International Journal of Electrical & Computer Sciences IJECS-IJENS Vol: 10 No: 03 16 Incremental View Maintenance: An Algorithmic Approach Abdulaziz S. Almazyad College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia mazyad@ksu.edu.sa Mohammad Khubeb Siddiqui College of Computer Engineering and Sciences, Al Kharj University, Al Kharj, Saudi Arabia khubeb@ksu.edu.sa Abstract- To maintain the materialized view is one of the crucial tasks in a warehousing environment. The results of incremental computation are affected by interfering updates and compensation is required. The conventional approaches used incremental algorithm causes some anomalies. To solve such anomalies we proposed the novel approach an incremental view maintenance approach by using some existing approach with the use of Version Store and Transaction ID. The information stored in the warehouse is in the form of materialized views. Materialized views are the derived relation, which are stored as the relation in the database, when some updates occur in the parent relation all its child relations also get updated by viewing to maintain the consistency and convergence of the database. In this paper we proposed an algorithm for incremental view maintenance with the inclusion of some existing approaches. We utilized the concept of version store for older versions of tables that have been updated at the source and we are also able to detect the update notification messages that are lost during updating the view. Through the concept of Version store we can retrieve the correct data of corresponding state. Keywords: Data Warehouse Materialized View, Version Store, Transaction ID, View Manager and View Maintenance I. INTRODUCTION ata warehouse means storage of data (may be in the size of terabytes of disk storage), data warehouse is a copy of transaction data specifically structured for querying and reporting, which stores volume of historical data. A data warehouse can be normalized or denormalized. It can be a relational database, multidimensional database, hierarchical database, object database, etc. It should be: Subject-oriented, Integrated, Non-volatile, Time-Variant, Accessible, and Process-Oriented. In data warehouses, materialized views act as a cache, a copy of data that can be quickly accessed because indexes are built up over that, you can use materialized views to pre compute and store aggregated data. In these environments Materialized Views are often referred to as summaries, because they store summarized data. They can also be used to pre compute joins with or without aggregations, replicating distributed data and it quickly accesses for complex joins. A materialized view eliminates the overhead associated with expensive joins and aggregations for a large or important class of queries. Materialized views are of three types Materialized Views with Aggregates, Materialized Views Containing Only Joins and Nested Materialized Views. Maintaining a view is one of the most important tasks in warehousing environment. A. Architecture of Data warehouse with view manager: As mentioned in fig 1. the blocks of the data warehouse with view manager are described as below: SOURCE: A database, application, file, or other storage facility from which the data in a data warehouse is derived. The source contains the operating data, flat files and stage files. The stage file receives the data from source process and it verifies its creditability and the required data files will be passed to warehouse through view manager. Source division also termed as top tier of architecture. STAGE FILE: A place where data is processed before entering into data warehouse, it includes the following operations data cleaning, integration, transformation, load and refresh. VIEW MANAGER: After staging the View manager transaction is initiated and the file is transferred to version store. VERSION STORE: Version store is storage of updated data. It stores old versions of tables that have been updated. A transaction number TXN is given to each transaction in the table so as to maintain the versioning. After matching the Query Transaction the answer is fetched as per the Transaction ID. WAREHOUSE: A relational database that is designed for query and analysis rather than transaction processing. A data warehouse usually contains historical data that is derived from D