Multiple Level Indexes

A multi-level index (also known as a hierarchical index or a B-tree index) is an indexing technique that uses multiple levels of index structures to efficiently locate data in a large dataset. It is an extension of a single-level index, which provides direct access to data based on the indexed key. A multi-level index reduces the time and resources required for data retrieval by breaking down the search process into multiple steps.

Here's how a multi-level index works:

Single-Level Index: At the lowest level, there is a single-level index (usually a B-tree or a similar data structure) that contains pointers to data blocks or disk locations where the actual data is stored. This index structure allows for direct access to data based on the indexed key and is useful for quickly locating data when the dataset is relatively small.
Root Level: Above the single-level index, there is a root level that contains pointers to the top-level index nodes. The root level acts as an entry point to the index and narrows down the search to the appropriate top-level index node.
Top-Level Index Nodes: At the top level, there are several index nodes that contain pointers to the second-level index nodes. These top-level index nodes divide the search space into smaller segments, making it more efficient to locate the data blocks containing the indexed values.
Second-Level Index Nodes: The second-level index nodes further divide the search space into smaller segments. They contain pointers to the third-level index nodes, which, in turn, contain pointers to the data blocks or disk locations where the actual data is stored.
Multiple Levels: The process continues with more levels of index nodes until the search space is divided enough to allow for efficient data retrieval. Each level of index nodes narrows down the search to a smaller portion of the dataset, reducing the number of data blocks that need to be accessed.
Search Process: When a query involves a search based on the indexed key, the multi-level index allows the database management system (DBMS) to traverse the index nodes, starting from the root level and moving down to the appropriate leaf level, which contains the data pointers. The DBMS uses the indexed key value to determine the correct branch to follow at each level of the index.

The use of multi-level indexes is particularly beneficial for large datasets, as it reduces the time and effort needed to locate specific data, even when the number of records is extensive. By breaking down the search into multiple steps, the multi-level index efficiently narrows down the search space, making data retrieval more manageable and optimized.