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Fundamentals of SQL - Basics with example - 19


LOCKS

Locks are the mechanisms used to prevent destructive interaction between users accessing same resource simultaneously. Locks provides high degree of data concurrency.

TYPES
1     Row level locks
2     Table level locks

ROW LEVEL LOCKS

In the row level lock a row is locked exclusively so that other cannot modify the row until the transaction holding the lock is committed or rolled back. This can be done by using select..for update clause.

Ex:
    SQL> select * from emp where sal > 3000 for update of comm.;

TABLE LEVEL LOCKS

A table level lock will protect table data thereby guaranteeing data integrity when data is being accessed concurrently by multiple users. A table lock can be held in several modes.

1     Share lock
2     Share update lock
3     Exclusive lock

SHARE LOCK

A share lock locks the table allowing other users to only query but not insert, update or delete rows in a table. Multiple users can place share locks on the same resource at the same time.

Ex:
     SQL> lock table emp in share mode;
SHARE UPDATE LOCK

It locks rows that are to be updated in a table. It permits other users to concurrently query, insert , update or even lock other rows in the same table. It prevents the other users from updating the row that has been locked.

Ex:
     SQL> lock table emp in share update mode;          

EXCLUSIVE LOCK

Exclusive lock is the most restrictive of tables locks. When issued by any user, it allows the other user to only query. It is similar to share lock but only one user can place exclusive lock on a table at a time.

Ex:
     SQL> lock table emp in share exclusive mode;

NOWAIT

If one user locked the table without nowait then another user trying to lock the same table then he has to wait until the user who has initially locked the table issues a commit or rollback statement. This delay could be avoided by appending a nowait clause in the lock table command.

Ex:
     SQL> lock table emp in exclusive mode nowait.

DEADLOCK

A deadlock occurs when tow users have a lock each on separate object, and they want to acquire a lock on the each other’s object. When this happens, the first user has to wait for the second user to release the lock, but the second user will not release it until the lock on the first user’s object is freed. In such a case, oracle detects the deadlock automatically and solves the problem by aborting one of the two transactions.

INDEXES


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

1     Unique index
2     Non-unique index
3     Btree index
4     Bitmap index
5     Composite index
6     Reverse key index
7     Function-based index
8     Descending index
9     Domain index
10  Object index
11  Cluster index
12  Text index
13  Index organized table
14  Partition index
v Local index
ü Local prefixed
ü Local non-prefixed
15                  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.

1      CONTEXT
2      CTXCAT
3      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;

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