Transaction Management and Recovery, 2 nd Edition. R. Ramakrishnan and J. Gehrke1 Transaction...

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ction Management and Recovery, 2 nd Edition. R. Ramakrishnan and J. Gehrke Transaction Management Overview Chapter 18

Transcript of Transaction Management and Recovery, 2 nd Edition. R. Ramakrishnan and J. Gehrke1 Transaction...

Page 1: Transaction Management and Recovery, 2 nd Edition. R. Ramakrishnan and J. Gehrke1 Transaction Management Overview Chapter 18.

Transaction Management and Recovery, 2nd Edition. R. Ramakrishnan and J. Gehrke 1

Transaction Management Overview

Chapter 18

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Transactions

Concurrent execution of user programs is essential for good DBMS performance. Because disk accesses are frequent, and relatively

slow, it is important to keep the cpu humming by working on several user programs concurrently.

A user’s program may carry out many operations on the data retrieved from the database, but the DBMS is only concerned about what data is read/written from/to the database.

A transaction is the DBMS’s abstract view of a user program: a sequence of reads and writes.

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Concurrency in a DBMS Users submit transactions, and can think of each

transaction as executing by itself. Concurrency is achieved by the DBMS, which interleaves

actions (reads/writes of DB objects) of various transactions.

Each transaction must leave the database in a consistent state if the DB is consistent when the transaction begins. DBMS will enforce some ICs, depending on the ICs

declared in CREATE TABLE statements. Beyond this, the DBMS does not really understand the

semantics of the data. (e.g., it does not understand how the interest on a bank account is computed).

Issues: Effect of interleaving transactions, and crashes.

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Atomicity of Transactions

A transaction might commit after completing all its actions, or it could abort (or be aborted by the DBMS) after executing some actions.

A very important property guaranteed by the DBMS for all transactions is that they are atomic. That is, a user can think of a Xact as always executing all its actions in one step, or not executing any actions at all. DBMS logs all actions so that it can undo the actions

of aborted transactions.

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Example

Consider two transactions (Xacts):

T1: BEGIN A=A+100, B=B-100 ENDT2: BEGIN A=1.06*A, B=1.06*B END

Intuitively, the first transaction is transferring $100 from B’s account to A’s account. The second is crediting both accounts with a 6% interest payment.

There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted together. However, the net effect must be equivalent to these two transactions running serially in some order.

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Example (Contd.)

Consider a possible interleaving (schedule):

T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

This is OK. But what about:T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

The DBMS’s view of the second schedule:

T1: R(A), W(A), R(B), W(B)T2: R(A), W(A), R(B), W(B)

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Scheduling Transactions

Serial schedule: Schedule that does not interleave the actions of different transactions.

Equivalent schedules: For any database state, the effect (on the set of objects in the database) of executing the first schedule is identical to the effect of executing the second schedule.

Serializable schedule: A schedule that is equivalent to some serial execution of the transactions.

(Note: If each transaction preserves consistency, every serializable schedule preserves consistency. )

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Anomalies with Interleaved Execution

Reading Uncommitted Data (WR Conflicts, “dirty reads”):

Unrepeatable Reads (RW Conflicts):

T1: R(A), W(A), R(B), W(B), AbortT2: R(A), W(A), C

T1: R(A), R(A), W(A), CT2: R(A), W(A), C

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Anomalies (Continued)

Overwriting Uncommitted Data (WW Conflicts):

T1: W(A), W(B), CT2: W(A), W(B), C

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Lock-Based Concurrency Control

Strict Two-phase Locking (Strict 2PL) Protocol: Each Xact must obtain a S (shared) lock on object

before reading, and an X (exclusive) lock on object before writing.

All locks held by a transaction are released when the transaction completes

If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.

Strict 2PL allows only serializable schedules.

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Aborting a Transaction If a transaction Ti is aborted, all its actions have to

be undone. Not only that, if Tj reads an object last written by Ti, Tj must be aborted as well!

Most systems avoid such cascading aborts by releasing a transaction’s locks only at commit time. If Ti writes an object, Tj can read this only after Ti commits.

In order to undo the actions of an aborted transaction, the DBMS maintains a log in which every write is recorded. This mechanism is also used to recover from system crashes: all active Xacts at the time of the crash are aborted when the system comes back up.

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The Log

The following actions are recorded in the log: Ti writes an object: the old value and the new value.

Log record must go to disk before the changed page! Ti commits/aborts: a log record indicating this action.

Log records are chained together by Xact id, so it’s easy to undo a specific Xact.

Log is often duplexed and archived on stable storage. All log related activities (and in fact, all CC related

activities such as lock/unlock, dealing with deadlocks etc.) are handled transparently by the DBMS.

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Recovering From a Crash

There are 3 phases in the Aries recovery algorithm: Analysis: Scan the log forward (from the most recent

checkpoint) to identify all Xacts that were active, and all dirty pages in the buffer pool at the time of the crash.

Redo: Redoes all updates to dirty pages in the buffer pool, as needed, to ensure that all logged updates are in fact carried out and written to disk.

Undo: The writes of all Xacts that were active at the crash are undone (by restoring the before value of the update, which is in the log record for the update), working backwards in the log. (Some care must be taken to handle the case of a crash occurring during the recovery process!)

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Summary

Concurrency control and recovery are among the most important functions provided by a DBMS.

Users need not worry about concurrency. System automatically inserts lock/unlock requests and

schedules actions of different Xacts in such a way as to ensure that the resulting execution is equivalent to executing the Xacts one after the other in some order.

Write-ahead logging (WAL) is used to undo the actions of aborted transactions and to restore the system to a consistent state after a crash. Consistent state: Only the effects of commited Xacts

seen.

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Transaction Management and Recovery, 2nd Edition. R. Ramakrishnan and J. Gehrke 15

Concurrency Control

Chapter 19

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Conflict Serializable Schedules

Two schedules are conflict equivalent if: Involve the same actions of the same

transactions Every pair of conflicting actions is ordered

the same way

Schedule S is conflict serializable if S is conflict equivalent to some serial schedule

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Example

A schedule that is not conflict serializable:

The cycle in the graph reveals the problem. The output of T1 depends on T2, and vice-versa.

T1: R(A), W(A), R(B), W(B)T2: R(A), W(A), R(B), W(B)

T1 T2A

B

Dependency graph

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Dependency Graph

Dependency graph: One node per Xact; edge from Ti to Tj if Tj reads/writes an object last written by Ti.

Theorem: Schedule is conflict serializable if and only if its dependency graph is acyclic

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Review: Strict 2PL

Strict Two-phase Locking (Strict 2PL) Protocol: Each Xact must obtain a S (shared) lock on

object before reading, and an X (exclusive) lock on object before writing.

All locks held by a transaction are released when the transaction completes

If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.

Strict 2PL allows only schedules whose precedence graph is acyclic

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Two-Phase Locking (2PL)

Two-Phase Locking Protocol Each Xact must obtain a S (shared) lock on

object before reading, and an X (exclusive) lock on object before writing.

A transaction can not request additional locks once it releases any locks.

If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.

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View Serializability Schedules S1 and S2 are view equivalent

if: If Ti reads initial value of A in S1, then Ti also

reads initial value of A in S2 If Ti reads value of A written by Tj in S1, then

Ti also reads value of A written by Tj in S2 If Ti writes final value of A in S1, then Ti also

writes final value of A in S2T1: R(A) W(A)T2: W(A)T3: W(A)

T1: R(A),W(A)T2: W(A)T3: W(A)

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Crash Recovery

Chapter 20

If you are going to be in the logging business, one of the things that you have to do is to learn about heavy equipment.

Robert VanNatta, Logging History of Columbia

County

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Review: The ACID properties

AA tomicity: All actions in the Xact happen, or none happen.

CC onsistency: If each Xact is consistent, and the DB starts consistent, it ends up consistent.

II solation: Execution of one Xact is isolated from that of other Xacts.

D D urability: If a Xact commits, its effects persist.

The Recovery Manager guarantees Atomicity & Durability.

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Motivation

Atomicity: Transactions may abort (“Rollback”).

Durability: What if DBMS stops running? (Causes?)

crash!• Desired Behavior after

system restarts:– T1, T2 & T3 should be

durable.– T4 & T5 should be

aborted (effects not seen).

T1T2T3T4T5

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Assumptions

Concurrency control is in effect. Strict 2PL, in particular.

Updates are happening “in place”. i.e. data is overwritten on (deleted from) the

disk.

A simple scheme to guarantee Atomicity & Durability?

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Handling the Buffer Pool

Force every write to disk? Poor response time. But provides durability.

Steal buffer-pool frames from uncommited Xacts? If not, poor throughput. If so, how can we ensure

atomicity?

Force

No Force

No Steal Steal

Trivial

Desired

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More on Steal and Force

STEAL (why enforcing Atomicity is hard) To steal frame F: Current page in F (say P) is written

to disk; some Xact holds lock on P. What if the Xact with the lock on P aborts? Must remember the old value of P at steal time

(to support UNDOing the write to page P).

NO FORCE (why enforcing Durability is hard) What if system crashes before a modified page is

written to disk? Write as little as possible, in a convenient place, at

commit time,to support REDOing modifications.

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Basic Idea: Logging

Record REDO and UNDO information, for every update, in a log. Sequential writes to log (put it on a separate disk). Minimal info (diff) written to log, so multiple updates fit

in a single log page.

Log: An ordered list of REDO/UNDO actions Log record contains:

<XID, pageID, offset, length, old data, new data>

and additional control info (which we’ll see soon).

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Write-Ahead Logging (WAL)

The Write-Ahead Logging Protocol: Must force the log record for an update before

the corresponding data page gets to disk. Must write all log records for a Xact before

commit. #1 guarantees Atomicity. #2 guarantees Durability.

Exactly how is logging (and recovery!) done? We’ll study the ARIES algorithms.

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WAL & the Log Each log record has a unique Log Sequence

Number (LSN). LSNs always increasing.

Each data page contains a pageLSN. The LSN of the most recent log record

for an update to that page.

System keeps track of flushedLSN. The max LSN flushed so far.

WAL: Before a page is written, pageLSN flushedLSN

LSNs

DB

pageLSNs

RAM

flushedLSN

pageLSN

Log recordsflushed to disk

“Log tail” in RAM

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Log RecordsPossible log record types: Update Commit Abort End (signifies end of

commit or abort) Compensation Log

Records (CLRs) for UNDO actions

prevLSNXIDtype

lengthpageID

offsetbefore-imageafter-image

LogRecord fields:

updaterecordsonly

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Other Log-Related State

Transaction Table: One entry per active Xact. Contains XID, status

(running/commited/aborted), and lastLSN.

Dirty Page Table: One entry per dirty page in buffer pool. Contains recLSN -- the LSN of the log record

which first caused the page to be dirty.

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Normal Execution of an Xact

Series of reads & writes, followed by commit or abort. We will assume that write is atomic on disk.

In practice, additional details to deal with non-atomic writes.

Strict 2PL. STEAL, NO-FORCE buffer management, with

Write-Ahead Logging.

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Checkpointing

Periodically, the DBMS creates a checkpoint, in order to minimize the time taken to recover in the event of a system crash. Write to log: begin_checkpoint record: Indicates when chkpt began. end_checkpoint record: Contains current Xact table and

dirty page table. This is a `fuzzy checkpoint’: Other Xacts continue to run; so these tables accurate

only as of the time of the begin_checkpoint record. No attempt to force dirty pages to disk; effectiveness of

checkpoint limited by oldest unwritten change to a dirty page. (So it’s a good idea to periodically flush dirty pages to disk!)

Store LSN of chkpt record in a safe place (master record).

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The Big Picture: What’s Stored Where

DB

Data pageseachwith apageLSN

Xact TablelastLSNstatus

Dirty Page TablerecLSN

flushedLSN

RAM

prevLSNXIDtype

lengthpageID

offsetbefore-imageafter-image

LogRecords

LOG

master record

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Simple Transaction Abort

For now, consider an explicit abort of a Xact. No crash involved.

We want to “play back” the log in reverse order, UNDOing updates. Get lastLSN of Xact from Xact table. Can follow chain of log records backward via the

prevLSN field. Before starting UNDO, write an Abort log record.

For recovering from crash during UNDO!

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Abort, cont.

To perform UNDO, must have a lock on data! No problem!

Before restoring old value of a page, write a CLR: You continue logging while you UNDO!! CLR has one extra field: undonextLSN

Points to the next LSN to undo (i.e. the prevLSN of the record we’re currently undoing).

CLRs never Undone (but they might be Redone when repeating history: guarantees Atomicity!)

At end of UNDO, write an “end” log record.

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Transaction Commit

Write commit record to log. All log records up to Xact’s lastLSN are

flushed. Guarantees that flushedLSN lastLSN. Note that log flushes are sequential,

synchronous writes to disk. Many log records per log page.

Commit() returns. Write end record to log.

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Crash Recovery: Big Picture

Start from a checkpoint (found via master record).

Three phases. Need to: Figure out which Xacts

committed since checkpoint, which failed (Analysis).

REDO all actions. (repeat history)

UNDO effects of failed Xacts.

Oldest log rec. of Xact active at crash

Smallest recLSN in dirty page table after Analysis

Last chkpt

CRASH

A R U

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Recovery: The Analysis Phase

Reconstruct state at checkpoint. via end_checkpoint record.

Scan log forward from checkpoint. End record: Remove Xact from Xact table. Other records: Add Xact to Xact table, set

lastLSN=LSN, change Xact status on commit.

Update record: If P not in Dirty Page Table,

Add P to D.P.T., set its recLSN=LSN.

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Recovery: The REDO Phase We repeat History to reconstruct state at crash:

Reapply all updates (even of aborted Xacts!), redo CLRs. Scan forward from log rec containing smallest

recLSN in D.P.T. For each CLR or update log rec LSN, REDO the action unless: Affected page is not in the Dirty Page Table, or Affected page is in D.P.T., but has recLSN > LSN, or pageLSN (in DB) LSN.

To REDO an action: Reapply logged action. Set pageLSN to LSN. No additional logging!

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Recovery: The UNDO Phase

ToUndo={ l | l a lastLSN of a “loser” Xact}Repeat:

Choose largest LSN among ToUndo. If this LSN is a CLR and undonextLSN==NULL

Write an End record for this Xact. If this LSN is a CLR, and undonextLSN != NULL

Add undonextLSN to ToUndo Else this LSN is an update. Undo the update, write a

CLR, add prevLSN to ToUndo.

Until ToUndo is empty.

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Example of Recovery

begin_checkpoint

end_checkpoint

update: T1 writes P5

update T2 writes P3

T1 abort

CLR: Undo T1 LSN 10

T1 End

update: T3 writes P1

update: T2 writes P5

CRASH, RESTART

LSN LOG

00

05

10

20

30

40

45

50

60

Xact TablelastLSNstatus

Dirty Page TablerecLSN

flushedLSN

ToUndo

prevLSNs

RAM

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Example: Crash During Restart!

begin_checkpoint, end_checkpoint

update: T1 writes P5

update T2 writes P3

T1 abort

CLR: Undo T1 LSN 10, T1 End

update: T3 writes P1

update: T2 writes P5

CRASH, RESTART

CLR: Undo T2 LSN 60

CLR: Undo T3 LSN 50, T3 end

CRASH, RESTART

CLR: Undo T2 LSN 20, T2 end

LSN LOG00,05

10

20

30

40,45

50

60

70

80,85

90

Xact TablelastLSNstatus

Dirty Page TablerecLSN

flushedLSN

ToUndo

undonextLSN

RAM

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Additional Crash Issues

What happens if system crashes during Analysis? During REDO?

How do you limit the amount of work in REDO? Flush asynchronously in the background. Watch “hot spots”!

How do you limit the amount of work in UNDO? Avoid long-running Xacts.

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Summary of Logging/Recovery

Recovery Manager guarantees Atomicity & Durability.

Use WAL to allow STEAL/NO-FORCE w/o sacrificing correctness.

LSNs identify log records; linked into backwards chains per transaction (via prevLSN).

pageLSN allows comparison of data page and log records.

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Summary, Cont.

Checkpointing: A quick way to limit the amount of log to scan on recovery.

Recovery works in 3 phases: Analysis: Forward from checkpoint. Redo: Forward from oldest recLSN. Undo: Backward from end to first LSN of

oldest Xact alive at crash. Upon Undo, write CLRs. Redo “repeats history”: Simplifies the

logic!