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indexing-types and advantages in speeding up sys perfomance

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indexing-types and advantages in speeding up sys perfomance

Postby debashree dutta »

A database index is a data structure that improves the speed of operations in a table. Indexes can be created using one or more columns, providing the basis for both rapid random lookups and efficient ordering of access to records. The disk space required to store the index is typically less than the storage of the table (since indexes usually contain only the key-fields according to which the table is to be arranged, and excludes all the other details in the table), yielding the possibility to store indexes into memory from tables that would not fit into it. In a relational database an index is a copy of part of a table. Some databases extend the power of indexing by allowing indexes to be created on functions or expressions. For example, an index could be created on upper(last_name), which would only store the uppercase versions of the last_name field in the index. Another option sometimes supported is the use of "filtered" indexes, where index entries are created only for those records that satisfy some conditional expression. A further aspect of flexibility is to permit indexing on user-defined functions, as well as expressions formed from an assortment of built-in functions. All of these indexing refinements are supported in Visual FoxPro, for example.[1]

Indexes may be defined as unique or non-unique. A unique index acts as a constraint on the table by preventing identical rows in the index and thus, the original columns.


Index architectures can be classified as clustered or non-clustered. A non-clustered index normally contains a reference to a block that contains the row data for which the particular index item has been constructed. This block will hold several other rows depending on the row size. For each index lookup on a non-clustered index, a data block that houses the row sought after must also be retrieved.

Clustering re-orders the data block in the same order as the index, hence it is also an operation on the data storage blocks as well as on the index. Exact operation of database systems vary, but because the row data can only be stored in one order physically, only one clustered index may be created on a given database table. Clustered indexes can greatly increase access speed, but usually only where the data is accessed sequentially in the same or reverse order of the clustered index, or when a range of items are selected.

Since the physical records are in this sort order on disk the next row item in the sequence is immediately before or after the last one, and so fewer data block reads are required. The primary feature of a clustered index is therefore the ordering of the physical data rows in accordance with the index blocks that point to them. Some databases separate the data and index blocks into separate files, while others intermix the two different types of data blocks within the same physical file(s). Databases that use the latter scheme may be said to store the actual data in the leaf node of the index, whereas, in fact there is still a distinction between the index and the data block, and the data blocks can be traversed without using the index by way of a link list that links the data blocks in order.

Types of indexes:-

1.Bitmap index

A bitmap index is a special kind of index that stores the bulk of its data as bitmaps and answers most queries by performing bitwise logical operations on these bitmaps. The most commonly used index, such as B+trees, are most effective if the values it indexes do not repeat or repeat a relatively smaller number of times. In contrast, the bitmap index is designed for cases where the values of a variable repeat very frequently. For example, the gender field in a customer database usually contains two distinct values, male or female. For such variables, the bitmap index can have a significant performance advantage over the commonly used trees.

2. Dense index

A dense index in databases is a file with pairs of keys and pointers for every record in the data file. Every key in this file is associated with a particular pointer to a record in the sorted data file. In clustered indexes with duplicate keys the dense index points to the first record with that key.

3.Sparse index

A sparse index in databases is a file with pairs of keys and pointers for every record in the data file. Every key in this file is associated with a particular pointer to the block in the sorted data file. In clustered indexes with duplicate keys the sparse index points to the lowest search key in each block.
debashree dutta
Posts: 9

Addition to the Bitmapped Indexes

Postby Rajnikanth »

Addition to the Debashree Dutta's post.

Oracle bitmap indexes are very different from standard b-tree indexes. In bitmap structures, a two-dimensional array is created with one column for every row in the table being indexed. Each column represents a distinct value within the bitmapped index. This two-dimensional array represents each value within the index multiplied by the number of rows in the table. At row retrieval time, Oracle decompresses the bitmap into the RAM data buffers so it can be rapidly scanned for matching values. These matching values are delivered to Oracle in the form of a Row-ID list, and these Row-ID values may directly access the required information.

The real benefit of bitmapped indexing occurs when one table includes multiple bitmapped indexes. Each individual column may have low cardinality. The creation of multiple bitmapped indexes provides a very powerful method for rapidly answering difficult SQL queries.

Posts: 46

Postby dutta »

Too many indexes can also spoil the performance of the database.
Posts: 3

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