1. Lecture 8 Index Organized Tables Clusters Index compression
Bitmap Indexes

2. Index Organized Tables
In Oracle Tables can be organized as:
HEAP (default, meaning unorganized)
INDEX (meaning Index Organized Table)
Index Organized Table:
In MsSQL called: CLUSTER INDEX, clusters in Oracle mean something else
Table data is stored together with primary key index

3. IOT tables - details Index Organized Table:
There is no separate table data storage, everything is stored in index data
Index structure is dynamic, physical location of the row can change → ROWIDs can change
Table access by primary key is very fast, faster than for HEAP organized tables

4. IOT tables - syntax
To create IOT table, add ORGANIZATION INDEX when creating a table
IOT table must have primary key
CREATE TABLE emp_iot (
id NUMBER PRIMARY KEY,
...
hire_date DATE
) ORGANIZATION INDEX;

5. IOT tables - overflow
Storing table data with index can improve performance – there is no separate data storage to look up
Storing data with index makes index larger – this degrades index performance
In some cases record data is large, it is not practical to store that in the PK index
IOT tables can have OVERFLOW area – if there is too much data it is stored in separate location

6. IOT overflow - syntax CREATE TABLE emp_iot ( id NUMBER PRIMARY KEY,
name VARCHAR2(100),
hire_date DATE,
description VARCHAR2(4000)
) ORGANIZATION INDEX
PCTTHRESHOLD 20
INCLUDING hire_date
OVERFLOW TABLESPACE users;

7. IOT tables – secondary indexes
For HEAP table, index contains ROWID
For IOT tables rows can be moved as index structure changes, ROWID cannot be fixed
IOT table always contains Primary Key index, other indexes are called Secondary Indexes
Secondary Index contains Logical ROWID
Logical ROWID contains:
Primary key of the row
ROWID guess – probable location of the row

8. IOT - secondary indexes, cont.
When using secondary index:
Database finds the Logical ROWID
It tries to locate the row by ROWID guess
If that fails, it searches for the row using primary key index
As a result, secondary indexes on IOT perform worse than indexes on HEAP organized tables

9. Clustered Tables In Oracle
Tables with common fields are stored together.
The common field is called a cluster key.
Records with the same cluster key are
stored together for faster access.
Oracle implements two types of clusters:
Index Clusters
Hash Clusters

10. Indexed Clusters Recommended for situations where:
Queries retrieve records over a range of values, for example
SELECT * FROM emp WHERE dept_id = 1
not just
SELECT * FROM emp WHERE id = 1
Tables do not have fixed size, they grow unpredictably

11. Indexed Clusters example
CREATE CLUSTER emp_phones_cluster (emp_id NUMBER) size 1024;
CREATE INDEX idx_emp_cluster ON CLUSTER emp_phones_cluster;

12. Indexed Clusters example, cont.
CREATE TABLE emp_clust (
id NUMBER PRIMARY KEY,
...
hire_date DATE
) CLUSTER emp_phones_cluster(id);
CREATE TABLE emp_phones_clust (
emp_id NUMBER REFERENCES emp_clust(id),
phone_number VARCHAR2(15),
) CLUSTER emp_phones_cluster(emp_id);

13. Using Indexed Clusters
Indexed clusters – advantages:
Rows stored together can be retrieved without additional join effort
Queries are faster when joining tables by cluster key
Disadvantages:
It can take longer when updating cluster key column in a table

14. Hash Clusters Hash Clusters:
Useful when queries retrieve records based on an equality condition on cluster key:
SELECT * FROM products WHERE id = 5;
Not useful for non-equality conditions:
SELECT * FROM products WHERE id < 5;
Useful when tables are static - they have fixed size. Maximum number of records and maximum space can be predicted.
Useful for dictionary tables, lookup tables etc.

15. Hash Clusters - example
CREATE CLUSTER products_cluster (
id number
) HASHKEYS 20;
CREATE TABLE products (
id number not null,
name varchar2(100),
...
) CLUSTER products_cluster(id);

16. Hash Clusters - details
Using Hash Clusters:
Do not create Cluster Index for hash cluster
Do not create index on cluster key for hash cluster
When using condition like:
SELECT * FROM zip_codes WHERE id = 5;
access is faster than index cluster or table with index.

17. Index Compression Oracle multi column indexes can be COMPRESSED
Uncompressed index stores values:
COL1, COL2, rowid
(123, 1, ROWID)
(123, 2, ROWID)
(123, 3, ROWID)
(200, 1, ROWID)
(200, 2, ROWID)
(200, 3, ROWID)

18. Index Compression, cont
Compressed index stores values:
COL1, COL2, rowid
Prefix: 123
(1, ROWID)
(2, ROWID)
(3, ROWID)
Prefix: 200

19. Using Index Compression
Index compression is useful:
For indexes with 2 or more columns. The first column must have many duplicated values.
Index organized tables can be compressed

20. Index Compression syntax
CREATE TABLE emp_phones_iot (
emp_id number not null,
phone_number varchar2(15),
PRIMARY KEY (emp_id, phone_number)
) ORGANIZATION INDEX COMPRESS 1;
CREATE INDEX emp_dept_idx ON
emp(dept_id, id) COMPRESS 1;

21. Bitmap Indexes Bitmap Indexes are intended for:
low cardinality columns (many duplicated values). This is the oposite of BTree indexes, which are best for unique or close to unique columns
tables not very frequently updated
Bitmap Indexes are only available in Oracle Enterprise Edition

22. Bitmap Indexes Characteristics
Must be non-unique
Include NULL values (BTree indexes do not)
Can be IOT secondary indexes
Cannot be compressed

23. Bitmap Indexes example
CREATE TABLE properties (
id NUMBER PRIMARY KEY,
bedrooms NUMBER,
bathrooms NUMBER,
garages NUMBER );
CREATE BITMAP INDEX idx_beds ON properties (bedrooms);
CREATE BITMAP INDEX idx_bths ON properties (bathrooms);
CREATE BITMAP INDEX idx_gar ON properties (garages);
SELECT id FROM properties
WHERE bedrooms = 3
AND bathrooms = 2
AND garages = 1;

24. Bitmap Indexes When creating bitmap index:
Oracle creates bitmap for each unique value in a column (plus NULL value)
Each bitmap has as many values as there are rows in the table

25. Bitmap Indexes example
Example table PROPERTIES
Bedroom index bitmap id
Bed
rooms
100 1
101 2
102 3
103
104
105
106
100
101
102
103
104
105
106 1 2 3

26. Bitmap Indexes example
Bedroom index bitmap
SELECT id FROM properties WHERE bedrooms=1
Get all 1-s from the first bitmap
SELECT id FROM properties
WHERE bedrooms = 1 OR bedrooms = 2
Combine bitmap 1 and 2, then get all 1-s
100
101
102
103
104
105
106 1 2 3

27. Bitmap Indexes Oracle supports many bitmap operations:
AND – AND operation between two bitmaps OR
NOT
MINUS (A MINUS B is A AND NOT B)
Bitmap range scans are supported (for example: WHERE bathroom <= 2)

28. Bitmap AND CREATE TABLE t1 (c1 NUMBER, c2 NUMBER);
CREATE BITMAP INDEX i1 ON t1 (c1);
CREATE BITMAP INDEX i2 ON t1 (c2);
SELECT c1,c2
FROM t1
WHERE c1 = 0 AND c2 = 0;
0 SELECT STATEMENT Optimizer=CHOOSE BITMAP CONVERSION (TO ROWIDS) BITMAP OR BITMAP INDEX (SINGLE VALUE) OF 'I1‘ BITMAP INDEX (SINGLE VALUE) OF 'I2‘

29. Bitmap OR CREATE TABLE t1 (c1 NUMBER, c2 NUMBER);
CREATE BITMAP INDEX i1 ON t1 (c1);
CREATE BITMAP INDEX i2 ON t1 (c2);
SELECT c1,c2
FROM t1
WHERE c1 = 0 OR c2 = 0;
0 SELECT STATEMENT Optimizer=CHOOSE TABLE ACCESS (BY INDEX ROWID) OF 'T1‘ BITMAP CONVERSION (TO ROWIDS) BITMAP OR BITMAP INDEX (SINGLE VALUE) OF 'I1‘ BITMAP INDEX (SINGLE VALUE) OF 'I2'

30. Bitmap MINUS CREATE TABLE t1 (c1 NUMBER, c2 NUMBER);
CREATE BITMAP INDEX i1 ON t1 (c1);
CREATE BITMAP INDEX i2 ON t1 (c2);
SELECT c1,c2
FROM t1
WHERE c1 = 0 AND c2 != 0;
0 SELECT STATEMENT Optimizer=CHOOSE TABLE ACCESS (BY INDEX ROWID) OF 'T1‘ BITMAP CONVERSION (TO ROWIDS) BITMAP MINUS BITMAP MINUS BITMAP INDEX (SINGLE VALUE) OF 'I1‘ BITMAP INDEX (SINGLE VALUE) OF 'I2‘ BITMAP INDEX (SINGLE VALUE) OF 'I2'

31. Bitmap MERGE CREATE TABLE t1 (c1 NUMBER, c2 NUMBER);
CREATE BITMAP INDEX i1 ON t1 (c1);
CREATE BITMAP INDEX i2 ON t1 (c2);
SELECT c1,c2
FROM t1
WHERE c1 > 0 AND c2 = 0;
0 SELECT STATEMENT Optimizer=CHOOSE TABLE ACCESS (BY INDEX ROWID) OF 'T1' BITMAP CONVERSION (TO ROWIDS) BITMAP AND BITMAP INDEX (SINGLE VALUE) OF 'I2‘ BITMAP MERGE BITMAP INDEX (RANGE SCAN) OF 'I1'

32. BTree bitmap execution plans
CREATE TABLE t2 (c1 NUMBER, c2 NUMBER);
CREATE INDEX it2 ON t2 (c1);
CREATE INDEX it3 ON t2 (c2);
SELECT c1,c2
FROM t2
WHERE c1 = 0 AND c2 = 0;
0 SELECT STATEMENT Optimizer=CHOOSE (Cost=3 Card=1 Bytes=5) BITMAP CONVERSION (TO ROWIDS) BITMAP AND BITMAP CONVERSION (FROM ROWIDS) INDEX (RANGE SCAN) OF 'IT3' (NON-UNIQUE) BITMAP CONVERSION (FROM ROWIDS) INDEX (RANGE SCAN) OF 'IT2' (NON- UNIQUE)