Database index

Usage and Benefits of Database Indexes - Database indexes improve the speed of data retrieval operations on a table. - Indexes allow for quick data location without searching every row. - Indexes can be created using one or more columns of a table. - They enable rapid random lookups and efficient access of ordered records. - Indexes can be created on transformed column values or user-defined functions. - Indexing technology in database software enables sub-linear time lookup. - Lookup performance can be improved by using different data structures for indexing. - Many index designs exhibit logarithmic or O(log(N)) lookup performance. - Some applications can achieve flat or O(1) performance with indexes. - Indexes are used to improve performance for databases with many objects. Database Constraints and Indexing - Indexes are used to enforce database constraints like UNIQUE, PRIMARY KEY, and FOREIGN KEY. - UNIQUE constraints can be implemented using indexes. - PRIMARY KEY columns are usually indexed by default in database systems. - FOREIGN KEY constraints often require indexing of both referencing and referenced columns. - EXCLUSION constraints can be enforced using indexes with fast searching capabilities. Index Architecture and Methods - Non-clustered indexes store data in arbitrary order but specify logical ordering. - Non-clustered indexes contain index keys in sorted order with pointers to the records. - Non-clustered indexes are used for non-primary key columns in JOIN, WHERE, and ORDER BY clauses. - Multiple non-clustered indexes can be created on a table. - Clustered indexes alter the data block to match the index, storing row data in order. Column Order and Index Performance - The order of columns in an index definition is important. - Retrieving row identifiers using only the first indexed column is possible. - Retrieving row identifiers using the second or greater indexed columns may not be efficient. - The order of search columns should be considered when creating indexes. - Index performance can be improved by creating indexes in the order of search columns. Types of Indexes and Implementations - Bitmap index: Stores data as bit arrays and performs bitwise logical operations. - Dense index: Contains pairs of keys and pointers for every record in the data file. - Sparse index: Contains pairs of keys and pointers for every block in the data file. - Reverse index: Reverses the key value before entering it in the index. - Primary index: Contains the key fields of the table and a pointer to the non-key fields. - Balanced trees: Popular index structure used for efficient searching. - B+ trees: Another commonly used index structure for efficient retrieval. - Hashes: Most commonly used index in data management for columns with unique values. - Microsoft SQL Server: Uses a clustered index where the leaf node corresponds to the actual data. - Single clustered index: Each relation can have a single clustered index and many unclustered indices. Note: The subtopic "Covering index" does not have enough information to form a comprehensive group. The subtopic "Index concurrency control" can be included in Group 2 or Group 5, depending on the focus of the organization. The subtopic "Standardization" can be included as a separate group.