Oracle8i Administrator's Guide
Release 2 (8.1.6)

Part Number A76956-01





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Managing Tables

This chapter describes the various aspects of managing tables, and includes the following topics:

Before attempting tasks described in this chapter, familiarize yourself with the concepts in Chapter 12, "Guidelines for Managing Schema Objects".

Guidelines for Managing Tables

This section describes guidelines to follow when managing tables, and includes the following topics:

Use these guidelines to make managing tables as easy as possible.

Design Tables Before Creating Them

Usually, the application developer is responsible for designing the elements of an application, including the tables. Database administrators are responsible for setting storage parameters and defining clusters for tables, based on information from the application developer about how the application works and the types of data expected.

Working with your application developer, carefully plan each table so that the following occurs:

Specify How Data Block Space Is to Be Used

By specifying the PCTFREE and PCTUSED parameters during the creation of each table, you can affect the efficiency of space utilization and amount of space reserved for updates to the current data in the data blocks of a table's data segment. The PCTFREE and PCTUSED parameters are discussed in "Managing Space in Data Blocks".

Specify Transaction Entry Parameters

By specifying the INITRANS and MAXTRANS parameters during the creation of each table, you can affect how much space is initially and can ever be allocated for transaction entries in the data blocks of a table's data segment. For information about setting the INITRANS and MAXTRANS parameters, see "Setting Storage Parameters".

Specify the Location of Each Table

If you have the proper privileges and tablespace quota, you can create a new table in any tablespace that is currently online. It is advisable to specify the TABLESPACE clause in a CREATE TABLE statement to identify the tablespace that will store the new table. If you do not specify a tablespace in a CREATE TABLE statement, the table is created in your default tablespace.

When specifying the tablespace to contain a new table, make sure that you understand implications of your selection. By properly specifying a tablespace during the creation of each table, you can:

The following situations illustrate how specifying incorrect storage locations for schema objects can affect a database:

Chapter 22, "Managing Users and Resources" contains information about assigning default tablespaces and tablespace quotas to users.

Parallelize Table Creation

You can parallelize the creation of tables created with a subquery in the CREATE TABLE statement. Because multiple processes work together to create the table, performance of the table creation can improve.

See Also:

For information about parallel execution, including parallel table creation, see the following books:

Consider Creating UNRECOVERABLE Tables

When you create an unrecoverable table, the table cannot be recovered from archived logs (because the needed redo log records are not generated for the unrecoverable table creation). Thus, if you cannot afford to lose the table, you should take a backup after the table is created. In some situations, such as for tables that are created for temporary use, this precaution may not be necessary.

You can create an unrecoverable table by specifying UNRECOVERABLE when you create a table with a subquery in the CREATE TABLE...AS SELECT statement. However, rows inserted afterwards are recoverable. In fact, after the statement is completed, all future statements are fully recoverable.

Creating an unrecoverable table has the following benefits:

In general, the relative performance improvement is greater for larger unrecoverable tables than for smaller tables. Creating small unrecoverable tables has little effect on the time it takes to create a table. However, for larger tables the performance improvement can be significant, especially when you are also parallelizing the table creation.

Estimate Table Size and Set Storage Parameters

Estimating the sizes of tables before creating them is useful for the following reasons:

Whether or not you estimate table size before creation, you can explicitly set storage parameters when creating each nonclustered table. (Clustered tables automatically use the storage parameters of the cluster.) Any storage parameter that you do not explicitly set when creating or subsequently altering a table automatically uses the corresponding default storage parameter set for the tablespace in which the table resides. Storage parameters are discussed in "Setting Storage Parameters".

If you explicitly set the storage parameters for the extents of a table's data segment, try to store the table's data in a small number of large extents rather than a large number of small extents.

Plan for Large Tables

There are no limits on the physical size of tables and extents. You can specify the keyword UNLIMITED for MAXEXTENTS, thereby simplifying your planning for large objects, reducing wasted space and fragmentation, and improving space reuse. However, keep in mind that while Oracle allows an unlimited number of extents, when the number of extents in a table grows very large, you may see an impact on performance when performing any operation requiring that table.


You cannot alter data dictionary tables to have MAXEXTENTS greater than the allowed block maximum. 

If you have such tables in your database, consider the following recommendations:

Table Restrictions

Before creating tables, make sure you are aware of the following restrictions:

Additionally, when you create a table that contains user-defined type data, Oracle maps columns of user-defined type to relational columns for storing the user-defined type data. These "hidden" relational columns are not visible in a DESCRIBE table statement and are not returned by a SELECT * statement. Therefore, when you create an object table, or a relational table with columns of REF, varray, nested table, or object type, the total number of columns that Oracle actually creates for the table may be more than those you specify, because Oracle creates hidden columns to store the user-defined type data.

The following formulas determine the total number of columns created for a table with user-defined type data:

Number of columns in an object table:

num_columns(object_table) =
  + num_columns(row_type)
  + number of top-level object columns in the object type of table
  + num_columns(object_type)

Number of columns in a relational table:

num_columns(relational_table) =
    number of scalar columns in the table
  + number of object columns in the table
  + SUM [num_columns(object_type(i))]   i= 1 -> n
  + SUM [num_columns(nested_table(j))]  j= 1 -> m
  + SUM [num_columns(varray(k))]        k= 1 -> p
  + SUM [num_columns(REF(l))]           l= 1 -> q

where in the given relational table:

object_type(i) is the ith object type column and
   n is the total number of such object type columns
nested_table(j) is the jth nested_table column and 
   m is the total number of such nested table columns
varray(k) is the kth varray column and 
   p is the total number of such varray columns, 
REF(l) is the lth REF column and 
   q is the total number of such REF columns.


num_columns(object identifier) = 1
num_columns(row_type)          = 1
num_columns(REF)               = 1, if REF is unscoped 
                               = 1, if the REF is scoped and the object identifier
                                 is system generated and the REF has no
                                 referential constraint
                               = 2, if the REF is scoped and the object identifier
                                 is system generated and the REF has a
                                 referential constraint
                               = 1 + number of columns in the primary key,
                                 if the object identifier is primary key based
num_columns(nested_table)      = 2
num_columns(varray)            = 1
num_columns(object_type)       = number of scalar attributes in the object type
                               + SUM[num_columns(object_type(i))]     i= 1 -> n
                               + SUM[num_columns(nested_table(j))]    j= 1 -> m
                               + SUM[num_columns(varray(k))]          k= 1 -> p
                               + SUM[num_columns(REF(l))]             l= 1 -> q

where in the given object type:

object_type(i) is an embedded object type attribute and
   n is the total number of such object type attributes,
nested_table(j) is an embedded nested_table attribute and
   m is the total number of such nested table attributes,
varray(k) is an embedded varray attribute and
   p is the total number of such varray attributes,
REF(l) is an embedded REF attribute and
   q is the total number of such REF attributes.

The following are some examples of computing the number of columns for an object table, or a relational table with columns of REF, varray, nested table, or object type.

Example 1:

CREATE TYPE physical_address_type AS OBJECT 
        (no CHAR(4), street CHAR(31), city CHAR(5), state CHAR(3)); 
CREATE TYPE phone_type AS VARRAY(5) OF CHAR(15); 
CREATE TYPE electronic_address_type AS OBJECT 
        (phones phone_type, fax CHAR(12), email CHAR(31)); 
CREATE TYPE contact_info_type AS OBJECT 
        (physical_address physical_address_type, 
         electronic_address electronic_address_type); 
CREATE TYPE employee_type AS OBJECT 
        (eno NUMBER, ename CHAR(60), 
         contact_info contact_info_type); 
CREATE TABLE employee_object_table OF employee_type; 

To calculate number of columns in employee object table, we first need to calculate number of columns required for employee_type:

num_columns(physical_address_type) = 
     number of scalar attributes = 4 
num_columns(phone_type) = 
     num_columns(varray) = 1 
num_columns(electronic_address_type) = 
     number of scalar attributes 
   + num_columns(phone_type) 
   = 2 + 1 = 3 
num_columns(contact_info_type) = 
   + num_columns(electronic_address_type) 
   = 3 + 4 = 7 
num_columns(employee_type) = 
     number of scalar attributes 
   + num_columns(contact_info_type) 
   = 2 + 7 = 9 

Now, use the formula for object tables:

num_columns (employee_object_table) = 
   + num_columns(row_type) 
   + number of top level object columns in employee_type 
   + num_columns(employee_type) 
   = 1 + 1 + 1 + 9 = 12 
Example 2:
CREATE TABLE employee_relational_table (einfo employee_type); 

num_columns (employee_relational_table) = 
     number of object columns in table 
   + num_columns(employee_type) 
   = 1 + 9 = 10 
Example 3:
CREATE TYPE project_type AS OBJECT (pno NUMBER, pname CHAR(30), budget NUMBER); 

CREATE TYPE project_set_type AS TABLE OF project_type; 

CREATE TABLE department 
        (dno NUMBER, dname CHAR(30), 
         mgr REF employee_type REFERENCES employee_object_table, 
         project_set project_set_type) 
NESTED TABLE project_set STORE AS project_set_nt; 

num_columns(department) = 
     number of scalar columns 
   + num_columns(mgr) 
   + num_columns(project_set) 
   = 2 + 2 + 2  = 6 

Creating Tables

To create a new table in your schema, you must have the CREATE TABLE system privilege. To create a table in another user's schema, you must have the CREATE ANY TABLE system privilege. Additionally, the owner of the table must have a quota for the tablespace that contains the table, or the UNLIMITED TABLESPACE system privilege.

Create tables using the SQL statement CREATE TABLE. When user SCOTT issues the following statement, he creates a nonclustered table named EMP in his schema and stores it in the USERS tablespace:

CREATE TABLE        emp (
         empno      NUMBER(5) PRIMARY KEY,
         ename      VARCHAR2(15) NOT NULL,
         job        VARCHAR2(10),
         mgr        NUMBER(5),
         hiredate   DATE DEFAULT (sysdate),
         sal        NUMBER(7,2),
         comm       NUMBER(7,2),
         deptno     NUMBER(3) NOT NULL
                     CONSTRAINT dept_fkey REFERENCES dept)
             NEXT 50K
             MAXEXTENTS 10
             PCTINCREASE 25 );

In this example, integrity constraints are defined on several columns of the table. Integrity constraints are discussed in "Managing Integrity Constraints". Several segment attributes are also explicitly specified for the table. These are explained in Chapter 12, "Guidelines for Managing Schema Objects".

It is also possible to create a temporary table. The definition of a temporary table is visible to all sessions, but the data in a temporary table is visible only to the session that inserts the data into the table. You use the CREATE GLOBAL TEMPORARY TABLE statement to create a temporary table. The ON COMMIT keywords indicate if the data in the table is transaction-specific (the default) or session-specific:

This example creates a temporary table that is transaction specific:

        (startdate DATE,
         enddate DATE,
         class CHAR(20))

Indexes can be created on temporary tables. They are also temporary and the data in the index has the same session or transaction scope as the data in the underlying table.

See Also:

For exact syntax, authorization, or restrictions information for CREATE TABLE and other statements discussed in this chapter, see Oracle8i SQL Reference.

For more information on temporary tables, see Oracle8i Concepts. 

Altering Tables

To alter a table, the table must be contained in your schema, or you must have either the ALTER object privilege for the table or the ALTER ANY TABLE system privilege.

A table in an Oracle database can be altered for the following reasons:

You can increase the length of an existing column. However, you cannot decrease it unless there are no rows in the table. Furthermore, if you are modifying a table to increase the length of a column of datatype CHAR, realize that this may be a time consuming operation and may require substantial additional storage, especially if the table contains many rows. This is because the CHAR value in each row must be blank-padded to satisfy the new column length.

When altering the data block space usage parameters (PCTFREE and PCTUSED) of a table, note that new settings apply to all data blocks used by the table, including blocks already allocated and subsequently allocated for the table. However, the blocks already allocated for the table are not immediately reorganized when space usage parameters are altered, but as necessary after the change. The data block storage parameters are described in "Managing Space in Data Blocks".

When altering the transaction entry settings (INITRANS, MAXTRANS) of a table, note that a new setting for INITRANS applies only to data blocks subsequently allocated for the table, while a new setting for MAXTRANS applies to all blocks (already and subsequently allocated blocks) of a table. To better understand these transaction entry setting parameters, see "Transaction Entry Settings (INITRANS and MAXTRANS)".

The storage parameters INITIAL and MINEXTENTS cannot be altered. All new settings for the other storage parameters (for example, NEXT, PCTINCREASE) affect only extents subsequently allocated for the table. The size of the next extent allocated is determined by the current values of NEXT and PCTINCREASE, and is not based on previous values of these parameters. Storage parameters are discussed in "Setting Storage Parameters".

You alter a table using the ALTER TABLE statement. The following statement alters the EMP table. It alters the data block storage parameters, and adds a new column named BONUS.

      ADD (bonus NUMBER (7,2))
      PCTFREE 30
      PCTUSED 60;

Some of the other usages of the ALTER TABLE statement are presented in the following sections:

Moving a Table to a New Segment or Tablespace

The ALTER TABLE...MOVE statement allows you to relocate data of a nonpartitioned table into a new segment, and optionally into a different tablespace for which you have quota. This statement also allows you to modify any of the table's storage attributes, including those which cannot be modified using ALTER TABLE.

The following statement moves the EMP table to a new segment specifying new storage parameters.

                NEXT 40K
                MINEXTENTS 2
                MAXEXTENTS 20
                PCTINCREASE 0 );

If the table includes LOB column(s), this statement can be used to move the table along with LOB data and LOB index segments (associated with this table) which the user explicitly specifies. If not specified, the default is to not move the LOB data and LOB index segments.

Manually Allocating Storage for a Table

Oracle dynamically allocates additional extents for the data segment of a table, as required. However, you might want to allocate an additional extent for a table explicitly. For example, when using the Oracle Parallel Server, an extent of a table can be allocated explicitly for a specific instance.

A new extent can be allocated for a table using the ALTER TABLE statement with the ALLOCATE EXTENT option.

You can also explicitly deallocate unused space using the DEALLOCATE UNUSED clause of ALTER TABLE. This is described in "Deallocating Space".

See Also:

For information about using the ALLOCATE EXTENT option in an OPS environment, see Oracle8i Parallel Server Administration, Deployment, and Performance. 

Dropping Columns

Oracle allows you to drop columns that are no longer needed from a table, including an index-organized table. This provides a convenient means to free space in a database, and avoids your having to export/import data then recreate indexes and constraints. Users require the ALTER privilege on the target table or the ALTER ANY TABLE system privilege to issue any of the drop column related statements below.

You cannot drop all columns from a table, nor can you drop columns from a table owned by SYS. Any attempt to do so will result in an error. For additional restrictions and options, see Oracle8i SQL Reference.

Removing Columns from Tables

When you issue an ALTER TABLE...DROP COLUMN statement, the column descriptor and the data associated with the target column are removed from each row in the table. You can drop multiple columns with one statement. The following statements are examples of dropping columns from the EMP table.

This statement drops only the SAL column:


The following statement drops both the SAL and COMM columns:

ALTER TABLE emp DROP (sal, comm);

Marking Columns Unused

If you are concerned about the length of time it could take to drop column data from all of the rows in a large table, you can use the ALTER TABLE...SET UNUSED statement. This statement marks one or more columns as unused, but does not actually remove the target column data or restore the disk space occupied by these columns. However, a column that is marked as unused will not be displayed in queries or data dictionary views, and its name is removed so that a new column can reuse that name. All constraints, indexes, and statistics defined on the column are also removed.

To mark the SAL and COMM columns as unused, execute the following statement.

ALTER TABLE emp SET UNUSED (sal, comm);

You can later remove columns that are marked as unused by issuing an ALTER TABLE...DROP UNUSED COLUMNS statement. Unused columns are also removed from the target table whenever an explicit drop of any particular column or columns of the table is issued.

The data dictionary views USER_UNUSED_COL_TABS, ALL_UNUSED_COL_TABS, or DBA_UNUSED_COL_TABS can be used to list all tables containing unused columns. The COUNT field shows the number of unused columns in the table.

SELECT * FROM dba_unused_col_tabs;

OWNER                       TABLE_NAME                  COUNT
--------------------------- --------------------------- ----------
SCOTT                       EMP                                  1
1 row selected.

Removing Unused Columns

The ALTER TABLE...DROP UNUSED COLUMNS statement is the only action allowed on unused columns. It physically removes unused columns from the table and reclaims disk space.

In the example that follows the optional keyword CHECKPOINT is specified. This option causes a checkpoint to be applied after processing the specified number of rows, in this case 250. Checkpointing cuts down on the amount of undo logs accumulated during the drop column operation to avoid a potential exhaustion of rollback segment space.


Dropping Tables

To drop a table, the table must be contained in your schema or you must have the DROP ANY TABLE system privilege.

To drop a table that is no longer needed, use the DROP TABLE statement. The following statement drops the EMP table:


If the table to be dropped contains any primary or unique keys referenced by foreign keys of other tables and you intend to drop the FOREIGN KEY constraints of the child tables, include the CASCADE option in the DROP TABLE statement, as shown below:



Before dropping a table, familiarize yourself with the consequences of doing so:

  • Dropping a table removes the table definition from the data dictionary. All rows of the table are no longer accessible.

  • All indexes and triggers associated with a table are dropped.

  • All views and PL/SQL program units dependent on a dropped table remain, yet become invalid (not usable). See "Managing Object Dependencies" for information about how Oracle manages dependencies.

  • All synonyms for a dropped table remain, but return an error when used.

  • All extents allocated for a nonclustered table that is dropped are returned to the free space of the tablespace and can be used by any other object requiring new extents or new objects. All rows corresponding to a clustered table are deleted from the blocks of the cluster.

Instead of dropping a table, you might want to truncate it. The TRUNCATE statement provides a fast, efficient method for deleting all rows from a table, but it does not affect any structures associated with the table being truncated (column definitions, constraints, triggers, etc.) or authorizations. The TRUNCATE statement is discussed in "Truncating Tables and Clusters".

Index-Organized Tables

This section describes aspects of managing index-organized tables, and includes the following topics:

What are Index-Organized Tables

Index-organized tables are tables with data rows grouped according to the primary key. This clustering is achieved using a B*-tree index. B*-tree indexes are special types of index trees that differ from regular table B-tree indexes in that they store both the primary key and non-key columns. The attributes of index-organized tables are stored entirely within the physical data structures for the index.

Why use Index-Organized Tables

Index-organized tables provide fast key-based access to table data for queries involving exact match and range searches. Changes to the table data (such as adding new rows, updating rows, or deleting rows) result only in updating the index structure (because there is no separate table storage area).

Also, storage requirements are reduced because key columns are not duplicated in the table and index. The remaining non-key columns are stored in the index structure.

Index-organized tables are particularly useful when you are using applications that must retrieve data based on a primary key. Index-organized tables are also suitable for modeling application-specific index structures. For example, content-based information retrieval applications containing text, image and audio data require inverted indexes that can be effectively modeled using index-organized tables.

Differences Between Index Organized and Regular Tables

Index-organized tables are like regular tables with a primary key index on one or more of its columns. However, instead of maintaining two separate storage spaces for the table and B*tree index, an index-organized table only maintains a single B*tree index containing the primary key of the table and other column values.

The following figure illustrates the structural difference between regular tables and index-organized tables.

Figure 13-1 Structure of Regular Table versus Index-Organized Table

Text description of tablesa.gif follows.

Text description of the illustration tablesa.gif.

Index-organized tables are suitable for accessing data by way of primary key or any key that is a valid prefix of the primary key. There is no duplication of key values and storage requirements are reduced because a separate index structure containing the key values and ROWID is not created.

See Also:

For more details about index-organized tables, see Oracle8i Concepts.

For details of the syntax involved in creating index-organized tables, see Oracle8i SQL Reference.  

Creating Index-Organized Tables

You use the CREATE TABLE statement to create index-organized tables, but you will need to provide the following additional information:

The following example creates an index-organized table:

CREATE TABLE docindex(
        token char(20), 
        doc_id NUMBER,
        token_frequency NUMBER,
        token_offsets VARCHAR2(512),
        CONSTRAINT pk_docindex PRIMARY KEY (token, doc_id))

The above example shows that the ORGANIZATION INDEX qualifier specifies an index-organized table, where the key columns and non-key columns reside in an index defined on columns that designate the primary key (TOKEN, DOC_ID) for the table.

Index-organized tables can store object types. For example, you can create an index-organized table containing a column of object type MYTYPE (for the purpose of this example) as follows:

CREATE TABLE iot (c1 NUMBER primary key, c2 mytype)

However, you cannot create an index-organized table of object types. For example, the following statement would not be valid:


Using the AS Subquery

You can create an index-organized table using the AS subquery. Creating an index-organized table in this manner enables you to load the table in parallel by using the PARALLEL option.

The following statement creates an index-organized table (in parallel) by selecting rows from a conventional table, RT:

    AS SELECT * FROM rt;

Using the Overflow Clause

The overflow clause specified in the earlier example indicates that any non-key columns of rows exceeding 20% of the block size are placed in a data segment stored in the OVF_TBS tablespace. The key columns should fit the specified threshold.

If an update of a non-key column causes the row to decrease in size, Oracle identifies the row piece (head or tail) to which the update is applicable and rewrites that piece.

If an update of a non-key column causes the row to increase in size, Oracle identifies the piece (head or tail) to which the update is applicable and rewrites that row piece. If the update's target turns out to be the head piece, note that this piece may again be broken into 2 to keep the row size below the specified threshold.

The non-key columns that fit in the index leaf block are stored as a row head-piece that contains a ROWID field linking it to the next row piece stored in the overflow data segment. The only columns that are stored in the overflow area are those that do not fit.

Choosing and Monitoring a Threshold Value

You should choose a threshold value that can accommodate your key columns, as well as the first few non-key columns (if they are frequently accessed).

After choosing a threshold value, you can monitor tables to verify that the value you specified is appropriate. You can use the ANALYZE TABLE...LIST CHAINED ROWS statement to determine the number and identity of rows exceeding the threshold value.

See Also:

For details about this use of the ANALYZE statement, see Oracle8i SQL Reference

Using the INCLUDING clause

In addition to specifying PCTTHRESHOLD, you can use the INCLUDING <column_name> clause to control which non-key columns are stored with the key columns. Oracle accommodates all non-key columns up to the column specified in the INCLUDING clause in the index leaf block, provided it does not exceed the specified threshold. All non-key columns beyond the column specified in the INCLUDING clause are stored in the overflow area.


Oracle moves all primary key columns of an indexed-organized table to the beginning of the table (in their key order), in order to provide efficient primary key based access. As an example:

                primary key(c,b))

The stored column order is: c b a d (instead of: a b c d). The last primary key column is b, based on the stored column order. The INCLUDING column can be the last primary key column (b in this example), or any non-key column (i.e., any column after b in the stored column order). 

The example presented earlier can be modified to create an index-organized table where the TOKEN_OFFSETS column value is always stored in the overflow area:

CREATE TABLE docindex(
        token CHAR(20), 
        doc_id NUMBER,
        token_frequency NUMBER,
        token_offsets VARCHAR2(512),
        CONSTRAINT pk_docindex PRIMARY KEY (token, doc_id))
        INCLUDING token_frequency
        OVERFLOW TABLESPACE ovf_tbs;

Here, only non-key columns up to TOKEN_FREQUENCY (in this case a single column only) are stored with the key column values in the index leaf block.

Using Key Compression

Creating an index-organized table using key compression enables you to eliminate repeated occurrences of key column prefix values.

Key compression breaks an index key into a prefix and a suffix entry. Compression is achieved by sharing the prefix entries among all the suffix entries in an index block. This sharing can lead to huge savings in space, allowing you to store more keys per index block while improving performance.

You can enable key compression using the COMPRESS clause while:

You can also specify the prefix length (as the number of key columns), which identifies how the key columns are broken into a prefix and suffix entry.

CREATE TABLE iot(i INT, j INT, k INT, l INT, PRIMARY KEY (i, j, k)) 

The preceding statement is equivalent to the following statement:

CREATE TABLE iot(i INT, j INT, k INT, l INT, PRIMARY KEY(i, j, k)) 

For the list of values (1,2,3), (1,2,4), (1,2,7), (1,3,5), (1,3,4), (1,4,4) the repeated occurrences of (1,2), (1,3) are compressed away.

You can also override the default prefix length used for compression as follows:

CREATE TABLE iot(i INT, j INT, k INT, l INT, PRIMARY KEY (i, j, k)) 

For the list of values (1,2,3), (1,2,4), (1,2,7), (1,3,5), (1,3,4), (1,4,4), the repeated occurrences of 1 are compressed away.

You can disable compression as follows:


See Also:

For more details about key compression, see Oracle8i Concepts and the Oracle8i SQL Reference. 

Maintaining Index-Organized Tables

Index-organized tables differ from regular tables only in physical organization; logically, they are manipulated in the same manner. You can use an index-organized table in place of a regular table in INSERT, SELECT, DELETE, and UPDATE statements.

Altering Index-Organized Tables

You can use the ALTER TABLE statement to modify physical and storage attributes for both primary key index and overflow data segments. All the attributes specified prior to the OVERFLOW keyword are applicable to the primary key index segment. All attributes specified after the OVERFLOW key word are applicable to the overflow data segment. For example, you can set the INITRANS of the primary key index segment to 4 and the overflow of the data segment INITRANS to 6 as follows:


You can also alter PCTTHRESHOLD and INCLUDING column values. A new setting is used to break the row into head and overflow tail pieces during subsequent operations. For example, the PCTHRESHOLD and INCLUDING column values can be altered for the DOCINDEX table as follows:


By setting the INCLUDING column to DOC_ID, all the columns that follow TOKEN_FREQUENCY and TOKEN_OFFSETS, are stored in the overflow data segment.

For index-organized tables created without an overflow data segment, you can add an overflow data segment by using the ADD OVERFLOW clause. For example, if the DOCINDEX table did not have an overflow segment, then you can add an overflow segment as follows:


Moving (Rebuilding) Index-Organized Tables

Because index-organized tables are primarily stored in a B*-tree index, you may encounter fragmentation as a consequence of incremental updates. However, you can use the ALTER TABLE...MOVE statement to rebuild the index and reduce this fragmentation.

The following statement rebuilds the index-organized table DOCINDEX after setting its INITRANS to 10:


You can move index-organized tables with no overflow data segment online using the ONLINE option. For example, if the DOCINDEX table does not have an overflow data segment, then you can perform the move online as follows:


The following statement rebuilds the index-organized table DOCINDEX along with its overflow data segment:


And in this last statement, index-organized table IOT is moved while the LOB index and data segment for C2 are rebuilt:


Scenario: Updating the Key Column

A key column update is logically equivalent to deleting the row with the old key value and inserting the row with the new key value at the appropriate place to maintain the primary key order.

Logically, in the following example, the employee row for dept_id=20 and
e_id=10 are deleted and the employee row for dept_id=23 and e_id=10 are inserted:

UPDATE employees
    SET dept_id=23
    WHERE dept_id=20 and e_id=10;

Analyzing Index-Organized Tables

Just like conventional tables, index-organized tables are analyzed using the ANALYZE statement:


The ANALYZE statement analyzes both the primary key index segment and the overflow data segment, and computes logical as well as physical statistics for the table.

Using the ORDER BY Clause with Index-Organized Tables

If an ORDER BY clause only references the primary key column or a prefix of it, then the optimizer avoids the sorting overhead as the rows are returned sorted on the primary key columns.

For example, you create the following table:

CREATE TABLE employees (dept_id INTEGER, e_id INTEGER, e_name 

The following queries avoid sorting overhead because the data is already sorted on the primary key:

SELECT * FROM employees ORDER BY (dept_id, e_id);
SELECT * FROM employees ORDER BY (dept_id);

If, however, you have an ORDER BY clause on a suffix of the primary key column or non-primary key columns, additional sorting is required (assuming no other secondary indexes are defined).

SELECT * FROM employees ORDER BY (e_id);
SELECT * FROM employees ORDER BY (e_name);

Converting Index-Organized Tables to Regular Tables

You can convert index-organized tables to regular tables using the Oracle IMPORT/EXPORT utilities, or the CREATE TABLE...AS SELECT statement.

To convert an index-organized table to a regular table:

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