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Database Indexing Techniques
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Composite Index
An index on two or more columns of a table. It enables efficient querying that involves conditions on the indexed columns.
Clustered Index
A type of index where the order of the rows in the database corresponds to the order of the index. Good for range queries and accessing data in a table.
Spatial Index
An index used for spatial data types such as geometries or geographic data. Supports efficient querying of spatial objects, such as finding points within a region.
Hash Index
An indexing technique where a hash function is used to compute the index of each item. Used for equality searches; not suitable for range queries.
Covering Index
An index that includes all the columns needed for a query. Avoids the need to go to the main table data, thus speeding up query performance.
B+ Tree
A B+ Tree is a balanced tree data structure that maintains sorted data in a way that allows for efficient insertion, deletion, and lookup operations. Commonly used in databases and filesystems for indexing.
Unique Index
An index that ensures all values in the index must be distinct. Helpful in maintaining data integrity by preventing duplicate entries in a column or set of columns.
Bitmap Index
An indexing technique that uses a bitmap for each distinct value of a column, enabling efficient querying on multiple columns. Common in data warehousing for OLAP operations.
Full-Text Index
An index that stores all the text in a document or set of documents, enabling complex text search queries. Used in search engines and text retrieval systems.
Inverted Index
A mapping from content, such as words or numbers, to its locations in a database. Used in document retrieval systems to enable quick full text searches.
Partial Index
An index built on only a subset of a table's rows, satisfying a particular WHERE clause. This reduces the size of the index and can improve performance.
Non-Clustered Index
An index structure separate from the data in a table. Provides a logical ordering of rows and includes pointers to the actual data. Allows for more indices than clustered indexes.
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