1. Database Management System
Lecture - 45
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Locking Idea
Before performing an operation a transaction applies for a S/E lock on an object
If object free or lock compatible then lock granted otherwise transaction will wait
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Deadlock
Deadlock is a situation when two transactions are waiting for each other to release a lock
The transaction involved in deadlock keep on waiting unless deadlock is over
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Deadlock
TIME TA TB t1
XLock (X)
……… t2
…….
XLock (Y) t3
Request Y
…….. t4
Wait
Request X t5 t6
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Deadlock Handling
Deadlock prevention
Deadlock detection and resolution
Prevention is not always possible
Deadlock is detected by wait-for graph
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Wait-for Graph TA TB TN TA TB TC TA TD
Victim Transaction
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Two-Phase Locking
2PL ensures serializability but generates deadlock
The locks are granted and released in two phases, the growing and shrinking phase
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Two-Phase Locking
A transaction must acquire a lock before doing any operation
Locks are only granted in growing phase, once a transaction enters in shrinking phase no locks can acquire
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Levels of Locking
Lock can be applied on attribute, record, file, group of files or even entire database
Granularity of locks
Finer the granularity more concurrency but more overhead
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Granularity
of Locks
Database
Area A
Area B
Area C
File A1
File A2
File A3
Rec A11
Rec A12
Rec A13
At A111
At A112
At A113
…….
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Granularity of Locks
When a lock at lower level is applied, compatibility is checked upward
How will a lock at higher level know about a lock at lower level
Individual checking is not feasible
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Intension Locks
When a lock is applied on a node, an intension shared (IS) or intension exclusive (IE) lock is applied on all nodes till the root
An intension lock at a node indicates a lock at the lower level
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Intension Locks
While applying for a lock on a node, compatibility with the intension lock is also checked
Share intension lock (SIX)
Conflicts with locks conflicting with S or IX; only one SIX
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Extended Comp Matrix
S IS X IX SIX N Y IS S IX X
SIX Y N
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Locking Summary
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Timestamping
No locks are used
Guarantees consistency and no deadlocks, however, certain transactions are cancelled
Based on the concept of timestamp
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Timestamp
An identifier that determines the relative order of the transactions
Greater timestamp younger the transaction
The transactions’ operations are allowed in the timestamp order
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Timestamp
Timestamps are also allocated to data items as well
A read timestamp and a write timestamp to determine the last transaction that read or wrote
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Two Problems
When a transaction wants to read an item that has been updated by a younger transaction
A transaction wants to write an item that has been read or written by a younger transaction
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Versions of Data Items
First problem is met by maintaining multiple versions of data items
Value read-timestamp write-timestamp
742 6 8
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Versions of Data Items
Value read-timestamp write-timestamp
742 6
1096 9 V1 V2
Transaction 8 wants to read the data item
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Versions of Data Items
Value read-timestamp write-timestamp V1
742 6 8 6 V2
1096 9 9
Transaction 8 gets the smaller nearest value
Read timestamp is changed
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Problem 2
Write request when an item read or written by smaller transaction
Value read-timestamp write-timestamp
742 8 6
1096 9 V1 V2
Transaction 7 wants to write the item
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The End
Thanks all
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Timestamp Algorithm
On read request
Check the read TS of latest version
If latest write TS < requested TS
Give the value of latest
otherwise find the largest smaller write TS and return that value
Update the read TS of data item
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Timestamp Algorithm
On write request
Check the read ant write TS of latest version
If either one is greater than the requested TS, cancel the transaction and restart
If none of latest is greater
Create a new version, place new value and current TS in write TS of data item
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27. Database Management System
Lecture - 45
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