241:. An index may be declared as UNIQUE, which creates an implicit constraint on the underlying table. Database systems usually implicitly create an index on a set of columns declared PRIMARY KEY, and some are capable of using an already-existing index to police this constraint. Many database systems require that both referencing and referenced sets of columns in a FOREIGN KEY constraint are indexed, thus improving performance of inserts, updates and deletes to the tables participating in the constraint.
682:
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302:(not to be confused with clustered index described previously). The records for the tables sharing the value of a cluster key shall be stored together in the same or nearby data blocks. This may improve the joins of these tables on the cluster key, since the matching records are stored together and less I/O is required to locate them. The cluster configuration defines the data layout in the tables that are parts of the cluster. A cluster can be keyed with a
568:, are most efficient if the values they index do not repeat or repeat a small number of times. In contrast, the bitmap index is designed for cases where the values of a variable repeat very frequently. For example, the sex field in a customer database usually contains at most three distinct values: male, female or unknown (not recorded). For such variables, the bitmap index can have a significant performance advantage over the commonly used trees.
1603:
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433:. This query would yield an email address for every customer whose email address ends with "@wikipedia.org", but even if the email_address column has been indexed the database must perform a full index scan. This is because the index is built with the assumption that words go from left to right. With a
322:
For example, in a phone book organized by city first, then by last name, and then by first name, in a particular city, one can easily extract the list of all phone numbers. However, it would be very tedious to find all the phone numbers for a particular last name. One would have to look within each
262:
is specified by the index. The data rows may be spread throughout the table regardless of the value of the indexed column or expression. The non-clustered index tree contains the index keys in sorted order, with the leaf level of the index containing the pointer to the record (page and the row number
285:
Clustering alters the data block into a certain distinct order to match the index, resulting in the row data being stored in order. Therefore, only one clustered index can be created on a given database table. Clustered indices can greatly increase overall speed of retrieval, but usually only where
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A covering index can dramatically speed up data retrieval but may itself be large due to the additional keys, which slow down data insertion and update. To reduce such index size, some systems allow including non-key fields in the index. Non-key fields are not themselves part of the index ordering
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Some database systems support an EXCLUSION constraint that ensures that, for a newly inserted or updated record, a certain predicate holds for no other record. This can be used to implement a UNIQUE constraint (with equality predicate) or more complex constraints, like ensuring that no overlapping
145:
An index is a copy of selected columns of data, from a table, that is designed to enable very efficient search. An index normally includes a "key" or direct link to the original row of data from which it was copied, to allow the complete row to be retrieved efficiently. Some databases extend the
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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
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It is used to index fields that are neither ordering fields nor key fields (there is no assurance that the file is organized on key field or primary key field). One index entry for every tuple in the data file (dense index) contains the value of the indexed attribute and pointer to the block or
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The order that the index definition defines the columns in is important. It is possible to retrieve a set of row identifiers using only the first indexed column. However, it is not possible or efficient (on most databases) to retrieve the set of row identifiers using only the second or greater
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Suppose a database contains N data items and one must be retrieved based on the value of one of the fields. A simple implementation retrieves and examines each item according to the test. If there is only one matching item, this can stop when it finds that single item, but if there are multiple
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A reverse-key index reverses the key value before entering it in the index. E.g., the value 24538 becomes 83542 in the index. Reversing the key value is particularly useful for indexing data such as sequence numbers, where new key values monotonically increase.
133:
at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed. Indexes can be created using one or more
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No standard defines how to create indexes, because the ISO SQL Standard does not cover physical aspects. Indexes are one of the physical parts of database conception among others like storage (tablespace or filegroups). RDBMS vendors all give a
770:. While in principle indexes can utilize the common database concurrency control methods, specialized concurrency control methods for indexes exist, which are applied in conjunction with the common methods for a substantial performance gain.
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of the clustered index corresponds to the actual data, not simply a pointer to data that resides elsewhere, as is the case with a non-clustered index. Each relation can have a single clustered index and many unclustered indices.
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To find the Name for ID 13, an index on (ID) is useful, but the record must still be read to get the Name. However, an index on (ID, Name) contains the required data field and eliminates the need to look up the record.
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In most cases, an index is used to quickly locate the data records from which the required data is read. In other words, the index is only used to locate data records in the table and not to return data.
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The primary index contains the key fields of the table and a pointer to the non-key fields of the table. The primary index is created automatically when the table is created in the database.
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time ranges or no intersecting geometry objects would be stored in the table. An index supporting fast searching for records satisfying the predicate is required to police such a constraint.
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index blocks that point to them. Some databases separate the data and index blocks into separate files, others put two completely different data blocks within the same physical file(s).
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Covering indexes are each for a specific table. Queries which JOIN/ access across multiple tables, may potentially consider covering indexes on more than one of these tables.
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used for this purpose. There are complex design trade-offs involving lookup performance, index size, and index-update performance. Many index designs exhibit logarithmic (
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A hash index in database is most commonly used index in data management. It is created on a column that contains unique values, such as a primary key or email address.
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162:, where index entries are created only for those records that satisfy some conditional expression. A further aspect of flexibility is to permit indexing on
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at the beginning of the search-term, the database software is unable to use the underlying index data structure (in other words, the WHERE-clause is
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392:. To process this statement without an index the database software must look at the last_name column on every row in the table (this is known as a
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206:. Since databases may contain many objects, and since lookup is a common operation, it is often desirable to improve performance.
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A covering index is a special case where the index itself contains the required data fields and can answer the required data.
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the data is accessed sequentially in the same or reverse order of the clustered index, or when a range of items is selected.
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power of indexing by letting developers create indexes on column values that have been transformed by functions or
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city's section for the entries with that last name. Some databases can do this, others just won't use the index.
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Daren
Bieniek; Randy Dess; Mike Hotek; Javier Loria; Adam Machanic; Antonio Soto; Adolfo Wiernik (January 2006).
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An inverted index maps a content word to the document containing it, thereby allowing full-text searches.
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An index is typically being accessed concurrently by several transactions and processes, and thus needs
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The indexed columns are typically non-primary key columns used in JOIN, WHERE, and ORDER BY clauses.
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matches, it must test everything. This means that the number of operations in the average case is
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but only included at the leaf level, allowing for a covering index with less overall index size.
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An index is any data structure that improves the performance of lookup. There are many different
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Indexes are useful for many applications but come with some limitations. Consider the following
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field to retrieve all matched records. Then a sequential lookup checks the matching with
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Indices can be implemented using a variety of data structures. Popular indices include
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217:(log(N))) lookup performance and in some applications it is possible to achieve flat (
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in the data file. Every key in this file is associated with a particular pointer to
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in the data page in page-organized engines; row offset in file-organized engines).
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in the data file. Every key in this file is associated with a particular pointer
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A bitmap index is a special kind of indexing that stores the bulk of its data as
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syntax with some specific options that depend on their software's capabilities.
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A sparse index in databases is a file with pairs of keys and pointers for every
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When the wildcard characters are used on both sides of the search word as
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When multiple databases and multiple tables are joined, it is called a
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field in the index. Another option sometimes supported is the use of
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There can be more than one non-clustered index on a database table.
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The physical order of the rows is not the same as the index order.
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on these bitmaps. The most commonly used indexes, such as
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that improves the speed of data retrieval operations on a
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Consider the following table (other fields omitted):
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1117:"Create indexes with included columns - SQL Server"
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Chapter 8: Building Fast-Performing
Database Models
183:software includes indexing technology that enables
49:. Unsourced material may be challenged and removed.
716:Another type of index used in database systems is
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16:Data structure for query optimization in databases
560:(bitmaps) and answers most queries by performing
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258:The data is present in arbitrary order, but the
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961:Oracle® Database Concepts 10g Release 1 (10.1)
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1091:"11.9. Index-Only Scans and Covering Indexes"
1066:SQL Server 2005 Implementation and Management
1047:SQL Server 2005 Books Online (September 2007)
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948:PostgreSQL 9.1.2 Documentation: CREATE TABLE
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150:. For example, an index could be created on
138:, providing the basis for both rapid random
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142:and efficient access of ordered records.
109:Learn how and when to remove this message
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1114:
1079:Covering Indexes for Query Optimization
249:Index architecture and indexing methods
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970:Database Systems: The Complete Book.
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194:is inefficient for large databases.
47:adding citations to reliable sources
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930: – Method for data management
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1062:"Chapter 4: Creating Indices"
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847:This can be done in SQL with
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1043:"Clustered Index Structures"
354:Applications and limitations
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1638:Database management systems
1168:Database management systems
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448:and a SQL query like this:
332:city, last_name, first_name
229:Indexes are used to police
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584:with pairs of keys and
175:Support for fast lookup
1579:Transaction processing
1534:Database normalization
1477:Query rewriting system
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689:This section is empty.
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446:reverse(email_address)
164:user-defined functions
1554:Referential integrity
991:Gavin Powell (2006).
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1544:Distributed database
972:Hector Garcia-Molina
959:Overview of Clusters
745:Microsoft SQL Server
528:{\displaystyle O(N)}
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231:database constraints
43:improve this article
1564:Relational calculus
1442:Concurrency control
1121:learn.microsoft.com
768:concurrency control
598:to the first record
1559:Relational algebra
1503:Query optimization
1308:Armstrong's axioms
1068:. Microsoft Press.
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221:(1)) performance.
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976:Jeffrey D. Ullman
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1508:Replication
1396:Transaction
1338:Foreign key
1318:CAP theorem
1265:Multi-model
1025:|work=
572:Dense index
362:statement:
306:index or a
239:FOREIGN KEY
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204:linear time
148:expressions
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1435:Components
1353:Unique key
1270:comparison
1204:comparison
1194:Relational
1187:comparison
1126:2023-04-08
1101:2023-04-08
935:References
700:April 2023
670:Hash index
588:for every
558:bit arrays
368:first_name
348:first_name
340:first_name
308:hash table
69:newspapers
1643:Databases
1491:Functions
1426:Partition
1253:In-memory
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1017:cite book
749:leaf node
578:databases
460:customers
415:customers
380:last_name
281:Clustered
156:last_name
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1513:Sharding
1369:Relation
1343:Superkey
1298:Database
1291:Concepts
911:See also
862:my_table
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734:B+ trees
666:record.
594:a record
586:pointers
566:B+ trees
441:sargable
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181:database
99:May 2024
1607:Outline
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481:reverse
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202:(N) or
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179:Most
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90:JSTOR
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