You can unsubscribe at any time. I need the answers for the following questions. Can anyone tell me how many columns can be created in a table? Can anyone tell me how many indexes can be created in a table? New and Improved Yahoo! Mail — MB free storage! We can create number of columns and as well as number of indexes,as there are not certainty for columns for a table so we cant fix also the indexes. By creating lots of indexes we only hamper our performance when it is interlinked to each other.
Basically we have clustered and non clustered indexes. In a particular table we ca create only a single cluster table and number of non cluster indexes. As now if we are focusing on maximum number of columns in a table it depends upon the cost optimisation and availability of size,partition and lots of thing. As per my knowledge am sharing the above things,if somebody found any exceptions to my comments please post earlier.
You can create an index on any column; however, if the column is not used in any of these situations, creating an index on the column does not increase performance and the index takes up resources unnecessarily.
Although the database creates an index for you on a column with an integrity constraint, explicitly creating an index on such a column is recommended. You can use the following techniques to determine which columns are best candidates for indexing:. Sometimes, if an index is not being used by default and it would be most efficient to use that index, you can use a query hint so that the index is used.
The following sections explain how to create, alter, and drop indexes using SQL commands, and give guidelines for managing indexes. Otherwise, the overhead of updating the index slows down the insert or load operation. The exception to this rule is that you must create an index for a cluster before you insert any data into the cluster. When you create an index on a table that already has data, Oracle Database must use sort space to create the index.
If the index is extremely large, it can be beneficial to complete the following steps:. Oracle Database Utilities for information on direct path load. Some columns are strong candidates for indexing. Columns with one or more of the following characteristics are good candidates for indexing:. The size of a single index entry cannot exceed roughly one-half minus some overhead of the available space in the data block.
Consult with the database administrator for assistance in determining the space required by an index. The more indexes, the more overhead is incurred as the table is altered. When rows are inserted or deleted, all indexes on the table must be updated. When a column is updated, all indexes on the column must be updated.
You must weigh the performance benefit of indexes for queries against the performance overhead of updates. A bitmap index is probably not useful for the other columns.
Instead, a unique B-tree index on these columns would likely provide the most efficient representation and retrieval. It consists of two separate bitmaps, one for each gender. A mapping function converts each bit in the bitmap to a rowid of the customers table. Each bit value depends on the values of the corresponding row in the table. For example, the bitmap for the M value contains a 1 as its first bit because the gender is M in the first row of the customers table.
An analyst investigating demographic trends of the customers may ask, "How many of our female customers are single or divorced?
Bitmap indexes can process this query efficiently by counting the number of 1 values in the resulting bitmap, as illustrated in Table To identify the customers who satisfy the criteria, Oracle Database can use the resulting bitmap to access the table.
Rows that satisfy some, but not all, conditions are filtered out before the table itself is accessed. This technique improves response time, often dramatically. For each value in a table column, the index stores the rowid of the corresponding row in the indexed table. In contrast, a standard bitmap index is created on a single table.
A bitmap join index is an efficient means of reducing the volume of data that must be joined by performing restrictions in advance. For an example of when a bitmap join index would be useful, assume that users often query the number of employees with a particular job type.
A typical query might look as follows:. The preceding query would typically use an index on jobs. To retrieve the data from the index itself rather than from a scan of the tables, you could create a bitmap join index as follows:.
As illustrated in Figure , the index key is jobs. A query of the number of accountants can use the index to avoid accessing the employees and jobs tables because the index itself contains the requested information.
In a data warehouse, the join condition is an equijoin it uses the equality operator between the primary key columns of the dimension tables and the foreign key columns in the fact table. Bitmap join indexes are sometimes much more efficient in storage than materialized join views, an alternative for materializing joins in advance.
Oracle Database uses a B-tree index structure to store bitmaps for each indexed key. For example, if jobs. The individual bitmaps are stored in the leaf blocks. Assume that the jobs. A bitmap index entry for this index has the following components:.
In this case, the session requires exclusive access to the index key entry for the old value Shipping Clerk and the new value Stock Clerk. The data for a bitmap index is stored in one segment. Oracle Database stores each bitmap in one or more pieces. Each piece occupies part of a single data block.
You can create indexes on functions and expressions that involve one or more columns in the table being indexed. A function-based index computes the value of a function or expression involving one or more columns and stores it in the index.
A function-based index can be either a B-tree or a bitmap index. For example, a function could add the values in two columns. Oracle Database Administrator's Guide to learn how to create function-based indexes. Oracle Database Performance Tuning Guide for more information about using function-based indexes. Function-based indexes are efficient for evaluating statements that contain functions in their WHERE clauses. The database only uses the function-based index when the function is included in a query.
The database can use the preceding index when processing queries such as Example partial sample output included. Example Query Containing an Arithmetic Expression. You create the following function-based index on the hr. A function-based index is also useful for indexing only specific rows in a table. To index only the A rows, you could write a function that returns a null value for any rows other than the A rows. You could create the index as follows:. Oracle Database Globalization Support Guide for information about linguistic indexes.
The optimizer can use an index range scan on a function-based index for queries with expressions in WHERE clause. The range scan access path is especially beneficial when the predicate WHERE clause has low selectivity. A virtual column is useful for speeding access to data derived from expressions. The optimizer performs expression matching by parsing the expression in a SQL statement and then comparing the expression trees of the statement and the function-based index.
This comparison is case-insensitive and ignores blank spaces. Oracle Database Performance Tuning Guide for more information about gathering statistics. Oracle Database Administrator's Guide to learn how to add virtual columns to a table.
An application domain index is a customized index specific to an application. Oracle Database provides extensible indexing to do the following:. Accommodate indexes on customized, complex data types such as documents, spatial data, images, and video clips see "Unstructured Data".
You can encapsulate application-specific index management routines as an indextype schema object and define a domain index on table columns or attributes of an object type. Extensible indexing can efficiently process application-specific operators.
The application software, called the cartridge , controls the structure and content of a domain index. The database interacts with the application to build, maintain, and search the domain index. The index structure itself can be stored in the database as an index-organized table or externally as a file. Oracle Database stores index data in an index segment. Space available for index data in a data block is the data block size minus block overhead, entry overhead, rowid, and one length byte for each value indexed.
For ease of administration you can store an index in a separate tablespace from its table. For example, you may choose not to back up tablespaces containing only indexes, which can be rebuilt, and so decrease the time and storage required for backups.
An index-organized table is a table stored in a variation of a B-tree index structure. In a heap-organized table , rows are inserted where they fit. In an index-organized table, rows are stored in an index defined on the primary key for the table. Each index entry in the B-tree also stores the non-key column values. Thus, the index is the data, and the data is the index.
Applications manipulate index-organized tables just like heap-organized tables, using SQL statements. For an analogy of an index-organized table, suppose a human resources manager has a book case of cardboard boxes. Each box is labeled with a number—1, 2, 3, 4, and so on—but the boxes do not sit on the shelves in sequential order. Instead, each box contains a pointer to the shelf location of the next box in the sequence.
Folders containing employee records are stored in each box. The folders are sorted by employee ID. The folder for employee is on top of , is on top of , and so on until box 1 is full. The next folder in the sequence is at the bottom of box 2.
In this analogy, ordering folders by employee ID makes it possible to search efficiently for folders without having to maintain a separate index.
Suppose a user requests the records for employees , , and Instead of searching an index in one step and retrieving the folders in a separate step, the manager can search the folders in sequential order and retrieve each folder as found.
Index-organized tables provide faster access to table rows by primary key or a valid prefix of the key. For example, the salary of employee is stored in the index row itself. Another benefit is the avoidance of the space overhead of a separate primary key index. Index-organized tables are useful when related pieces of data must be stored together or data must be physically stored in a specific order. Oracle Database Administrator's Guide to learn how to manage index-organized tables.
Oracle Database Performance Tuning Guide to learn how to use index-organized tables to improve performance. The database system performs all operations on index-organized tables by manipulating the B-tree index structure.
Table summarizes the differences between index-organized tables and heap-organized tables. The rowid uniquely identifies a row. Primary key constraint may optionally be defined. Sequential full table scan returns all rows in some order. A full index scan or fast full index scan returns all rows in some order.
Can be stored in a table cluster with other tables. Can contain virtual columns only relational heap tables are supported. Figure illustrates the structure of an index-organized departments table. The leaf blocks contain the rows of the table, ordered sequentially by primary key. For example, the first value in the first leaf block shows a department ID of 20 , department name of Marketing , manager ID of , and location ID of An index-organized table stores all data in the same structure and does not need to store the rowid.
As shown in Figure , leaf block 1 in an index-organized table might contain entries as follows, ordered by primary key:. A scan of the index-organized table rows in primary key order reads the blocks in the following sequence:. To contrast data access in a heap-organized table to an index-organized table, suppose block 1 of a heap-organized departments table segment contains rows as follows:. A B-tree index leaf block for this heap-organized table contains the following entries, where the first value is the primary key and the second is the rowid :.
A scan of the table rows in primary key order reads the table segment blocks in the following sequence:. When creating an index-organized table, you can specify a separate segment as a row overflow area. In index-organized tables, B-tree index entries can be large because they contain an entire row, so a separate segment to contain the entries is useful. In contrast, B-tree entries are usually small because they consist of the key and rowid.
For instance, a table with four 3-column indexes where the leading two columns are the same may work very efficiently on select statements but cause a heavy penalty on inserts and updates. Just one 2-column index on the leading two columns may provide acceptable query performance while greatly improving DML. A 2-column table with a primary key and a two-column index has 1. Making the table an Index Organized Table reduced the need for indexes because the table is the index.
Also IOTs can have indexes on non-leading columns if required. Again this has to be balanced with the overhead of maintaining the IOT. Lastly, do not be afraid to use temporary indexes.
If you run a nightly report that requires 6 hours to run, but will run in 30 mins with a specific index, you might want to create the index before running the report and drop it upon completion.
I work with clients that drop certain indexes to expedite the bill run, then recreate then for the normal application. They create indexes each night and drop them in the morning. There is nothing wrong with dynamically changing you database to respond to varying tasks if it results in efficiency.
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