Concurrency Control and Recovery

• In real life:• users access the database concurrently, and• systems crash.

• Concurrent access to the database also improves performance, yields better utilization of resources.

• BUT: if not careful, concurrent access can lead to incorrect database states. Crashes can also leave the database in incoherent states.

• Basic concurrency/recovery concept: transaction • executed atomically. All or nothing.

• We cover:• transactions in SQL• implementation of transactions and recovery.

Flight Reservation get values for :flight, :date, :seat

EXEC SQL SELECT occupied INTO :occ FROM Flight WHERE fltNum = :flight AND fltdt= :date AND fltSeat=:seat if (!occ) { EXEC SQL UPDATE Flights SET occupied = ‘true’ WHERE fltNum= :flight AND fltdt= :date AND fltSeat=:seat /* more code missing */ } else /* notify customer that seat is not available */

Problem #1

Customer 1 - finds a seat empty

Customer 2 - finds the same seat empty

Customer 1 - reserves the seat.

Customer 2 - reserves the seat.

Customer 1 will not be happy.

serializability

Bank TransfersTransfer :amount from :account1 to :account2

EXEC SQL SELECT balance INTO :balance1 FROM Accounts WHERE accNo = :account1

if (balance1 >= amount) EXEC SQL UPDATE Accounts SET balance = balance + :amount WHERE acctNo = :account2; EXEC SQL UPDATE Accounts SET balance = balance - :amount WHERE acctNo = :account1;

Crash...

TransactionsThe user/programmer can group a sequence of commands so that they are executed atomically and in a serializable fashion:

• Transaction commit: all the operations should be done and recorded.

• Transaction abort: none of the operations should be done.

In SQL:

• EXEC SQL COMMIT;

• EXEC SQL ROLLBACK;

Easier said than done...

ACIDACID PropertiesAAtomicity: all actions of a transaction happen, or none happen.

CConsistency: if a transaction is consistent, and the database starts from a consistent state, then it will end in a consistent state.

IIsolation: the execution of one transaction is isolated from other transactions.

DDurability: if a transaction commits, its effects persist in the database.

How Do We Assure ACID?Concurrency control:

Guarantees consistency and isolation, given atomicity.

Logging and Recovery:

Guarantees atomicity and durability.

If you are going to be in the logging business, one of the thingsthat you’ll have to do is learn about heavy equipment. -- Robert VanNatta Logging History of Columbia County

More on SQL and TransactionsRead only transactions:

• if the transaction is only reading, we can allow more operations in parallel.

EXEC SQL SET TRANSACTION READ ONLY;

The default is:

SET TRANSACTION READ WRITE;

Dirty Data

Data that has been written by a transaction that has not committedyet is called dirty data.

Do we allow our transaction to read dirty data? It may go away…

In SQL:

SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED

Note: default for READ UNCOMMITTED transactions is that they are READ ONLY.

Problems with Dirty DataTransfer program: 1. Add $N to account 2. 2. If account 1 has enough for the transfer, then: subtract $N from account 1, and commit else: Subtract $N from account 2, and commitBad scenario: A1: $100, A2: $200, A3: $300 T1: transfer $150 from A1 to A2 T2: transfer $250 from A2 to A3.Events:• T2 does step 1, -> A3 has $550• T1 does step 1, -> A2 has $350• T2 does step 2 (then), all is ok (A2 now has $100)• T1 does step 2 and finds that A1 doesn’t have enough funds so A2 ends up with -$50.

Concurrency Control Methods

• Schedules• Serial schedules• Serializable schedules

• Locking• Lock manager• 2 Phase Locking• Deadlocks:

• Prevention• Detection

Schedules•A schedule is an interleaving of a set of actionsof different transactions, such that the actions of any single transaction are in order.

• A schedule represents some actual sequence of database actions.

• In a complete schedule, every transaction either commits or aborts.

• Initial state + Schedule -> Final state.

Acceptable SchedulesSerial schedules:

• The transactions run one at a time from beginning to completion.

• Note: there are many possible serial schedules. Each one is OK. The DBMS does not provide any guarantee in which order concurrently submitted transactions are executed.

Serializable schedules:

• Final state is what some serial schedule would have produced.

Aborted Transactions

Slight modification to the definition:

A schedule is serializable if it is equivalent to a serial scheduleof committed transactions.

• As if the aborted transactions never happened.

Two issues to consider w.r.t. aborted transactions:

• how does one undo the effect of a transaction?

• What if another transaction sees the effects of an aborted one?

LocksConcurrency control is usually done via locking.

The lock manager maintains a list of entries:• object identifier (can be page, record, etc.)• number of objects holding lock on the object• nature of the lock (shared or exclusive)• pointer to a list of lock requests.

Lock compatibility table:

If a transaction cannot get a lock, it is suspended on a wait queue.

-- S X

--

S

X

Handling Lock Requests

Lock Request (OID, Mode)

Currently Locked?

Grant Lock

Empty Wait Queue?

Mode==X Mode==S

No

YesNo

Yes

Put on Queue

Yes

No

Exclusive lock on OID?

Two-Phase Locking (2PL)

• 2 phase locking:• if T wants to read an object, it first obtains an S lock.• If T wants to write an object, it first obtains an X lock.• If T releases any lock, it can acquire no new locks.

• Recall: all this is done transparently to the user by the DBMS.

• 2PL guarantees serializability!

• Why??

lock point

growing phase

shrinking phase

Time

# oflocks

Serializability GraphsTwo actions conflict if they access the same data item.

The precedence graph contains:

• A node for every committed transaction

• An arc from Ti to Tj if an action of Ti precedes and conflicts with an action of Tj.

• T1 transfers $100 from A to B, T2 adds 6% to bothR1(A), W1(A), R2(A), W2(A), R2(B), W2(B), R1(B), W1(B)

T1 T2

Conflict Serializability• 2 schedules are conflict equivalent if:

– they have the same sets of actions, and– each pair of conflicting actions is ordered in the same way.

• A schedule is conflict serializable if it is conflict equivalent to a serial schedule.– Note: Some serializable schedules are not conflict

serializable!• Theorem: A schedule is conflict serializable iff its precedence

graph is acyclic.• Theorem: 2PL ensures that the precedence graph will be acyclic!

DeadlocksSuppose we have the following scenario:

• T1 asks for an exclusive lock on A• T2 asks for an exclusive lock on B• T1 asks for a shared lock on B• T2 asks for a shared lock on A

Both T1 and T2 are waiting! We have a DEADLOCK.

Possible solutions:

• Prevent deadlocks to start with, or• Detect when they happen and do something about it.

Deadlock Prevention• Give each transaction a timestamp. “Older” transactions have higher priority.

• Assume Ti requests a lock, but Tj holds a conflicting lock. We can follow two strategies:

• Wait-die: if Ti has higher priority, it waits; else Ti aborts.• Wound-wait: if Ti has higher priority, abort Tj; else Ti waits.

• Note: after aborting, restart with original timestamp!

Both strategies guarantee deadlock-free behavior!

An Alternative to Prevention

• In theory, deadlock can involve many transactions:T1 waits-for T2 waits-for T3 ...waits-for T1

• In practice, most “deadlock cycles” involve only 2 transactions.

• Don’t need to prevent deadlock!What’s the problem with prevention?

• Allow it to happen, then notice it and fix it.Deadlock detection.

Deadlock Detection

• Lock Manager maintains a “Waits-for” graph:• Node for each transaction.• Arc from Ti to Tj if Tj holds a lock and Ti is waiting for it.

• Periodically check graph for cycles.

• “Shoot” some transaction to break the cycle.

• Simpler hack: time-outs.T1 made no progress for a while? Shoot it.

Detection Versus Prevention

• Prevention might abort too many transactions.• Detection might allow deadlocks to tie up resources

for a while.– Can detect more often, but it’s time-consuming.

• The usual answer:– Detection is the winner.– Deadlocks are pretty rare.– If you get a lot of deadlocks, reconsider your

schema/workload!

Review: ACID ACID PropertiesAAtomicity: all actions of a transaction happen, or none happen.

CConsistency: if a transaction is consistent, and the database starts from a consistent state, then it will end in a consistent state.

IIsolation: the execution of one transaction is isolated from other transactions.

DDurability: if a transaction commits, its effects persist in the database.

The Recovery Manager guarantees Atomicity & Durability.