Database System Concepts, 6th Ed.
Chapter 16: Recovery System
Chapter 16: Recovery System
Outline Outline
Failure Classification
Storage Structure
Recovery and Atomicity
Log-Based Recovery
Recovery Algorithm
Recovery with Early Lock Release
ARIES Recovery Algorithm
Remote Backup Systems
Failure Classification Failure Classification
Transaction failure :
Logical errors: transaction cannot complete due to some internal error condition
System errors: the database system must terminate an active transaction due to an error condition (e.g., deadlock)
System crash: a power failure or other hardware or software failure causes the system to crash.
Fail-stop assumption: non-volatile storage contents are assumed to not be corrupted as result of a system crash
Database systems have numerous integrity checks to prevent corruption of disk data
Disk failure: a head crash or similar disk failure destroys all or part of disk storage
Destruction is assumed to be detectable: disk drives use
checksums to detect failures
Recovery Algorithms Recovery Algorithms
Consider transaction T
ithat transfers $50 from account A to account B
Two updates: subtract 50 from A and add 50 to B
Transaction T
irequires updates to A and B to be output to the database.
A failure may occur after one of these modifications have been made but before both of them are made.
Modifying the database without ensuring that the transaction will commit may leave the database in an inconsistent state
Not modifying the database may result in lost updates if failure occurs just after transaction commits
Recovery algorithms have two parts
1.
Actions taken during normal transaction processing to ensure enough information exists to recover from failures
2.
Actions taken after a failure to recover the database contents to a
state that ensures atomicity, consistency and durability
Storage Structure Storage Structure
Volatile storage:
does not survive system crashes
examples: main memory, cache memory
Nonvolatile storage:
survives system crashes
examples: disk, tape, flash memory,
non-volatile (battery backed up) RAM
but may still fail, losing data
Stable storage:
a mythical form of storage that survives all failures
approximated by maintaining multiple copies on distinct nonvolatile
media
Stable-Storage Implementation Stable-Storage Implementation
Maintain multiple copies of each block on separate disks
copies can be at remote sites to protect against disasters such as fire or flooding.
Failure during data transfer can still result in inconsistent copies.
Block transfer can result in
Successful completion
Partial failure: destination block has incorrect information
Total failure: destination block was never updated
Protecting storage media from failure during data transfer (one solution):
Execute output operation as follows (assuming two copies of each block):
1. Write the information onto the first physical block.
2. When the first write successfully completes, write the same information onto the second physical block.
3. The output is completed only after the second write successfully completes.
Stable-Storage Implementation (Cont.) Stable-Storage Implementation (Cont.)
Protecting storage media from failure during data transfer (cont.):
Copies of a block may differ due to failure during output operation. To recover from failure:
1. First find inconsistent blocks:
1. Expensive solution: Compare the two copies of every disk block.
2. Better solution:
Record in-progress disk writes on non-volatile storage (Non- volatile RAM or special area of disk).
Use this information during recovery to find blocks that may be inconsistent, and only compare copies of these.
Used in hardware RAID systems
2. If either copy of an inconsistent block is detected to have an error (bad checksum), overwrite it by the other copy. If both have no error, but are different, overwrite the second block by the first block
.
Data Access Data Access
Physical blocks are those blocks residing on the disk.
System buffer blocks are the blocks residing temporarily in main memory.
Block movements between disk and main memory are initiated through the following two operations:
input(B) transfers the physical block B to main memory.
output(B) transfers the buffer block B to the disk, and replaces the appropriate physical block there.
We assume, for simplicity, that each data item fits in, and is stored
inside, a single block.
Data Access (Cont.) Data Access (Cont.)
Each transaction T
i has its private work-area in which local copies of alldata items accessed and updated by it are kept.
T
i's local copy of a data item X is denoted by x
i. BX denotes block containing X
Transferring data items between system buffer blocks and its private work-area done by:
read(X) assigns the value of data item X to the local variable xi
.
write(X) assigns the value of local variable xi to data item {X} in the
buffer block.
Transactions
Must perform read(X) before accessing X for the first time (subsequent reads can be from local copy)
The write(X) can be executed at any time before the transaction commits
Note that output(B
X) need not immediately follow write(X). System can
perform the output operation when it deems fit.
Example of Data Access Example of Data Access
X Y
A B
x
1y
1buffer Buffer Block A
Buffer Block B
input(A)
output(B) read(X)
disk work area
of T
1memory
Recovery and Atomicity Recovery and Atomicity
To ensure atomicity despite failures, we first output
information describing the modifications to stable storage without modifying the database itself.
We study log-based recovery mechanisms in detail
We first present key concepts
And then (module 17) present the actual recovery algorithm
Less used alternative: shadow-paging (brief details presented in the book).
In this Module we assume serial execution of transactions.
In Module 17, we consider the case of concurrent
transaction execution.
Log-Based Recovery Log-Based Recovery
A log is kept on stable storage.
The log is a sequence of log records, which maintains information about update activities on the database.
When transaction T
istarts, it registers itself by writing a record <T
istart>
to the log
Before T
iexecutes write(X), a log record <T
i, X, V
1, V
2>
is written, where V
1is the value of X before the write (the old value), and V
2is the value to be written to X (the new value).
When T
ifinishes it last statement, the log record <T
icommit> is written.
Two approaches using logs
Immediate database modification
Deferred database modification
Database Modification Database Modification
The immediate-modification scheme allows updates of an
uncommitted transaction to be made to the buffer, or the disk itself, before the transaction commits
Update log record must be written before a database item is written
We assume that the log record is output directly to stable storage
(Will see later that how to postpone log record output to some extent)
Output of updated blocks to disk storage can take place at any time before or after transaction commit
Order in which blocks are output can be different from the order in which they are written.
The deferred-modification scheme performs updates to buffer/disk only at the time of transaction commit
Simplifies some aspects of recovery
But has overhead of storing local copy
We cover here only the immediate-modification scheme
Transaction Commit
A transaction is said to have committed when its commit log record is output to stable storage
All previous log records of the transaction must have been output already
Writes performed by a transaction may still be in the buffer when
the transaction commits, and may be output later
Immediate Database Modification Example Immediate Database Modification Example
Log Write Output
<T
0start>
<T
0, A, 1000, 950>
<T
o, B, 2000, 2050>
A = 950 B = 2050
<T
0commit>
<T
1start>
<T
1, C, 700, 600>
C = 600
B
B, B
C<T
1commit>
B
A
Note: B
Xdenotes block containing X.
BC output before T1
commits
BA output after T0
commits
Undo and Redo Operations
Undo of a log record <T
i, X, V
1, V
2> writes the old value V
1to X
Redo of a log record <T
i, X, V
1, V
2> writes the new value V
2to X
Undo and Redo of Transactions
undo(T
i) restores the value of all data items updated by T
ito their old values, going backwards from the last log record for T
i
Each time a data item X is restored to its old value V a special log record (called redo-only) <T
i, X, V> is written out
When undo of a transaction is complete, a log record
<T
iabort> is written out (to indicate that the undo was completed)
redo(T
i) sets the value of all data items updated by T
ito the new values, going forward from the first log record for T
i
No logging is done in this case
Undo and Redo Operations (Cont.)
The undo and redo operations are used in several different circumstances:
The undo is used for transaction rollback during normal operation(in case a transaction cannot complete its execution due to some logical error).
The undo and redo operations are used during recovery from failure.
We need to deal with the case where during recovery
from failure another failure occurs prior to the system
having fully recovered.
Transaction rollback (during normal operation) Transaction rollback (during normal operation)
Let T
ibe the transaction to be rolled back
Scan log backwards from the end, and for each log record of T
iof the form <T
i, X
j, V
1, V
2>
Perform the undo by writing V
1to X
j,
Write a log record <T
i, X
j, V
1>
such log records are called compensation log records
Once the record <T
istart> is found stop the scan and write the
log record <T
iabort>
Undo and Redo on Recovering from Failure Undo and Redo on Recovering from Failure
When recovering after failure:
Transaction T
ineeds to be undone if the log
contains the record <T
istart>,
but does not contain either the record <T
icommit> or <T
iabort>.
Transaction T
ineeds to be redone if the log
contains the records <T
istart>
and contains the record <T
icommit> or <T
iabort>
It may seem strange to redo transaction T
iif the record <T
iabort>
record is in the log. To see why this works, note that if <T
iabort> is in the log, so are the redo-only records written by the undo operation.
Thus, the end result will be to undo T
i's modifications in this case.
This slight redundancy simplifies the recovery algorithm and enables faster overall recovery time.
such a redo redoes all the original actions including the steps that
restored old value. Known as repeating history
Immediate Modification Recovery Example Immediate Modification Recovery Example
Below we show the log as it appears at three instances of time.
Recovery actions in each case above are:
(a) undo (T
0): B is restored to 2000 and A to 1000, and log records
<T
0, B, 2000>, <T
0, A, 1000>, <T
0, abort> are written out
(b) redo (T
0) and undo (T
1): A and B are set to 950 and 2050 and C is
restored to 700. Log records <T
1, C, 700>, <T
1, abort> are written out.
(c) redo (T
0) and redo (T
1): A and B are set to 950 and 2050
respectively. Then C is set to 600
Checkpoints Checkpoints
Redoing/undoing all transactions recorded in the log can be very slow
Processing the entire log is time-consuming if the system has run for a long time
We might unnecessarily redo transactions which have already output their updates to the database.
Streamline recovery procedure by periodically performing checkpointing
All updates are stopped while doing checkpointing
1.
Output all log records currently residing in main memory onto stable storage.
2.
Output all modified buffer blocks to the disk.
3.
Write a log record < checkpoint L> onto stable storage where L is a
list of all transactions active at the time of checkpoint.
Checkpoints (Cont.) Checkpoints (Cont.)
During recovery we need to consider only the most recent transaction T
ithat started before the checkpoint, and transactions that started after T
i.
Scan backwards from end of log to find the most recent
<checkpoint L> record
Only transactions that are in L or started after the checkpoint need to be redone or undone
Transactions that committed or aborted before the checkpoint already have all their updates output to stable storage.
Some earlier part of the log may be needed for undo operations
Continue scanning backwards till a record <T
istart> is found for every transaction T
iin L.
Parts of log prior to earliest <T
istart> record above are not
needed for recovery, and can be erased whenever desired.
Example of Checkpoints Example of Checkpoints
T
1can be ignored (updates already output to disk due to checkpoint)
T
2and T
3redone.
T
4undone
T
cT
fT
1T
2T
3T
4checkpoint system failure
Disk Crash Disk Crash
What happens if the disk crashes and the data on it is gone?
Recovery Schemes
So far:
We covered key concepts
We assumed serial execution of transactions
Now:
We discuss concurrency control issues
We present the components of the basic recovery algorithm
Later:
We present extensions to allow more concurrency
Concurrency Control and Recovery
With concurrent transactions, all transactions share a single disk buffer and a single log
A buffer block can have data items updated by one or more transactions
We assume that if a transaction T
ihas modified an item, no other transaction can modify the same item until T
ihas committed or aborted
i.e. the updates of uncommitted transactions should not be visible to other transactions
Otherwise how do we perform undo if T
1updates A, then T
2updates A and commits, and finally T
1has to abort?
Can be ensured by obtaining exclusive locks on updated items and holding the locks till end of transaction (strict two-phase locking)
Log records of different transactions may be interspersed in the log.
Example of Data Access with Concurrent transactions Example of Data Access with Concurrent transactions
X Y
A B
x
1y
1buffer Buffer Block A
Buffer Block B
input(A)
output(B) read(X)
write(Y)
disk work area
of T
1work area of T
2memory
x
2Recovery Algorithm
Logging (during normal operation):
<T
istart> at transaction start
<T
i, X
j, V
1, V
2> for each update, and
<T
icommit> at transaction end
Transaction rollback (during normal operation)
Let T
ibe the transaction to be rolled back
Scan log backwards from the end, and for each log record of T
iof the form <T
i, X
j, V
1, V
2>
perform the undo by writing V
1to X
j,
write a log record <T
i, X
j, V
1>
– such log records are called compensation log records
Once the record <T
istart> is found stop the scan and write the log
record <T
iabort>
Recovery from failure: Two phases
Redo phase: replay updates of all transactions, whether they committed, aborted, or are incomplete
Undo phase: undo all incomplete transactions
Redo phase:
1.
Find last <checkpoint L> record, and set undo-list to L.
2.
Scan forward from above <checkpoint L> record
1.
Whenever a record <T
i, X
j, V
1, V
2> is found, redo it by writing V
2to X
j2.
Whenever a log record <T
istart> is found, add T
ito undo-list
3.
Whenever a log record <T
icommit> or <T
iabort> is found, remove T
ifrom undo-list
Recovery Algorithm (Cont.)
Recovery Algorithm (Cont.)
Recovery Algorithm (Cont.) Recovery Algorithm (Cont.)
Undo phase:
1.
Scan log backwards from end
1.
Whenever a log record <T
i, X
j, V
1, V
2> is found where T
iis in undo-list perform same actions as for transaction rollback:
1. perform undo by writing V
1to X
j. 2. write a log record <T
i, X
j, V
1>
2.
Whenever a log record <T
istart> is found where T
iis in undo- list,
1. Write a log record <T
iabort>
2. Remove T
ifrom undo-list
3.
Stop when undo-list is empty
i.e.,<T
istart> has been found for every transaction in undo-list
After undo phase completes, normal transaction processing can
commence
Example of Recovery
Example of Recovery
Log Record Buffering Log Record Buffering
Log record buffering: log records are buffered in main memory, instead of of being output directly to stable storage.
Log records are output to stable storage when a block of log records in the buffer is full, or a log force operation is executed.
Log force is performed to commit a transaction by forcing all its log records (including the commit record) to stable storage.
Several log records can thus be output using a single output operation,
reducing the I/O cost.
Log Record Buffering (Cont.) Log Record Buffering (Cont.)
The rules below must be followed if log records are buffered:
Log records are output to stable storage in the order in which they are created.
Transaction T
ienters the commit state only when the log record
<T
icommit> has been output to stable storage.
Before a block of data in main memory is output to the database, all log records pertaining to data in that block must have been output to stable storage.
This rule is called the write-ahead logging or WAL rule
– Strictly speaking WAL only requires undo information to be
output
Database Buffering Database Buffering
Database maintains an in-memory buffer of data blocks
When a new block is needed, if buffer is full an existing block needs to be removed from buffer
If the block chosen for removal has been updated, it must be output to disk
The recovery algorithm supports the no-force policy: i.e., updated blocks need not be written to disk when transaction commits
force policy: requires updated blocks to be written at commit
More expensive commit
The recovery algorithm supports the steal policy:i.e., blocks containing
updates of uncommitted transactions can be written to disk, even before
the transaction commits
Database Buffering (Cont.) Database Buffering (Cont.)
If a block with uncommitted updates is output to disk, log records with undo information for the updates are output to the log on stable storage first
(Write ahead logging)
No updates should be in progress on a block when it is output to disk.
Can be ensured as follows.
Before writing a data item, transaction acquires exclusive lock on block containing the data item
Lock can be released once the write is completed.
Such locks held for short duration are called latches.
To output a block to disk
1.
First acquire an exclusive latch on the block
1.
Ensures no update can be in progress on the block
2.
Then perform a log flush
3.
Then output the block to disk
4.
Finally release the latch on the block
Buffer Management (Cont.) Buffer Management (Cont.)
Database buffer can be implemented either
in an area of real main-memory reserved for the database, or
in virtual memory
Implementing buffer in reserved main-memory has drawbacks:
Memory is partitioned before-hand between database buffer and applications, limiting flexibility.
Needs may change, and although operating system knows best
how memory should be divided up at any time, it cannot change
the partitioning of memory.
Buffer Management (Cont.) Buffer Management (Cont.)
Database buffers are generally implemented in virtual memory in spite of some drawbacks:
When operating system needs to evict a page that has been modified, the page is written to swap space on disk.
When database decides to write buffer page to disk, buffer page may be in swap space, and may have to be read from swap space on disk and output to the database on disk, resulting in extra I/O!
Known as dual paging problem.
Ideally when OS needs to evict a page from the buffer, it should pass control to database, which in turn should
1.
Output the page to database instead of to swap space (making sure to output log records first), if it is modified
2.
Release the page from the buffer, for the OS to use
Dual paging can thus be avoided, but common operating systems
do not support such functionality.
Fuzzy Checkpointing Fuzzy Checkpointing
To avoid long interruption of normal processing during
checkpointing, allow updates to happen during checkpointing
Fuzzy checkpointing is done as follows:
1.
Temporarily stop all updates by transactions
2.
Write a <checkpoint L> log record and force log to stable storage
3.
Note list M of modified buffer blocks
4.
Now permit transactions to proceed with their actions
5.
Output to disk all modified buffer blocks in list M
blocks should not be updated while being output
Follow WAL: all log records pertaining to a block must be output before the block is output
6.
Store a pointer to the checkpoint record in a fixed position
last_checkpoint on disk
Fuzzy Checkpointing (Cont.) Fuzzy Checkpointing (Cont.)
When recovering using a fuzzy checkpoint, start scan from the checkpoint record pointed to by last_checkpoint
Log records before last_checkpoint have their updates reflected in database on disk, and need not be redone.
Incomplete checkpoints, where system had crashed while performing checkpoint, are handled safely
……
<checkpoint L>
…..
<checkpoint L>
…..
Log last_checkpoint
Failure with Loss of Nonvolatile Storage Failure with Loss of Nonvolatile Storage
So far we assumed no loss of non-volatile storage
Technique similar to checkpointing used to deal with loss of non- volatile storage
Periodically dump the entire content of the database to stable storage
No transaction may be active during the dump procedure; a procedure similar to checkpointing must take place
Output all log records currently residing in main memory onto stable storage.
Output all buffer blocks onto the disk.
Copy the contents of the database to stable storage.
Output a record <dump> to log on stable storage.
Recovering from Failure of Non-Volatile Storage Recovering from Failure of Non-Volatile Storage
To recover from disk failure
restore database from most recent dump.
Consult the log and redo all transactions that committed after the dump
Can be extended to allow transactions to be active during dump;
known as fuzzy dump or online dump
Similar to fuzzy checkpointing
Recovery with Early Lock Release Recovery with Early Lock Release
and Logical Undo
and Logical Undo
Recovery with Early Lock Release Recovery with Early Lock Release
Support for high-concurrency locking techniques, such as those used for B
+-tree concurrency control, which release locks early
Supports “logical undo”
Recovery based on “repeating history”, whereby recovery executes
exactly the same actions as normal processing
Logical Undo Logging Logical Undo Logging
Operations like B
+-tree insertions and deletions release locks early.
They cannot be undone by restoring old values (physical undo), since once a lock is released, other transactions may have updated the B
+-tree.
Instead, insertions (resp. deletions) are undone by executing a deletion (resp. insertion) operation (known as logical undo).
For such operations, undo log records should contain the undo operation to be executed
Such logging is called logical undo logging, in contrast to physical undo logging
Operations are called logical operations
Other examples:
delete of tuple, to undo insert of tuple
– allows early lock release on space allocation information
subtract amount deposited, to undo deposit
– allows early lock release on bank balance
Physical Redo Physical Redo
Redo information is logged physically (that is, new value for each write) even for operations with logical undo
Logical redo is very complicated since database state on disk may not be “operation consistent” when recovery starts
Physical redo logging does not conflict with early lock release
Operation Logging Operation Logging
Operation logging is done as follows:
1.
When operation starts, log <T
i, O
j, operation-begin>. Here O
jis a unique identifier of the operation instance.
2.
While operation is executing, normal log records with physical redo and physical undo information are logged.
3.
When operation completes, <T
i, O
j, operation-end, U> is logged, where U contains information needed to perform a logical undo information.
Example: insert of (key, record-id) pair (K5, RID7) into index I9
<T1, O1, operation-begin>
….
<T1, X, 10, K5>
<T1, Y, 45, RID7>
<T1, O1, operation-end, (delete I9, K5, RID7)>
Physical redo of steps in insert
Operation Logging (Cont.) Operation Logging (Cont.)
If crash/rollback occurs before operation completes:
the operation-end log record is not found, and
the physical undo information is used to undo operation.
If crash/rollback occurs after the operation completes:
the operation-end log record is found, and in this case
logical undo is performed using U; the physical undo information for the operation is ignored.
Redo of operation (after crash) still uses physical redo information.
Transaction Rollback with Logical Undo Transaction Rollback with Logical Undo
Rollback of transaction T
iis done as follows:
Scan the log backwards
1.
If a log record <T
i, X, V
1, V
2> is found, perform the undo and log a al
<T
i, X, V
1>.
2.
If a <T
i, O
j, operation-end, U> record is found
Rollback the operation logically using the undo information U.
– Updates performed during roll back are logged just like during normal operation execution.
– At the end of the operation rollback, instead of logging an operation-end record, generate a record
<T
i, O
j, operation-abort>.
Skip all preceding log records for T
iuntil the record
<T
i, O
joperation-begin> is found
Transaction Rollback with Logical Undo (Cont.) Transaction Rollback with Logical Undo (Cont.)
Transaction rollback, scanning the log backwards (cont.):
3.
If a redo-only record is found ignore it
4.
If a <T
i, O
j, operation-abort> record is found:
skip all preceding log records for T
iuntil the record
<T
i, O
j, operation-begin> is found.
5.
Stop the scan when the record <T
i, start> is found
6.
Add a <T
i, abort> record to the log Some points to note:
Cases 3 and 4 above can occur only if the database crashes while a transaction is being rolled back.
Skipping of log records as in case 4 is important to prevent multiple
rollback of the same operation.
Transaction Rollback with Logical Undo
Transaction rollback during normal operation
Failure Recovery with Logical Undo
Transaction Rollback: Another Example Transaction Rollback: Another Example
Example with a complete and an incomplete operation
<T1, start>
<T1, O1, operation-begin>
….
<T1, X, 10, K5>
<T1, Y, 45, RID7>
<T1, O1, operation-end, (delete I9, K5, RID7)>
<T1, O2, operation-begin>
<T1, Z, 45, 70>
T1 Rollback begins here
<T1, Z, 45> redo-only log record during physical undo (of incomplete O2)
<T1, Y, .., ..> Normal redo records for logical undo of O1 …
<T1, O1, operation-abort> What if crash occurred immediately after this?
Recovery Algorithm with Logical Undo Recovery Algorithm with Logical Undo
Basically same as earlier algorithm, except for changes described earlier for transaction rollback
1.
(Redo phase): Scan log forward from last < checkpoint L> record till end of log
1.
Repeat history by physically redoing all updates of all transactions,
2.
Create an undo-list during the scan as follows
undo-list is set to L initially
Whenever <T
istart> is found T
iis added to undo-list
Whenever <T
icommit> or <T
iabort> is found, T
iis deleted from undo-list
This brings database to state as of crash, with committed as well as uncommitted transactions having been redone.
Now undo-list contains transactions that are incomplete, that is,
have neither committed nor been fully rolled back.
Recovery with Logical Undo (Cont.) Recovery with Logical Undo (Cont.)
Recovery from system crash (cont.)
2.
(Undo phase): Scan log backwards, performing undo on log records of transactions found in undo-list.
Log records of transactions being rolled back are processed as described earlier, as they are found
Single shared scan for all transactions being undone
When <T
istart> is found for a transaction T
iin undo-list, write a
<T
iabort> log record.
Stop scan when <T
istart> records have been found for all T
iin undo-list
This undoes the effects of incomplete transactions (those with neither
commit nor abort log records). Recovery is now complete.
ARIES
ARIES Recovery Algorithm
ARIES ARIES
ARIES is a state of the art recovery method
Incorporates numerous optimizations to reduce overheads during normal processing and to speed up recovery
The recovery algorithm we studied earlier is modeled after ARIES, but greatly simplified by removing optimizations
Unlike the recovery algorithm described earlier, ARIES
1.
Uses log sequence number (LSN) to identify log records
Stores LSNs in pages to identify what updates have already been applied to a database page
2.
Physiological redo
3.
Dirty page table to avoid unnecessary redos during recovery
4.
Fuzzy checkpointing that only records information about dirty pages, and does not require dirty pages to be written out at checkpoint time
More coming up on each of the above …
ARIES Optimizations ARIES Optimizations
Physiological redo
Affected page is physically identified, action within page can be logical
Used to reduce logging overheads
– e.g. when a record is deleted and all other records have to be moved to fill hole
»
Physiological redo can log just the record deletion
»
Physical redo would require logging of old and new values for much of the page
Requires page to be output to disk atomically
– Easy to achieve with hardware RAID, also supported by some disk systems
– Incomplete page output can be detected by checksum techniques,
»
But extra actions are required for recovery
»
Treated as a media failure
ARIES Data Structures ARIES Data Structures
ARIES uses several data structures
Log sequence number (LSN) identifies each log record
Must be sequentially increasing
Typically an offset from beginning of log file to allow fast access – Easily extended to handle multiple log files
Page LSN
Log records of several different types
Dirty page table
ARIES Data Structures: Page LSN ARIES Data Structures: Page LSN
Each page contains a PageLSN which is the LSN of the last log record whose effects are reflected on the page
To update a page:
X-latch the page, and write the log record
Update the page
Record the LSN of the log record in PageLSN
Unlock page
To flush page to disk, must first S-latch page
Thus page state on disk is operation consistent – Required to support physiological redo
PageLSN is used during recovery to prevent repeated redo
Thus ensuring idempotence
ARIES Data Structures: Log Record ARIES Data Structures: Log Record
Each log record contains LSN of previous log record of the same transaction
LSN in log record may be implicit
Special redo-only log record called compensation log record (CLR) used to log actions taken during recovery that never need to be undone
Serves the role of operation-abort log records used in earlier recovery algorithm
Has a field UndoNextLSN to note next (earlier) record to be undone
Records in between would have already been undone
Required to avoid repeated undo of already undone actions
LSN TransID PrevLSN RedoInfo UndoInfo
LSN TransID UndoNextLSN RedoInfo
1 2 3 4 4' 3' 2' 1'
ARIES Data Structures: DirtyPage Table ARIES Data Structures: DirtyPage Table
DirtyPageTable
List of pages in the buffer that have been updated
Contains, for each such page
PageLSN of the page
RecLSN is an LSN such that log records before this LSN have already been applied to the page version on disk
– Set to current end of log when a page is inserted into dirty page table (just before being updated)
– Recorded in checkpoints, helps to minimize redo work
ARIES Data Structures
ARIES Data Structures: Checkpoint Log ARIES Data Structures: Checkpoint Log
Checkpoint log record
Contains:
DirtyPageTable and list of active transactions
For each active transaction, LastLSN, the LSN of the last log record written by the transaction
Fixed position on disk notes LSN of last completed checkpoint log record
Dirty pages are not written out at checkpoint time
Instead, they are flushed out continuously, in the background
Checkpoint is thus very low overhead
can be done frequently
ARIES Recovery Algorithm ARIES Recovery Algorithm
ARIES recovery involves three passes
Analysis pass: Determines
Which transactions to undo
Which pages were dirty (disk version not up to date) at time of crash
RedoLSN: LSN from which redo should start
Redo pass:
Repeats history, redoing all actions from RedoLSN
RecLSN and PageLSNs are used to avoid redoing actions already reflected on page
Undo pass:
Rolls back all incomplete transactions
Transactions whose abort was complete earlier are not undone – Key idea: no need to undo these transactions: earlier undo
actions were logged, and are redone as required
Aries Recovery: 3 Passes Aries Recovery: 3 Passes
Analysis, redo and undo passes
Analysis determines where redo should start
Undo has to go back till start of earliest incomplete transaction
Last checkpoint
Log
Time End of Log
Analysis pass Redo pass
Undo pass
ARIES Recovery: Analysis ARIES Recovery: Analysis
Analysis pass
Starts from last complete checkpoint log record
Reads DirtyPageTable from log record
Sets RedoLSN = min of RecLSNs of all pages in DirtyPageTable
In case no pages are dirty, RedoLSN = checkpoint record’s LSN
Sets undo-list = list of transactions in checkpoint log record
Reads LSN of last log record for each transaction in undo-list from checkpoint log record
Scans forward from checkpoint
.. Cont. on next page …
ARIES Recovery: Analysis (Cont.) ARIES Recovery: Analysis (Cont.)
Analysis pass (cont.)
Scans forward from checkpoint
If any log record found for transaction not in undo-list, adds transaction to undo-list
Whenever an update log record is found
If page is not in DirtyPageTable, it is added with RecLSN set to LSN of the update log record
If transaction end log record found, delete transaction from undo-list
Keeps track of last log record for each transaction in undo-list
May be needed for later undo
At end of analysis pass:
RedoLSN determines where to start redo pass
RecLSN for each page in DirtyPageTable used to minimize redo work
All transactions in undo-list need to be rolled back
ARIES Redo Pass ARIES Redo Pass
Redo Pass: Repeats history by replaying every action not already reflected in the page on disk, as follows:
Scans forward from RedoLSN. Whenever an update log record is found:
1.
If the page is not in DirtyPageTable or the LSN of the log record is less than the RecLSN of the page in DirtyPageTable, then skip the log record
2.
Otherwise fetch the page from disk. If the PageLSN of the page fetched from disk is less than the LSN of the log record, redo the log record
NOTE: if either test is negative the effects of the log record have
already appeared on the page. First test avoids even fetching the
page from disk!
ARIES Undo Actions ARIES Undo Actions
When an undo is performed for an update log record
Generate a CLR containing the undo action performed (actions performed during undo are logged physicaly or physiologically).
CLR for record n noted as n’ in figure below
Set UndoNextLSN of the CLR to the PrevLSN value of the update log record
Arrows indicate UndoNextLSN value
ARIES supports partial rollback
Used e.g. to handle deadlocks by rolling back just enough to release reqd. locks
Figure indicates forward actions after partial rollbacks
records 3 and 4 initially, later 5 and 6, then full rollback
1 2 3 4 4' 3' 5 6 6' 5' 2' 1'
ARIES: Undo Pass ARIES: Undo Pass
Undo pass:
Performs backward scan on log undoing all transaction in undo-list
Backward scan optimized by skipping unneeded log records as follows:
Next LSN to be undone for each transaction set to LSN of last log record for transaction found by analysis pass.
At each step pick largest of these LSNs to undo, skip back to it and undo it
After undoing a log record
– For ordinary log records, set next LSN to be undone for transaction to PrevLSN noted in the log record
– For compensation log records (CLRs) set next LSN to be undo to UndoNextLSN noted in the log record
»
All intervening records are skipped since they would have been undone already
Undos performed as described earlier
Recovery Actions in ARIES
Other ARIES Features Other ARIES Features
Recovery Independence
Pages can be recovered independently of others
E.g. if some disk pages fail they can be recovered from a backup while other pages are being used
Savepoints:
Transactions can record savepoints and roll back to a savepoint
Useful for complex transactions
Also used to rollback just enough to release locks on deadlock
Other ARIES Features (Cont.) Other ARIES Features (Cont.)
Fine-grained locking:
Index concurrency algorithms that permit tuple level locking on indices can be used
These require logical undo, rather than physical undo, as in earlier recovery algorithm
Recovery optimizations: For example:
Dirty page table can be used to prefetch pages during redo
Out of order redo is possible:
redo can be postponed on a page being fetched from disk, and
performed when page is fetched.
Meanwhile other log records can continue to be processed
Remote Backup Systems
Remote Backup Systems
Remote Backup Systems Remote Backup Systems
Remote backup systems provide high availability by allowing transaction
processing to continue even if the primary site is destroyed.
Remote Backup Systems (Cont.) Remote Backup Systems (Cont.)
Detection of failure: Backup site must detect when primary site has failed
to distinguish primary site failure from link failure maintain several communication links between the primary and the remote backup.
Heart-beat messages
Transfer of control:
To take over control backup site first perform recovery using its copy of the database and all the long records it has received from the
primary.
Thus, completed transactions are redone and incomplete transactions are rolled back.
When the backup site takes over processing it becomes the new primary
To transfer control back to old primary when it recovers, old primary
must receive redo logs from the old backup and apply all updates
locally.
Remote Backup Systems (Cont.) Remote Backup Systems (Cont.)
Time to recover: To reduce delay in takeover, backup site periodically proceses the redo log records (in effect, performing recovery from
previous database state), performs a checkpoint, and can then delete earlier parts of the log.
Hot-Spare configuration permits very fast takeover:
Backup continually processes redo log record as they arrive, applying the updates locally.
When failure of the primary is detected the backup rolls back
incomplete transactions, and is ready to process new transactions.
Alternative to remote backup: distributed database with replicated data
Remote backup is faster and cheaper, but less tolerant to failure
more on this in Chapter 19
Remote Backup Systems (Cont.) Remote Backup Systems (Cont.)
Ensure durability of updates by delaying transaction commit until update is logged at backup; avoid this delay by permitting lower degrees of durability.
One-safe: commit as soon as transaction’s commit log record is written at primary
Problem: updates may not arrive at backup before it takes over.
Two-very-safe: commit when transaction’s commit log record is written at primary and backup
Reduces availability since transactions cannot commit if either site fails.
Two-safe: proceed as in two-very-safe if both primary and backup are active. If only the primary is active, the transaction commits as soon as is commit log record is written at the primary.
