In an ordered index, index entries are stored classified on the search key value. E.g., author catalog in library. It is used for fast random access and the files in this may have fast several indexes on different search key. In the order Indices if the file containing the records is sequentially ordered, the index whose search key specifies the sequential order of the file is the primary index or cluster index.
In a sequentially ordered file, the index whose search key specifies the sequential order of the file. Also called clustering index.
An index whose search key specifies an order different from the sequential request of the file. Also called non-clustering index.
A bitmap index is a special kind of index that stores the bulk of its data as bit arrays (bitmaps) and answers most queries by performing bitwise logical operations on these bitmaps. The most commonly used index, such as B+ trees, are most efficient if the values it indexes do not move or iterate a smaller number of times.
In contrast, the bitmap index is designed for cases where the values of a variable repeat very frequently. For example, the gender field in a client database usually contains two clear values: male or female. For specified variables, the bitmap index can have a significant performance benefit over the commonly used trees.
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A dense index in database is a file with pairs of keys and pointers for every record in the data file. Every key in this file is associated with a special pointer to a listing in the sorted information record. In clustered indices with duplicate keys, the dense index points to the first record with that key.
Index record appears for every search-key value in the file.
A sparse index in databases is a file with pairs of keys and pointers for every block in the data file. Every key in this enter is associated with a particular mark to the block in the classified data file.
In clustered indices with duplicate keys, the sparse index points to the lowest search key in each block. Primary key is a sparse index.
A reverse index key value before entering it in the index. E.g., the measure 24538 becomes 83542 in the index. Reversing the key value is peculiarly useable for indexing data such as sequence numbers, where new key values monotonically increase.
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