Heap-Organized table 和 Index-Organized table 说明

Heap-Organized Table	Index-Organized Table
The rowid uniquely identifies a row. Primary key constraint may optionally be defined.	Primary key uniquely identifies a row. Primary key constraint must be defined.
Physical rowid in ROWID pseudocolumn allows building secondary indexes.	Logical rowid in ROWID pseudocolumn allows building secondary indexes.
Individual rows may be accessed directly by rowid.	Access to individual rows may be achieved indirectly by primary key.
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.	Cannot be stored in a table cluster.
Can contain a column of the LONG data type and columns of LOB data types.	Can contain LOB columns but not LONG columns.
Can contain virtual columns (only relational heap tables are supported).	Cannot contain virtual columns.

Figure 3-3 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 201, and location ID of 1800.

Figure 3-3 Index-Organized Table

Description of "Figure 3-3 Index-Organized Table"

An index-organized table stores all data in the same structure and does not need to store the rowid. As shown in Figure 3-3, leaf block 1 in an index-organized table might contain entries as follows, ordered by primary key:

20,Marketing,201,1800

30,Purchasing,114,1700

Leaf block 2 in an index-organized table might contain entries as follows:

50,Shipping,121,1500

60,IT,103,1400

A scan of the index-organized table rows in primary key order reads the blocks in the following sequence:

1.Block 1

2.Block 2

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:

50,Shipping,121,1500

20,Marketing,201,1800

Block 2 contains rows for the same table as follows:

30,Purchasing,114,1700

60,IT,103,1400

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:

20,AAAPeXAAFAAAAAyAAD

30,AAAPeXAAFAAAAAyAAA

50,AAAPeXAAFAAAAAyAAC

60,AAAPeXAAFAAAAAyAAB

A scan of the table rows in primary key order reads the table segment blocks in the following sequence:

Thus, the number of block I/Os in this example is double the number in the index-organized example.

See Also:

· "Table Organization"

· "Introduction to Logical Storage Structures"

Index-Organized Tables with Row Overflow Area

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.

If a row overflow area is specified, then the database can divide a row in an index-organized table into the following parts:

（1）The index entry

This part contains column values for all the primary key columns, a physical rowid that points to the overflow part of the row, and optionally a few of the non-key columns. This part is stored in the index segment.

（2）The overflow part

This part contains column values for the remaining non-key columns. This part is stored in the overflow storage area segment.

Secondary Indexes on Index-Organized Tables

A secondary index is an index on an index-organized table. In a sense, it is an index on an index. The secondary index is an independent schema object and is stored separately from the index-organized table.

As explained in "Rowid Data Types", Oracle Database uses row identifiers called logical rowids for index-organized tables. A logical rowid is a base64-encoded representation of the table primary key. The logical rowid length depends on the primary key length.

Rows in index leaf blocks can move within or between blocks because of insertions. Rows in index-organized tables do not migrate as heap-organized rows do (see "Chained and Migrated Rows"). Because rows in index-organized tables do not have permanent physical addresses, the database uses logical rowids based on primary key.

For example, assume that the departments table is index-organized. The location_id column stores the ID of each department. The table stores rows as follows, with the last value as the location ID:

10,Administration,200,1700

20,Marketing,201,1800

30,Purchasing,114,1700

40,Human Resources,203,2400

A secondary index on the location_id column might have index entries as follows, where the value following the comma is the logical rowid:

Secondary indexes provide fast and efficient access to index-organized tables using columns that are neither the primary key nor a prefix of the primary key. For example, a query of the names of departments whose ID is greater than 1700 could use the secondary index to speed data access.

Logical Rowids and Physical Guesses

Secondary indexes use the logical rowids to locate table rows. A logical rowid includes a physical guess, which is the physical rowid of the index entry when it was first made. Oracle Database can use physical guesses to probe directly into the leaf block of the index-organized table, bypassing the primary key search. When the physical location of a row changes, the logical rowid remains valid even if it contains a physical guess that is stale.

For a heap-organized table, access by a secondary index involves a scan of the secondary index and an additional I/O to fetch the data block containing the row. For index-organized tables, access by a secondary index varies, depending on the use and accuracy of physical guesses:

1. Without physical guesses, access involves two index scans: a scan of the secondary index followed by a scan of the primary key index.

2. With physical guesses, access depends on their accuracy:

（1）With accurate physical guesses, access involves a secondary index scan and an additional I/O to fetch the data block containing the row.

（2）With inaccurate physical guesses, access involves a secondary index scan and an I/O to fetch the wrong data block (as indicated by the guess), followed by an index unique scan of the index organized table by primary key value.

Bitmap Indexes on Index-Organized Tables

A secondary index on an index-organized table can be a bitmap index. As explained in "Bitmap Indexes", a bitmap index stores a bitmap for each index key.

When bitmap indexes exist on an index-organized table, all the bitmap indexes use a heap-organized mapping table. The mapping table stores the logical rowids of the index-organized table. Each mapping table row stores one logical rowid for the corresponding index-organized table row.

The database accesses a bitmap index using a search key. If the database finds the key, then the bitmap entry is converted to a physical rowid.

With heap-organized tables, the database uses the physical rowid to access the base table.

With index-organized tables, the database uses the physical rowid to access the mapping table, which in turn yields a logical rowid that the database uses to access the index-organized table. Figure 3-4 illustrates index access for a query of the departments_iot table.

Figure 3-4 Bitmap Index on Index-Organized Table

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