Managing Index-Organized Tables

Creating an Index-Organized Table

The following statement creates an index-organized table:

CREATE TABLE admin_docindex(
        token char(20), 
        doc_id NUMBER,
        token_frequency NUMBER,
        token_offsets VARCHAR2(512),
        CONSTRAINT pk_admin_docindex PRIMARY KEY (token, doc_id))
    ORGANIZATION INDEX 
    TABLESPACE admin_tbs
    PCTTHRESHOLD 20
    OVERFLOW TABLESPACE admin_tbs2;

Specifying ORGANIZATION INDEX causes the creation of an index-organized table, admin_docindex, where the key columns and nonkey columns reside in an index defined on columns that designate the primary key or keys for the table. In this case, the primary keys are token and doc_id. An overflow segment is specified and is discussed in "Using the Overflow Clause".

Creating Index-Organized Tables that Contain Object Types

Index-organized tables can store object types. The following example creates object type admin_typ, then creates an index-organized table containing a column of object type admin_typ:

CREATE OR REPLACE TYPE admin_typ AS OBJECT
    (col1 NUMBER, col2 VARCHAR2(6));
CREATE TABLE admin_iot (c1 NUMBER primary key, c2 admin_typ)
    ORGANIZATION INDEX;

You can also create an index-organized table of object types. For example:

CREATE TABLE admin_iot2 OF admin_typ (col1 PRIMARY KEY)
    ORGANIZATION INDEX;

Another example, that follows, shows that index-organized tables store nested tables efficiently. For a nested table column, the database internally creates a storage table to hold all the nested table rows.

CREATE TYPE project_t AS OBJECT(pno NUMBER, pname VARCHAR2(80));
/
CREATE TYPE project_set AS TABLE OF project_t;
/
CREATE TABLE proj_tab (eno NUMBER, projects PROJECT_SET)
    NESTED TABLE projects STORE AS emp_project_tab
                ((PRIMARY KEY(nested_table_id, pno)) 
    ORGANIZATION INDEX)
    RETURN AS LOCATOR;

The rows belonging to a single nested table instance are identified by a nested_table_id column. If an ordinary table is used to store nested table columns, the nested table rows typically get de-clustered. But when you use an index-organized table, the nested table rows can be clustered based on the nested_table_id column.

Using the Overflow Clause

The overflow clause specified in the statement shown in "Creating an Index-Organized Table" indicates that any nonkey columns of rows exceeding 20% of the block size are placed in a data segment stored in the admin_tbs2 tablespace. The key columns should fit the specified threshold.

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

If an update of a nonkey column causes the row to increase in size, the database identifies the piece (head or tail) to which the update is applicable and rewrites that row piece. If the target of the update turns out to be the head piece, note that this piece can again be broken into two to keep the row size below the specified threshold.

The nonkey 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 nonkey 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.

Using the INCLUDING Clause

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

CREATE TABLE admin_iot4(a INT, b INT, c INT, d INT, 
                primary key(c,b))
    ORGANIZATION INDEX;

The following CREATE TABLE statement is similar to the one shown earlier in "Creating an Index-Organized Table" but is modified to create an index-organized table where the token_offsets column value is always stored in the overflow area:

CREATE TABLE admin_docindex2(
        token CHAR(20), 
        doc_id NUMBER,
        token_frequency NUMBER,
        token_offsets VARCHAR2(512),
        CONSTRAINT pk_admin_docindex2 PRIMARY KEY (token, doc_id))
    ORGANIZATION INDEX 
    TABLESPACE admin_tbs
    PCTTHRESHOLD 20
    INCLUDING token_frequency
    OVERFLOW TABLESPACE admin_tbs2;

Here, only nonkey columns prior to token_offsets (in this case a single column only) are stored with the key column values in the index leaf block.

Parallelizing Index-Organized Table Creation

The CREATE TABLE...AS SELECT statement enables you to create an index-organized table and load data from an existing table into it. By including the PARALLEL clause, the load can be done in parallel.

The following statement creates an index-organized table in parallel by selecting rows from the conventional table hr.jobs:

CREATE TABLE admin_iot3(i PRIMARY KEY, j, k, l) 
     ORGANIZATION INDEX 
     PARALLEL
     AS SELECT * FROM hr.jobs;

This statement provides an alternative to parallel bulk-load using SQL*Loader.

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 in each index block while improving performance.

You can enable key compression using the COMPRESS clause while:

• Creating an index-organized table

• Moving an index-organized table

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 admin_iot5(i INT, j INT, k INT, l INT, PRIMARY KEY (i, j, k)) 
    ORGANIZATION INDEX COMPRESS;

The preceding statement is equivalent to the following statement:

CREATE TABLE admin_iot6(i INT, j INT, k INT, l INT, PRIMARY KEY(i, j, k)) 
    ORGANIZATION INDEX COMPRESS 2;

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 admin_iot7(i INT, j INT, k INT, l INT, PRIMARY KEY (i, j, k)) 
    ORGANIZATION INDEX COMPRESS 1;

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:

ALTER TABLE admin_iot5 MOVE NOCOMPRESS;

One application of key compression is in a time-series application that uses a set of time-stamped rows belonging to a single item, such as a stock price. Index-organized tables are attractive for such applications because of the ability to cluster rows based on the primary key. By defining an index-organized table with primary key (stock symbol, time stamp), you can store and manipulate time-series data efficiently. You can achieve more storage savings by compressing repeated occurrences of the item identifier (for example, the stock symbol) in a time series by using an index-organized table with key compression.

Altering Index-Organized Tables

All of the alter options available for ordinary tables are available for index-organized tables. This includes ADD, MODIFY, and DROP COLUMNS and CONSTRAINTS. However, the primary key constraint for an index-organized table cannot be dropped, deferred, or disabled

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:

ALTER TABLE admin_docindex INITRANS 4 OVERFLOW INITRANS 6;

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 admin_docindex table as follows:

ALTER TABLE admin_docindex PCTTHRESHOLD 15 INCLUDING doc_id;

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, you can add an overflow segment to table admin_iot3 as follows:

ALTER TABLE admin_iot3 ADD OVERFLOW TABLESPACE admin_tbs2;

Moving (Rebuilding) Index-Organized Tables

Because index-organized tables are primarily stored in a B-tree index, you can 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 admin_docindex:

ALTER TABLE admin_docindex MOVE;

You can rebuild index-organized tables online using the ONLINE keyword. The overflow data segment, if present, is rebuilt when the OVERFLOW keyword is specified. For example, to rebuild the admin_docindex table but not the overflow data segment, perform a move online as follows:

ALTER TABLE admin_docindex MOVE ONLINE;

To rebuild the admin_docindex table along with its overflow data segment perform the move operation as shown in the following statement. This statement also illustrates moving both the table and overflow data segment to new tablespaces.

ALTER TABLE admin_docindex MOVE TABLESPACE admin_tbs2 
    OVERFLOW TABLESPACE admin_tbs3;

In this last statement, an index-organized table with a LOB column (CLOB) is created. Later, the table is moved with the LOB index and data segment being rebuilt and moved to a new tablespace.

CREATE TABLE admin_iot_lob
   (c1 number (6) primary key,
    admin_lob CLOB)
   ORGANIZATION INDEX
   LOB (admin_lob) STORE AS (TABLESPACE admin_tbs2);
.
.
.
ALTER TABLE admin_iot_lob MOVE LOB (admin_lob) STORE AS (TABLESPACE admin_tbs3); 

Creating a Secondary Index on an Index-Organized Table

The following statement shows the creation of a secondary index on the docindex index-organized table where doc_id and token are the key columns:

CREATE INDEX Doc_id_index on Docindex(Doc_id, Token);

This secondary index allows the database to efficiently process a query, such as the following, the involves a predicate on doc_id:

SELECT Token FROM Docindex WHERE Doc_id = 1;

Maintaining Physical Guesses in Logical Rowids

A logical rowid can include a guess, which identifies the block location of a row at the time the guess is made. Instead of doing a full key search, the database uses the guess to search the block directly. However, as new rows are inserted, guesses can become stale. The indexes are still usable through the primary key-component of the logical rowid, but access to rows is slower.

Collect index statistics with the DBMS_STATS package to monitor the staleness of guesses. The database checks whether the existing guesses are still valid and records the percentage of rows with valid guesses in the data dictionary. This statistic is stored in the PCT_DIRECT_ACCESS column of the DBA_INDEXES view (and related views).

To obtain fresh guesses, you can rebuild the secondary index. Note that rebuilding a secondary index on an index-organized table involves reading the base table, unlike rebuilding an index on an ordinary table. A quicker, more light weight means of fixing the guesses is to use the ALTER INDEX ... UPDATE BLOCK REFERENCES statement. This statement is performed online, while DML is still allowed on the underlying index-organized table.

After you rebuild a secondary index, or otherwise update the block references in the guesses, collect index statistics again.

Bitmap Indexes

Bitmap indexes on index-organized tables are supported, provided the index-organized table is created with a mapping table. This is done by specifying the MAPPING TABLE clause in the CREATE TABLE statement that you use to create the index-organized table, or in an ALTER TABLE statement to add the mapping table later.

Collecting Optimizer Statistics for Index-Organized Tables

To collect optimizer statistics, use the DBMS_STATS package.

For example, the following statement gathers statistics for the index-organized countries table in the hr schema:

EXECUTE DBMS_STATS.GATHER_TABLE_STATS ('HR','COUNTRIES');

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

• The logical statistics can be queried using USER_TABLES, ALL_TABLES or DBA_TABLES.

• You can query the physical statistics of the primary key index segment using USER_INDEXES, ALL_INDEXES or DBA_INDEXES (and using the primary key index name). For example, you can obtain the primary key index segment physical statistics for the table admin_docindex as follows:

  SELECT LAST_ANALYZED, BLEVEL,LEAF_BLOCKS, DISTINCT_KEYS 
     FROM DBA_INDEXES WHERE INDEX_NAME= 'PK_ADMIN_DOCINDEX';
  

• You can query the physical statistics for the overflow data segment using the USER_TABLES, ALL_TABLES or DBA_TABLES. You can identify the overflow entry by searching for IOT_TYPE = 'IOT_OVERFLOW'. For example, you can obtain overflow data segment physical attributes associated with the admin_docindex table as follows:

  SELECT LAST_ANALYZED, NUM_ROWS, BLOCKS, EMPTY_BLOCKS 
     FROM DBA_TABLES WHERE IOT_TYPE='IOT_OVERFLOW' 
            and IOT_NAME= 'ADMIN_DOCINDEX';
  

  See Also:

  • Oracle Database Performance Tuning Guide for more information about collecting optimizer statistics

  • Oracle Database PL/SQL Packages and Types Reference for more information about of the DBMS_STATS package

Validating the Structure of Index-Organized Tables

Use the ANALYZE statement if you want to validate the structure of your index-organized table or to list any chained rows. These operations are discussed in the following sections located elsewhere in this book:

• "Validating Tables, Indexes, Clusters, and Materialized Views"

• "Listing Chained Rows of Tables and Clusters"

  Note:

  There are special considerations when listing chained rows for index-organized tables. These are discussed in the Oracle Database SQL Language Reference.