Transaction management overview l.jpg
This presentation is the property of its rightful owner.
Sponsored Links
1 / 47

Transaction Management Overview PowerPoint PPT Presentation


  • 139 Views
  • Uploaded on
  • Presentation posted in: General

Transaction Management Overview. Chapter 18. 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.

Download Presentation

Transaction Management Overview

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Transaction management overview l.jpg

Transaction Management Overview

Chapter 18


Transactions l.jpg

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


Concurrency in a dbms l.jpg

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.


Atomicity of transactions l.jpg

Atomicity of Transactions

  • A transaction mightcommitafter 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 undothe actions of aborted transactions.


Example l.jpg

Example

  • Consider two transactions (Xacts):

T1:BEGIN A=A+100, B=B-100 END

T2: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.


Example contd l.jpg

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)


Scheduling transactions l.jpg

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. )


Anomalies with interleaved execution l.jpg

Anomalies with Interleaved Execution

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

  • Unrepeatable Reads (RW Conflicts):

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

T2:R(A), W(A), C

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

T2:R(A), W(A), C


Anomalies continued l.jpg

Anomalies (Continued)

  • Overwriting Uncommitted Data (WW Conflicts):

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

T2:W(A), W(B), C


Lock based concurrency control l.jpg

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.


Aborting a transaction l.jpg

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 abortsby 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.


The log l.jpg

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 diskbeforethe 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.


Recovering from a crash l.jpg

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!)


Summary l.jpg

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.


Concurrency control l.jpg

Concurrency Control

Chapter 19


Conflict serializable schedules l.jpg

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


Example17 l.jpg

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)

A

T1

T2

Dependency graph

B


Dependency graph l.jpg

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


Review strict 2pl l.jpg

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


Two phase locking 2pl l.jpg

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.


View serializability l.jpg

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 S2

T1: R(A) W(A)

T2: W(A)

T3: W(A)

T1: R(A),W(A)

T2: W(A)

T3: W(A)


Crash recovery l.jpg

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


Review the acid properties l.jpg

Review: The ACID properties

  • Atomicity: All actions in the Xact happen, or none happen.

  • Consistency: If each Xact is consistent, and the DB starts consistent, it ends up consistent.

  • Isolation: Execution of one Xact is isolated from that of other Xacts.

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

  • The Recovery Manager guarantees Atomicity & Durability.


Motivation l.jpg

Motivation

  • Atomicity:

    • Transactions may abort (“Rollback”).

  • Durability:

    • What if DBMS stops running? (Causes?)

  • Desired Behavior after system restarts:

    • T1, T2 & T3 should be durable.

    • T4 & T5should be aborted (effects not seen).

crash!

T1

T2

T3

T4

T5


Assumptions l.jpg

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?


Handling the buffer pool l.jpg

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?

No Steal

Steal

Force

Trivial

Desired

No Force


More on steal and force l.jpg

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.


Basic idea logging l.jpg

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).


Write ahead logging wal l.jpg

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 beforecommit.

  • #1 guarantees Atomicity.

  • #2 guarantees Durability.

  • Exactly how is logging (and recovery!) done?

    • We’ll study the ARIES algorithms.


Wal the log l.jpg

DB

RAM

LSNs

pageLSNs

flushedLSN

pageLSN

WAL & the Log

  • Each log record has a unique Log Sequence Number (LSN).

    • LSNs always increasing.

  • Each data pagecontains 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

Log records

flushed to disk

“Log tail”

in RAM


Log records l.jpg

prevLSN

XID

type

pageID

length

offset

before-image

after-image

Log Records

LogRecord fields:

Possible log record types:

  • Update

  • Commit

  • Abort

  • End (signifies end of commit or abort)

  • Compensation Log Records (CLRs)

    • for UNDO actions

update

records

only


Other log related state l.jpg

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 firstcaused the page to be dirty.


Normal execution of an xact l.jpg

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.


Checkpointing l.jpg

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).


The big picture what s stored where l.jpg

prevLSN

XID

type

pageID

length

offset

before-image

after-image

The Big Picture: What’s Stored Where

LOG

RAM

DB

LogRecords

Xact Table

lastLSN

status

Dirty Page Table

recLSN

flushedLSN

Data pages

each

with a

pageLSN

master record


Simple transaction abort l.jpg

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!


Abort cont l.jpg

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.


Transaction commit l.jpg

Transaction Commit

  • Write commit record to log.

  • All log records up to Xact’s lastLSN are flushed.

    • Guarantees that flushedLSN ³ lastLSN.

    • Note that log flushes are sequential, synchronous writes to disk.

    • Many log records per log page.

  • Commit() returns.

  • Write end record to log.


Crash recovery big picture l.jpg

Crash Recovery: Big Picture

Oldest log rec. of Xact active at crash

  • Start from a checkpoint (found via master record).

  • Three phases. Need to:

    • Figure out which Xacts committed since checkpoint, which failed (Analysis).

    • REDOall actions.

      • (repeat history)

    • UNDO effects of failed Xacts.

Smallest recLSN in dirty page table after Analysis

Last chkpt

CRASH

A

R

U


Recovery the analysis phase l.jpg

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.


Recovery the redo phase l.jpg

Recovery: The REDO Phase

  • We repeat History to reconstruct state at crash:

    • Reapply allupdates (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) ³ LSN.

  • To REDO an action:

    • Reapply logged action.

    • Set pageLSN to LSN. No additional logging!


Recovery the undo phase l.jpg

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.


Example of recovery l.jpg

RAM

Example of Recovery

LSN LOG

00

05

10

20

30

40

45

50

60

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

prevLSNs

Xact Table

lastLSN

status

Dirty Page Table

recLSN

flushedLSN

ToUndo


Example crash during restart l.jpg

RAM

Example: Crash During Restart!

LSN LOG

00,05

10

20

30

40,45

50

60

70

80,85

90

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

undonextLSN

Xact Table

lastLSN

status

Dirty Page Table

recLSN

flushedLSN

ToUndo


Additional crash issues l.jpg

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.


Summary of logging recovery l.jpg

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.


Summary cont l.jpg

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!


  • Login