CA2655735A1 - Data profiling - Google Patents

Data profiling Download PDF

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Publication number
CA2655735A1
CA2655735A1 CA 2655735 CA2655735A CA2655735A1 CA 2655735 A1 CA2655735 A1 CA 2655735A1 CA 2655735 CA2655735 CA 2655735 CA 2655735 A CA2655735 A CA 2655735A CA 2655735 A1 CA2655735 A1 CA 2655735A1
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Canada
Prior art keywords
data
field
values
fields
records
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CA 2655735
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French (fr)
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CA2655735C (en
Inventor
Joel Gould
Carl Feynman
Paul Bay
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Ab Initio Technology LLC
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Ab Initio Software Corporation
Joel Gould
Carl Feynman
Paul Bay
Ab Initio Software Llc
Architecture Llc
Ab Initio Technology Llc
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Publication of CA2655735A1 publication Critical patent/CA2655735A1/en
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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23—Updating
    • G06F16/2365—Ensuring data consistency and integrity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2453—Query optimisation
    • G06F16/24534—Query rewriting; Transformation
    • G06F16/24542—Plan optimisation
    • G06F16/24544—Join order optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24553—Query execution of query operations
    • G06F16/24554—Unary operations; Data partitioning operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24553—Query execution of query operations
    • G06F16/24554—Unary operations; Data partitioning operations
    • G06F16/24556—Aggregation; Duplicate elimination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/258—Data format conversion from or to a database
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/40—Data acquisition and logging

Abstract

Processing data includes profiling data from a data source, including reading the data from the data source, computing summary data characterizing the data while reading the data, and storing profile information that is based on the summary data. The data is then processed from the data source. This processing includes accessing the stored profile information and processing the data according to the accessed profile information.

Claims (82)

1. A method for processing data including:

profiling data from a data source, including reading the data from the data source, computing summary data characterizing the data while reading the data, and storing profile information that is based on the summary data; and processing the data from the data source, including accessing the stored profile information and processing the data according to the accessed profile information.
2. The method of claim 1 wherein processing the data from the data source further includes reading the data from the data source.
3. The method of claim 1 wherein profiling the data is performed without maintaining a copy of the data outside the data source.
4. The method of claim 3 wherein the data includes variable record structure records with at least one of a conditional field and a variable number of fields.
5. The method of claim 4 wherein computing summary data characterizing the data while reading the data includes interpreting the variable record structure records while computing summary data characterizing the data.
6. The method of claim 1 wherein the data source includes a data storage system.
7. The method of claim 6 wherein the data storage system includes a database system.
8. The method of claim 1 wherein computing the summary data includes counting a number of occurrences for each of a set of distinct values for a field.
9. The method of claim 8 wherein storing profile information includes storing statistics for the field based on the counted number of occurrences for said field.
10. The method of claim 1 further including maintaining a metadata store that contains metadata related to the data source
11. The method of claim 10 wherein storing the profile information includes updating the metadata related to the data source.
12. The method of claim 10 wherein profiling the data and processing the data each make use of metadata for the data source
13. The method of claim 1 wherein profiling data from the data source further includes determining a format specification based on the profile information.
14. The method of claim 1 wherein profiling data from the data source further includes determining a validation specification based on the profile information.
15. The method of claim 14 wherein processing the data includes identifying invalid records in the data based on the validation specification.
16. The method of claim 1 wherein profiling data from the data source further includes specifying data transformation instructions based on the profile information.
17. The method of claim 16 wherein processing the data includes applying the transformation instructions to the data.
18. The method of claim 1 wherein processing the data includes importing the data into a data storage subsystem.
19. The method of claim 18 wherein processing the data includes validating the data prior to importing the data into a data storage subsystem.
20. The method of claim 19 wherein validating the data includes comparing characteristics of the data to reference characteristics for said data.
21. The method of claim 20 wherein the reference characteristics include statistical properties of the data.
22. The method of claim 1 wherein profiling the data includes profiling said data in parallel, including partitioning the data into parts and processing the parts using separate ones of a first set of parallel components.
23. The method of claim 22 wherein profiling the data in parallel further includes computing the summary data for different fields of the data using separate ones of a second set of parallel components.
24. The method of claim 23 wherein profiling the data in parallel further includes repartitioning outputs of the first set of parallel components to form inputs for the second set of parallel components.
25. The method of claim 22 wherein profiling the data in parallel includes reading the data from a parallel data source, each part of the parallel data source being processed by a different one of the first set of parallel components.
26. A method for processing data including:

profiling data from a data source, including reading the data from the data source, computing summary data characterizing the data while reading the data, and storing profile information that is based on the summary data; wherein profiling the data includes profiling said data in parallel, including partitioning the data into parts and processing the parts using separate ones of a first set of parallel components.
27. Software including instructions adapted to perform all the method steps of any of claims 1 through 26 when executed on a data processing system.
28. The software of claim 27 embodied on a computer-readable medium.
29. A data processing system including:

a profiling module configured to read data from a data source, to compute summary data characterizing the data while reading the data, and to store profile information that is based on the summary data; and a processing module configured to access the stored profile information and to process the data from the data source according to the accessed profile information.
30. A data processing system including:

means for profiling data from a data source, including means for reading the data from the data source, means for computing summary data characterizing the data while reading the data, and means for storing profile information that is based on the summary data; and means for processing the data from the data source, including means for accessing the stored profile information and means for processing the data according to the accessed profile information.
31. A method for processing data including:

accepting information characterizing values of a first field in records of a first data source and information characterizing values of a second field in records of a second data source;

computing quantities characterizing a relationship between the first field and the second field based on the accepted information; and presenting information relating the first field and the second field.
32. The method of claim 31 wherein presenting the information includes presenting the information to a user.
33. The method of claim 31 wherein the first data source and the second data source are the same data source.
34. The method of claim 31 wherein at least one of the first data source and the second data source includes a database table.
35. The method of claim 31 wherein the quantities characterizing the relationship include quantities characterizing joint characteristics of the values of the first field and of the second field.
36. The method of claim 35 wherein the information characterizing the values of the first field includes information characterizing a distribution of values of said first field.
37. The method of claim 36 wherein the information characterizing the distribution of values of the first field includes plurality of data records, each associating a different value and a corresponding number of occurrences of said value in the first field in the first data source.
38. The method of claim 36 wherein the information characterizing the values of the second field includes information characterizing a distribution of values of said field.
39. The method of claim 38 wherein computing the quantities characterizing the joint characteristics includes processing the information characterizing the distribution of values of the first field and of the second field to compute quantities related to a plurality of categories of co-occurrence of values.
40. The method of claim 39 wherein the information characterizing the distribution of values of the first field and of the second field includes a plurality of data records, each associating a different value and a corresponding number of occurrences of said value and wherein processing the information characterizing said distributions of values includes computing information characterizing a distribution of values in a join of the first data source and the second data source on the first field and the second field, respectively.
41. The method of claim 39 wherein the quantities related to the plurality of categories of co-occurrence of values includes a plurality of data records, each associated with one of the categories of co-occurrence and including a number of unique values of the first and the second fields in said category.
42. The method of claim 35 wherein computing the quantities characterizing the joint characteristics of the values of the first field and the second field includes computing information characterizing a distribution of values in a join of the first data source and the second data source using the first field and the second field, respectively.
43. The method of claim 35 wherein computing the quantities characterizing the joint characteristics of the values of the first field and the second field includes computing quantities related to a plurality of categories of co-occurrence of values.
44. The method of claim 42 wherein the categories of co-occurrence of values includes values that occur at least once in one of the first field and the second field but not in the other of said fields.
45. The method of claim 42 wherein the categories of co-occurrence of values includes values that occur exactly once in each of the first field and the second field.
46. The method of claim 42 wherein the categories of co-occurrence of values includes values that occur exactly once in one of the first field and the second field and more than once in the other of said fields.
47. The method of claim 42 wherein the categories of co-occurrence of values includes values that occur more than once in each of the first field and the second field.
48. The method of claim 35 further including the steps of accepting information characterizing values and computing quantities characterizing joint characteristics of the values are repeated for a plurality of pairs of first and second fields.
49. The method of claim 48 wherein each of the plurality of pairs of fields has a unique identifier that is included with values in the pairs of fields to compute the quantities characterizing the joint characteristics of the values.
50. The method of claim 48 further including presenting information relating the fields of one or more of the plurality of pairs of fields.
51. The method of claim 50 wherein presenting the information relating the fields of one or more of the plurality of pairs of fields includes identifying fields as candidate fields of one of a plurality of types of relationships of fields.
52. The method of claim 51 wherein the plurality of types of relationships of fields includes a primary key and foreign key relationship.
53. The method of claim 51 wherein the plurality of types of relationships of fields includes a common domain relationship.
54. The method of claim 31 wherein computing the quantities includes computing said quantities based on logical values that are converted from literal values of the first field and of the second field.
55. The method of claim 37 wherein computing the quantities includes computing said quantities in parallel, including partitioning the data records into parts and processing the parts using separate ones of a set of parallel components.
56. The method of claim 55 wherein the parts are based on values of the first field and of the second field.
57. The method of claim 56 wherein data records having the same value are in the same part.
58. Software including instructions adapted to perform all the method steps of any of claims 31 through 57 when executed on a data processing system.
59. The software of claim 58 embodied on a computer-readable medium.
60. A system for processing data including:

a values processing module configured to accept information characterizing values of a first field in records of a first data source and information characterizing values of a second field in records of a second data source;

a relationship processing module configured to compute quantities characterizing a relationship between the first field and the second field based on the accepted information;

an interface configured to present information relating the first field and the second field.
61. A system for processing data including:

means for accepting information characterizing values of a first field in records of a first data source and information characterizing values of a second field in records of a second data source;

means for computing quantities characterizing a relationship between the first field and the second field based on the accepted information;

means for presenting information relating the first field and the second field.
62. A method for processing data including:

identifying a plurality of subsets of fields of data records of a data source;

determining co-occurrence statistics for each of the plurality of subsets; and identifying one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset.
63. The method of claim 62 wherein at least one of the subsets of fields is a subset of two fields.
64. The method of claim 62 wherein identifying one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset includes identifying one or more of the plurality of subsets as having one of a plurality of possible predetermined functional relationships.
65. The method of claim 62 wherein determining the co-occurrence statistics includes forming data elements each identifying a pair of fields and identifying a pair of values occurring in the pair of fields in one of the data records.
66. The method of claim 62 wherein determining the co-occurrence statistics includes:

partitioning the data records into parts, the data records having a first field and a second field;

determining a quantity based on a distribution of values that occur in the second field of one or more records in a first of the parts, the one or more records having a common value occurring in a first field of the one or more records; and combining the quantity with other quantities from records in other of the parts to generate a total quantity.
67. The method of claim 66 wherein identifying one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset includes identifying a functional relationship between the first and second fields based on the total quantity.
68. The method of claim 66 wherein the parts are based on values of the first field and of the second field.
69. The method of claim 66 wherein the parts are processed using separate ones of a set of parallel components.
70. The method of claim 62 wherein identifying one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset includes determining a degree of match to said functional relationship.
71. The method of claim 70 wherein the degree of match includes a number of exceptional records that are not consistent with said functional relationship.
72. The method of claim 62 wherein the functional relationship includes a mapping of at least some of the values of a first field onto at least some of the values of a second field.
73. The method of claim 72 wherein the mapping is a many-to-one mapping.
74. The method of claim 72 wherein the mapping is a one-to-many mapping.
75. The method of claim 72 wherein the mapping is a one-to-one mapping.
76. The method of claim 62 further including filtering the plurality of subsets based on information characterizing values in fields of the plurality of subsets.
77. The method of claim 62 wherein the data records include records of a database table.
78. The method of claim 77 wherein the data records include records of a plurality of database tables.
79. Software including instructions adapted to perform all the method steps of any of claims 62 through 78 when executed on a data processing system.
80. The software of claim 79 embodied on a computer-readable medium.
81. A system for processing data including:

an identification processing module configured to identify a plurality of subsets of fields of data records of a data source;

a statistics processing module configured to determine co-occurrence statistics for each of the plurality of subsets; and a functional relationship processing module configured to identify one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset.
82. A system for processing data including:

means for identifying a plurality of subsets of fields of data records of a data source;
means for determining co-occurrence statistics for each of the plurality of subsets; and means for identifying one or more of the plurality of subsets as having a functional relationship among the fields of the identified subset.
CA2655735A 2003-09-15 2004-09-15 Data profiling Active CA2655735C (en)

Applications Claiming Priority (7)

Application Number Priority Date Filing Date Title
US50290803P 2003-09-15 2003-09-15
US60/502,908 2003-09-15
US51303803P 2003-10-20 2003-10-20
US60/513,038 2003-10-20
US53295603P 2003-12-22 2003-12-22
US60/532,956 2003-12-22
CA002538568A CA2538568C (en) 2003-09-15 2004-09-15 Data profiling

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CA2655735A1 true CA2655735A1 (en) 2005-03-31
CA2655735C CA2655735C (en) 2011-01-18

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CA2655731A Active CA2655731C (en) 2003-09-15 2004-09-15 Functional dependency data profiling

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US (5) US7849075B2 (en)
EP (3) EP2261820A3 (en)
JP (3) JP5328099B2 (en)
KR (4) KR20090039803A (en)
CN (1) CN102982065B (en)
AT (1) ATE515746T1 (en)
AU (3) AU2004275334B9 (en)
CA (3) CA2538568C (en)
HK (1) HK1093568A1 (en)
WO (1) WO2005029369A2 (en)

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