What is the Bitmap index?

BITMAP Index is a specific type of data structure. In computer science, data structures are the methods of organization and classification to use it in the most effective way. The advantage of using this particular data structure is that some information can be processed faster and will require less hardware memory. In particular, the BITMAP index is commonly used to solve data stores. When the data is organized, it is possible to go through and select different trends or patterns to better understand. This means that the data is divided into a table and defined by numbers representing different values ​​in the data. In general, data indices of this type are more efficient if defined data do not mean the same values ​​repeatedly. On the other hand, the bitmap index is best used when the values ​​are repeated.

The repetition total can be described as low cardinal data - that is, when the information displayed can only have a very small number of results. The same value would therefore be repeated several times. PoisonIt is from examples when values ​​define male and women. There are only two different ways to describe gender, so each column in the table would have low cardinals and was perfect for displaying with the bitmap index.

Although the display of this kind of data in the index allows reading it faster, there is a compromise. The very condensed structure allows it to be easy to read, but at the same time the data must be processed with CPU several times to decompress it in simpler terms that the computer understands. In addition, the adjustment of the bitmap index can be very time consuming. Because everything is very systematic and specific, one thing that Need to be changed can cause a change throughout the structure.

Another advantage of bitmap indices is that they require very little memory storage. The database index often has more components than the data itself and requires additional space to be stored. At the use ofThis is not the case with the Bitmap index. It condenses data into smaller, easier reading parts and releases space that may not be used.