Importance

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Abstract

System and methods are described for improved indexing and processing (e.g., query processing) of date-based information. A date value may be viewed as comprising year (y), month (m), and day (d) components. A DateIndex index data structure is defined to comprise three distinct groups of bitmaps: one for years, another for months, and another for days, respectively. This index can be created on a column having a datatype of 'date' (e.g., standard SQL datatype which stores date literals). A month group is defined to contain exactly 12 bitmaps (call them M[1], M[2], . . . , M[12]) to track rows meeting at a specified month range for a particular column. Each successive bitmap within the group stores a successively smaller subrange of possible month values (e.g., month 1-12, month 2-12, month 3-12, and so forth and so on). In a similar manner, bitmaps may be created for tracking day and year ranges. Additionally, an 'existence bitmap' (EBM) is used to track whether particular rows exist in a given column being indexed. Armed with this information, the system can now resolve a desired query operation using set algebra. Depending on the particular date value(s) under consideration, use of set algebra may often be optimized, thereby reducing the number of bitmap operations required. By providing a new index structure specifically designed for date columns, the approach significantly reduces the number of bitmap operations required to do each of these operations and also significantly reduces the amount of I/O required to do each operation.

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First Claim