International Business Machines Corporation

You-Chin Gene Fuh

Patrick Dooling Bossman

Terence Patrick Purcell

Serge Bourbonnais

Hong Min

Fen-Ling Lin

Chan-Hua Liu

Yun Yu Wang

James Z Teng

Miao Zheng

Binghua Zhen

Ping Wang

Ke Wei Wei

Thomas Abel Beavin

James Zu-Chia Teng

Li Jun Xia

Sauraj Goswami

Yoichi Tsuji

Adarsh R Pannu

Xin Yang

Jing Cheng

Xiang Sean Zhou

Xiao Li

Curt Lee Cotner

David B Petersen

Yao-Ching Stephen Chen

Jing Zhou

Yefim Shuf

Jeffrey Allen Berger

John Joseph Campbell

Lee-Chin Hsu Liu

Shuanglin Guo

Austin F M D'Costa

Li-Mey P Lee

Allan Benjamin Lebovitz

Yi Jin

Michael R Shadduck

Tyrone Yu

Ying-Lin Chen

Hong Jing Ying

Shuo Li

Hubertus Franke

Vijayshankar Raman

Balakrishna Raghavendra Iyer

Guogen Zhang

Inderpal Singh Narang

Wei Han

Heng Liu

Jeffrey William Josten

Lin Qiao

Holger Karn

Apostol Ivanov Natsev

Andrei Fedorovich Lurie

Bryan Frederick Smith

Jian Wei Zhang

Ning Wang

Michael S Meier

Hsin Pan

Ying Zeng

Chunfeng Pei

Stephen Walter Turnbaugh

Frank Darl Bower

Joseph F Sinnott, Jr

Weidong Chen

Jie Zhang

Michelle Meichiou Jou

Michael Schenker

Yue Huang

Ou Jin

Kun Peng Ren

Kouhorng Allen Yang

James R Porell

Kou-Horng A Yang

Changjiu Xian

Terrence P Purcell

Systems for replication group partitioning include a workload profiling module configured to analyze historical workload data for a plurality of data elements to identify and categorize one or more transaction patterns; and a recommendation module configured to generate a recommended partitioning of the plurality of data elements into one or more replication groups, based on the one or more transaction patterns, that are optimized toward a partitioning goal.

Replication group partitioning

Methods and systems for replication group partitioning include analyzing historical workload data for a plurality of data elements to generate one or more transaction patterns and generating a recommended partitioning of the plurality of data elements into one or more replication groups, based on the one or more transaction patterns, that are optimized toward a partitioning goal.

A system for providing continuous availability comprises a second computing site that is geographically remote from a first computing site. The second computing site comprises a storage unit configured to store units of work data and data synchronously replicated from the first computing site. The second computing site further comprises a group of workloads configured to process the units of work data asynchronously replicated from the first computing site. The second computing site further comprises a software replication module configured not to replicate any data while the first computing site is available.

Zero-data loss recovery for active-active sites configurations

Techniques for restoring point-in-time and transaction consistency across consistency groups between a first and a second independent database management system (DBMS) for a disaster recovery. Several consistency groups (CGs) are defined for replication. For each CG in the first DBMS data changes are transmitted to a second DBMS. A timestamp representing a most recently received commit log record or a heartbeat during periods of inactivity for a CG is stored in a database table at regular intervals. At regular intervals, the timestamp is compared with timestamps for other CGs to identify a common time at which data to be applied to the CGs in the second DBMS have been received into a recoverable data store. The received data is applied to the CGs in the second DBMS up to the common time.

Restoring database consistency integrity

Apparatuses and methods for optimizing access path are provided. Execution of a query statement is sampled to obtain the information about a plurality of executing instances, the information about each executing instance comprises the literal value of the query statement in the instance and the filter factor corresponding to the literal value. The plurality of instances are grouped into a plurality of groups based on the filter factors corresponding to the literal values. The average filter factor of each group and the occurrence frequency of the group are obtained. The candidate access path created for the average filter factor of each group is accordingly obtained, and by taking the occurrence frequencies as weights, the weighted execution cost of each candidate access path is calculated for each group. The candidate access path with the minimum sum of the weighted execution costs for all groups is determined as the optimal access path.

Method and apparatus for optimizing access path in database

Embodiments of the invention relate to organizing data records in a relational database. An aspect of the invention includes creating index items for a plurality of data records. Each index item includes a counter and the creating results in a plurality of counters. The numerical values of counters in corresponding index items are updated for data records in the plurality of data records that are subjected to random access. The plurality of data records are reorganized based upon the numerical values of the plurality of counters.

Method of and apparatus for organizing data records in a relational database

A method of transferring files in a data-processing network using a current node within the network includes reading an outbound content and outbound characteristics of an outbound file. An outbound message is created having outbound strings including a first set of the outbound strings representing the outbound characteristics and a second set of the outbound strings representing the outbound content. The outbound message is sent to a receiver node within the network. An inbound message is received from a sender node within the network. The inbound message has inbound strings including a first set of the inbound strings representing inbound characteristics and a second set of the inbound strings representing inbound content. An inbound file having the inbound content is stored, and the inbound characteristics are applied to the inbound file.

Generating a test workload for a database

Techniques are provided for tuning work. In response to identifying a trigger for a work, automatic tuning is invoked. The trigger indicates that a performance goal for the work has been missed. The work is analyzed. A tuning operation is selected for the work based on a tuning history. The selected tuning operation is implemented for the work.

Tuning of work to meet performance goal

An adaptive query execution plan enhancement is provided by: selecting a sample of literal sets from an execution history of a query statement; determining a plurality of access paths by applying each literal set in the sample to the query statement; for each given access path of the plurality of access paths, determining a total execution cost by applying each literal set in the sample to the given access path; and selecting a preferred access path from the plurality of access paths based on the total execution costs for each given access path. A plurality of preferred access paths for a plurality of query statements in an application workload is collected and may be presented as a query execution plan enhancement recommendation to users.

Adaptive query execution plan enhancement

Techniques for database table look-up are provided. The techniques include storing one or more column attributes of a database table in a data structure, wherein the data structure also comprises a record identification (RID) column of a table, one or more predicate columns corresponding to the RID column, and a sequence number column that is associated with one or more updated records, generating a key using one or more portions from one or more of the one or more predicate columns, using the key to partition the data structure, wherein partitioning the data structure comprises partitioning the one or more predicate columns for evaluation, and evaluating the one or more predicate columns against the data structure for each matching predicate column-data structure partition.

Database table look-up

A method, system, and computer program product are provided for retrieving records into a main memory. A first number of gaps and a first total gap size are received for a list of records from a database subsystem. A determination is made of a first average gap size using the first number of gaps and the first total gap size. A determination is made as to whether the first average gap size is greater than a prestaging threshold value. Responsive to the first average gap size being equal to or less than the prestaging threshold value, a prestaging flag is set for the list of records. Then, the list of records is retrieved into the main memory using prestaging.

System and method for an adaptive list prefetch

A database query is partitioned into an initial partition including a plurality of parallel groups, and is executed, via an execution plan, based on the initial partition. A sampling subset of data is identified from the plurality of parallel groups. Substantially in parallel with the executing of the query, the execution plan is executed on the sampling subset of data as a sampling thread. The execution plan is modified based on feedback from the execution of the execution plan on the sampling subset of data.

Method, apparatus, and computer program product for adaptive query parallelism partitioning with look-ahead probing and feedback

An apparatus, system, and method are disclosed for improving query execution plan efficiency in a database management system. The present invention binds both static database queries and dynamic database queries to new query execution plans (QEPs) that produce the same result set as a former QEP bound to the database queries. Next, the present invention identifies one of the former QEPs and the new QEP as an active QEP and automatically collects execution statistics for one of the former QEPs and the new QEP. Finally, the present invention automatically selects one of the former QEPs and the new QEP as the active QEP in response to completion of the automatic collection of execution statistics, the active QEP selected such that the automatically selected QEP provides optimal execution performance based on performance criteria in comparison to the automatically unselected QEP, the active QEP selected based on the execution statistics.

Query execution plan efficiency in a database management system

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San Jose, CA, United States of America

You-Chin Gene Fuh