1. Advanced Topics: Indexes & Transactions
Instructor: Mohamed Eltabakh
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2. Indexes
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3. Why Indexes
With or without indexes, the query answer should be the same
Indexes are needed for efficiency and fast access of data
Without index, we check all 10,000 students
SELECT *
FROM Student
WHERE sNumber = ;
Assume we have 10,000 students
With index, we can reach that student directly
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4. Direct Access vs. Sequential Access
SELECT *
FROM Student
WHERE sNumber = ;
Without index, we check all 10,000 students
(sequential access)
With index, we can reach that student directly
(direct access)
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5. What is an Index Student
A index is an auxiliary file that makes it more efficient to search for a record in the data file
The index is usually specified on one field of the file
Although it could be specified on several fields
The index is stored separately from the base table
Each table may have multiple indexes
Student
Can create an index on sNumber
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg 3
Matt
Can create a second index on sName
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6. Example: Index on sNumber
Student
Index on sNumber
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3 1 2 3 4 10
100
Index file is always sorted
Index size is much smaller than the table size
Now any query (equality or range) on sNumber can be efficiently answered (Binary search on the index)

7. Example: Index on sName
Student
Index on sName
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3
Dave
Greg
John
Matt
Duplicates values have duplicate entries in the index
Now any query (equality or range) on sName can be efficiently answered (Binary search on the index)

8. Creating an Index Student
Create Index <name> On <tablename>(<colNames>);
Student
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3
DB System knows how to:
1- create the index
2- when and how to use it
Create Index sNumberIndex On Student(sNumber);
Create Index sNameIndex On Student(SName);

9. Multiple Predicates Student
1- The best the DBMS can do is using addressIndex  ‘320FL’
2- From those tuples, check sName = ‘Dave’
Student
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10
50WA … 4
John .. 3
200LA
SELECT *
FROM Student
WHERE address = ‘320FL’
AND sName = ‘Dave’;
Create Index addessIndex On Student(address);
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10. Multi-Column Indexes
Columns X, Y are frequently queried together (with AND)
Each column has many duplicates
Then, consider creating a multi-column index on X, Y
SELECT *
FROM Student
WHERE address = ‘320FL’
AND sName = ‘Dave’;
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10
50WA … 4
John .. 3
200LA
Directly returns this record only
Create Index nameAdd On Student(sName, address);

11. Using an Index
DBMS automatically figures out which index to use based on the query
SELECT *
FROM Student
WHERE sNumber = ;
Student
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3
Automatically uses SNumberIndex
Create Index sNumberIndex On Student(sNumber);
Create Index sNameIndex On Student(SName);
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12. How Do Indexes Work?
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13. Types of Indexes Primary vs. Secondary
Single-Level vs. Multi-Level (Tree Structure)
Clustered vs. Non-Clustered
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14. Primary vs. Secondary Indexes
Index on the primary key of a relation is called primary index (only one)
Index on any other column is called secondary index (can be many)
In primary index, all values are unique
In secondary indexes, values may have duplicates
Student
Index on SSN is a Primary Index
SSN
sNumber
sName
address
pNum
11111 1
Dave
320FL
22222 2
Greg
33333
100
Matt
44444 10 …
55555 4
John ..
66666 3
Index on sNumber is a Secondary Index
Index on sName is a Secondary Index

15. Single-Level Indexes Student Index is one-level sorted list
Given a value v to query
Perform a binary search in the index to find it (Fast)
Follow the link to reach the actual record
Student
Index on sNumber
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3 1 2 3 4 10
100

16. Multi-Level Index Student
Build index on top of the index (can go multiple levels)
When searching for value v:
Find the largest entry ≤ v, and follow its pointer
Student
2nd level
sNumber
sName
address
pNum 1
Dave
320FL 2
Greg
100
Matt 10 … 4
John .. 3 1 2 3 4 10
100
1st level 1 4
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Index on sNumber

17. Clustered vs. Non-Clustered
Assume there is index X on column C
If the records in the table are stored sorted based on C
X  Clustered index
Otherwise, X  Non-Clustered index
Primary index is a clustered index
Student
SSN
sNumber
sName
address
11111 1
Dave
320FL
22222 2
Greg
33333
100
Matt
44444 10 …
55555 4
John
66666 3
11111
22222
33333
44444
55555
66666 1 2 3 4 10
100
Non-Clustered
index
Clustered index

18. Index Maintenance
Indexes are used in queries
But, need to be maintained when data change
Insert, update, delete
DBMS automatically handles the index maintenance
When insert new records  the indexed field is added to the index
When delete records  their values are deleted from the index
When update an indexed value  delete the old value from index & insert the new value
There is a cost for maintaining an index, however its benefit is usually more (if used a lot)
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19. Summary of Indexes
Indexes are auxiliary structures for efficient searching and querying
Query answer is the same with or without index
What to index depends on which columns are frequently queried (in Where clause)
Main operations
Create Index <name> On <tablename>(<colNames>);
Drop Index <name>;
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20. Transactions
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21. Transactions solve these problems
What is a Transaction
A set of operations on a database that are treated as one unit
Execute All or None
Transactions have semantics at the application level
Want to reserve two seats in a flight
Transfer money from account A to account B …
What if two users are reserving the same flight seat at the same time???
Transactions solve these problems

22. Transactions By default, each SQL statement is a transaction
Can change the default behavior
SQL > Start transaction;
SQL > Insert ….
SQL > Update …
SQL > Delete ..
SQL > Select …
SQL> Commit | Rollback;
All of these statements are now one unit
(either all succeed all fail)
End transaction
successfully
Cancel the transaction

23. Transaction Properties
Four main properties
Atomicity – A transaction if one atomic unit
Consistency – A transaction ensures DB is consistent
Isolation – A transaction is considered as if no other transaction
was executing simultaneously
Durability – Changes made by a transaction must persist
ACID: Atomicity, Consistency, Isolation, Durability
ACID properties are enforced by the DBMS
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24. What is the right answer??? Wrong, Inconsistent data
Consistency Issue
Many users may update the data at the same time
How to ensure the result is consistent x 2 3 4 10
100 2 1
Update T
Set x = x * 3;
Update T
Set x = x + 2; 3
What is the right answer??? x 12 15 14 32
302
Wrong, Inconsistent data

25. Serial Order of Transactions
Given N concurrent transactions T1, T2, …TN
Serial order is any permutation of these transactions (N!)
T1, T2, T3, …TN
T2, T3, T1, …, TN …
DBMS will ensure that the end-result from executing the N transactions (concurrently) matches one of the serial order execution
That is called Serializability
As if transactions are executed in serial order
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26. Serializable Execution
Given N concurrent transactions T1, T2, …TN
DBMS will execute them concurrently (at the same time)
But, the final effect matches one of the serial order executions x 2 3 4 10
100
Update T
Set x = x * 3;
Update T
Set x = x + 2; x 12 15 18 36
306 x 8 11 14 32
302

27. That is the default in DBMS
Isolation Levels
Read Uncommitted
Read Committed
Repeatable Read
Serializable
Gets stronger & avoids problems
That is the default in DBMS
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28. 1- READ UNCOMMITTED NonRepeatable read (bad) Dirty read (bad)
Session 2
BEGIN TRANSACTION----- select color from cust
where id=500;
color
------
red
select color from cust
-----
blue
COMMIT
Session 1
BEGIN TRANSACTION-----
update cust set color='blue'
where id=500;
COMMIT | V
Time
NonRepeatable read (bad)
Dirty read
(bad)

29. 2- READ COMMITTED Dirty Read  Solved NonRepeatable read (bad)
Session 2
BEGIN TRANSACTION----- select color from cust
where id=500;
color
------
red
select color from cust
-----
blue
COMMIT
Session 1
BEGIN TRANSACTION-----
update cust set color='blue'
where id=500;
COMMIT | V
Time
NonRepeatable read (bad)

30. 2- READ COMMITTED Phantom (bad) Session 2
BEGIN TRANSACTION----- select color from cust
where id=500;
color
------
red
select color from cust
-----
COMMIT
Session 1
BEGIN TRANSACTION-----
delete cust where id=500;
COMMIT | V
Time
Phantom (bad)

31. NonRepeatable Read Solved
Session 2
BEGIN TRANSACTION----- select color from cust
where id=500;
color
------
red
select color from cust
-----
COMMIT
Session 1
BEGIN TRANSACTION-----
update cust set color='blue'
where id=500;
COMMIT | V
Time

32. Phantom (For Delete)  Solved
3- REPEATABLE READ
Phantom (For Delete)  Solved
Session 2
BEGIN TRANSACTION----- select color from cust
where id=500;
color
------
red
select color from cust
-----
COMMIT
Session 1
BEGIN TRANSACTION-----
delete cust where id=500;
COMMIT | V
Time

33. 3- REPEATABLE READ Phantom Insert (bad) Session 2
BEGIN TRANSACTION----- select id from cust
where color=‘blue’; id --
select id from cust
500
COMMIT
Session 1
BEGIN TRANSACTION-----
Insert into cust(id, color) values (500, ‘blue’);
COMMIT | V
Time
Phantom Insert (bad)

34. 4- SERIALIZABLE Phantom  Solved Session 2
BEGIN TRANSACTION----- select id from cust
where color=‘blue’; id --
select id from cust
COMMIT
Session 1
BEGIN TRANSACTION-----
Insert into cust(id, color) values (500, ‘blue’);
COMMIT | V
Time

35. Summary of Transactions
Unit of work in DBMS
Either executed All or None
Ensures consistency among many concurrent transactions
Ensures persistent data once committed (using recovery techniques)
Main ACID properties
Atomicity, Consistency, Isolation, Durability
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36. END !!!
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37. Friday’s Lecture (Revision + short Quiz)
Final Exam
Dec. 13, at 8:15am – 9:30am (75 mins)
Closed book, open sheet
Answer in the same exam sheet
Material Included
ERD
SQL (Select, Insert, Update, Delete)
Views, Triggers, Assertions
Cursors, Stored Procedures/Functions
Material Excluded
Relational Model & Algebra
Normalization Theory
ODBC/JDBC
Indexes and Transactions
Friday’s Lecture (Revision + short Quiz)