West Florida University
March 18, 2014
Data partitioning is a tool that can help manage the day-to-day needs of an organization. Each organization has unique values that drive business. All organizations have policies and processes that are influenced by their environment and industry. The use of data partitioning can help productivity by recognizing the need to categorize data to tailor unique needs. This approach does require some effort. To transition to a new database approach, organizations need to assess the pros and cons of a database transition. The scale of an organization’s database may be the one factor that drives ...view middle of the document...
131). This process illustrates the effectiveness of partitioning. Important and frequently accessed data is weighted accordingly. This allows the database platforms to perform load shedding. Non-pertinent files are ignored. Meanwhile the database’s rules are a mitigation tool to ensure that system performance is optimized.
Horizontal partitioning brings advantages to a database administrator. This type of partitioning utilizes the speed and efficiency for a database’s rows. This is useful in that queries can be made for specific values on row so that unnecessary queries aren’t made of unintended data. The platform oracle provides users with three types of horizontal partitioning; range, hash, and list partitioning.
For databases with large numerical values, range partitioning creates a process for the user to extract unique values. According to Hoffer (2012), “each partition is defined by a range of values (lower and upper key value limits) for one or more columns of the normalized table. A table row is inserted in the proper partition, based on its initial values for the range fields (pp. 217). This value based process gives the user an opportunity to narrow data to a specific range instead of examining the entire set of numerical values on a row. For example, a user can use range partitioning to see the revenue a company created in sales from the Thanksgiving holiday to the New Year’s Day holiday instead of a month-by-month row.
Hash partitioning is a tool that can be utilized if the range partitioning method is not preferred. Hoffer (2012) explains, “in which data are evenly spread across partitions independent of any partition key value. Hash partitioning overcomes the uneven distribution of rows that is possible with range partitioning. It works well if the goal is to distribute data evenly across devices” (pp. 218). Hash partitioning is a useful option when rows are to be retrieved but they are independent of the range values. If a user wants to access three random days of sales alone, this value is range independent thus the hash method would be an effective method to retrieve these values.
The third horizontal partitioning is the list partitioning. This method can be used to categorize values that have a common relationship. According to Hoffer (2012), “List partitioning, in which the partitions are defined based on predefined list of values of the partitioning key” (pp.218). List partitioning can be used for example to make queries to access a list of shirts that where sold in a companies’ database.
Like horizontal partitioning, vertical partitioning provides an efficient method to access data. Alsultanny (2010) explains, “Vertical partitioning splits a relational table into a number of pieces, also called partitions, and replicates a primary key in each partition. This reduces the average row length, and in consequence minimizes the total number of read and write operations”(p.273). Vertical partitioning provides...