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The performance of NoSQL databases is usually evaluated using the metric of throughput, which is measured as operations per second. Performance evaluation must pay attention to the right benchmarks such as production configurations, parameters of the databases, anticipated data volume, and concurrent user workloads.
Since the cache exists to bridge the speed gap, its performance measurement and metrics are important in designing and choosing various parameters like cache size, associativity, replacement policy, etc. Cache performance depends on cache hits and cache misses, which are the factors that create constraints to system performance.
For instance, when customer data are duplicated and attached with each product bought, then redundancy of data is a known source of inconsistency since a given customer might appear with different values for one or more of their attributes. [4]
Referential integrity is a property of data stating that all its references are valid. In the context of relational databases, it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist. [1]
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points. This process condenses extensive ...
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In computer science, performance prediction means to estimate the execution time or other performance factors (such as cache misses) of a program on a given computer. It is being widely used for computer architects to evaluate new computer designs, for compiler writers to explore new optimizations, and also for advanced developers to tune their programs.
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