A case study presented at the 2009 Enterprise Search Summit by World Vital Records CEO Paul Allen. Mr. Allen discussed the challenge of cost effective scaling, ability to index and query large data sets, and stay competitive in the market place.

1. Indexing and Searching
Massive Data Sets
PAUL ALLEN
CEO
May 13, 2009
Enterprise Search Summit

2. About
 WorldVitalRecords.com
 Provides access to genealogy databases and family history
tools, including birth, death, military, census, and parish
records
 WorldHistory.com
 Provides historical and biographical content
 We’re Related Application on Facebook
 Designed to help users find their family members, build a
family tree and share news and photos with family.
 There are 15,636,941 active users as of March 2009.
May 13, 2009
Enterprise Search Summit

3.  Founded in 2006 and includes several key members
of the original Ancestry.com team
 Has goal to be #2 genealogy company on web
 Currently has
12,000+ databases

1.2 billion names

25,000 subscribers

Enterprise Search Summit May 13, 2009

4. The Challenge
 Rapidly expanding data set to grow into the billions of
records
 Mixture of structured and unstructured data
 Indexing and search costs to handle this massive content
repository quickly escalate
 Increased customer traffic placing additional load on
query servers requiring additional servers and costs
How do I provide an affordable search
solution to handle the explosive data
growth?
May 13, 2009
Enterprise Search Summit

5. My Experience With Massive Data Sets
 Saw content repositories grow to
billions of records
 Saw millions spent on capital
expenditures on servers and data
centers
 Saw millions spent on annual server
maintenance and energy costs
May 13, 2009
Enterprise Search Summit

6. My Options
 Build proprietary search engine
 Buy a solution from an Enterprise Search Vendor
 Build a Lucene open source search platform
May 13, 2009
Enterprise Search Summit

7. Traditional Solution to Handle Massive Data Sets
Lots of servers!
Lots of money!
May 13, 2009
Enterprise Search Summit

8. Cluster Architecture
 Cluster made up of rows and columns of servers
 Determinants of cluster size
 Size of index
Determines number of columns

Amount of peak traffic (queries per second)

Determines the number of rows

May 13, 2009
Enterprise Search Summit

9. Index Size – Number of Columns
Index size = 80 gb = 5 columns
Query Servers needed = 5
Collation Server
Query Query Query Query
Query
Server Server Server Server
Server
8 GB 8 GB 8 GB 8 GB
8 GB
Assumptions:
Up to 50% of index (16 gb for each cluster) resides mostly in cache
QPS per server = 20 qps

10. Peak Traffic Load – Number of Columns
Index size = 20 G – 5 columns needed
Max Traffic Rate = 100 queries per second (QPS) – 10 rows needed
Query Servers needed = 5 columns x 10 rows = 50 servers
Collation Server
Query Server Query Server Query Server Query Server Query Server
Assumptions:
Server memory = 8 GB
Up to 50% of index resides in cache
QPS per server = 10 qps

11. WVR Server Configuration
Collation
Server
8 gb 8 gb 8 gb 8 gb 8 gb 8 gb 16 gb
800,000,000 records
Maximum Query volume system capacity = 7 queries per second
64 bit Windows based servers
Dual core CPUs
Enterprise Search Summit May 13, 2009

12. Future WVR Cluster Needs
 Projections show
 1+ terabyte of data (3.5 billion records)
 200 queries per second at peak load
Would require a cluster architecture of:
29 columns

40 rows

WVR would need 1,160 query servers!
Over $3.5 million in initial capital expenditure
Over $2.3 million in recurring yearly costs
May 13, 2009
Enterprise Search Summit

13. Search Challenges
 Many solutions work well with
 Low traffic
 Initial small data sets
 As data and traffic grows; however, so do the costs
and associated problems
Slow indexing times

Low queries per second capacity

Ranked search would have required a significant expansion of

servers to handle the increased search load
Required skilled staff to modify and optimize to handle growth

Enterprise Search Summit May 13, 2009

14. Enterprise Search Solution
May 13, 2009
Enterprise Search Summit

15. Perfect Search Approach
 Replace Existing Lucene
 Utilize PS Indexing
 Utilize PS Search Engine
 Match Business Rules
 Incorporate Near Exact modules
 Soundex, Metaphone
 Match or improve results
 Provide query results back to WVR for display
 Disk-based index
Enterprise Search Summit May 13, 2009

16. Data Growth Past Year
August 2008 May 2009 % Growth
Number of Records 800,000,000 1,200,000,000 50%
Number of Databases 9,000 12,000 33%
May 13, 2009
Enterprise Search Summit

17. Current WVR Perfect Search Server Configuration
Collation
Server
8 gb 8 gb 8 gb 8 gb 8 gb 8 gb 16 gb
1.2 billion records
12,000 databases
Maximum Query volume system capacity = 40 queries per second
5x faster!
64 bit Windows based servers
Dual core CPUs
Enterprise Search Summit May 13, 2009

18. Benefits to Worldvitalrecords.com
 Reduce indexing time to 1/100 of Lucene times
 Reduce query servers from 7 to 1
 Provided sub-second query response times
 Allows for continued dramatic customer growth
without significant server expansion
 Allow World Vital Records to compete with market
leaders at a fraction of the server capitalization and
maintenance costs
Enterprise Search Summit May 13, 2009

19. Future Growth Projections
 World Vital Records Growth Plans
 1+ terabyte (3 times growth in data)
 200 queries per second (20 times growth in customers)
Perfect Lucene
Search
Servers 20 1160
Server Capital Expenditure $60,000 $3,480,000
Recurring Power /Maintenance Costs $40,000 $2,320,000
May 13, 2009
Enterprise Search Summit

20. Questions?
Paul Allen, CEO, FamilyLink.com
paul@familylink.com
May 13, 2009
Enterprise Search Summit