EP2742444A1 - Holistic database record repair - Google Patents
Holistic database record repairInfo
- Publication number
- EP2742444A1 EP2742444A1 EP12726383.8A EP12726383A EP2742444A1 EP 2742444 A1 EP2742444 A1 EP 2742444A1 EP 12726383 A EP12726383 A EP 12726383A EP 2742444 A1 EP2742444 A1 EP 2742444A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- records
- database
- duplicate
- dependency
- computer program
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- 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
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- 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
-
- 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
Definitions
- the present invention relates to holistic database record repair. BACKGROUND
- a database is a collection of information arranged in an organized manner.
- a typical database might include medical, financial or accounting information, demographics and market survey data, bibliographic or archival data, personnel and organizational information, public governmental records, private business or customer data such as addresses and phone numbers, etc.
- Such information is usually contained in computer files arranged in a pre-selected database format, and the data contents within them can be maintained for convenient access on magnetic media, both for storage and for updating the file contents as needed.
- Poor data quality can have undesirable implications for the effectiveness of a business or other organization or entity. For example, in healthcare, where incorrect information about patients in an Electronic Health Record (EHR) may lead to wrong treatments and prescriptions, ensuring the accuracy of database entries is of prime importance.
- EHR Electronic Health Record
- a computer implemented method for repairing records of a database comprising determining a first set of records of the database which violate a functional dependency of the database, determining a second set of records of the database comprising duplicate records, computing a cost metric representing a measure for the cost of mutually dependency modifying records in the first and second sets;
- Duplicate records can be determined using a duplication mechanism to group duplicate records into respective clusters, wherein records within respective ones of the clusters represent the same entity.
- a set of equivalence classes for records of the first and second sets consisting of multiple record-attribute pairs can be determined.
- attribute values for records in respective ones of the equivalence classes are the same in the modified database instance.
- a pair of equivalence classes can be merged into a new class to resolve a functional dependency violation or to perform a deduplication.
- the first set of records of the database which violate a functional dependency of the database can be refreshed as can the second set of records of the database comprising duplicate records as a result of the step of merging.
- a computer implemented method for generating a set of updates for a database including multiple records comprising performing a duplicate-record-aware repair of functional dependency violations for records of the database, and performing a functional-dependency-aware deduplication of records of the database.
- a computer program embedded on a non-transitory tangible computer readable storage medium including machine readable instructions that, when executed by a processor, implement a method for updating a database comprising determining a first set of records of the database which violate a functional dependency of the database, determining a second set of records of the database comprising duplicate records, computing a cost metric representing a measure for the cost of mutually dependency modifying records in the first and second sets, modifying records in the first and second sets on the basis of the cost metric to provide a modified database instance.
- Duplicate records can be determined using a duplication detector to group duplicate records into respective clusters, wherein records within respective ones of the clusters represent the same entity.
- a set of equivalence classes for records of the first and second sets consisting of multiple record-attribute pairs can be determined.
- attribute values for records in respective ones of the equivalence classes are the same in the modified database instance.
- a pair of equivalence classes can be merged into a new class to resolve a functional dependency violation or to perform a deduplication.
- the first set of records of the database which violate a functional dependency of the database can be refreshed, as can the second set of records of the database comprising duplicate records as a result of the step of merging.
- a computer program embedded on a non-transitory tangible computer readable storage medium including machine readable instructions that, when executed by a processor, implement a method for updating a database comprising performing a duplicate-record-aware repair of functional dependency violations for records of the database and performing a functional-dependency- aware deduplication of records of the database.
- Figure 1 is a schematic representation of a small database instance
- Figure 2 is a schematic block diagram of a method according to an example
- Figure 3 is a schematic block diagram of a method according to an example
- Figure 4 is a schematic block diagram of an apparatus according to an example.
- a method for repairing records of a database which can be inconsistent, incorrect or missing due to duplication and inconsistencies with respect to integrity constraints of the database. Accordingly, deduplication can be performed, which determines and merges duplicate records, as well as the repairing of functional dependency (FD) violations.
- FD functional dependency
- Deduplication utilises a measure of similarity or closeness between records in a database to determine candidacy for duplicates.
- FD repair utilises the notion that the minimal amount of changes to make a database consistent are more likely to be correct.
- the two tasks are applied one after the other (e.g., deduplication and then data repair)
- it is atypical for the resultant database to be consistent and free of duplicates because, after FD repair, records can change and new duplicate records may emerge.
- violations to constraints may emerge in the database.
- figure 1 is a schematic representation of a small database instance.
- the database of Figure 1 includes records that relate personal information of certain people. That is, the database attributes are: Name, telephone information: area code (AC) and Phone; address information: Street, City, State and Zip.
- F ⁇ F 2 and F 3 there are defined a set of functional dependency constraints, F ⁇ F 2 and F 3 :
- D contains violations with respect to the specified FDs. For example, records t 2 and t 3 violate F 2 since they agree on the Zip attribute, but do not agree on the City and State attributes. Similarly, t 3 and t 4 violate F 4 . Also note that D contains duplicate records. For example, and t 2 are candidates to be duplicates due to the similarities between their attributes values.
- instance D d In order to repair the database instance D, a deduplication operation could be applied. In this case, instance D d would be obtained.
- the deduplication considers that ⁇ t-i , t 2 ⁇ and ⁇ t 3 , t 4 ⁇ are two clusters of duplicate records due to the similarity between the attributes values, while ⁇ t 5 ⁇ remains in a cluster by itself.
- the instance D d is arrived at by merging each cluster of duplicates.
- D d is inconsistent with respect to the FDs, since the two resulting records from the merge of ⁇ t- ⁇ , t 2 ⁇ and ⁇ t 3 , t 4 ⁇ violate F 2 . Therefore, the violations now need to be repaired. Violations with respect to F 2 can be resolved by making the affected records agree on City and State attributes, which in turn triggers another violation to F-i to be resolved by making the records ⁇ t-i , t 2 ⁇ and ⁇ t 3 , t 4 ⁇ agree on the AC and Street attributes. Finally, the instance D dr (D after applying deduplication followed by an FD repair) is obtained.
- the illustrated interaction between the two problems indicates that deduplication and merging records should be aware of the constraints and consistency of the database, while repairing FD inconsistency should be aware of the identified duplicates.
- the sequence of applying FD repair and deduplication affects the final database instance obtained.
- the space of possible clean instances is exponential because of the number of possibilities for repairing FD violations and the number of ways to merge duplicate records.
- a method for generating a set of updates for a database that seeks a clean instance with minimum distance from the original database instance.
- a clean instance of a database is free from FD violations and unwanted duplicate records.
- a database instance D over a relation schema R is considered, with attr(R) denoting its set of attributes.
- the domain of an attribute A e attr(R) is denoted by dom(A).
- a set of constraints ⁇ is defined over R in the form of a set of FDs, and t[A] denotes the value of a given attribute A e attr(R) in a database record t.
- An FD has the form of X ⁇ Y, where X c attr(R) (left hand side, LHS) and Y c attr(R) (right hand side, RHS) are subsets of the attributes attr(R).
- a database instance D is said to satisfy the constraints ⁇ if it satisfies every FD F e ⁇ .
- a modification can be performed so that t ⁇ City] is changed to 'New York' or t 2 [Zip] is changed to a value which is not equal to '10023'.
- respective clusters of candidate duplicate records can be merged (or fused) into a single record using a merging function using any one of several techniques that have been proposed to detect duplicate records.
- the merging of duplicate records will result in a record that is close to all the records within the cluster in question.
- t- ⁇ and t 2 may be in a cluster of duplicates.
- a single record replacement for the two records is constructed from ⁇ t-i , t 2 ⁇ .
- a deduplication mechanism can be any suitable deduplication mechanism suitable for determining candidate duplicate entries for records of a database.
- a link between deduplication and FD repair occurs in that both define equivalence between attribute values.
- all their attributes values should typically be equivalent. That is, for an attribute A e attr(R), t[A] should be the same for all t e C, where C is a cluster of duplicates.
- FD F X ⁇ Y. If there is a group of records S where t[X] are the same for all t e S , then t[Y] should be equivalent and have the same value for all t e S.
- Equivalence due to deduplication is conditioned based on decisions obtained from a deduplication mechanism, Dup, which depends on the attribute values of records.
- Equivalence due to FDs is conditioned based on the equality of the LHS attribute values.
- Such equivalence can be represented in an equivalence relation that involves complex dependencies.
- a method for repairing a database provides a modified database instance D' such that: 1.
- D' is produced by introducing minimal changes to D That is, in terms of item 3, applying the deduplication mechanism Dup on D does not detect new duplicates.
- a data cleaning process to get D' from D requires a sequence of value modification operations and the replacement of duplicates with a single record.
- the cost of a cleaning process to repair a database in order to arrive at a modified instance can be defined as:
- an FD repair is determined by performing a minimal amount of changes to a database instance in order to make it consistent or clean, thereby resulting in a modified database instance.
- a single record is determined which is used as a replacement for the corresponding cluster of records.
- the record that is close to all the records within the cluster is the selected one. Implicitly, this can be interpreted as finding the minimal amount of changes to attributes' values to make the records within a cluster identical. Accordingly, given a database D, a duplication mechanism Dup and a set of constraints ⁇ , a method according to an example determines a modified database instance D' for which the cost associated with arriving at the modification, Cost(D, D'), is minimum.
- a database can be initially repaired such that it is consistent with respect to a set of given FDs.
- the output consistent database instance can then be used in the process of identifying duplicate records to be merged.
- a merger can result in a new record that is composed of a combination of attributes values of the original records that are being merged. Therefore, a simple merge for the duplicate records may introduce violations to the given FDs.
- a consistency aware merger (CAM) of a set of records can be used in the example.
- the main purpose is to produce a consistent database while making all identified clusters of duplicates identical, such that the final repaired database instance can be constructed, such as by using a "select distinct" SQL statement for example.
- a database instance D' which is arrived at as a result of a CAM to an instance D, is defined in an example as a database in which:
- the requirements for D' are further qualified such that, given a database D, a duplication mechanism Dup and a set of constraints ⁇ , a cost associated with arriving at a modified database instance D', Cost(D, D'), is minimised.
- the selected record, which is used to represent the cluster may not be the best representation for the entity.
- the record that is close to all the records within the clusters is a good representation, and moreover, it will encounter the least amount of changes to the cluster of records to make them identical.
- identified duplicates can be considered as additional constraints to be considered as well as ⁇ when repairing a database. Since deduplication identifies equivalence between attributes' values for a given cluster of duplicates, similarly, the FD defines equivalence between the RHS attributes conditioned on the equality on the LHS attributes.
- a consistency aware merger can be encoded into a single FD repair problem by defining identified duplicates as an additional FD constraint, such that, in order to arrive at a modified database instance, a method can include the steps: 1. Construct a new instance D" with the new relation R" such that:
- R" is the same as R after addition a new attribute D_id.
- Equivalence classes are defined to provide a representation for the interactions between different equivalences introduced by the FDs and a selected deduplication mechanism.
- an equivalence class consists of record-attribute pairs (t, A), where t identifies a record and A is an attribute.
- the semantic of a set of an equivalence class eg is that attribute values t[A] have the same value for all (t, A) e eq in D'.
- Both FD resolution and deduplication defines equivalence between attributes values.
- Equivalence classes provide a mechanism to aid in separating the decision of which attributes values need to be equivalent from the decision of what value should be assigned to the class itself.
- each class eg will have a target value, targ(eq) to be applied in the database.
- the chosen value for the target of an equivalence class results in a cost.
- the cost of setting targ(eq) v is
- the resolution of FD violations and deduplication can be unified by merging equivalence classes.
- F X ⁇ A and a set of records S that violates F because they agree on the X attributes, but do not agree on A
- the violations can be resolved by merging the equivalence classes eq(t, A) for all t e S.
- the function eq(t, A) refers to the equivalence class that contains (t, A).
- FIG. 2 is a schematic block diagram of a method according to an example.
- equivalence classes are initialized. More specifically, an equivalence class 203 is created for each record-attribute pair 205 from records 207 of a database 209.
- equivalence classes 203 are merged until the FD constraints ⁇ are satisfied, and the duplicate records appear as identical, such that one record from each cluster of the identical duplicates is maintained. Accordingly, the result of the merge 21 1 is a set of records with FD constraints satisfied 213 and duplicate records merged 215.
- merging can be performed by a merge engine operable to process data representing equivalence classes 203 according to the method outlined herein.
- vioList(F) contains all records that violate F.
- attribute A e attr(R) if the currently identified clusters of duplicates are ⁇ C l , C 2 ,..., C m ⁇ , then dupList(A) contains the records of each cluster C, if the records do not agree on attribute A.
- vioList(F 3 ) ⁇ t 3 , t 4 ⁇
- vioList(F 1 ) contains all the records
- vioList(F 2 ) is initially empty.
- Dup (D) ⁇ t- ⁇ , t 2 ⁇ , ⁇ t 3 , t 4 ⁇ , ⁇ t 5 ⁇ ⁇
- dupList(Phone) ⁇ t 3 , t 4 ⁇
- dupList (Street) ⁇ ti, t 2 ⁇ for example.
- a repair operation is a merge of a set E of equivalence classes into a new class eq.
- a target, targ(eq) is calculated. If E was merged to resolve the violation of a set of records S with respect to an FD F:X ⁇ A , then S is removed from vioList(F). If the merge was due to attribute A equivalence because of deduplication, then S is removed from dupList(A). In case the merge results in changing the targ(eq(t, A)), the violations and duplicates are recomputed.
- t 4 [Zip] changes to '10023' instead of '98368', which was the previous target value of eq-i. Due to this update, t 4 may now violate other FDs that contain the modified attribute ZIP. Also, the similarity between t 4 and the other records has changed. Accordingly, deduplication needs to be recomputed again in order to update the dupList listing.
- FIG. 3 is a schematic block diagram of a method according to an example.
- An algorithm 300 starts by initializing the equivalence classes 203 as mentioned earlier.
- algorithm 300 can be one which follows the following process:
- next best set of equivalence classes to merge or the operation with the current least cost is selected using an algorithm such as below:
- a set of records S and a list that refers to either vioList or dupList is computed according to the algorithm used in block 305.
- the algorithm of block 305 typically searches among all current conflicting equivalences in the database (due to FD violation or deduplication) and selects the least cost equivalence to apply.
- a set of equivalence classes can be merged according to an algorithm in block 307, which can be an algorithm such as below:
- Block 307 takes the output of block 305 as input parameters, which is a set S of records and the list List.
- An attribute is A if List is vioList(F : X ⁇ A), or it is dupList(A). Then, using the set of records S, the set E of equivalence classes to be merged is obtained. Subsequently, the consequence of changing the target values to up date the data structures vioList and dupList is dealt with.
- a suitable filter can then be applied, such as an SQL "select distinction" command over attr(R) from D'.
- FIG 4 is a schematic block diagram of an apparatus according to an example suitable for implementing any of the system or processes described above.
- Apparatus 400 includes one or more processors, such as processor 401 , providing an execution platform for executing machine readable instructions such as software. Commands and data from the processor 401 are communicated over a communication bus 399.
- the system 400 also includes a main memory 402, such as a Random Access Memory (RAM), where machine readable instructions may reside during runtime, and a secondary memory 405.
- main memory 402 such as a Random Access Memory (RAM)
- the secondary memory 405 includes, for example, a hard disk drive 407 and/or a removable storage drive 430, representing a floppy diskette drive, a magnetic tape drive, a compact disk drive, etc., or a nonvolatile memory where a copy of the machine readable instructions or software may be stored.
- the secondary memory 405 may also include ROM (read only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM).
- data representing any one or more of updates, possible updates or candidate replacement entries, and listings for identified tuples may be stored in the main memory 402 and/or the secondary memory 405.
- the removable storage drive 430 reads from and/or writes to a removable storage unit 409 in a well-known manner.
- a user interfaces with the system 400 with one or more input devices 41 1 , such as a keyboard, a mouse, a stylus, and the like in order to provide user input data.
- the display adaptor 415 interfaces with the communication bus 399 and the display 417 and receives display data from the processor 401 and converts the display data into display commands for the display 417.
- a network interface 419 is provided for communicating with other systems and devices via a network (not shown).
- the system can include a wireless interface 421 for communicating with wireless devices in the wireless community.
- the system 400 shown in figure 4 is provided as an example of a possible platform that may be used, and other types of platforms may be used as is known in the art.
- One or more of the steps described above may be implemented as instructions embedded on a computer readable medium and executed on the system 400.
- the steps may be embodied by a computer program, which may exist in a variety of forms both active and inactive. For example, they may exist as software program(s) comprised of program instructions in source code, object code, executable code or other formats for performing some of the steps.
- any of the above may be embodied on a computer readable medium, which include storage devices and signals, in compressed or uncompressed form.
- suitable computer readable storage devices include conventional computer system RAM (random access memory), ROM (read only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), and magnetic or optical disks or tapes.
- Examples of computer readable signals, whether modulated using a carrier or not, are signals that a computer system hosting or running a computer program may be configured to access, including signals downloaded through the Internet or other networks. Concrete examples of the foregoing include distribution of the programs on a CD ROM or via Internet download. In a sense, the Internet itself, as an abstract entity, is a computer readable medium.
- equivalence classes 405 can reside in memory 402 having been derived from records of a database 209.
- one or more of algorithms of blocks 300, 305 or 307 can reside in memory 402 such as to provide respective engines 403 for cleaning, merging and selecting records of a database, including a modified instance of a database for example. That is, engine 403 can be a cleaning engine or a merge engine according to an example, which are operable to perform the processes associated with the tasks of blocks 300, 305, 307 for example.
- a database 209 is shown in figure 4 as a standalone database connected to bus 399. However, it can be a database which can be queried and have data written to it from a remote location using the wired or wireless network connections mentioned above. Alternatively, database 209 may be stored in memory 405, such as on a HDD of system 400 for example.
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- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GB1114740.2A GB2493962A (en) | 2011-08-26 | 2011-08-26 | Database record repair |
PCT/EP2012/060029 WO2013029818A1 (en) | 2011-08-26 | 2012-05-29 | Holistic database record repair |
Publications (1)
Publication Number | Publication Date |
---|---|
EP2742444A1 true EP2742444A1 (en) | 2014-06-18 |
Family
ID=44838739
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP12726383.8A Ceased EP2742444A1 (en) | 2011-08-26 | 2012-05-29 | Holistic database record repair |
Country Status (3)
Country | Link |
---|---|
EP (1) | EP2742444A1 (en) |
GB (1) | GB2493962A (en) |
WO (1) | WO2013029818A1 (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9116934B2 (en) | 2011-08-26 | 2015-08-25 | Qatar Foundation | Holistic database record repair |
-
2011
- 2011-08-26 GB GB1114740.2A patent/GB2493962A/en not_active Withdrawn
-
2012
- 2012-05-29 WO PCT/EP2012/060029 patent/WO2013029818A1/en active Application Filing
- 2012-05-29 EP EP12726383.8A patent/EP2742444A1/en not_active Ceased
Non-Patent Citations (2)
Title |
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None * |
See also references of WO2013029818A1 * |
Also Published As
Publication number | Publication date |
---|---|
GB201114740D0 (en) | 2011-10-12 |
WO2013029818A1 (en) | 2013-03-07 |
GB2493962A (en) | 2013-02-27 |
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