Microsoft Technology Licensing, LLC

Informix Software, Inc.

Murali M Krishna

Robert H Gerber

Surajit J Chaudhuri

James Robert Hamilton

Balan Sethu Raman

Paul Sherwood Taylor

Nicolas Bruno

Ming-Chuan Wu

Shrinivas Ashwin

John F Ludeman

Samuel H Smith

Anurag Kashyap

Prakash Sundaresan

Shengsong Ni

Scott Alan Shurts

Mechanisms and techniques for database fragment cloning and management are provided. A database object, such as a table, rowset or index, is divided into fragments. Each fragment is cloned to create cloned fragments, which operationally are substantially identical to one another. One or more of the cloned fragments may be designated as a primary cloned fragment for performing database operations or as a secondary cloned fragment for serving as backup. Updates to each fragment are implemented on the primary cloned fragment and are then propagated from the primary cloned fragment to the corresponding secondary cloned fragments. A cloned fragment can go offline, becoming unavailable to be updated. When the cloned fragment returns online, the cloned fragment is refreshed with data included in the primary cloned fragment. While being refreshed, the cloned fragment may continue to be updated. The cloned fragment is eligible to be designated as a primary cloned fragment when the refreshing process has been completed.

Database fragment cloning and management

A method of estimating cardinality of a join of tables using multi-column density values and additionally using coarser density values of a subset of the multi-column density attributes. In one embodiment, the subset of attributes for the coarser densities is a prefix of the set of multi-column density attributes. A number of tuples from each table that participate in the join may be estimated using densities of the subsets. The cardinality of the join can be estimated using the multi-column density for each table and the estimated number of tuples that participate in the join from each table.

Cardinality estimation of joins

Method and apparatus for optimizing the processing of join queries based on join cardinality. Embodiments implement the methods in query optimizers in relational database management systems. A good join order for a multiple join query is found with a metric that compares the relative merits of candidate join orders as a whole. Embodiments estimate the join selectivity of foreign key--foreign key joins, where both participating tables are foreign keys with respect to a primary or unique key of one primary table. A graph representation of a query is processed to estimate the join cardinality of an arbitrarily large number of filters and joins, including any combination of primary key--foreign key joins and foreign key--foreign key joins.

Cardinality-based join ordering

A computer implemented method for generating a response to a join. Two tables are divided into fragments. A join fragment map identifies, for each respective fragment from the first table, the fragments from the second table which contain a record that satisfies the join predicate with a record from the respective fragment from the first table. The map is used to eliminate fragments which cannot satisfy the join predicate.

Method and apparatus for performing a join query in a database system

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Bellevue, WA, United States of America

Murali M Krishna