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Index ing and Fast   Search engine  NBITSearch parameters www.nbitsearch.com Novosib-BIT LLC version  1.03.3
NBITSearch System NBITSearch is a search engine with an open   API . ---------------------------   NBITSearch  is  a  programme kernel   for ―   Database Management Systems ,  - ―  Warehouses   of Large Data,  - ―  Search Systems applied to any Objects . .
The System is Designed for ,[object Object],high-speed   exact   and   fuzzy   search  for objects   with   minimum   use   of RAM . for
Exact   and   Fuzzy Search Interval queries  provide    fuzzy   ( inexact )   search .     Precise   ( exact )   search  is   a particular case of   fuzzy   search .
Indexable   Objects Objects  S of any types  T
The system   indexes objects  S of any   types  T simultaneously by  a  set any functions   F (S) . Multifunctionality
Sizes of Indexable Arrays The most tangible effect in the speed of search is shown for such arrays of   objects , which support ≈ 50  ÷  100  million and more objects   for one index.  A size of arrays of   indexable objects   can be   1 0  ÷  100  terabyte and larger .
Indexing Limitations One index supports ≈ 2  billion of its   objects . Limitations of   number of   indexes   are   artificial .
What is a Billion? 1  billion   seconds   is ≈ 32  years . 1  billion pages for   a laser   printer   is     a pile with a   height   of  ≈ 100  km .
Indexing Speed Estimator : T  ~  ( N )  * LOG (N) T   –  time of forming one index , N  – number of indexable objects .
Compactness of Indexes A size of one index can vary within the range of   0 . 1 %  ÷  5 . 0 % of the size of indexable objects .
Search Speed Time estimation of defining the   address   of the first potential   block of data :   T  ~  LOG (N)     T  –  time of   “logic   probing” , N  – number of   indexed objects .
Search Speed A speed of fetching the result of interval queries from a hard disk   can be 10  ÷  100  times higher than   (for the large data array) , the speed of   similar   operation   in a standard relational   DBMS .
Search Speed A speed of fetching the result of interval queries from a hard disk   can be   1000  times  ( and more )  higher than (for the large data array) ,   the   speed   of similar   operation when solving the problems with the use of brute force method .
Search Speed A time of fetching    the result of interval queries from a hard disk depends   linearly   on objects number in result set .
Search Memory Due to compactness of indexes   the system loads each of them   in RAM entirely   before queries are made .
Search Memory A size of memory buffers to fetch the   data   depends on   user’s   needs . This size is often infinitesimal (~10 megabyte) .
Reading of Result Set Reading the result set from a hard disk   to RAM   is   optimum : magnetic head does not oscillate .
THANK YOU ! www.nbitsearch.com Technology developed with support from  FASIE formed by the Government of Russian Federation Novosib-BIT LLC  ©  2004 - 201 1 Patented

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NBITSearch. Features.

  • 1. Index ing and Fast Search engine NBITSearch parameters www.nbitsearch.com Novosib-BIT LLC version 1.03.3
  • 2. NBITSearch System NBITSearch is a search engine with an open API . --------------------------- NBITSearch is a programme kernel for ― Database Management Systems , - ― Warehouses of Large Data, - ― Search Systems applied to any Objects . .
  • 3.
  • 4. Exact and Fuzzy Search Interval queries provide fuzzy ( inexact ) search . Precise ( exact ) search is a particular case of fuzzy search .
  • 5. Indexable Objects Objects S of any types T
  • 6. The system indexes objects S of any types T simultaneously by a set any functions F (S) . Multifunctionality
  • 7. Sizes of Indexable Arrays The most tangible effect in the speed of search is shown for such arrays of objects , which support ≈ 50 ÷ 100 million and more objects for one index. A size of arrays of indexable objects can be 1 0 ÷ 100 terabyte and larger .
  • 8. Indexing Limitations One index supports ≈ 2 billion of its objects . Limitations of number of indexes are artificial .
  • 9. What is a Billion? 1 billion seconds is ≈ 32 years . 1 billion pages for a laser printer is a pile with a height of ≈ 100 km .
  • 10. Indexing Speed Estimator : T ~ ( N ) * LOG (N) T – time of forming one index , N – number of indexable objects .
  • 11. Compactness of Indexes A size of one index can vary within the range of 0 . 1 % ÷ 5 . 0 % of the size of indexable objects .
  • 12. Search Speed Time estimation of defining the address of the first potential block of data : T ~ LOG (N) T – time of “logic probing” , N – number of indexed objects .
  • 13. Search Speed A speed of fetching the result of interval queries from a hard disk can be 10 ÷ 100 times higher than (for the large data array) , the speed of similar operation in a standard relational DBMS .
  • 14. Search Speed A speed of fetching the result of interval queries from a hard disk can be 1000 times ( and more ) higher than (for the large data array) , the speed of similar operation when solving the problems with the use of brute force method .
  • 15. Search Speed A time of fetching the result of interval queries from a hard disk depends linearly on objects number in result set .
  • 16. Search Memory Due to compactness of indexes the system loads each of them in RAM entirely before queries are made .
  • 17. Search Memory A size of memory buffers to fetch the data depends on user’s needs . This size is often infinitesimal (~10 megabyte) .
  • 18. Reading of Result Set Reading the result set from a hard disk to RAM is optimum : magnetic head does not oscillate .
  • 19. THANK YOU ! www.nbitsearch.com Technology developed with support from FASIE formed by the Government of Russian Federation Novosib-BIT LLC © 2004 - 201 1 Patented