Arun Swami

A method for processing activity records. The method includes obtaining an activity record, and generating an anonymization dictionary. Generating the anonymization dictionary includes detecting, in the activity record, a set of target entities to be anonymized, making a determination that a resource is associated with a subset of the target entities of the set of target entities, and after making the determination, assigning an anonymized identity to the subset of target entities, and… Show more

A method for processing activity records. The method includes obtaining an activity record, and generating an anonymization dictionary. Generating the anonymization dictionary includes detecting, in the activity record, a set of target entities to be anonymized, making a determination that a resource is associated with a subset of the target entities of the set of target entities, and after making the determination, assigning an anonymized identity to the subset of target entities, and generating an anonymization identifier for each target entity in the subset of target entities to obtain a set of anonymization identifiers, each including the anonymized identity. The method further includes processing the activity record using the anonymization dictionary to obtain an anonymized activity record and storing the anonymized activity record. Show less

The present disclosure includes systems and techniques relating to representation and retrieval of data structures in databases. In general, embodiments of the invention feature a computer program product and a method including storing a generalized directed acyclic graph (DAG) in a database, wherein the storing includes encoding path information of the generalized DAG in entries of a path table in the database, the encoding includes converting the path information into text strings, and the… Show more

The present disclosure includes systems and techniques relating to representation and retrieval of data structures in databases. In general, embodiments of the invention feature a computer program product and a method including storing a generalized directed acyclic graph (DAG) in a database, wherein the storing includes encoding path information of the generalized DAG in entries of a path table in the database, the encoding includes converting the path information into text strings, and the entries of the path table correspond to paths in the generalized DAG from nodes of the generalized DAG to a root node of the generalized DAG; triggering generation of a lexical index of the path table using the text strings, wherein the lexical index separately lists tokens included in the entries; and retrieving one or more portions of the generalized DAG from the database for in-memory operations. Show less

A system and method is provided for distributed relational databases for parallel sorting of a relation wherein the relation is a set of tuples to be sorted on multiple sort sites which completely decouples the return phase from the sort phase in order to eliminate the merge phase. The method involves selecting one coordinator site from any of the available logical sites, then generating and sorting a local sample on each of the available storage sites before sending the local random sample… Show more

A system and method is provided for distributed relational databases for parallel sorting of a relation wherein the relation is a set of tuples to be sorted on multiple sort sites which completely decouples the return phase from the sort phase in order to eliminate the merge phase. The method involves selecting one coordinator site from any of the available logical sites, then generating and sorting a local sample on each of the available storage sites before sending the local random sample from each storage site to the designated coordinator site wherein the local random samples are merged to provide a single global sample. The coordinator site determines the global interval key values based on the global sample. The interval key values being determined such that each interval fits in a single sort site's main memory, wherein the tuples between two interval key values define the interval. The interval key values are sent to the various storage sites wherein each storage site scans its portion of the relation in order to determine for each tuple the assigned interval and its corresponding sort site before sending each tuple to the assigned sort site. At each sort site the tuples are stored in temporary files using a single temporary file for each interval whereafter repeating, for each interval on each sort site, the steps of reading an interval and performing an in-memory sort in any fashion of the interval read before sending the tuples of the sorted interval to the sink site. Show less

A method of index scanning involves scanning one or more selected indexes and determining the number of data transfers required to traverse all or a portion of a selected index for a selected number of buffer pool sizes. The number of page transfers to scan a whole table of interest versus the number of page transfers to scan each relevant index in accordance with the buffer pool size is determined for a query. The number of page transfers required in proportion to the selectivity of starting… Show more

A method of index scanning involves scanning one or more selected indexes and determining the number of data transfers required to traverse all or a portion of a selected index for a selected number of buffer pool sizes. The number of page transfers to scan a whole table of interest versus the number of page transfers to scan each relevant index in accordance with the buffer pool size is determined for a query. The number of page transfers required in proportion to the selectivity of starting and stopping conditions is determined and scaled down in proportion to the selectivity of any starting and stopping conditions present in the search criteria in the query. A suitable correction factor is applied to the number of transfers to account for few rows remaining to be transferred after applying the search criteria, the buffer pool being large, or a low degree of clustering for an index,, as well as accounting for any remaining index sargable search criteria. The search procedures that results in the least number of page transfers in then implemented. Show less

A database management system determines, in a single pass over an unordered database, the quantile information. The system sequentially compares each tuple in the data set to a test value, and then selectively inserts the tuple in a test set having a cardinality less than the cardinality of the data set based upon the comparison. The system next uses the quantile information to estimate the number of tuples in the database which satisfy a user-defined predicate to generate an efficient query… Show more

A database management system determines, in a single pass over an unordered database, the quantile information. The system sequentially compares each tuple in the data set to a test value, and then selectively inserts the tuple in a test set having a cardinality less than the cardinality of the data set based upon the comparison. The system next uses the quantile information to estimate the number of tuples in the database which satisfy a user-defined predicate to generate an efficient query plan. Show less

A high dimensional indexing method is disclosed which takes a set of objects that can be viewed as N-dimensional data vectors and builds an index which treats the objects like k-dimensional points. The method first defines and applies a set of feature extraction functions that admit some similarity measure for each of the stored objects in the database. The feature vector is then transformed in a manner such that the similarity measure is preserved and that the information of the feature vector… Show more

A high dimensional indexing method is disclosed which takes a set of objects that can be viewed as N-dimensional data vectors and builds an index which treats the objects like k-dimensional points. The method first defines and applies a set of feature extraction functions that admit some similarity measure for each of the stored objects in the database. The feature vector is then transformed in a manner such that the similarity measure is preserved and that the information of the feature vector v is concentrated in only a few coefficients. The entries of the feature vectors are truncated such that the entries which contribute little on the average to the information of the transformed vectors are removed. An index based on the truncated feature vectors is subsequently built using a point access method (PAM). A preliminary similarity search can then be conducted on the set of truncated transformed vectors using the previously created index to retrieve the qualifying records. A second search on the previously retrieved set of vectors is used to eliminate the false positives and to get the results of the desired similarity search. Show less

A method for choosing join selectivities in a query optimizer in a relational database management system is disclosed which facilitates the estimation of join result sizes by a query optimizer in a relational database system, wherein a new relation R is to be joined with an intermediate relation I, and wherein the selectivity values for each eligible join predicate are known. The method has the steps of determining the equivalence classes for a plurality of join attributes and then computing… Show more

A method for choosing join selectivities in a query optimizer in a relational database management system is disclosed which facilitates the estimation of join result sizes by a query optimizer in a relational database system, wherein a new relation R is to be joined with an intermediate relation I, and wherein the selectivity values for each eligible join predicate are known. The method has the steps of determining the equivalence classes for a plurality of join attributes and then computing for each relation an estimate of the cardinality and the number of distinct values in each attribute after all the local predicates have been included. These are used in further computation of join selectivities and join result sizes. The join predicates must then be processed by correctly choosing the join selectivities. The join result sizes can then be correctly calculated. Show less

A join optimization method is provided for use with a data processor for optimizing the processing of a query for retrieval of data from a relational computer database. The database is organized by relations and data is retrieved by preforming join operations on the relations. The join operations are optimized by randomly selecting an initial order for the join operations, assigning optimal join methods based on the initial order, finding an optimal order based on the assigned methods and… Show more

A join optimization method is provided for use with a data processor for optimizing the processing of a query for retrieval of data from a relational computer database. The database is organized by relations and data is retrieved by preforming join operations on the relations. The join operations are optimized by randomly selecting an initial order for the join operations, assigning optimal join methods based on the initial order, finding an optimal order based on the assigned methods and repeating a polynomial number of times. The Krishanmurthy, Boral and Zaniolo (KBZ) Algorithm is used to determine a join optimization sequence and further refinement is provided by determining costs for alternate join order sequences using alternate join methods. Show less