
FAST-FSTIDX-24
(Index) Search
QR Server
FAST-FSTIDX-25
(Index) Search
QR Server
FAST-FSTIDX-16
Index (Search)
12 Docprocs+
FAST-FSTIDX-26
(Index) Search
QR Server
FAST-ADM-3
Web Analyzer
12 Docprocs+
FS4SP – Server Calculation Matrix
Max item count
(in Millions) Adm + WA
Indexers
(1 row)
SharePoint
Crawlers
Crawl DB
Server Redundancy Total
1 0 1 0 0 1 2
10 1 1 1 1 2 6
40 2 3 2 1 3 11
100 3 6 3 1 6 19
150 5 10 5 1 10 31
200 6 14 6 2 14 42
500 10 34 16 2 34 96
FS4SP – Disk Calculation Matrix
Disclaimer:
This table is based on early testing and results from an internal dogfood project. The numbers might not be
representative for the customer environment and data. Please use caution when using these numbers for sizing.
Max item count
(in Millions) Adm Web Analyzer Crawl DB Server Indexer
1 1 x 72 GB 1 x 5 GB 1 x 10 GB 1 x 120 GB
10 1 x 72 GB 1 x 50 GB 1 x 40 GB 1 x 1.2 TB
40 1 x 72 GB 1 x 60 GB 1 x 150 GB 3 x 2.0 TB
100 1 x 72 GB 2 x 75 GB 1 x 350 GB 6 x 2.0 TB
150 1 x 72 GB 4 x 75 GB 1 x 500 GB 10 x 2.0 TB
200 1 x 72 GB 5 x 75 GB 2 x 350 GB 14 x 2.0 TB
500 1 x 72 GB 9 x 75 GB 2 x 500 GB 34 x 2.0 TB
Feeding and Indexing Performance
• Feed and indexing processing chain in FS4SP
has the components below:
– Crawler
– Content Distributors
– Item Processing
– Indexing Dispatcher
– Primary Indexer
– Backup Indexer
Feeding and Indexing Performance
Crawlers
Content
Distributors
Document
Processors
Indexing
Dispatchers
Primary
Indexers
Secondary
indexers
1 2 3 4 5
6
7
8
9
Feeding and Indexing Performance
Crawlers
Content
Distributors
Document
Processors
Indexing
Dispatchers
Primary
Indexers
Secondary
indexers
1
Questions???

Weitere ähnliche Inhalte

Was ist angesagt?

SharePoint Search Topology and Optimization
SharePoint Search Topology and OptimizationSharePoint Search Topology and Optimization
SharePoint Search Topology and OptimizationMike Maadarani
 
Data Analysis @ Daum | Devon 2012
Data Analysis @ Daum | Devon 2012Data Analysis @ Daum | Devon 2012
Data Analysis @ Daum | Devon 2012Daum DNA
 
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...Mikael Svenson
 
Kql and the content search web part
Kql and the content search web part Kql and the content search web part
Kql and the content search web part InnoTech
 
Analyzing Web Archives
Analyzing Web ArchivesAnalyzing Web Archives
Analyzing Web Archivesvinaygo
 
Take Cloud Hybrid Search to the Next Level
Take Cloud Hybrid Search to the Next LevelTake Cloud Hybrid Search to the Next Level
Take Cloud Hybrid Search to the Next LevelJeff Fried
 
Understanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchUnderstanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchJeff Fried
 
Understanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchUnderstanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchJeff Fried
 
Eventually Elasticsearch: Eventual Consistency in the Real World
Eventually Elasticsearch: Eventual Consistency in the Real WorldEventually Elasticsearch: Eventual Consistency in the Real World
Eventually Elasticsearch: Eventual Consistency in the Real WorldBeyondTrees
 
Using server logs to your advantage
Using server logs to your advantageUsing server logs to your advantage
Using server logs to your advantageAlexandra Johnson
 
Agility and Scalability with MongoDB
Agility and Scalability with MongoDBAgility and Scalability with MongoDB
Agility and Scalability with MongoDBMongoDB
 
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...MongoDB
 
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDays
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDaysConexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDays
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDaysCAPSiDE
 
Webinar: Fusion for Business Intelligence
Webinar: Fusion for Business IntelligenceWebinar: Fusion for Business Intelligence
Webinar: Fusion for Business IntelligenceLucidworks
 
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDB
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDBMongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDB
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDBMongoDB
 
Barcelona MUG MongoDB + Hadoop Presentation
Barcelona MUG MongoDB + Hadoop PresentationBarcelona MUG MongoDB + Hadoop Presentation
Barcelona MUG MongoDB + Hadoop PresentationNorberto Leite
 
Scaling Recommendations, Semantic Search, & Data Analytics with solr
Scaling Recommendations, Semantic Search, & Data Analytics with solrScaling Recommendations, Semantic Search, & Data Analytics with solr
Scaling Recommendations, Semantic Search, & Data Analytics with solrTrey Grainger
 
MongoDB & Hadoop - Understanding Your Big Data
MongoDB & Hadoop - Understanding Your Big DataMongoDB & Hadoop - Understanding Your Big Data
MongoDB & Hadoop - Understanding Your Big DataMongoDB
 
search driven intranets
search driven intranetssearch driven intranets
search driven intranetsJeff Fried
 

Was ist angesagt? (20)

SharePoint Search Topology and Optimization
SharePoint Search Topology and OptimizationSharePoint Search Topology and Optimization
SharePoint Search Topology and Optimization
 
Data Analysis @ Daum | Devon 2012
Data Analysis @ Daum | Devon 2012Data Analysis @ Daum | Devon 2012
Data Analysis @ Daum | Devon 2012
 
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...
Search Queries Explained – A Deep Dive into Query Rules, Query Variables and ...
 
Kql and the content search web part
Kql and the content search web part Kql and the content search web part
Kql and the content search web part
 
Analyzing Web Archives
Analyzing Web ArchivesAnalyzing Web Archives
Analyzing Web Archives
 
Take Cloud Hybrid Search to the Next Level
Take Cloud Hybrid Search to the Next LevelTake Cloud Hybrid Search to the Next Level
Take Cloud Hybrid Search to the Next Level
 
MongoDB and Spark
MongoDB and SparkMongoDB and Spark
MongoDB and Spark
 
Understanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchUnderstanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid Search
 
Understanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid SearchUnderstanding and Applying Cloud Hybrid Search
Understanding and Applying Cloud Hybrid Search
 
Eventually Elasticsearch: Eventual Consistency in the Real World
Eventually Elasticsearch: Eventual Consistency in the Real WorldEventually Elasticsearch: Eventual Consistency in the Real World
Eventually Elasticsearch: Eventual Consistency in the Real World
 
Using server logs to your advantage
Using server logs to your advantageUsing server logs to your advantage
Using server logs to your advantage
 
Agility and Scalability with MongoDB
Agility and Scalability with MongoDBAgility and Scalability with MongoDB
Agility and Scalability with MongoDB
 
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
 
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDays
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDaysConexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDays
Conexión de MongoDB con Hadoop - Luis Alberto Giménez - CAPSiDE #DevOSSAzureDays
 
Webinar: Fusion for Business Intelligence
Webinar: Fusion for Business IntelligenceWebinar: Fusion for Business Intelligence
Webinar: Fusion for Business Intelligence
 
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDB
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDBMongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDB
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDB
 
Barcelona MUG MongoDB + Hadoop Presentation
Barcelona MUG MongoDB + Hadoop PresentationBarcelona MUG MongoDB + Hadoop Presentation
Barcelona MUG MongoDB + Hadoop Presentation
 
Scaling Recommendations, Semantic Search, & Data Analytics with solr
Scaling Recommendations, Semantic Search, & Data Analytics with solrScaling Recommendations, Semantic Search, & Data Analytics with solr
Scaling Recommendations, Semantic Search, & Data Analytics with solr
 
MongoDB & Hadoop - Understanding Your Big Data
MongoDB & Hadoop - Understanding Your Big DataMongoDB & Hadoop - Understanding Your Big Data
MongoDB & Hadoop - Understanding Your Big Data
 
search driven intranets
search driven intranetssearch driven intranets
search driven intranets
 

Andere mochten auch

Metodos de recolecion de informacion
Metodos de recolecion de informacionMetodos de recolecion de informacion
Metodos de recolecion de informacionJulian sanchez
 
Blog-3-Biodynamic-Psychotherapy
Blog-3-Biodynamic-PsychotherapyBlog-3-Biodynamic-Psychotherapy
Blog-3-Biodynamic-PsychotherapyElya Steinberg
 
Cv renny mathew_hw engineer
Cv renny mathew_hw engineerCv renny mathew_hw engineer
Cv renny mathew_hw engineerRnny Mthew
 
Kstc - strategic management consultant
Kstc - strategic management consultantKstc - strategic management consultant
Kstc - strategic management consultantVishal Beharie
 

Andere mochten auch (10)

Metodos de recolecion de informacion
Metodos de recolecion de informacionMetodos de recolecion de informacion
Metodos de recolecion de informacion
 
Blog-3-Biodynamic-Psychotherapy
Blog-3-Biodynamic-PsychotherapyBlog-3-Biodynamic-Psychotherapy
Blog-3-Biodynamic-Psychotherapy
 
new doc 1520161009104140082
new doc 1520161009104140082new doc 1520161009104140082
new doc 1520161009104140082
 
Resume
ResumeResume
Resume
 
Tcpip
TcpipTcpip
Tcpip
 
Post production
Post productionPost production
Post production
 
Cv renny mathew_hw engineer
Cv renny mathew_hw engineerCv renny mathew_hw engineer
Cv renny mathew_hw engineer
 
El rey leon
El rey leonEl rey leon
El rey leon
 
Kstc - strategic management consultant
Kstc - strategic management consultantKstc - strategic management consultant
Kstc - strategic management consultant
 
Os nossos 45 anos
Os nossos 45 anosOs nossos 45 anos
Os nossos 45 anos
 

Ähnlich wie Improve Performance in Fast Search for SharePoint - Comperio

SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...
SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...
SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...European SharePoint Conference
 
Apache CarbonData+Spark to realize data convergence and Unified high performa...
Apache CarbonData+Spark to realize data convergence and Unified high performa...Apache CarbonData+Spark to realize data convergence and Unified high performa...
Apache CarbonData+Spark to realize data convergence and Unified high performa...Tech Triveni
 
Enterprise Search Summit Keynote: A Big Data Architecture for Search
Enterprise Search Summit Keynote: A Big Data Architecture for SearchEnterprise Search Summit Keynote: A Big Data Architecture for Search
Enterprise Search Summit Keynote: A Big Data Architecture for SearchSearch Technologies
 
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
 
Enterprise Search in SharePoint 2010
Enterprise Search in SharePoint 2010Enterprise Search in SharePoint 2010
Enterprise Search in SharePoint 2010bgerman
 
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...EPC Group
 
Asia Pacific SharePoint Capacity Planning by Joel Oleson
Asia Pacific SharePoint Capacity Planning by Joel OlesonAsia Pacific SharePoint Capacity Planning by Joel Oleson
Asia Pacific SharePoint Capacity Planning by Joel OlesonJoel Oleson
 
Database and Analytics on the AWS Cloud
Database and Analytics on the AWS CloudDatabase and Analytics on the AWS Cloud
Database and Analytics on the AWS CloudAmazon Web Services
 
Managing your black friday logs Voxxed Luxembourg
Managing your black friday logs Voxxed LuxembourgManaging your black friday logs Voxxed Luxembourg
Managing your black friday logs Voxxed LuxembourgDavid Pilato
 
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon RedshiftAmazon Web Services
 
Why MongoDB over other Databases - Habilelabs
Why MongoDB over other Databases - HabilelabsWhy MongoDB over other Databases - Habilelabs
Why MongoDB over other Databases - HabilelabsHabilelabs
 
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...Michael Noel
 
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices Session
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices SessionSPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices Session
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices SessionMichael Noel
 
Streaming data for real time analysis
Streaming data for real time analysisStreaming data for real time analysis
Streaming data for real time analysisAmazon Web Services
 
Leveraging Amazon Redshift for Your Data Warehouse
Leveraging Amazon Redshift for Your Data WarehouseLeveraging Amazon Redshift for Your Data Warehouse
Leveraging Amazon Redshift for Your Data WarehouseAmazon Web Services
 
SharePoint 2013 Search Topology and Optimization
SharePoint 2013 Search Topology and OptimizationSharePoint 2013 Search Topology and Optimization
SharePoint 2013 Search Topology and OptimizationMike Maadarani
 
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 practicesEric Shupps
 
Highly available and scalable architectures
Highly available and scalable architecturesHighly available and scalable architectures
Highly available and scalable architecturesPhil Wicklund
 
Planning SharePoint 2013 Search for IT PROs
Planning SharePoint 2013 Search for IT PROsPlanning SharePoint 2013 Search for IT PROs
Planning SharePoint 2013 Search for IT PROsBenjamin Athawes
 

Ähnlich wie Improve Performance in Fast Search for SharePoint - Comperio (20)

SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...
SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...
SQL Server and SharePoint - Best Practices presented by Steffen Krause, Micro...
 
Apache CarbonData+Spark to realize data convergence and Unified high performa...
Apache CarbonData+Spark to realize data convergence and Unified high performa...Apache CarbonData+Spark to realize data convergence and Unified high performa...
Apache CarbonData+Spark to realize data convergence and Unified high performa...
 
Enterprise Search Summit Keynote: A Big Data Architecture for Search
Enterprise Search Summit Keynote: A Big Data Architecture for SearchEnterprise Search Summit Keynote: A Big Data Architecture for Search
Enterprise Search Summit Keynote: A Big Data Architecture for Search
 
Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)Share point 2013 enterprise search (public)
Share point 2013 enterprise search (public)
 
Enterprise Search in SharePoint 2010
Enterprise Search in SharePoint 2010Enterprise Search in SharePoint 2010
Enterprise Search in SharePoint 2010
 
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...
EPC Group - Comprehensive Overview of SharePoint 2010's Enterprise Search Cap...
 
Asia Pacific SharePoint Capacity Planning by Joel Oleson
Asia Pacific SharePoint Capacity Planning by Joel OlesonAsia Pacific SharePoint Capacity Planning by Joel Oleson
Asia Pacific SharePoint Capacity Planning by Joel Oleson
 
Database and Analytics on the AWS Cloud
Database and Analytics on the AWS CloudDatabase and Analytics on the AWS Cloud
Database and Analytics on the AWS Cloud
 
Managing your black friday logs Voxxed Luxembourg
Managing your black friday logs Voxxed LuxembourgManaging your black friday logs Voxxed Luxembourg
Managing your black friday logs Voxxed Luxembourg
 
Oz search
Oz search Oz search
Oz search
 
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon Redshift
 
Why MongoDB over other Databases - Habilelabs
Why MongoDB over other Databases - HabilelabsWhy MongoDB over other Databases - Habilelabs
Why MongoDB over other Databases - Habilelabs
 
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...
SPSAD - Ultimate SharePoint Infrastructure Best Practices Session - SharePoin...
 
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices Session
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices SessionSPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices Session
SPSSV 2013 - Ultimate SharePoint Infrastructure Best Practices Session
 
Streaming data for real time analysis
Streaming data for real time analysisStreaming data for real time analysis
Streaming data for real time analysis
 
Leveraging Amazon Redshift for Your Data Warehouse
Leveraging Amazon Redshift for Your Data WarehouseLeveraging Amazon Redshift for Your Data Warehouse
Leveraging Amazon Redshift for Your Data Warehouse
 
SharePoint 2013 Search Topology and Optimization
SharePoint 2013 Search Topology and OptimizationSharePoint 2013 Search Topology and Optimization
SharePoint 2013 Search Topology and Optimization
 
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
 
Highly available and scalable architectures
Highly available and scalable architecturesHighly available and scalable architectures
Highly available and scalable architectures
 
Planning SharePoint 2013 Search for IT PROs
Planning SharePoint 2013 Search for IT PROsPlanning SharePoint 2013 Search for IT PROs
Planning SharePoint 2013 Search for IT PROs
 

Mehr von Comperio - Search Matters.

Samhandlingsløsninger med søk på tvers av kilder
Samhandlingsløsninger med søk på tvers av kilderSamhandlingsløsninger med søk på tvers av kilder
Samhandlingsløsninger med søk på tvers av kilderComperio - Search Matters.
 
NDC lightning SharePoint 2013 and Enterprise Search
NDC lightning SharePoint 2013 and Enterprise SearchNDC lightning SharePoint 2013 and Enterprise Search
NDC lightning SharePoint 2013 and Enterprise SearchComperio - Search Matters.
 
Welcome virksomhetssøk og sosial samhandling - Comperio
Welcome virksomhetssøk og sosial samhandling - ComperioWelcome virksomhetssøk og sosial samhandling - Comperio
Welcome virksomhetssøk og sosial samhandling - ComperioComperio - Search Matters.
 
SharePoint 2013 Enterprise Search Prjoect Learnings - Comperio
SharePoint 2013 Enterprise Search Prjoect Learnings - ComperioSharePoint 2013 Enterprise Search Prjoect Learnings - Comperio
SharePoint 2013 Enterprise Search Prjoect Learnings - ComperioComperio - Search Matters.
 
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013Comperio - Search Matters.
 
Information wants to be free - Comperio seminar oslo14may2013
Information wants to be free - Comperio seminar oslo14may2013Information wants to be free - Comperio seminar oslo14may2013
Information wants to be free - Comperio seminar oslo14may2013Comperio - Search Matters.
 
Produktivitet 1.0 - Comperio Seminar oktober 2012
Produktivitet 1.0 - Comperio Seminar oktober 2012Produktivitet 1.0 - Comperio Seminar oktober 2012
Produktivitet 1.0 - Comperio Seminar oktober 2012Comperio - Search Matters.
 
Search solutions for big data and collaboration - Comperio seminar October 2012
Search solutions for big data and collaboration - Comperio seminar October 2012Search solutions for big data and collaboration - Comperio seminar October 2012
Search solutions for big data and collaboration - Comperio seminar October 2012Comperio - Search Matters.
 

Mehr von Comperio - Search Matters. (17)

Samhandlingsløsninger med søk på tvers av kilder
Samhandlingsløsninger med søk på tvers av kilderSamhandlingsløsninger med søk på tvers av kilder
Samhandlingsløsninger med søk på tvers av kilder
 
Søkeløsningen dine kolleger drømmer om
Søkeløsningen dine kolleger drømmer omSøkeløsningen dine kolleger drømmer om
Søkeløsningen dine kolleger drømmer om
 
SharePoint Search mot 360 og ProArc
SharePoint Search mot 360 og ProArcSharePoint Search mot 360 og ProArc
SharePoint Search mot 360 og ProArc
 
NDC lightning SharePoint 2013 and Enterprise Search
NDC lightning SharePoint 2013 and Enterprise SearchNDC lightning SharePoint 2013 and Enterprise Search
NDC lightning SharePoint 2013 and Enterprise Search
 
Search Driven Websites - Comperio
Search Driven Websites - ComperioSearch Driven Websites - Comperio
Search Driven Websites - Comperio
 
Search Analytics - Comperio
Search Analytics - ComperioSearch Analytics - Comperio
Search Analytics - Comperio
 
Welcome virksomhetssøk og sosial samhandling - Comperio
Welcome virksomhetssøk og sosial samhandling - ComperioWelcome virksomhetssøk og sosial samhandling - Comperio
Welcome virksomhetssøk og sosial samhandling - Comperio
 
Virksomhetssøk for prosjekt - Comperio
Virksomhetssøk for prosjekt  - ComperioVirksomhetssøk for prosjekt  - Comperio
Virksomhetssøk for prosjekt - Comperio
 
SharePoint 2013 Enterprise Search Prjoect Learnings - Comperio
SharePoint 2013 Enterprise Search Prjoect Learnings - ComperioSharePoint 2013 Enterprise Search Prjoect Learnings - Comperio
SharePoint 2013 Enterprise Search Prjoect Learnings - Comperio
 
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013
Yammer and office 365 roadmap update - Comperio seminar oslo14 May2013
 
Information wants to be free - Comperio seminar oslo14may2013
Information wants to be free - Comperio seminar oslo14may2013Information wants to be free - Comperio seminar oslo14may2013
Information wants to be free - Comperio seminar oslo14may2013
 
Fileserver Search Assessment - Comperio
Fileserver Search Assessment - ComperioFileserver Search Assessment - Comperio
Fileserver Search Assessment - Comperio
 
Sökmotorn i SharePoint 2013 - Comperio
Sökmotorn i SharePoint 2013 - ComperioSökmotorn i SharePoint 2013 - Comperio
Sökmotorn i SharePoint 2013 - Comperio
 
Big Data – good news for Enterprise Search
Big Data – good news for Enterprise SearchBig Data – good news for Enterprise Search
Big Data – good news for Enterprise Search
 
Produktivitet 1.0 - Comperio Seminar oktober 2012
Produktivitet 1.0 - Comperio Seminar oktober 2012Produktivitet 1.0 - Comperio Seminar oktober 2012
Produktivitet 1.0 - Comperio Seminar oktober 2012
 
Search solutions for big data and collaboration - Comperio seminar October 2012
Search solutions for big data and collaboration - Comperio seminar October 2012Search solutions for big data and collaboration - Comperio seminar October 2012
Search solutions for big data and collaboration - Comperio seminar October 2012
 
Hvordan lykkes med intern Facebook og Google
Hvordan lykkes med intern Facebook og GoogleHvordan lykkes med intern Facebook og Google
Hvordan lykkes med intern Facebook og Google
 

Kürzlich hochgeladen

WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersRaghuram Pandurangan
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfPrecisely
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 

Kürzlich hochgeladen (20)

WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information Developers
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 

Improve Performance in Fast Search for SharePoint - Comperio

  • 1. OSLO STOCKHOLM LONDON BOSTON Improve Performance in FAST Search for SharePoint 2010 (FS4SP) Enda Flynn – Marketing Manager Job Maelane - Senior Consultant
  • 2. Financials Financially stabile and secure Profitable growth when expanding AAA Rating (D&B) Employees 50 + specialists and growing Ability to attract highly qualified employees Customers 90 + 3 continents Search Projects 200 + FAST projects completed Comperio | Search Matters.
  • 3. Agenda • Comperio Search Introduction • FS4SP Architecture Overview • Factors influencing performance • Analyzing Feeding & Indexing • Questions
  • 4. Common Issues • “Crawler is slow. Crawler takes too long” • “Queries are slow” • “Incremental indexing takes a long time” • “Indexing fails”
  • 5. FAST Search Server 2010 Summary of architectural components Content
  • 7. Hardware – Best Practices CPU: 2 x 2GHz+ (Quad/six core) Memory: 24-48 GB Disk: 2 x 300 GB, SAS, 10K RPM (RAID 1) CPU: 2 x 2GHz+ (Quad/six core) Memory: 24-48 GB Disk alternatives: 1.0 TB: 8 x 300 GB, SAS, 10K RPM (RAID10) 1.8 TB: 8 x 300 GB, SAS, 10K RPM (RAID 5) 3.6 TB: 16 x 300 GB, SAS, 10K RPM (RAID 5+0) New: 7.2 TB: 16 x 600 GB, SAS, 10K RPM (RAID 5+0) SAN: Configured for “database performance” Storage Server Admin / Processing Server
  • 8. • Index latency – How long, on average, a document takes to index • Documents per second – How many documents processed and indexed per second • Query latency – How quickly are the results generated from a query • Queries per second (QPS) – How many queries are processed per second How is search performance measured?
  • 9. • Search Administration Reports • Crawl Rate Per Content Source • Crawl Rate Per Type • Crawl Processing Per Activity • Crawl Processing Per Component • Crawl Queue • Query Latency and more • Web Analytics Reports • Total Number of Search Queries • Top queries • Failed queries • Best Bet usage • Keywords usage and more FS4SP- Search Administration Reports Analyze Ribbon - More date range options - Filtering search scope - Search query text - Export to Spreadsheet etc. Web Analytics Web Part - Display popular items on a site (such as popular content, popular search queries, or search results)
  • 10. • No of documents • Content types • Deep or shallow refiners • Entity extraction • Complex queries (many terms) • Substring search • Lemmatisation • Spell check • Maximum and average document size • And many more…. What influences performance? Lots of things!
  • 11. Resource Consumptions CPU RAM DISK TRANS DISK SPACE NETW B/W Content Distributor      Document Processor      Index Dispatcher      Indexer      Search Engine      QR Server      Admin Services      Web Link Analysis     
  • 12. FAST Search for SharePoint Scale out Content Volume Query Volume Scale-out multiple “dimensions” Query Volume Content Volume Indexing freshness Redundancy options Search Indexing Performance targets* 15M Docs/node 25 QPS/node *Depends on content and hardware specifics Search and Indexing Crawling and Content Processing Query and Result Processing Back-end with extreme and flexible scale out options
  • 13. FS4SP – Medium Deployment FAST Search for SharePoint 2010 Farm FAST-ADM-1 Admin Content Distributor 1 Web Analyzer 12 Docprocs+ FAST-FSTIDX-11 Index (Search) 12 Docprocs+ FAST-FSTIDX-12 Index (Search) 12 Docprocs+ FAST-FSTIDX-21 (Index) Search QR Server FAST-FSTIDX-22 (Index) Search QR Server FAST-ADM-2 Content Distributor 2 Web Analyzer 12 Docprocs+ (Enterprise Crawler) FAST-FSTIDX-13 Index (Search) 12 Docprocs+ FAST-FSTIDX-23 (Index) Search QR Server SP2010 Farm SQL 2008 Cluster WFE Query SSA WFE Query SSA SP Crawl People Crawl SP Crawl People Crawl Crawl DB Search Admin DB
  • 14. FS4SP – Large Deployment SP2010 Farm FAST Search for SharePoint 2010 Farm SQL 2008 Cluster WFE Query SSA WFE Query SSA SP Crawl People Crawl SP Crawl People Crawl Crawl DB Search Admin DB SP Crawl FAST-ADM-1 Admin ConfigServer Spelltuner SamAdmin Content Distributor 1 Web Analyzer 12 Docprocs+ FAST-FSTIDX-11 Index (Search) 12 Docprocs+ FAST-FSTIDX-12 Index (Search) 12 Docprocs+ FAST-FSTIDX-21 (Index) Search QR Server FAST-FSTIDX-22 (Index) Search QR Server FAST-ADM-2 Content Distributor 2 Web Analyzer 12 Docprocs+ FAST-FSTIDX-13 Index (Search) 12 Docprocs+ FAST-FSTIDX-23 (Index) Search QR Server FAST-FSTIDX-14 Index (Search) 12 Docprocs+ FAST-FSTIDX-15 Index (Search) 12 Docprocs+ FAST-FSTIDX-24 (Index) Search QR Server FAST-FSTIDX-25 (Index) Search QR Server FAST-FSTIDX-16 Index (Search) 12 Docprocs+ FAST-FSTIDX-26 (Index) Search QR Server FAST-ADM-3 Web Analyzer 12 Docprocs+
  • 15. FS4SP – Server Calculation Matrix Max item count (in Millions) Adm + WA Indexers (1 row) SharePoint Crawlers Crawl DB Server Redundancy Total 1 0 1 0 0 1 2 10 1 1 1 1 2 6 40 2 3 2 1 3 11 100 3 6 3 1 6 19 150 5 10 5 1 10 31 200 6 14 6 2 14 42 500 10 34 16 2 34 96
  • 16. FS4SP – Disk Calculation Matrix Disclaimer: This table is based on early testing and results from an internal dogfood project. The numbers might not be representative for the customer environment and data. Please use caution when using these numbers for sizing. Max item count (in Millions) Adm Web Analyzer Crawl DB Server Indexer 1 1 x 72 GB 1 x 5 GB 1 x 10 GB 1 x 120 GB 10 1 x 72 GB 1 x 50 GB 1 x 40 GB 1 x 1.2 TB 40 1 x 72 GB 1 x 60 GB 1 x 150 GB 3 x 2.0 TB 100 1 x 72 GB 2 x 75 GB 1 x 350 GB 6 x 2.0 TB 150 1 x 72 GB 4 x 75 GB 1 x 500 GB 10 x 2.0 TB 200 1 x 72 GB 5 x 75 GB 2 x 350 GB 14 x 2.0 TB 500 1 x 72 GB 9 x 75 GB 2 x 500 GB 34 x 2.0 TB
  • 17. Feeding and Indexing Performance • Feed and indexing processing chain in FS4SP has the components below: – Crawler – Content Distributors – Item Processing – Indexing Dispatcher – Primary Indexer – Backup Indexer
  • 18. Feeding and Indexing Performance Crawlers Content Distributors Document Processors Indexing Dispatchers Primary Indexers Secondary indexers 1 2 3 4 5 6 7 8 9
  • 19. Feeding and Indexing Performance Crawlers Content Distributors Document Processors Indexing Dispatchers Primary Indexers Secondary indexers 1