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Method and System for Smart Materialized Query Tables and Reconciliation in a Network of Systems

IP.com Disclosure Number: IPCOM000237059D
Publication Date: 2014-May-29
Document File: 4 page(s) / 283K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system for smart materialized query tables and reconciliation in a network of systems is disclosed.

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Method and System for Smart Materialized Query Tables and Reconciliation in a Network of Systems

Disclosed is a method and system for smart materialized query tables and reconciliation in a network of systems.

The demand for the 24x7x365 operation of data centers increases with the ubiquitous network access by customers. Also, the volume of data processed by data centers is growing exponentially. These two factors cause that the time window available for data centers to perform critical business operations such as Close the Day (COD) becomes ever shorter. The data centers utilize sophisticated database management systems (DBMS) to manage the ever increasing data volumes. The efficiency of query processing becomes the critical factor in the data center operation. Often, the efficient data processing is realized by DBMSes by implementing and using materialized query tables (MQTs). These are also known as automatic summary tables and materialized views. Specifically, in business intelligence / data warehousing environments a sound MQT strategy is a critical success factor for performance and scalability. Lack of proper MQTs degrades the overall system performance and can have disastrous results in analytical support. Some DBMSes employ the concept of the MQT advisor. The MQT advisor
is a software solution that constantly analyzes the performance signature of the database workload and provides information on what MQTs would dramatically speed up the execution of database requests and thus cut the processing time and the overall system utilization. The problem is, however, that MQT creation is a resource intensive task that cannot be performed at the time when system is performing the business critical operations such as COD. If the COD operation does not finish in the allocated window, the consequence may be potentially large business losses. Currently, the process of creating MQTs recommended by the MQT advisor is postponed to times where no critical operations are performed and that operation my be significantly delayed. This seriously hampers the system's ability to react quickly to changing system performance challenges.

Figure 1 depicts a Primary Server which is unable to create indexes due to high system utilization.

Figure 1

The disclosed method utilizes the secondary (backup) server in an interconnected network of systems (such as High

Availability or Disaster Recovery cluster) to build MQTs advised by the MQT advisor running on the primary (production) server. After the creation, the MQTs are moved to the primary server. The Materialized Query Table Reconcile and Attach Module (MRAM) is used to reconcile the MQT created on the secondary server with the current data image on the primary server. The reconciled MQT is then used by the DBMS to dramatically improve data access efficiency.

Compared to the existing art the proposed solution has the following advantages:

Utilizes existing hardware and software resources without a nee...