WO2004036456A2 - Method and system for online analytical processing (olap) - Google Patents

Method and system for online analytical processing (olap) Download PDF

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Publication number
WO2004036456A2
WO2004036456A2 PCT/EP2003/050620 EP0350620W WO2004036456A2 WO 2004036456 A2 WO2004036456 A2 WO 2004036456A2 EP 0350620 W EP0350620 W EP 0350620W WO 2004036456 A2 WO2004036456 A2 WO 2004036456A2
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WO
WIPO (PCT)
Prior art keywords
dimension
data
sorting
sequence
pivot
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
Application number
PCT/EP2003/050620
Other languages
English (en)
French (fr)
Other versions
WO2004036456A3 (en
Inventor
Patrick Arras
Alfons Steinhoff
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
IBM Deutschland GmbH
International Business Machines Corp
Original Assignee
IBM Deutschland GmbH
International Business Machines Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by IBM Deutschland GmbH, International Business Machines Corp filed Critical IBM Deutschland GmbH
Priority to JP2004544289A priority Critical patent/JP4609995B2/ja
Priority to US10/530,936 priority patent/US7340476B2/en
Priority to AU2003286187A priority patent/AU2003286187A1/en
Publication of WO2004036456A2 publication Critical patent/WO2004036456A2/en
Publication of WO2004036456A3 publication Critical patent/WO2004036456A3/en
Anticipated expiration legal-status Critical
Priority to US11/948,033 priority patent/US7774302B2/en
Priority to US12/015,551 priority patent/US7856458B2/en
Ceased legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28Databases characterised by their database models, e.g. relational or object models
    • G06F16/283Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/953Organization of data
    • Y10S707/957Multidimensional
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99943Generating database or data structure, e.g. via user interface

Definitions

  • the present invention generally concerns database management systems performed by computers, in particular to corresponding OLAP (OnLine Analytical Processing) and Data Warehouse applications. More specifically, the invention relates to a method and system for generating user-defined presentations or views of data records contained in such a database management system. Even more specifically, the invention is related to database management systems with very large number of data records .
  • OLAP OnLine Analytical Processing
  • OLAP is computer processing that enables a user to easily and selectively extract and view data from different points-of- view. For example, a user can request that data be analyzed to display a spreadsheet showing all of a telecommunication company's mobile phone products sold in a country in a specific month of the year, compare revenue figures with those for the same products in the preceding month, and then see a comparison of other product sales in that country in the same time period.
  • OLAP data is stored in a multidimensional database.
  • a relational database can be thought of as two-dimensional
  • a multidimensional database considers each data attribute, often called “data key”, such as product, geographic sales region, and time period as a separate "dimension.”
  • OLAP software can locate the intersection of dimensions, e.g. 'all products sold in the Eastern region above a certain price during a certain time period', and display them. Attributes such as time periods can be broken down into sub-attributes .
  • OLAP can be used for data mining or the discovery of previously un-discerned relationships between data items.
  • An OLAP database does not need to be as large as a data warehouse, since not all transactional data is needed for trend analysis.
  • ODBC Open Database Connectivity
  • data records to be presented in a single cell of an underlying matrix presentation are continuously arranged in a subsequence comprising respective of said placeholder values.
  • These single cells of said pivot presentation thus are generated using corresponding of said subsequences.
  • a data subsequence of the whole sequence of data records can be used.
  • Each of these cells needed for the user-specified pivot presentation is particularly defined a starting point in the sequence by which the required data of the facts table to be presented are accessed.
  • a particular data record dimension of the database can be used more times in different aggregation stages of a pivot presentation without any runtime problems. Due to use of only vector operations for subsequent different pivot views of a given database, preceding generated sequences of data records for providing a user-defined pivot view are kept valid for the following pivot views and thus subsequently following pivot views are always deduced from an existing pivot view thus not destructing an already existing pivot view.
  • pivot presentation mechanism is not limited to 2-dimensional but can also be applied to n-dimensional pivot presentations. In the n-dimensional case, however, the above mentioned sequence vector is (n-1) -dimensional .
  • Fig. 4a-c illustrate typical vector operations for generating a sequence vector in accordance with the present invention
  • Fig. 5-6g show overview table diagrams for illustrating how real facts data are sorted in order to obtain a desired pivot view in accordance with the present invention
  • FIG. 2c and consists of two columns 260, 270, the left column 260 containing continuous numbers from again ,1' to ,20' in the present example and the right column 270 containing the pre-mentioned index values 275 depicted in Fig. 2a in an ordered arrangement that enables sequentially building-up the pivot view of Fig. 2b.
  • a first integer vector 410 provides the sorting order of the facts of the underlying facts column, in relation to the respective key dimension and the occurrence of the elements (reference values) within the key dimensions.
  • a second integer vector 400 provides a First Block Element (FBE) indicating, for each occurrence of a key dimension element (e.g. 'Brown'), the first element of its corresponding block within the sorting sequence 410.
  • FBE First Block Element
  • the 'Fact#' column of the 'Sorted Sequence' tabled is filled with the 'Fact' column of the 'Sorted Sequence' table of the corresponding dimension 410, i.e. a right-hand dimension in the corresponding sorting sequence step.
  • the contents of 'Result Permutation' are erased after the two pre-mentioned initialization steps so that these fields can be newly filled in during the next sorting step.
  • the number of lines in that table equals the number of facts contained in the real facts table.
  • the processing steps conducted in the following are determined by the sorting order related to the key dimension 'Article' which is designated 'Sorted Sequence' in the Figures .
  • the sorting mechanism itself is illustrated in more detail in the picture sequence shown in Figures 6a - 6g.
  • Each of these pictures shows a single sorting step, the whole sequence of sorting steps shown in that sequence thus depicting only part of the entire sorting procedure.
  • the whole procedure is based on inter-linkage of the shown four tables.
  • the table for the key dimension 'Article' being designated 'Sorted Sequence' resulting from the previous sorting step for the key dimension 'Customer' is processed in the order of the parameter 'Pseq' from '1' to '20'.
  • a corresponding index designated 'TmpGrp' is determined for each of the fact numbers contained in column 'Fact#'.
  • the overall procedure is to determine a separate sorting sequence for each pivot dimension.
  • the overall sequence is generated by applying the sorting procedure on the separately generated sequences starting with the result of the first and taking the next as the input for the "Mapping' table and "Sort position pointer' table as described above.

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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)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
PCT/EP2003/050620 2002-10-18 2003-09-11 Method and system for online analytical processing (olap) Ceased WO2004036456A2 (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
JP2004544289A JP4609995B2 (ja) 2002-10-18 2003-09-11 オンライン分析処理(olap)のための方法およびシステム
US10/530,936 US7340476B2 (en) 2002-10-18 2003-09-11 Method for online analytical processing (OLAP)
AU2003286187A AU2003286187A1 (en) 2002-10-18 2003-09-11 Method and system for online analytical processing (olap)
US11/948,033 US7774302B2 (en) 2002-10-18 2007-11-30 Online analytical processing (OLAP)
US12/015,551 US7856458B2 (en) 2002-10-18 2008-01-17 Online analytical processing (OLAP)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP02023362.3 2002-10-18
EP02023362 2002-10-18

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US11/948,033 Continuation US7774302B2 (en) 2002-10-18 2007-11-30 Online analytical processing (OLAP)

Publications (2)

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WO2004036456A2 true WO2004036456A2 (en) 2004-04-29
WO2004036456A3 WO2004036456A3 (en) 2004-09-30

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US (3) US7340476B2 (enExample)
JP (1) JP4609995B2 (enExample)
CN (1) CN1688998A (enExample)
AU (1) AU2003286187A1 (enExample)
TW (1) TWI230344B (enExample)
WO (1) WO2004036456A2 (enExample)

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US8495007B2 (en) * 2008-08-28 2013-07-23 Red Hat, Inc. Systems and methods for hierarchical aggregation of multi-dimensional data sources
US20100076935A1 (en) * 2008-09-09 2010-03-25 Ahmir Hussain Method, system, and computer for analytical reporting and archiving of data
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US8751564B2 (en) * 2011-04-19 2014-06-10 Echostar Technologies L.L.C. Reducing latency for served applications by anticipatory preprocessing
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US8635229B2 (en) 2011-10-18 2014-01-21 International Business Machines Corporation Sequenced query processing in data processing system
US8938416B1 (en) 2012-01-13 2015-01-20 Amazon Technologies, Inc. Distributed storage of aggregated data
US8660985B2 (en) * 2012-04-11 2014-02-25 Renmin University Of China Multi-dimensional OLAP query processing method oriented to column store data warehouse
US9721321B1 (en) * 2012-04-12 2017-08-01 Farshad Nayeri Automated interactive dynamic audio/visual performance with integrated data assembly system and methods
CN103678420B (zh) * 2012-09-25 2017-02-01 北大方正集团有限公司 一种建立多维数据集的方法和多维数据集处理装置
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Also Published As

Publication number Publication date
US7774302B2 (en) 2010-08-10
TWI230344B (en) 2005-04-01
JP2006503357A (ja) 2006-01-26
CN1688998A (zh) 2005-10-26
TW200413969A (en) 2004-08-01
US20080082563A1 (en) 2008-04-03
US20080183740A1 (en) 2008-07-31
US20060010147A1 (en) 2006-01-12
AU2003286187A1 (en) 2004-05-04
WO2004036456A3 (en) 2004-09-30
US7340476B2 (en) 2008-03-04
JP4609995B2 (ja) 2011-01-12
US7856458B2 (en) 2010-12-21

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