Method of generating attribute cardinality maps

• US 6,865,567 B1
• Filed: 01/19/2000
• Issued: 03/08/2005
• Est. Priority Date: 07/30/1999
• Status: Expired due to Term

• Current Assignee: Basantkumar John Oommen, Murali Thiyagarajah
• Original Assignee: Basantkumar John Oommen, Murali Thiyagarajah
• Inventors: Oommen, Basantkumar John, Thiyagarajah, Murali
• Primary Examiner(s): Metjahic, Safet
• Assistant Examiner(s): AL HASHEMI, SANA A
• Application Number:
  US09/487,328
• Time in Patent Office: 1,875 Days
• Field of Search: 707/104.1, 707/102, 707/2, 707/1, 707/100
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24542 Plan optimisation
• CPC Class Codes: G06F 16/24545 Selectivity estimation or determination
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing

Abstract

This invention provides a novel means for creating a histogram for use in minimizing response time and resource consumption when optimizing a query in a database, and other like structures, the histogram being created by placing ordered elements into specific range until the next element to be considered for inclusion in the range is a predetermined distance from the (generalized) mean value associated with the elements within the range, whereupon that next element is placed in the following range. Similarly, the following ranges are closed when the next element to be considered for inclusion in the range is greater than a predetermined distance from the (generalized) mean value associated with the elements in that range, whereupon that next element is placed in the following range. For each range, the location and size of the range is recorded with, for example, the mean value, the slope or other attribute characterizing one or more elements in the range. The invention has also applications in pattern recognition, message routing, and in actuarial sciences.

Claims

1. A computer-implemented method for estimating the computational efficiency of a search within a database comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements from the database and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range, each of the at least one range having at least an element, an arithmetic mean of each range equal to the arithmetic mean of the values associated with the at least an element within said range, a specific range from the at least one range comprising a plurality of elements from the data set adjacent each other within the defined order, wherein the arithmetic mean of the specific range is within a predetermined maximum distance from a value associated with an element within the specific range, the predetermined maximum distance being independent of the number of elements within the specific range and their associated values;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing said value related to an estimate of a value associated with an element within the range and data relating to the size and location of the range, to provide a histogram of said value associated with an element within the range and data relating to the size and location of the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

2. A method as defined in claim 1 wherein the at least one range comprises a plurality of ranges, and wherein some ranges from the plurality of ranges have a different number of elements and some ranges from the plurality of ranges have different areas, an area of each range equal to the product of the arithmetic mean of said range and the number of elements within said range.

3. A method as defined in claim 2 wherein the step of determining the at least one range is performed so as to limit variance between the values associated with the elements within a same range from the at least one range, the limitation forming further data of the histogram.

4. A method as defined in claim 3 wherein a value associated with each element within a range from the at least one range is within $\varepsilon$

=

τ

⁡

[ln⁡

(li-1)]-1

where τ

is the tolerance value used in generating the R-ACM and i is the location of the element within a histogram sector of length l.

5. A method as defined in claim 3 wherein the at least a value related to an estimate of a value for an element within the range includes a value relating to the arithmetic mean, and wherein the at least data relating to the range comprises data relating to both endpoints of the range.

6. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. using a suitably programmed processor, defining a first bin as a current bin;

b. using the suitably programmed processor, selecting an element and adding it to the current bin as the most recently added element to the current bin;

c. selecting an element from within the data set, the selected element not within a bin and adjacent the most recently added element;

d. determining at least a mean of the values associated with elements within the bin;

e. when the most recently selected element differs from a mean from the at least a mean by an amount less than a predetermined amount, adding the most recently selected element to the current bin as the most recently added element to the current bin and returning to step (c);

f. when the selected element differs from the mean from the at least a mean by an amount more than the predetermined amount, creating a new bin as the current bin and adding the selected element to the new bin as the most recently added element to the current bin and returning to step (c); and

,

g. providing data relating to each bin including data indicative of a range of elements within each bin as the determined at least one range.

7. A method as defined in claim 6 comprising the step of:

providing a value, τ

, of the predetermined maximum distance.

8. A method as defined in claim 6 wherein the at least a mean comprises an arithmetic mean and wherein the mean from the at least a mean is the arithmetic mean.

9. A method as defined in claim 6 wherein adjacent elements are selected from a start location within the data set in order sequentially toward an end of the data set.

10. A method as defined in claim 6 wherein adjacent elements are selected from a start location in an alternating fashion toward a beginning of the data set and toward an end of the data set.

11. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. selecting an element from within the data set;

b. determining a bin with which to associate the element;

c. when the determined bin is empty, adding the element to the bin;

d. when the determined bin is other than empty, determining at least a mean of the values associated with elements within the determined bin;

e. when the most recently selected element differs from a mean from the at least a mean by an amount less than a predetermined amount, adding the most recently selected element to the determined bin and returning to step (a);

f. when the selected element differs from the mean from the at least a mean by an amount more than the predetermined amount, adding the selected element to the determined bin and dividing the determined bin into one of two bins and three bins, one of which includes the selected element and returning to step (a); and

,

g. providing data relating to each bin including data indicative of a range of elements within the bin.

12. A method as defined in claim 11 wherein the at least a mean comprises an arithmetic mean and wherein the mean from the at least a mean is the arithmetic mean.

13. A method as defined in claim 12 comprising the step of:

determining a first arithmetic mean of a first selected bin;

determining a second arithmetic mean of a second selected bin adjacent the first selected bin;

comparing the first and second arithmetic means; and

, when the arithmetic means are within a predetermined distance of each other, merging the first selected bin and the second selected bin to form a single merged bin including all the elements of the first selected bin and all the elements of the second selected bin.

14. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. using a suitably programmed processor, defining a first bin as a current bin;

b. using the suitably programmed processor, selecting an element and adding it to the current bin as the most recently added element to the current bin;

c. selecting elements adjacent the most recently added element(s);

d. determining a first mean of the values associated with elements within the bin and determining a second mean of the selected elements;

e. when the second mean differs from the first mean by an amount less than a predetermined amount, adding the most recently selected elements to the current bin as the most recently added elements and returning to step (c);

f. when the second mean differs from the first mean by an amount more than the predetermined amount, creating a new bin as the current bin and adding at least one of the selected elements to the new bin as the most recently added element(s) to the current bin and returning to step (c); and

,

g. providing data relating to each bin including data indicative of a range of elements within the bin.

15. A method as defined in claim 14 wherein the step of (f) includes the steps of:

(F1) determining a first element within the selected elements to add to the new current bin;

(F2) adding the selected element(s) before the first element to the previous current bin; and

,

(F3) adding the selected element(s) from and including the first element to the new current bin.

16. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. using a suitably programmed processor, defining a first bin as a current bin;

b. using the suitably programmed processor, selecting an element and adding it to the current bin as the most recently added element to the current bin;

c. selecting an element from within the data set, the selected element not within a bin and adjacent the most recently added element;

d. determining the Generalized positive-2 mean of the current bin as the sum of the squares of the values associated with elements within the bin divided by the number of the elements within the bin and taking the square root of the resulting quotient;

e. determining the Generalized negative-2 mean of the current bin as the sum of the square-roots of the values associated with element within the bin divided by the number of the elements within the bin and squaring the resulting quotient;

f. when the value associated with the selected element is lower than the said Generalized positive-2 mean, determining a difference between the value associated with the selected element and the said Generalized positive-2 mean, and when the value associated with the selected element is higher than the said Generalized negative-2 mean, determining a difference between the value associated with the selected element and the said Generalized negative-2 mean;

g. when a difference is other than greater than the predetermined amount, adding the selected element to the current bin as the most recently added element to the current bin and returning to step (c);

h. when a difference is greater than the predetermined amount, defining a new bin as the current bin, adding the selected element to the current bin as the most recently added element to the current bin, and returning to step (c); and

,

i. providing data relating to each bin including data indicative of a range of elements within each bin as the determined at least one range.

17. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. using a suitably programmed processor, defining a first bin as a current bin;

b. using the suitably programmed processor, selecting an element and adding it to the current bin as the most recently added element to the current bin;

c. selecting an element from within the data set, the selected element not within a bin and adjacent the most recently added element;

d. determining the Generalized positive-k mean of the current bin for a predetermined k as the sum of the k^th powers of the values associated with elements within the bin divided by the number of the elements within the bin and taking the k^th root of the resulting quotient;

e. determining the Generalized negative-k mean of the current bin as the sum of the k^th roots of the values associated with elements within the bin divided by the number of the elements within the bin and raising the quotient to the k^th power;

f. when the value associated with the selected element is lower than the said Generalized positive-k mean, determining a difference between the value associated with the selected element and the said Generalized positive-k mean, and when the value associated with the selected element is higher than the said Generalized negative-k mean, determining a difference between the value associated with the selected element and the said Generalized negative-k mean;

g. when a difference is other than greater than the predetermined amount, adding the selected element to the current bin as the most recently added element to the current bin and returning to step (c);

h. when a difference is greater than the predetermined amount, defining a new bin as the current bin, adding the selected element to the current bin as the most recently added element to the current bin, and returning to step (c); and

,

i. providing data relating to each bin including data indicative of a range of elements within each bin as the determined at least one range.

18. A method as defined in claim 3 wherein the step of determining at least one range comprises the steps of:

a. using a suitably programmed processor, defining a first bin as a current bin;

b. using the suitably programmed processor, selecting an element and adding it to the current bin as the most recently added element to the current bin;

c. selecting an element from within the data set, the selected element not within a bin and adjacent the most recently added element;

d. determining a current largest value as the largest of the values associated with elements within the bin;

e. determining a current smallest value as the smallest of the values associated with elements within the bin;

f. when the value associated with the selected element is lower than the current largest value, determining a difference between the value associated with the selected element and the current largest value, and when the value associated with the selected element is higher than the current smallest value, determining a difference between the value associated with the selected element and the current smallest value;

g. when a difference is other than greater than the predetermined amount, adding the selected element to the current bin as the most recently added element to the current bin and returning to step (c);

h. when a difference is greater than the predetermined amount, defining a new bin as the current bin, adding the selected element to the current bin as the most recently added element to the current bin, and returning to step (c); and

,

i. providing data relating to each bin including data indicative of a range of elements within each bin as the determined at least one range.

19. A method as defined in claim 18 wherein the predetermined amount is equal to 2(τ

).

20. A method as defined in claim 1 wherein the step of determining at least one range comprises the steps of:

a. selecting a group of elements within the data set and adjacent one another within the ordering;

b. determining a mean of the values associated with each selected element within the selected group of elements;

c. comparing a value associated with each selected element in the group to the mean value to determine a difference;

d. when a value is different from the mean by more than a predetermined amount, returning to step (a); and

,

e. when all values are different from the mean by less than or equal to the predetermined amount, creating a bin including the selected group of elements and returning to step (a).

21. A method as defined in claim 20 comprising the steps of

(F1) selecting an element adjacent the bin including the selected group of elements, the selected element other than an element within a bin;

(F2) determining a mean of the values associated with each element within the bin and the selected element; and

(F3) when the value of the selected element differs from the mean by less than or equal to the predetermined amount, adding the selected element to the bin and returning to step (F3).

22. A method as defined in claim 1 comprising the step of:

providing the mean associated with the range as an estimate of a value associated with an element within said range.

23. A method as defined in claim 22 comprising the step of:

estimating a reliability of the estimated value.

24. A method as defined in claim 23 wherein the estimated value is used for estimating the computational efficiency of a search within a database.

25. A method as defined in claim 1 comprising the step of:

estimating a value associated with a selected range of elements as a sum of the products of the arithmetic mean for each range and a number of elements within both the range and the selected range.

26. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements from the database and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range, each of the at least one range having at least an element, an arithmetic mean of each range equal to the arithmetic mean of the values associated with the at least an element within said range, a specific range from the at least one range comprising a plurality of elements from the data set adjacent each other within the defined order, wherein the arithmetic mean of the specific range is within a predetermined maximum distance from a value associated with an element within the specific range, the predetermined maximum distance independent of the number of elements within the specific range and their associated values;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing at least a value related to an estimate of a value associated with an element within the range and at least data relating to the size and location of the range;

b. determining a routing table in dependence upon the histogram; and

,

c. estimating a value for use in network routing in dependence upon the routing table.

27. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements from the database and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range, each of the at least one range having at least an element, an arithmetic mean of each range equal to the arithmetic mean of the values associated with the at least an element within said range, a specific range from the at least one range comprising a plurality of elements from the data set adjacent each other within the defined order, wherein the arithmetic mean of the specific range is within a predetermined maximum distance from a value associated with an element within the specific range, the predetermined maximum distance independent of the number of elements within the specific range and their associated values;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing at least a value related to an estimate of a value associated with an element within the range and at least data relating to the size and location of the range;

b. providing the mean associated with the range as an estimate of a value associated with an element within said range; and

c. using the estimate for determining an approach to searching within a plurality of different databases given a predetermined limited time for conducting the search, wherein the approach is selected to approximately maximise the probability of successfully completing the search.

28. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining a plurality of ranges, each of the plurality of ranges having at least an element, a known statistical correlation existing between values associated with elements in a same range, some ranges from the plurality of ranges comprising a plurality of elements from the data set adjacent each other within the defined order, the statistical correlation for those ranges indicative of a maximum error between an estimated value associated with an element within the range and the value associated with the element, the maximum error other than the difference between the total area of the range and the estimated value, wherein an area of each range is equal to the product of the arithmetic mean of said range and the number of elements within said range;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing at least a value related to an estimate of a value associated with an element within the range and at least data relating to the size and location of the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

29. A method as defined in claim 28 wherein a range from the some ranges define a range of values associated with elements within the range, and wherein the range of values has a maximum upper limit and a minimum lower limit, the lower limit other than zero and the upper limit other than the area of the range.

30. A method as defined in claim 29 wherein a value associated with each element within a range from the some ranges is within a known maximum error of an estimated value for that element and wherein the maximum error is different for some elements in a same range than for others.

31. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range having a length such that the value associated with at least one element within the range is within a predetermined maximum distance of at least one other element within the range;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing at least a value related to an estimate of a value associated with an element within the range and at least data relating to the size and location of the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

32. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range having a length such that the value associated with every element within the range is within a predetermined maximum distance of every other element within the range;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. for each range storing at least a value related to an estimate of a value associated with an element within the range and at least data relating to the size and location of the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

33. A computer readable program storage medium, the medium embodying one or more instructions executable by the computer to perform method steps, the method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining at least one range, each of the at least one range having at least an element, an arithmetic mean of each range equal to the arithmetic mean of the values associated with the at least an element within said range, a specific range from the at least a range comprising a plurality of elements from the data set adjacent each other within the defined order, wherein the arithmetic mean of the specific range is within a predetermined maximum distance from a value associated with an element within the specific range, the predetermined maximum distance independent of the number of elements within the specific range and their associated values;

iii. determining at least a value related to an estimate of a value associated with an element within the range; and

iv. storing for each range at least a value related to the mean and at least data relating to the size and location of the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

34. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. determining a range within the data set, the range comprising a plurality of elements from the data set and adjacent within the order; and

,

iii. storing a plurality of values indicative of a straight line defining an approximate upper boundary of the values associated with each element within the range, the straight line indicating different values for different elements within the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

35. A method as defined in claim 34 wherein the range has a mean equal to the mean of the values associated with the plurality of elements within said range and an area of the range equal to the product of the mean of said range and the number of elements within said range;

and comprising the steps of;

iv. providing a value associated with specific elements within the range; and

v. determining a straight line approximating the determined value for each of the specific elements and having an area therebelow determined according to the value of the straight line at the first element in the range plus the value of the straight line at the last element in the range which sum is multiplied by the number of elements within the range divided by 2, the area below the straight line being approximately equal to the area of the range.

36. A method as defined in claim 35 comprising the steps of:

vi. providing a second range within the data set, the second range adjacent the first range and comprising a plurality of elements from the data set and adjacent within the order, the provided second range having a mean equal to the mean of the values associated with the at least an element within said range and an area of the range equal to the product of the mean of said range and the number of elements within said range;

vii. providing a value associated with specific elements within the second range;

viii. determining a second straight line approximating the determined value for each of the specific elements within the second range and having an area therebelow determined according to the value of the second straight line at the first element in the second range plus the value of the second straight line at the last element in the second range which sum is multiplied by the number of elements within the second range divided by 2, the area below the straight line being approximately equal to the area of the second range; and

, storing a plurality of values indicative of the second straight line.

37. A method as defined in claim 36 wherein the step of determining the straight line and of determining the second straight line are performed such that the adjacent endpoints of the first straight line and the second straight line are a same point.

38. A method as defined in claim 37 wherein the step of determining the second straight line is performed in dependence upon the endpoint of the first straight line adjacent the second range.

39. A method as defined in claim 35 wherein the step of determining a range is performed so as to limit variance between values associated with elements in the range and the straight line, the limitation forming further statistical data of the histogram.

40. A method as defined in claim 39 wherein the step of determining a range is performed so as to limit average error between some values associated with elements in the range and the straight line.

41. A method as defined in claim 39 wherein the step of determining a range is performed so as to limit least squared error between some values associated with elements in the range and the straight line.

42. A method as defined in claim 34 wherein the plurality of values are indicative of a range beginning, a range ending, a value at the range beginning and a value at the range ending.

43. A method as defined in claim 42 wherein the plurality of values includes data for determining a straight line approximating the values associated with elements within the range, and differing therefrom by an amount less than a known amount less than each associated value.

52. A method as defined in claim 34 comprising the step of estimating a value associated with an element based on the location of the straight line at the element.

59. A method as defined in claim 34 comprising the step of estimating a value associated with a selected range of elements as a sum of areas below the straight lines for portions of ranges within the selected range.

44. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. providing a range within the data set, the range comprising a plurality of elements from the data set and adjacent within the order;

iii. determining a straight line indicating different values for different elements within the range; and

,

iv. storing a plurality of values indicative of a straight line defining an approximate upper boundary of the values associated with each element within the range, the straight line indicating different values for different elements within the range; and

b. using the histogram of data for estimating the computational efficiency of a search within a database.

45. A method as defined in claim 44 wherein the provided range has a mean equal to the mean of the values associated with the at least an element within said range and an area of the range equal to the product of the mean of said range and the number of elements within said range;

and wherein the step (iii) comprises the steps of;

(iii1) providing a value associated with specific elements within the range; and

,

(iii2) determining a straight line approximating the determined value for each of the specific elements and having an area therebelow determined according to the value of the straight line at the first element in the range, plus the value of the straight line at the last element in the range which sum is multiplied by the number of elements within the range divided by 2, the area below the straight line being approximately equal to the area of the range.

46. A method as defined in claim 45 comprising the steps of:

v. providing a second range within the data set, the second range adjacent the first range and comprising a plurality of elements from the data set and adjacent within the order, the provided second range having a mean equal to the mean of the values associated with the at least an element within said range and an area of the range equal to the product of the mean of said range and the number of elements within said range;

vi. providing a value associated with specific elements within the second range;

vii. determining a second straight line approximating the determined value for each of the specific elements within the second range and having an area therebelow determined according to the value of the second straight line at the first element in the second range, plus the value of the second straight line at the last element in the second range which sum is multiplied by the number of elements within the second range divided by 2, the area below the straight line approximately equal to the area of the second range; and

, storing a plurality of values indicative of the second straight line.

47. A method as defined in claim 46 wherein the step of determining the straight line and of determining the second straight line are performed such that the adjacent endpoints of the first straight line and the second straight line are a same point.

48. A method as defined in claim 47 wherein the step of determining the second straight line is performed in dependence upon the endpoint of the first straight line adjacent the second range.

49. A method as defined in claim 48 wherein the step of determining the straight line is performed so as to limit variance between values associated with elements in the range and the straight line, the limitation forming further statistical data of the histogram.

50. A method as defined in claim 49 wherein the step of determining the straight line is performed so as to limit average error between some values associated with elements in the range and the straight line.

51. A method as defined in claim 49 wherein the step of determining the straight line is performed so as to limit least squared error between some values associated with elements in the range and the straight line.

54. A method as defined in claim 44 comprising the step of estimating a value associated with an element based on the location of the straight line at the element.

55. A method as defined in claim 54 comprising the step of estimating a reliability of the estimated value.

56. A method as defined in claim 54 comprising the step of using the estimated value, estimating the computational efficiency of a search within a database.

60. A method as defined in claim 44 comprising the step of estimating a value associated with a selected range of elements as a sum of areas below the straight lines for portions of ranges within the selected range.

57. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. providing a range within the data set, the range comprising a plurality of elements from the data set and adjacent within the order;

iii. determining a straight line indicating different values for different elements within the range; and

,

iv. storing a plurality of values indicative of a straight line defining an approximate upper boundary of the values associated with each element within the range, the straight line indicating different values for different elements within the range;

b. determining a routing table in dependence upon the histogram; and

,

c. determining an estimate of a value within the routing table for determining a network routing.

53. A method as defined in claim 57 comprising the step of estimating a reliability of the estimated value.

58. A computer-implemented method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. providing a range within the data set, the range comprising a plurality of elements from the data set and adjacent within the order;

iii. determining a straight line indicating different values for different elements within the range; and

,

iv. storing a plurality of values indicative of a straight line defining an approximate upper boundary of the values associated with each element within the range, the straight line indicating different values for different elements within the range;

b. estimating a value associated with an element based on the location of the straight line at the element; and

c. using the estimate for determining an approach to searching within a plurality of different databases given a predetermined limited time for conducting the search, wherein the approach is determined to approximately maximise the probability of successfully completing the search.

61. A computer readable program storage medium, the medium embodying one or more instructions executable by the computer to perform method steps, the method comprising the steps of:

a. generating a histogram of data, comprising the steps of;

i. providing a data set representing a plurality of elements and a value associated with each element, the data set having a property defining an order of the elements therein;

ii. providing a range within the data set, the range comprising a plurality of elements from the data set and adjacent within the order;

iii. determining a straight line indicating different values for different elements within the range; and

,

iv. storing a plurality of values indicative of a straight line defining an approximate upper boundary of the values associated with each element within the range, the straight line indicating different values for different elements within the range and

b. using the histogram of data for estimating the computational efficiency of a search within a database.