• Rewrite SQL (Leccotech)
• Create Index
• Redefine Main memory structures (SGA in Oracle)
• Change the Block Size
• Materialized Views, Denormalization
• Export/Import (drop indexes): defragment
• Check Locks
• Separate data by category in proper tablespaces
• Partition Database
• Redundant Arrays of Inexpensive Disks (RAID)
• Redefining Client-Server Architecture
• Buy Hardware
When to Index
• Large tables A field that you query by
• Field with high cardinality (not sex where
card. Is only 2)
• Smaller Fields and Fixed length are
(Obs:Most DBMSs automatically index PK)
Different Type of Indexes
• B-Trees (traditional) indexes
• Bitmap indexes
• Index-Organized Tables
• Reverse-Key Indexes
Create Index command
• Create index <iName> on
• Create index cidx on orders (cid);
Why do we create an index ?
(OLTP x Data Warehouse)
• A) To speed up query (SELECT) ?
• B) To speed up data entry (insert/update/delete) ?
• C) All of the above ?
• Anytime a PK is created, an index is
• Anytime when the type of index is not
specificied, the type of index created is
B-Tree (Balanced Tree)
• Most popular type of index structure for any
programming language or database.
• When you don‟t know what to do, the best
option is usually a B-Tree. They are flexible
and perform well (not very well) in several
• It is really the B+ tree or B* tree
• One node corresponds to one block/page
(minimum disk I-O).
• Non-Leaf nodes(n keys, n+1 pointers)
• Leaf-Nodes (contain n entries, where each
entry has an index and a pointer to a data
block). Also, each node has a pointer to
• All leaves are at the same height.
Good Indexing (B-Tree)
• Table must be reasonably large
• Field is queried by frequently
• Field has a high cardinality (don‟t index by
sex, where the cardinality is 2!!).
• Badly balanced trees may inhibit
performance. Destroying and re-creating
index may improve performance.
• Bitmap indexes contain the key value and a
bitmap listing the value of 0 or 1 (yes/no)
for each row indicating whether the row
contains that value or not.
• May be a good option for indexing fields
that have low cardinality (opposite of B-
Bitmap Index (cont.)
• Syntax: Create Bitmap index ….
• Bitmap index works better with equality tests = or
in (not with < or > )
• Bitmap index maintenance can be expensive; an
individual bit may not be locked; a single update
locks a large portion of index.
• Bitmap indexes are best in read-only
• B-trees and Bitmap index keys are used to
find rows requiring I/O to process index
• Hash gets rows with a key based algorithm
• Rows are stored based on a hashed value
• Index size should be known at index
– create index cidx on orders (cid) hashed;
Hash Index work best with
• Very-high cardinality columns
• Only equal (=) tests are used
• Index values do not change
• Number of rows are known ahead of time
• Table data is incorporated into the B-Tree
using the PK as the index.
• Table data is always in order of PK. Many
sorts can be avoided.
• Especially useful for “lookup” type tables
• Index works best when there are few (and
small) columns in your table other than the
Reverse Key Indexes
• Key „1234‟ becomes „4321‟, etc.
• Only efficient for few scenarios envolving
parallel processing and a hughe amount of
• By reversing key values, index blocks might
be more evenly distributed reducing the
likelihood of densely or sparsely populated
Conclusions on Indexes
• For high-cardinality key values, B-Tree
indexes are usually best.
• B-Trees work with all types of comparisons
and gracefully shrink and grow as table
• For low cardinality read-only environments,
Bitmaps may be a good option.
• A query optimizer parsers your SQL/Query
into a sequence of relational algebra
operations, determining an execution plan.
• The query optimizer figures out the best
execution plan based on rules of thumb and
information provided in the Data Dictionary
Oracle Query Optimizer
• Up to version 6, Oracle Used a Rule Based
Optimizer. After version 6, Oracle offered
the Cost Based and the Rule Based
Optimizer. The default is now the Cost
• To view how the query plan you must use
either set autotrace on or explain plan. Set
autotrace on is much simpler. Explain plan
is a little bit more efficient, but more
Typical SQL operations
(results of autotrace)
• TABLE ACCESS FULL
• TABLE ACCESS BY ROWID
• INDEX RANGE SCAN
• INDEX UNIQUE SCAN
• NESTED LOOPS
• TABLE ACCESS FULL (full table scan):
Oracle will look at every row in the table to
find the requested information. This is
usually the slowest way to access a table.
TABLE ACCESS BY ROWID
Oracle will use the ROWID method
to find a row in the table.
ROWID is a special column detailing
an exact Oracle block where
the row can be found. This is the
fastest way to access a table (faster
than any index. Less flexible than any
INDEX RANGE SCAN
Oracle will search an index for a
range of values. Usually, this even
occurs when a range or between
operation is specified by the query or
when only the leading columns in a
composite index are specified by the
where clause. Can perform well or
poorly, based on the size of the range
and the fragmentation of the index.).
INDEX UNIQUE SCAN
Oracle will perform this operation
when the table‟s primary key or
a unique key is part of the where
clause. This is the most efficient
way to search an index.
Indicates that a join operation is occurring.
Can perform well or poorly, depending on
performance on the index and table
operations of the individual tables being
Tuning SQL and PL/SQL
Sometimes, Same Query written more than
Generating more than 100 execution plans.
Some firms have products that re-write
correctly written SQL queries
• SELECT ROWID, …
INTO :EMP_ROWID, …
WHERE EMP.EMP_NO = 56722
UPDATE EMP SET EMP.NAME = …
WHERE ROWID = :EMP_ROWID;
• Less Flexible
• Are very useful for removing duplicates of
• Not exists in place of NOT IN
• Joins in place of Exists
• Avoid sub-selects
• Exists in place of distinct
• UNION in place of OR on an index column
• WHERE instead of ORDER BY