Index is typically a listing of keywords accompanied by the
location of information on a subject. We can create indexes explicitly to speed
up SQL statement execution on a table. The index points directly to the
location of the rows containing the value.
WHY INDEXES?
Indexes are most useful on larger tables, on columns that are
likely to appear in where clauses as simple equality.
TYPES
Ø Unique index
Ø Non-unique index
Ø Btree index
Ø Bitmap index
Ø Composite index
Ø Reverse key index
Ø Function-based index
Ø Descending index
Ø Domain index
Ø Object index
Ø Cluster index
Ø Text index
Ø Index organized table
Ø Partition index
v Local index
ü Local prefixed
ü Local non-prefixed
v Global index
ü Global prefixed
ü Global non-prefixed
UNIQUE INDEX
Unique indexes guarantee that no two rows of a table have
duplicate values in the columns that define the index. Unique index is
automatically created when primary key or unique constraint is created.
Ex:
SQL> create unique index stud_ind on student(sno);
NON-UNIQUE INDEX
Non-Unique indexes do not impose the above restriction on the
column values.
Ex:
SQL> create index stud_ind on student(sno);
BTREE INDEX or ASCENDING INDEX
The default type of index used in an oracle database is the btree
index. A btree index is designed to provide both rapid access to individual
rows and quick access to groups of rows within a range. The btree index does
this by performing a succession of value comparisons. Each comparison
eliminates many of the rows.
Ex:
SQL> create index stud_ind on student(sno);
BITMAP INDEX
This can be used for low cardinality columns: that is columns in
which the number of distinct values is snall when compared to the number of the
rows in the table.
Ex:
SQL> create bitmap index stud_ind on student(sex);
COMPOSITE INDEX
A composite index also called a concatenated index is an index
created on multiple columns of a table. Columns in a composite index can appear
in any order and need not be adjacent columns of the table.
Ex:
SQL> create bitmap index stud_ind on student(sno, sname);
REVERSE KEY INDEX
A reverse key index when compared to standard index, reverses each
byte of the column being indexed while keeping the column order. When the
column is indexed in reverse mode then the column values will be stored in an index
in different blocks as the starting value differs. Such an arrangement can help
avoid performance degradations in indexes where modifications to the index are
concentrated on a small set of blocks.
Ex:
SQL> create index stud_ind on student(sno, reverse);
We can rebuild a reverse key index into normal index using the
noreverse keyword.
Ex:
SQL> alter index stud_ind rebuild noreverse;
FUNCTION BASED INDEX
This will use result of the function as key instead of using
column as the value for the key.
Ex:
SQL> create index stud_ind on student(upper(sname));
DESCENDING INDEX
The order used by B-tree indexes has been ascending order. You can
categorize data in B-tree index in descending order as well. This feature can
be useful in applications where sorting operations are required.
Ex:
SQL> create index stud_ind on student(sno desc);
TEXT INDEX
Querying text is different from querying data because words have
shades of meaning, relationships to other words, and opposites. You may want to
search for words that are near each other, or words that are related to thers.
These queries would be extremely difficult if all you had available was the
standard relational operators. By extending SQL to
include text indexes, oracle text permits you to ask very complex questions
about the text.
To use oracle text, you need to create a text index on the column in which the text is stored. Text index is
a collection of tables and indexes that store information about the text stored
in the column.
TYPES
There are several different types of indexes available in oracle
9i. The first, CONTEXT is supported in oracle 8i as well as
oracle 9i. As of oracle 9i, you can use the CTXCAT text
index fo further enhance your text index management and query capabilities.
Ø CONTEXT
Ø CTXCAT
Ø CTXRULE
The CTXCAT index type supports the transactional
synchronization of data between the base table and its text index. With CONTEXT indexes, you need to manually tell oracle to update the values in
the text index after data changes in base table. CTXCAT index types do not generate score values during the text queries.
HOW TO CREATE TEXT INDEX?
You can create a text index via a special version of the create
index comman. For context index, specify the ctxsys.context index type and for
ctxcat index, specify the ctxsys.ctxcat index type.
Ex:
Suppose you have a table called BOOKS with the following columns
Title, Author, Info.
SQL> create
index book_index on books(info) indextype is ctxsys.context;
SQL> create
index book_index on books(info) indextype is ctxsys.ctxcat;
TEXT QUERIES
Once a text index is created on the info column of BOOKS table, text-searching capabilities increase dynamically.
CONTAINS & CATSEARCH
CONTAINS
function takes two parameters – the column name and the search string.
Syntax:
Contains(indexed_column, search_str);
If you create a CTXCAT index, use the CATSEARCH function in place of CONTAINS. CATSEARCH takes three parameters – the column name, the search string and
the index set.
Syntax:
Contains(indexed_column, search_str, index_set);
HOW A TEXT QEURY WORKS?
When a function such as CONTAINS or CATSEARCH is used in query, the text portion of the query is processed by
oracle text. The remainder of the query is processed just like a regular query
within the database. The result of the text query processing and the regular
query processing are merged to return a single set of records to the user.
SEARCHING FOR AN EXACT MATCH OF A WORD
The following queries will search for a word called ‘prperty’
whose score is greater than zero.
SQL> select
* from books where contains(info, ‘property’) > 0;
SQL> select
* from books where catsearch(info, ‘property’, null) > 0;
Suppose if you want to know the score of the ‘property’ in each
book, if score values for individual searches range from 0 to 10 for each
occurrence of the string within the text then use the score function.
SQL> select
title, score(10) from books where contains(info, ‘property’, 10) > 0;
SEARCHING FOR AN EXACT MATCH OF MULTIPLE WORDS
The following queries will search for two words.
SQL> select
* from books where contains(info, ‘property AND
harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property AND
harvests’, null) > 0;
Instead of using AND you could hae used an ampersand(&).
Before using this method, set define off so the & character will not be
seen as part of a variable name.
SQL> set
define off
SQL> select
* from books where contains(info, ‘property & harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property
harvests’, null) > 0;
The following queries will search for more than two words.
SQL> select
* from books where contains(info, ‘property AND
harvests AND workers’) > 0;
SQL> select
* from books where catsearch(info, ‘property harvests workers’, null) > 0;
The following queries will search for either of the two words.
SQL> select
* from books where contains(info, ‘property OR
harvests’) > 0;
Instead of OR you can use a vertical line (|).
SQL> select
* from books where contains(info, ‘property | harvests’)
> 0;
SQL> select
* from books where catsearch(info, ‘property |
harvests’, null) > 0;
In the following queries the ACCUM(accumulate)
operator adds together the scores of the individual searches and compares the
accumulated score to the threshold value.
SQL> select
* from books where contains(info, ‘property ACCUM
harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property ACCUM harvests’,
null) > 0;
Instead of OR you can use a comma(,).
SQL> select
* from books where contains(info, ‘property , harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property , harvests’, null) > 0;
In the following queries the MINUS
operator subtracts the score of the second term’s search from the score of the
first term’s search.
SQL> select
* from books where contains(info, ‘property MINUS
harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property NOT harvests’,
null) > 0;
Instead of MINUS you can use – and instead of NOT you can use ~.
SQL> select
* from books where contains(info, ‘property -
harvests’) > 0;
SQL> select
* from books where catsearch(info, ‘property ~ harvests’,
null) > 0;
SEARCHING FOR AN EXACT MATCH OF A PHRASE
The following queries will search for the phrase. If the search
phrase includes a reserved word within oracle text, the you must use curly
braces ({}) to enclose text.
SQL> select
* from books where contains(info, ‘transactions {and} finances’) > 0;
SQL> select
* from books where catsearch(info, ‘transactions {and} finances’, null) > 0;
You can enclose the entire phrase within curly braces, in which
case any reserved words within the phrase will be treated as part of the search
criteria.
SQL> select
* from books where contains(info, ‘{transactions and finances}’) > 0;
SQL> select
* from books where catsearch(info, ‘{transactions and finances}’, null) > 0;
SEARCHING FOR WORDS THAT ARE NEAR EACH OTHER
The following queries will search for the words that are in
between the search terms.
SQL> select
* from books where contains(info, ‘workers NEAR harvests’)
> 0;
Instead of NEAR you can use ;.
SQL> select
* from books where contains(info, ‘workers ; harvests’) > 0;
In CONTEXT index queries, you can specify the maximum
number of words between the search terms.
SQL> select
* from books where contains(info, ‘NEAR((workers,
harvests),10)’ > 0;
USING WILDCARDS DURING SEARCHES
You can use wildcards to expand the list of valid search terms
used during your query. Just as in regular text-string wildcard processing, two
wildcards are available.
% - percent sign; multiple-character
wildcard
_ - underscore; single-character wildcard
SQL> select
* from books where contains(info, ‘worker%’) > 0;
SQL> select
* from books where contains(info, ‘work___’) > 0;
SEARCHING FOR WORDS THAT SHARE THE SAME STEM
Rather than using wildcards, you can use stem-expansion
capabilities to expand the list of text strings. Given the ‘stem’ of a word,
oracle will expand the list of words to search for to include all words having
the same stem. Sample expansions are show here.
Play - plays playing played playful
SQL> select
* from books where contains(info, ‘$manage’) > 0;
SEARCHING FOR FUZZY MATCHES
A fuzzy match expands the specified search term to include words
that are spelled similarly but that do not necessarily have the same word stem.
Fuzzy matches are most helpful when the text contains misspellings. The
misspellings can be either in the searched text or in the search string
specified by the user during the query.
The following queries will not return anything because its search
does not contain the word ‘hardest’.
SQL> select
* from books where contains(info, ‘hardest’) > 0;
It does, however, contains the word ‘harvest’. A fuzzy match will
return the books containing the word ‘harvest’ even though ‘harvest’ has a different
word stem thant the word used as the search term.
To use a fuzzy match, precede the search term with a question
mark, with no space between the question mark and the beginning of the search
term.
SQL> select
* from books where contains(info, ‘?hardest’) > 0;
SEARCHING FOR WORDS THAT SOUND LIKE OTHER WORDS
SOUNDEX, expands search terms based on how the word sounds. The
SOUNDEX expansion method uses the same text-matching logic available via the
SOUNDEX function in SQL.
To use the SOUNDEX option, you must precede the search term with
an exclamation mark(!).
SQL> select
* from books where contains(info, ‘!grate’) > 0;
INDEX SYNCHRONIZATION
When using CONTEXT indexes, you need to manage the text index
contents; the text indexes are not updated when the base table is updated. When
the table was updated, its text index is out of sync with the base table. To
sync of the index, execute the SYNC_INDEX procedure of the CTX_DDL package.
SQL> exec CTX_DDL.SYNC_INDEX(‘book_index’);
INDEX SETS
Historically, problems with queries of text indexes have occurred
when other criteria are used alongside text searches as part of the where
clause. To improve the mixed query capability, oracle features index sets. The
indexes within the index set may be structured relational columns or on text
columns.
To create an index set, use the CTX_DDL
package to create the index set and add indexes to it. When you create a text
index, you can then specify the index set it belongs to.
SQL> exec CTX_DDL.CREATE_INDEX_SET(‘books_index_set’);
The add non-text indexes.
SQL> exec CTX_DDL.ADD_INDEX(‘books_index_set’, ‘title_index’);
Now create a CTXCAT text index. Specify ctxsys.ctxcat as the
index type, and list the index set in the parameters clause.
SQL> create
index book_index on books(info) indextype is ctxsys.ctxcat
parameters(‘index
set books_index_set’);
INDEX-ORGANIZED TABLE
An index-organized table keeps its data sorted according to the
primary key column values for the table. Index-organized tables store their data
as if the entire table was stored in an index.
An index-organized table allows you to store the entire table’s
data in an index.
Ex:
SQL> create table student (sno number(2),sname varchar(10),smarks
number(3)
constraint pk
primary key(sno) organization index;
PARTITION INDEX
Similar to partitioning tables, oracle allows you to partition
indexes too. Like table partitions,
index partitions could be in different tablespaces.
LOCAL INDEXES
Ø Local keyword tells oracle to create a separte
index for each partition.
Ø In the local prefixed index the partition
key is specified on the left prefix. When the underlying table is partitioned
baes on, say two columns then the index can be prefixed on the first column
specified.
Ø Local prefixed indexes can be unique or non
unique.
Ø Local indexes may be easier to manage than
global indexes.
Ex: SQL> create index stud_index on student(sno) local;
GLOBAL INDEXES
Ø A global index may contain values from
multiple partitions.
Ø An index is global prefixed if it is
partitioned on the left prefix of the index columns.
Ø The global clause allows you to create a
non-partitioned index.
Ø Global indexes may perform uniqueness
checks faster than local (partitioned) indexes.
Ø You cannot create global indexes for hash
partitions or subpartitions.
Ex: SQL> create index stud_index on student(sno) global;
Similar to table partitions, it is possible to move them from one
device to another. But unlike table partitions, movement of index partitions
requires individual reconstruction of the index or each partition (only in the
case of global index).
Ex: SQL> alter index stud_ind rebuild partition p2
Ø Index partitions cannot be dropped
manually.
Ø They are dropped implicitly when the data
they refer to is dropped from the partitioned table.
MONITORING USE OF INDEXES
Once you turned on the monitoring the use of indexes, then we can
check whether the table is hitting the index or not.
To monitor the use of index use the follwing syntax.
Syntax:
alter index index_name monitoring usage;
then check for the details in V$OBJECT_USAGE view.
If you want to stop monitoring use the following.
Syntax:
alter index index_name nomonitoring usage;
DATA MODEL
Ø ALL_INDEXES
Ø DBA_INDEXES
Ø USER_INDEXES
Ø ALL_IND-COLUMNS
Ø DBA-IND_COLUMNS
Ø USER_IND_COLUMNS
Ø ALL_PART_INDEXES
Ø DBA_PART_INDEXES
Ø USER_PART_INDEXES
Ø V$OBJECT_USAGE
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