International Business Machines Corporation

Quanzhong Li

Guy Maring Lohman

Latha S Colby

Mir Hamid Pirahesh

Richard Sefton Sidle

Eugene Jon Shekita

Kevin Scott Beyer

Fatma Ozcan

Volker Gerhard Markl

Ioana Roxana Stanoi

Robbert Van Der Linden

Minglong Shao

Uttam Jain

Zografoula Vagena

Thomas Fanghaenel

Embodiments of the invention relate to a multi-level database compression technique to compress table data objects stored in pages. A compact dictionary structure is encoded that represents frequent values of data at any level of granularity. More than one level of compression is provided, wherein input to a finer level of granularity is an output of a coarser level of granularity. Based upon the encoded dictionary structure, a compression technique is applied to a stored page to compress each row on the page. Similarly, a de-compression technique may be applied to decompress the compressed data, utilizing the same dictionary structures at each level of granularity.

Multi-level database compression

According to one embodiment of the present invention, a method for processing join predicates in full-text indexes is provided. The method includes evaluating local predicates of an outer full text index to generate a first posting list of documents. For each document in the first posting list, the value of a join attribute is determined and an inner full text index is probed to obtain a second posting list of documents containing one of the join attributes determined for each document. Local predicates of an inner full text index are evaluated to generate a third posting list of documents, and the second posting list is merged with the third posting list to generate a merge list of documents. Documents in the first posting list may be paired up with documents in the merge list.

Join algorithms over full text indexes

A method is disclosed for executing a predetermined query plan, the method comprising: executing a portion of the query plan; providing a reordered query plan; comparing ranking metrics for the query plans; and executing the query plan having the lower ranking metric.

Adaptively reordering joins during query execution

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San Jose, CA, United States of America

Quanzhong Li