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It speeds up most requests for data so that large databases can be reached more easily. We eventually function on the pieces and combine the outputs, returning them to the customer. The server breaks up a request for a user database into parts and sends each part to a separate computer. Speed is the main advantage of parallel databases. The benefits of the parallel database are explained below − Speed A system that processes large transactions can improve response time, as well as throughput by performing subtasks of each transaction in parallel. Response time − The amount of time it takes to complete a single task from the time it is submitted. A system that processes a large number of small transactions can improve throughput by processing many transactions in parallel. Throughput − The number of tasks that can be completed in a given time interval. There are two main resources of performance of a database system, which are explained below − This working of parallel database is explained in the diagram given below −
PARALLEL QUERY PROCESSING IN DBMS SERIAL
Step 3 − In parallel processing, many operations are performed simultaneously as opposed to serial processing, in which the computational steps are performed sequentially. Step 2 − The driving force behind parallel database systems is the demand of applications that have to query extremely large databases of the order of terabytes or that have to process a large number of transactions per second. Step 1 − Parallel processing divides a large task into many smaller tasks and executes the smaller tasks concurrently on several CPU’s and completes it more quickly. Let us discuss how parallel database works in step by step manner − A parallel database is one which involves multiple processors and working in parallel on the database used to provide the services.Ī parallel database system seeks to improve performance through parallelization of various operations like loading data, building index and evaluating queries parallel systems improve processing and I/O speeds by using multiple CPU’s and disks in parallel.