ESTIMATION OF COLUMN CARDINALITY IN A PARTITIONED RELATIONALDATABASE

    公开(公告)号:CA2317081C

    公开(公告)日:2004-06-01

    申请号:CA2317081

    申请日:2000-08-28

    Applicant: IBM CANADA

    Abstract: Column cardinality for a table in a partitioned relational database is estimated. In each node in the database containing partitioned portions of the table a hashing function is carried out to generate a hash data set for each node, according to one of sample counting, linear counting or logarithmic counting techniques. The hash data sets are merged in a coordinator node to generate a combined hash data set. The combined hash data set is counted and correcte d according to the appropriate sample counting, linear counting or logarithmic counting techniques. The resulting count is adjusted for hash collisions and the resultant value is used to estimate the column cardinality of the table.

    METHOD AND SYSTEM TO CONTROL DATA ACCES USING SECURITY LABELCOMPONENTS

    公开(公告)号:CA2459004A1

    公开(公告)日:2005-08-20

    申请号:CA2459004

    申请日:2004-02-20

    Applicant: IBM CANADA

    Abstract: For a data processing system having memory for storing data elements, a meth od for directing the data processing system to control user access to the store d data elements. Each stored data element is associated with a set of data security label components. Each user is associated with a set of user security label components. The method includes receiving a user request to access the stored data elements, comparing the s et of user security label components against the set of data security label components associated with the users, and determining whether to permit access to the stored data responsive to the received user request based on results of the comparison. There is an access control system and a computer program product which implements the method.

    COMPUTATION OF FREQUENT DATA VALUES

    公开(公告)号:CA2374298A1

    公开(公告)日:2003-09-01

    申请号:CA2374298

    申请日:2002-03-01

    Applicant: IBM CANADA

    Inventor: RJAIBI WALID

    Abstract: A method is provided for computing frequent value statistics, such as the to p most frequent values in a data column, in a database management system using a combination of hashing techniques and a varying and dynamic threshold value to compute the N most frequent values within a data column. A varying threshold value allows the method to ignore any dat a value that is not at least more frequent than the least frequent data value already in the list. During the column scan, a data value can enter and exit the list of most frequent values depending upo n the data value's own frequency relative to that of another data value. On completion of the colum n scan, the list created already holds the N most frequent values obviating the need for a further so rt operation. The method is suited for use in database management systems where performance and reliable statistics are valued.

    COMPUTING FREQUENT VALUE STATISTICS IN A PARTITIONED RELATIONAL DATABASE

    公开(公告)号:CA2433377A1

    公开(公告)日:2004-12-25

    申请号:CA2433377

    申请日:2003-06-25

    Applicant: IBM CANADA

    Inventor: RJAIBI WALID

    Abstract: A system, method and program product for computing frequent value statistics such as frequent values in a column in a partitioned relational database is provided. The technique provided may be employed across a number of nodes of a partitioned relationa l database and is general enough to handle the case where a column is the single partitioning key of the database table as well as the case where the column is not the single partitioning ke y of the database table. The technique involves hashing column entries to a hash data set on a node, collecting the hash entries into another hash data set on a coordinating node into a combined ha sh data set, hashing entries from a table portion residing on the coordinating node into the combined hash data set and computing frequent value from the combined hash data scat. Each hash dat a set is an array of counts and the combined hash data set is a combined array of counts.

    INCREMENTAL CARDINALITY ESTIMATION FOR A SET OF DATA VALUES

    公开(公告)号:CA2390350A1

    公开(公告)日:2003-12-10

    申请号:CA2390350

    申请日:2002-06-10

    Applicant: IBM CANADA

    Abstract: A technique is provided for incrementally maintaining column cardinality estimates in database management systems. The system catalog table containing a cardinali ty estimate for a column is extended to include an appropriate data structure. A modified line ar counting technique is used in a first embodiment of a method for column cardinality estimation. Moreover, a modified logarithmic counting technique is used in a second, preferred embodiment of a column cardinality estimation method to reduce storage requirements for the data structure. The cardinality estimate is produced by an initial scan of the data but is then further maintained without requiring a full scan of the data. Data changes are reflected incrementally in modifications to the initial cardinality estimate, keeping the cardinality statistics more current with respect to the database condition. The technique of the invention typically provides a capability for a database management system to produce more efficient search plans providing more effective responses to user queries through the use of improved cardinality statistics.

    ESTIMATION OF COLUMN CARDINALITY IN A PARTITIONED RELATIONALDATABASE

    公开(公告)号:CA2317081A1

    公开(公告)日:2002-02-28

    申请号:CA2317081

    申请日:2000-08-28

    Applicant: IBM CANADA

    Abstract: Column cardinality for a table in a partitioned relational database is estimated. In each node in the database containing partitioned portions of the table a hashing function is carried out to generate a hash data set for each node, according to one of sample counting, linear counting or logarithmic counting techniques. The hash data sets are merged in a coordinator node to generate a combined hash data set. The combined hash data set is counted and correcte d according to the appropriate sample counting, linear counting or logarithmic counting techniques. The resulting count is adjusted for hash collisions and the resultant value is used to estimate the column cardinality of the table.

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