US20110231404A1 - File storage and retrieval method - Google Patents

File storage and retrieval method Download PDF

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US20110231404A1
US20110231404A1 US12/928,255 US92825510A US2011231404A1 US 20110231404 A1 US20110231404 A1 US 20110231404A1 US 92825510 A US92825510 A US 92825510A US 2011231404 A1 US2011231404 A1 US 2011231404A1
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index
characters
related information
address
pointers
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Richard A. Van Voorhis
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10File systems; File servers

Definitions

  • This invention relates to a file storage and retrieval technique for processing alphanumeric information that has particular advantages in implementing database queries.
  • data is typically stored in some form of non-volatile storage system, such as magnetic disks, in the form of data files. These files are subdivided into data records, which are subsets of the file itself. Processing is done within each file by accessing the data records. Users conduct transactions against a file, inserting, deleting retrieving and updating data records.
  • a more efficient, but still cumbersome and time consuming, search method requires creating a search key for each data record which uniquely identifies the record.
  • Each search key is associated with a record pointer that indicates the location in the computer storage system of the data record associated with the search key.
  • a common type of pointer is a relative record number.
  • the data records themselves need not be kept in sequential order, but may be stored in random locations in the computer storage system.
  • a search for a particular data record is enhanced by sequentially searching a compiled index of such search key records (comprising search keys and record pointers), rather than the date records themselves. However, such sequential searching is still relatively slow.
  • a much more efficient method for such a key index is to create a “tree” structure, rather than a sequential file, for the key records.
  • One such tree structure is a B-Tree, an example of which is shown in FIG. 1 .
  • the use of B-Trees to structure indexes for data files in computer storage systems is well known in the prior art. (See, for example, Knuth. The Art of Computer Programming, Volume 3, pages 473-479).
  • a B-Tree consists of nodes which can be either a root node, branch nodes or leaf nodes.
  • a branch node contains-at least one search key and related pointers (such as relative addresses, node numbers) to other nodes.
  • a leaf node contains at least one search key and a pointer to a data record.
  • One node in the tree is the root node or starting point, which can be either a leaf node (only for a tree with a single node) or a branch node.
  • the “height” of a tree is equivalent to the number of nodes traversed from the root node to a leaf node.
  • Searching for a data record is accomplished by comparing a key to the contents of the root node, branching to branch nodes based on such comparisons, comparing the key to the contents of such branch nodes, and continuing “down” the height of the tree until a leaf node is reached.
  • the key is compared to the contents of the leaf node, and one of the pointers in the leaf node is used to locate the desired data record (if one exists).
  • each node contains one search key and two associated pointers.
  • Such a tree structure sometimes referred to as a binary tree, theoretically provides a very efficient search method. If the number of nodes in this type of tree is equal to or less than 2 n , then only “n” comparisons are required to locate a data record pointer in any leaf node.
  • a simple binary tree is inefficient. Most data bases are stored on relatively slow storage systems, such as magnetic disks. The time required to access any item of data (such as a tree node) on such a storage device is dominated by the “seek” time required for the storage unit to physically locate the desired storage address. Following each seek, the contents of a node may be read into the high-speed memory of the computer system.
  • a simple binary tree for each access of a node, only a two-way decision (to the left or right branch from that node) can be made since the node contains only one search key. If instead of containing only one search per node, a node contains several search keys, then for each seek operation, several keys will be read into the high speed memory of the computer system.
  • search key per node With one search key per node, a comparison and determination can be made that the item sought for is one half the remainder of the tree. With “n ⁇ 1” search keys per node, the search can be narrowed to “1/n” of the remainder of the tree (for example, with 9 search keys per node, a search can be narrowed to “1110” of the remainder of the tree).
  • This type of structure is known in the prior art as a “multi-way” tree. See FIG. 3 .
  • the height of the tree, and hence the search time, is dramatically decreased if the number of search keys per node is increased.
  • B+-Tree which uses query values in place of actual search key values in the branch nodes and places all key values in leaf nodes, as shown in FIG. 4 .
  • This structure has all of the advantages of B-Trees as well as having a much smaller index for accessing for keys.
  • B+-Trees use multiple query values in branch nodes, as shown in FIG. 5 and FIG. 7 as well as multiple keys per leaf node, as shown in FIGS. 6 and 7 .
  • the present invention solves the problem of accessing data in a database. Since all words and/or selected phrases in the database are stored as concatenated strings of their ASCII characters, any word or phrase can be found with only one access. This requires systems to have very large indexes within a database which will be a result of computer systems in the very near future. This process may also be scaled back for use on today's system.
  • the inventive file storage and retrieval method uses the ASCII values of the characters in the search string concatenated together to form a numeric value which serves as the index to the data itself, see FIG. 8 , or as the index which holds the address of the location of the data in the system. See FIG. 9 .
  • ASCII character string indexes are written into the file to allow quick access when retrieving information. This means that any character string written to a file can be retrieved directly in just one access.
  • FIG. 1 is a schematic diagram of the B-Tree Index Structure for indexing data records in a computer storage system. This diagram shows the basic elements of tree structures.
  • FIG. 2 is a schematic diagram of a B-Tree Index Structure, Binary Tree, w/1 Key and 2 Branches/Node.
  • FIG. 3 is a schematic diagram of a B-Tree Index Structure, Multi-Way Tree, w/2 Keys and 3 Branches/Node.
  • FIG. 4 is a schematic diagram of a B+-Tree Index Structure W/1 Query Value and 2 Branches/Node and 1 Key/Leaf Node.
  • FIG. 6 is a schematic diagram of a B+-Tree Index Structure w/1 Query Value and 2 Branches/Node and 3 Keys/Leaf Node.
  • FIG. 7 is a schematic diagram of a B+-Tree Index Structure w/1 Query Values and 3 Branches/Node and 3 Keys/Leaf Node.
  • FIG. 8 is a schematic diagram of concatenated ASCII String Values used as an address with the data stored at the same location.
  • FIG. 9 is a schematic diagram of concatenated ASCII String Values used as an indirect address which holds the address of the stored data.
  • FIG. 10 is a schematic diagram showing concatenated ASCII values of a string used as an index for storing associated data. The date is stored at the same index.
  • FIG. 11 is a schematic diagram showing concatenated ASCII values of a string used as an index for storing associated data.
  • the associated data is stored at another indirect address.
  • the inventive file storage and retrieval technique is primarily designed for use with large data files running on static (non-movable) media systems of the future. This creative idea, however, lends itself to use in current day systems as well.
  • Any indexing scheme may be used to create this database.
  • a string of characters is used as a key to the database the prior and next pointers have already been established and are stored as data in the database record.
  • the concatenated ASCII values of the string may be used as an index to store the associated data.
  • This data is then written to the database as shown in FIG. 10 . In this example the data is written at the index constituting the concatenated ASCII values of the characters in the string.
  • Data may also be written to the database as shown in FIG. 11 .
  • This figure shows an example of storing the data related to the string characters at an indirect address which is stored at the index constituting the concatenated ASCII values of the string characters.
  • indexes created by concatenating the ASCII values of the string characters may become very large but systems of the future should easily be able to accommodate addresses well over ten to the 100th power.

Abstract

A file storage and retrieval method or technique for processing alpha numeric information that has particular advantages when accessing data in a database on a computer. The retrieval technique uses the ASCII values of characters in a search string concatenated together to form a numeric value which serves as the index to the data itself or to the index which holds the computer address of the location of the data. This technique allows data to be accessed with only one access when searching for a word or phrase within a database and lends itself for use on static storage systems of the future as well as on current disk based systems.

Description

    CROSS REFERENCE TO RELATED APPLICATIONS
  • This application is a continuation of U.S. patent application Ser. No. 11/378,122 entitled “FILE STORAGE AND RETRIEVAL SYSTEM,” filed Mar. 17, 2006, the contents of which are hereby incorporated by reference, and which claims priority to provisional application No. 60/775,753 filed on Feb. 21, 2006, the contents of which are hereby incorporated by reference.
  • 1. FIELD OF THE INVENTION
  • This invention relates to a file storage and retrieval technique for processing alphanumeric information that has particular advantages in implementing database queries.
  • 2. BRIEF DESCRIPTION OF THE PRIOR ART
  • In the computer arts, data is typically stored in some form of non-volatile storage system, such as magnetic disks, in the form of data files. These files are subdivided into data records, which are subsets of the file itself. Processing is done within each file by accessing the data records. Users conduct transactions against a file, inserting, deleting retrieving and updating data records.
  • For very large data bases it is extremely inefficient and time-consuming to sequentially search all data records in a file in order to find a particular record to access, modify or delete, or to locate the appropriate place to add a new record.
  • A more efficient, but still cumbersome and time consuming, search method requires creating a search key for each data record which uniquely identifies the record. Each search key is associated with a record pointer that indicates the location in the computer storage system of the data record associated with the search key. A common type of pointer is a relative record number. Through the use of such record pointers, the data records themselves need not be kept in sequential order, but may be stored in random locations in the computer storage system. A search for a particular data record is enhanced by sequentially searching a compiled index of such search key records (comprising search keys and record pointers), rather than the date records themselves. However, such sequential searching is still relatively slow.
  • A much more efficient method for such a key index is to create a “tree” structure, rather than a sequential file, for the key records. One such tree structure is a B-Tree, an example of which is shown in FIG. 1. The use of B-Trees to structure indexes for data files in computer storage systems is well known in the prior art. (See, for example, Knuth. The Art of Computer Programming, Volume 3, pages 473-479).
  • A B-Tree consists of nodes which can be either a root node, branch nodes or leaf nodes. A branch node contains-at least one search key and related pointers (such as relative addresses, node numbers) to other nodes. A leaf node contains at least one search key and a pointer to a data record. One node in the tree is the root node or starting point, which can be either a leaf node (only for a tree with a single node) or a branch node. The “height” of a tree is equivalent to the number of nodes traversed from the root node to a leaf node. Searching for a data record is accomplished by comparing a key to the contents of the root node, branching to branch nodes based on such comparisons, comparing the key to the contents of such branch nodes, and continuing “down” the height of the tree until a leaf node is reached. The key is compared to the contents of the leaf node, and one of the pointers in the leaf node is used to locate the desired data record (if one exists).
  • In the most simple B-Tree, see FIG. 2, each node contains one search key and two associated pointers. Such a tree structure, sometimes referred to as a binary tree, theoretically provides a very efficient search method. If the number of nodes in this type of tree is equal to or less than 2n, then only “n” comparisons are required to locate a data record pointer in any leaf node.
  • In practice, a simple binary tree is inefficient. Most data bases are stored on relatively slow storage systems, such as magnetic disks. The time required to access any item of data (such as a tree node) on such a storage device is dominated by the “seek” time required for the storage unit to physically locate the desired storage address. Following each seek, the contents of a node may be read into the high-speed memory of the computer system. In a simple binary tree, for each access of a node, only a two-way decision (to the left or right branch from that node) can be made since the node contains only one search key. If instead of containing only one search per node, a node contains several search keys, then for each seek operation, several keys will be read into the high speed memory of the computer system. With one search key per node, a comparison and determination can be made that the item sought for is one half the remainder of the tree. With “n−1” search keys per node, the search can be narrowed to “1/n” of the remainder of the tree (for example, with 9 search keys per node, a search can be narrowed to “1110” of the remainder of the tree). This type of structure is known in the prior art as a “multi-way” tree. See FIG. 3.
  • It is advantageous to have as many search keys as possible per node. Thus, for each seek of a node, several search keys can be examined and a more efficient determination can be made as to the location of the next node or, in the case of a leaf node, of a data record. The height of the tree, and hence the search time, is dramatically decreased if the number of search keys per node is increased.
  • An even later development in tree structures is the B+-Tree which uses query values in place of actual search key values in the branch nodes and places all key values in leaf nodes, as shown in FIG. 4. (See, for example, D. Comer 1979, “The Ubiquitous B-Tree,” ACM Computing Surveys Vol. 11, No. 2, June, 1979, pgs. 130-131). This structure has all of the advantages of B-Trees as well as having a much smaller index for accessing for keys. B+-Trees use multiple query values in branch nodes, as shown in FIG. 5 and FIG. 7 as well as multiple keys per leaf node, as shown in FIGS. 6 and 7.
  • The state of the art appears to be in some similar form of the B-Tree and the B+-Tree as shown here as prior art.
  • The process of actually building a tree structure using any of the current methods results in branches becoming unbalanced based on the order in which keys are added and/or deleted from the data base. When the branches are out of balance more than 2n+1 comparisons may be required when searching for one particular key. These structures must be balanced regularly and never remain in a totally balanced condition. B+-Trees additionally may require new query values to be established while being balanced.
  • The present invention solves the problem of accessing data in a database. Since all words and/or selected phrases in the database are stored as concatenated strings of their ASCII characters, any word or phrase can be found with only one access. This requires systems to have very large indexes within a database which will be a result of computer systems in the very near future. This process may also be scaled back for use on today's system.
  • SUMMARY OF THE INVENTION
  • The inventive file storage and retrieval method uses the ASCII values of the characters in the search string concatenated together to form a numeric value which serves as the index to the data itself, see FIG. 8, or as the index which holds the address of the location of the data in the system. See FIG. 9. When a database is created these ASCII character string indexes are written into the file to allow quick access when retrieving information. This means that any character string written to a file can be retrieved directly in just one access.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The features of the present invention which are believed to be novel are set forth with particularity in the appended claims. The present invention, both as to its organization and manner of operation, together with further objects and advantages thereof, may best be understood with reference to the following description, taken in connection with the accompanying drawings in which:
  • FIG. 1 is a schematic diagram of the B-Tree Index Structure for indexing data records in a computer storage system. This diagram shows the basic elements of tree structures.
  • FIG. 2 is a schematic diagram of a B-Tree Index Structure, Binary Tree, w/1 Key and 2 Branches/Node.
  • FIG. 3 is a schematic diagram of a B-Tree Index Structure, Multi-Way Tree, w/2 Keys and 3 Branches/Node.
  • FIG. 4 is a schematic diagram of a B+-Tree Index Structure W/1 Query Value and 2 Branches/Node and 1 Key/Leaf Node.
  • FIG. 5 is a schematic diagram of a B+-Tree Index Structure w/2 Query Values and 3 Branches/Node and 1 Key/Leaf Node.
  • FIG. 6 is a schematic diagram of a B+-Tree Index Structure w/1 Query Value and 2 Branches/Node and 3 Keys/Leaf Node.
  • FIG. 7 is a schematic diagram of a B+-Tree Index Structure w/1 Query Values and 3 Branches/Node and 3 Keys/Leaf Node.
  • FIG. 8 is a schematic diagram of concatenated ASCII String Values used as an address with the data stored at the same location.
  • FIG. 9 is a schematic diagram of concatenated ASCII String Values used as an indirect address which holds the address of the stored data.
  • FIG. 10 is a schematic diagram showing concatenated ASCII values of a string used as an index for storing associated data. The date is stored at the same index.
  • FIG. 11 is a schematic diagram showing concatenated ASCII values of a string used as an index for storing associated data. The associated data is stored at another indirect address.
  • DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
  • Throughout this description, the preferred embodiment and examples shown should be considered as exemplars, rather than limitations on the method of the present invention.
  • The inventive file storage and retrieval technique is primarily designed for use with large data files running on static (non-movable) media systems of the future. This creative idea, however, lends itself to use in current day systems as well.
  • This inventive Structure is best illustrated through an example as follows:
  • Any indexing scheme may be used to create this database. When a string of characters is used as a key to the database the prior and next pointers have already been established and are stored as data in the database record. The concatenated ASCII values of the string may be used as an index to store the associated data. This data is then written to the database as shown in FIG. 10. In this example the data is written at the index constituting the concatenated ASCII values of the characters in the string.
  • Data may also be written to the database as shown in FIG. 11. This figure shows an example of storing the data related to the string characters at an indirect address which is stored at the index constituting the concatenated ASCII values of the string characters.
  • The indexes created by concatenating the ASCII values of the string characters may become very large but systems of the future should easily be able to accommodate addresses well over ten to the 100th power.

Claims (6)

1. (canceled)
2. (canceled)
3. A file storage and retrieval method for accessing data in a database on a computer comprising the steps of:
in a search string comprised of alphanumeric characters, using an ordered numeric value for each of said alphanumeric characters;
concatenating together said ordered numeric value of each of said alphanumeric characters beginning with an ordered numeric value of a first character in said search string and continuing to concatenate ordered numeric values of said alphanumeric characters sequentially through all said alphanumeric characters in said search string to a last character of said search string to form a numeric index value that serves as an index;
wherein at said index either an address or related information resides;
wherein said related information is selected from a group consisting of said search string, pointers to a prior index, pointers to a next index, pointers to a prior address, pointers to a next address, and any remaining data;
wherein said related information is stored at said index or wherein said numeric index value serves as an index to said address where said related information is stored;
wherein said related information or said address may be accessed by only one access.
4. A method of accessing data in a computer database comprising the steps of:
in a word or phrase comprised of characters, substituting ordered numeric values for said characters of said word or phrase;
concatenating said ordered numeric values of said characters of said word or phrase beginning with an ordered numeric value of a first character in said word or phrase and continuing to concatenate an ordered numeric value of each of said characters sequentially through all said characters in said word or phrase to a last character of said word or phrase to create an index value that serves as an index;
wherein at said index either an address or related information resides;
wherein said related information is selected from a group consisting of said word or phrase, pointers to a prior index, pointers to a next index, pointers to a prior address, pointers to a next address, and any remaining data;
finding said word or phrase stored in a computer with only one access using said index of said database, wherein said word or phrase and said related information is stored at said index in just one access or finding said address where said word or phrase and said related information is stored in said computer in just one access.
5. A computer database file storage and retrieval method comprising the steps of:
in a search string comprised of characters, using ordered numeric values for said characters of said search string;
concatenating said ordered numeric values of said characters of said search string together beginning with an ordered numeric value of a first character in said search string and continuing to concatenate an ordered numeric value of each of said characters sequentially through all of said characters in said search string to a last character of said search string to form a numeric value that serves as an index;
wherein at said index either an address or related information resides;
wherein said related information is selected from a group consisting of said search string, pointers to a prior index, pointers to a next index, pointers to a prior address, pointers to a next address, and any remaining data;
utilizing said numeric value as said index to access said related information stored in a computer at said index or utilizing said numeric value as said index to access said address of a location that the related information is stored in said computer;
wherein said search string and said related information can be retrieved from the database file in just one access or wherein the address where the search string and said related information is stored in said computer can be retrieved from the database file in just one access.
6. An indexing scheme for a computer database comprising the steps of:
in a string of characters, using ordered numeric values of said characters in said string;
concatenating said ordered numeric values of said characters beginning with an ordered numeric value of a first character in said string and continuing to concatenate an ordered numeric value of each of said characters sequentially through all said characters in said string to a last character of said string for use as an index;
wherein at said index either an address or related information resides;
wherein said related information is selected from a group consisting of said string of said characters, pointers to a prior index, pointers to a next index, pointers to a prior address, pointers to a next address, and any remaining data;
using said concatenated ordered numeric values of said characters as said index to a database to store in a computer, said related information at one of said index or at said address, or using said concatenated ordered numeric values to retrieve the related information from said computer wherein said string of said characters can be retrieved from said index in just one access or wherein the address of the related information stored in the computer can be retrieved from the database in just one access.
US12/928,255 2006-02-21 2010-12-07 File storage and retrieval method Abandoned US20110231404A1 (en)

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Publication number Priority date Publication date Assignee Title
US7908276B2 (en) * 2006-08-25 2011-03-15 Qnx Software Systems Gmbh & Co. Kg Filesystem having a filename cache
US20110246473A1 (en) * 2009-09-16 2011-10-06 John Stec Computerized method for analyizing innovation interrelationships within and between large patent portfolios
US20160335294A1 (en) * 2015-05-15 2016-11-17 Bjorn J. Gruenwald System and Method for Organizing Data
US11567972B1 (en) * 2016-06-30 2023-01-31 Amazon Technologies, Inc. Tree-based format for data storage

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4068298A (en) * 1975-12-03 1978-01-10 Systems Development Corporation Information storage and retrieval system
US5218700A (en) * 1990-01-30 1993-06-08 Allen Beechick Apparatus and method for sorting a list of items
US5283894A (en) * 1986-04-11 1994-02-01 Deran Roger L Lockless concurrent B-tree index meta access method for cached nodes
WO1995010091A1 (en) * 1993-10-04 1995-04-13 Robert Dixon Method and apparatus for data storage and retrieval
US5519858A (en) * 1992-01-10 1996-05-21 Digital Equipment Corporation Address recognition engine with look-up database for storing network information
US5704060A (en) * 1995-05-22 1997-12-30 Del Monte; Michael G. Text storage and retrieval system and method
US5873087A (en) * 1991-07-18 1999-02-16 International Business Machines Corporation Computer system for storing data in hierarchical manner
US20060224578A1 (en) * 2005-04-01 2006-10-05 Microsoft Corporation Optimized cache efficiency behavior
US7926061B2 (en) * 2004-01-29 2011-04-12 Klingman Edwin E iMEM ASCII index registers
US8179316B2 (en) * 2006-12-15 2012-05-15 Thales Set mode passive location in TOA/TDOA modes

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4068298A (en) * 1975-12-03 1978-01-10 Systems Development Corporation Information storage and retrieval system
US5283894A (en) * 1986-04-11 1994-02-01 Deran Roger L Lockless concurrent B-tree index meta access method for cached nodes
US5218700A (en) * 1990-01-30 1993-06-08 Allen Beechick Apparatus and method for sorting a list of items
US5873087A (en) * 1991-07-18 1999-02-16 International Business Machines Corporation Computer system for storing data in hierarchical manner
US5519858A (en) * 1992-01-10 1996-05-21 Digital Equipment Corporation Address recognition engine with look-up database for storing network information
WO1995010091A1 (en) * 1993-10-04 1995-04-13 Robert Dixon Method and apparatus for data storage and retrieval
US5704060A (en) * 1995-05-22 1997-12-30 Del Monte; Michael G. Text storage and retrieval system and method
US7926061B2 (en) * 2004-01-29 2011-04-12 Klingman Edwin E iMEM ASCII index registers
US20060224578A1 (en) * 2005-04-01 2006-10-05 Microsoft Corporation Optimized cache efficiency behavior
US8179316B2 (en) * 2006-12-15 2012-05-15 Thales Set mode passive location in TOA/TDOA modes

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