Title: Bitmap
Content: Bitmap In computing, a bitmap is a mapping from some domain (for example, a range of integers) to bits. It is also called a bit array or bitmap index. The more general term pix-map refers to a map of pixels, where each one may store more than two colors, thus using more than one bit per pixel. Often "bitmap" is used for this as well. In some contexts, the term "bitmap" implies one bit per pixel, while "pixmap" is used for images with multiple bits per pixel. A bitmap is a type of memory organization or image file format used

Title: Bitmap
Content: to store digital images. The term "bitmap" comes from the computer programming terminology, meaning just a "map of bits", a spatially mapped array of bits. Now, along with "pixmap", it commonly refers to the similar concept of a spatially mapped array of pixels. Raster images in general may be referred to as bitmaps or pixmaps, whether synthetic or photographic, in files or memory. Many graphical user interfaces use bitmaps in their built-in graphics subsystems; for example, the Microsoft Windows and OS/2 platforms' GDI subsystem, where the specific format used is the "Windows and OS/2 bitmap file format", usually named with

Title: Bitmap
Content: the file extension of codice_1 (or codice_2 for "device-independent bitmap"). Besides BMP, other file formats that store literal bitmaps include InterLeaved Bitmap (ILBM), Portable Bitmap (PBM), X Bitmap (XBM), and Wireless Application Protocol Bitmap (WBMP). Similarly, most other image file formats, such as JPEG, TIFF, PNG, and GIF, also store bitmap images (as opposed to vector graphics), but they are not usually referred to as "bitmaps", since they use compressed formats internally. In typical uncompressed bitmaps, image pixels are generally stored with a variable number of bits per pixel which identify its color, the color depth. Pixels of 8 bits

Title: Bitmap index
Content: Bitmap index A bitmap index is a special kind of database index that uses bitmaps. Bitmap indexes have traditionally been considered to work well for "low-cardinality columns", which have a modest number of distinct values, either absolutely, or relative to the number of records that contain the data. The extreme case of low cardinality is Boolean data (e.g., does a resident in a city have internet access?), which has two values, True and False. Bitmap indexes use bit arrays (commonly called bitmaps) and answer queries by performing bitwise logical operations on these bitmaps. Bitmap indexes have a significant space and

Title: Bitmap index
Content: the RID-lists as bitmaps. Since each bitmap represents one distinct value, this is the basic bitmap index. As the column cardinality increases, each bitmap becomes sparse and it may take more disk space to store the bitmaps than to store the same content as RID-lists. In this case, it switches to use the RID-lists, which makes it a B+tree index. One of the strongest reasons for using bitmap indexes is that the intermediate results produced from them are also bitmaps and can be efficiently reused in further operations to answer more complex queries. Many programming languages support this as a

Question: A bitmap is a collection of what?
Answer: Dots