Database Reference
In-Depth Information
400
Exact-count
Equi-width
Equi-depth
2500
Exact-sum
Equi-width
Equi-depth
350
300
2000
250
1500
200
1000
150
100
500
50
0
0
20 30 40 50 60 70 80 90 100
5
10
15
20
25
Number of linkages (1000)
Number of tuples (1000)
(a) Runtime vs. linkage size.
(b) Runtime vs. tuple size.
450
350
400
Exact-sum
Equi-width
Equi-depth
Exact-sum
Equi-width
Equi-depth
300
350
250
300
200
250
200
150
150
100
100
50
50
0
0
3
4
5
6
7
200
250
300
350
400
Degree
Number of components
(c) Runtime vs. degree.
(d) Runtime vs. component.
Fig. 7.13
Efficiency and scalability of
sum
query evaluation.
300
2500
Exact-min
Reuse
Reuse and pruning
Exact-min
Reuse
Reuse and pruning
250
2000
200
1500
150
1000
100
500
50
0
0
20
40
60
80
100
5
10
15
20
25
Number of linkages (1000)
Number of linkages (1000)
(a) Runtime vs. linkage size.
(b) Runtime vs. tuple size.
700
Exact-min
Reuse
Reuse and pruning
Exact-min
Reuse
Reuse and pruning
250
600
200
500
400
150
300
100
200
50
100
0
0
3
4
5
6
7
200
250
300
350
400
Degree
Number of components
(c) Runtime vs. degree.
(d) Runtime vs. component.
Fig. 7.14
Efficiency and scalability of
min
query evaluation.
minimal age of the patients appearing in both data sets?
For each linked pair, we
use the average ages in the Cancer Registry and the Social Security Death Index.
If we only consider the linked pairs whose probability pass the matching threshold
0
.
25, then the minimum age is 35. However, by considering all linked pairs whose
