Parallel Databases
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Parallel Databases
Parallel databases are databases that are designed to process data in parallel, using multiple processors or computers. Parallel databases are used to improve the performance and scalability of large databases by distributing data and processing across multiple servers.
In a parallel database system, data is divided into multiple partitions or shards and stored across multiple servers. Each server is responsible for processing a subset of the data, which allows the database to process queries faster and more efficiently than a traditional database. Parallel databases can also handle larger volumes of data, as the data can be distributed across multiple servers, allowing for more efficient use of resources.
One of the primary benefits of parallel databases is their ability to process queries in parallel. This means that multiple processors or computers can work together to execute a single query, which can significantly reduce the time required to process large volumes of data. Parallel databases use a variety of techniques to achieve parallelism, including parallel query processing, parallel data loading, and parallel indexing.
Parallel query processing involves breaking a single query into multiple smaller queries that can be executed in parallel. Each processor or computer is assigned a subset of the data, and the results are combined to produce the final output. Parallel data loading involves loading data into the database in parallel, using multiple processors or computers. Parallel indexing involves creating indexes on the data in parallel, which can improve the speed of queries by reducing the amount of data that needs to be scanned.
Another benefit of parallel databases is their ability to scale horizontally. This means that additional servers can be added to the database to increase its processing power and storage capacity. This allows parallel databases to handle larger volumes of data and support more users than traditional databases.
There are several types of parallel databases, including shared-memory parallel databases, shared-disk parallel databases, and shared-nothing parallel databases. Shared-memory parallel databases use a single server with multiple processors to process data. Shared-disk parallel databases use multiple servers that share a common disk subsystem to process data. Shared-nothing parallel databases use multiple servers that do not share any resources to process data.
In conclusion, parallel databases are a powerful tool for processing large volumes of data. They allow for parallel processing of queries, which can significantly improve performance and scalability. Parallel databases are also highly scalable, allowing for the addition of additional servers to handle increased workload and data storage needs. With the growth of big data and the increasing demand for real-time data processing, parallel databases are becoming increasingly important in the world of data management.
Parallel Databases
RUBRIC
Excellent Quality
95-100%
Introduction 45-41 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Literature Support
91-84 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Methodology
58-53 points
Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met.
Average Score
50-85%
40-38 points
More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided.
83-76 points
Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration.
52-49 points
Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met.
Poor Quality
0-45%
37-1 points
The background and/or significance are missing. No search history information is provided.
75-1 points
Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration.
48-1 points
There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met
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