Bitmap indices are efficient for processing queries on low-cardinality attributes. But the storage of requirements for simple bitmap index is unacceptable, when the cardinality (the number of distinct values) of the attribute is very high. A common approach to solve this problem is to build bitmap index with segmentation. According to some base, decompose the attribute value into appropriate components. Consider the domain of an attribute value is [0,999], simple bitmap index needs 1000 bitmaps, and segmentation bitmap index needs 30 bitmaps based<10,10,10>. Segmentation bitmap index can effectively reduce the space of the bitmap index, but also reduce the efficiency of query processing. Especially when processing membership queries with segmentation bitmap index, the same bitmap will be scanned, because of the multiple components. In order to avoid scanning same bitmap, and improve query efficiency, the optimization algorithm of processing membership queries was given.
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