Chapter 17: Recovery System

Chapter 17: Recovery System

اسلاید 1: Chapter 17: Recovery System

اسلاید 2: Chapter 17: Recovery SystemFailure ClassificationStorage StructureRecovery and AtomicityLog-Based RecoveryShadow PagingRecovery With Concurrent TransactionsBuffer ManagementFailure with Loss of Nonvolatile StorageAdvanced Recovery TechniquesARIES Recovery AlgorithmRemote Backup Systems

اسلاید 3: Failure ClassificationTransaction failure :Logical errors: transaction cannot complete due to some internal error conditionSystem 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 by system crashDatabase 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 storageDestruction is assumed to be detectable: disk drives use checksums to detect failures

اسلاید 4: Recovery AlgorithmsRecovery algorithms are techniques to ensure database consistency and transaction atomicity and durability despite failuresFocus of this chapterRecovery algorithms have two partsActions taken during normal transaction processing to ensure enough information exists to recover from failuresActions taken after a failure to recover the database contents to a state that ensures atomicity, consistency and durability

اسلاید 5: Storage StructureVolatile storage:does not survive system crashesexamples: main memory, cache memoryNonvolatile storage:survives system crashesexamples: disk, tape, flash memory, non-volatile (battery backed up) RAM Stable storage:a mythical form of storage that survives all failuresapproximated by maintaining multiple copies on distinct nonvolatile media

اسلاید 6: Stable-Storage ImplementationMaintain multiple copies of each block on separate diskscopies 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 inSuccessful completionPartial failure: destination block has incorrect informationTotal failure: destination block was never updatedProtecting storage media from failure during data transfer (one solution):Execute output operation as follows (assuming two copies of each block):Write the information onto the first physical block.When the first write successfully completes, write the same information onto the second physical block.The output is completed only after the second write successfully completes.

اسلاید 7: 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:First find inconsistent blocks:Expensive solution: Compare the two copies of every disk block.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 systemsIf 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.

اسلاید 8: Data AccessPhysical blocks are those blocks residing on the disk. 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.Each transaction Ti has its private work-area in which local copies of all data items accessed and updated by it are kept. Tis local copy of a data item X is called xi.We assume, for simplicity, that each data item fits in, and is stored inside, a single block.

اسلاید 9: Data Access (Cont.)Transaction transfers data items between system buffer blocks and its private work-area using the following operations :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.both these commands may necessitate the issue of an input(BX) instruction before the assignment, if the block BX in which X resides is not already in memory.Transactions Perform read(X) while accessing X for the first time; All subsequent accesses are to the local copy. After last access, transaction executes write(X).output(BX) need not immediately follow write(X). System can perform the output operation when it deems fit.

اسلاید 10: Example of Data AccessxYABx1y1 bufferBuffer Block A Buffer Block Binput(A)output(B) read(X)write(Y)diskwork areaof T1work areaof T2 memoryx2

اسلاید 11: Recovery and AtomicityModifying the database without ensuring that the transaction will commit may leave the database in an inconsistent state.Consider transaction Ti that transfers $50 from account A to account B; goal is either to perform all database modifications made by Ti or none at all. Several output operations may be required for Ti (to output A and B). A failure may occur after one of these modifications have been made but before all of them are made.

اسلاید 12: Recovery and Atomicity (Cont.)To ensure atomicity despite failures, we first output information describing the modifications to stable storage without modifying the database itself.We study two approaches:log-based recovery, andshadow-pagingWe assume (initially) that transactions run serially, that is, one after the other.

اسلاید 13: Log-Based RecoveryA log is kept on stable storage. The log is a sequence of log records, and maintains a record of update activities on the database.When transaction Ti starts, it registers itself by writing a <Ti start>log recordBefore Ti executes write(X), a log record <Ti, X, V1, V2> is written, where V1 is the value of X before the write, and V2 is the value to be written to X.Log record notes that Ti has performed a write on data item Xj Xj had value V1 before the write, and will have value V2 after the write. When Ti finishes it last statement, the log record <Ti commit> is written. We assume for now that log records are written directly to stable storage (that is, they are not buffered)Two approaches using logsDeferred database modificationImmediate database modification

اسلاید 14: Deferred Database ModificationThe deferred database modification scheme records all modifications to the log, but defers all the writes to after partial commit.Assume that transactions execute seriallyTransaction starts by writing <Ti start> record to log. A write(X) operation results in a log record <Ti, X, V> being written, where V is the new value for XNote: old value is not needed for this schemeThe write is not performed on X at this time, but is deferred.When Ti partially commits, <Ti commit> is written to the log Finally, the log records are read and used to actually execute the previously deferred writes.

اسلاید 15: Deferred Database Modification (Cont.)During recovery after a crash, a transaction needs to be redone if and only if both <Ti start> and<Ti commit> are there in the log.Redoing a transaction Ti ( redoTi) sets the value of all data items updated by the transaction to the new values.Crashes can occur while the transaction is executing the original updates, or while recovery action is being takenexample transactions T0 and T1 (T0 executes before T1):T0: read (A)T1 : read (C)A: - A - 50 C:-C- 100Write (A) write (C)read (B)B:- B + 50write (B)

اسلاید 16: Deferred Database Modification (Cont.)Below we show the log as it appears at three instances of time.If log on stable storage at time of crash is as in case:(a) No redo actions need to be taken(b) redo(T0) must be performed since <T0 commit> is present (c) redo(T0) must be performed followed by redo(T1) since <T0 commit> and <Ti commit> are present

اسلاید 17: Immediate Database ModificationThe immediate database modification scheme allows database updates of an uncommitted transaction to be made as the writes are issuedsince undoing may be needed, update logs must have both old value and new valueUpdate log record must be written before database item is writtenWe assume that the log record is output directly to stable storageCan be extended to postpone log record output, so long as prior to execution of an output(B) operation for a data block B, all log records corresponding to items B must be flushed to stable storageOutput of updated blocks can take place at any time before or after transaction commitOrder in which blocks are output can be different from the order in which they are written.

اسلاید 18: Immediate Database Modification ExampleLog Write Output<T0 start><T0, A, 1000, 950>To, B, 2000, 2050 A = 950 B = 2050<T0 commit><T1 start><T1, C, 700, 600> C = 600 BB, BC<T1 commit> BANote: BX denotes block containing X.x1

اسلاید 19: Immediate Database Modification (Cont.)Recovery procedure has two operations instead of one: undo(Ti) restores the value of all data items updated by Ti to their old values, going backwards from the last log record for Tiredo(Ti) sets the value of all data items updated by Ti to the new values, going forward from the first log record for TiBoth operations must be idempotentThat is, even if the operation is executed multiple times the effect is the same as if it is executed onceNeeded since operations may get re-executed during recovery When recovering after failure:Transaction Ti needs to be undone if the log contains the record <Ti start>, but does not contain the record <Ti commit>.Transaction Ti needs to be redone if the log contains both the record <Ti start> and the record <Ti commit>.Undo operations are performed first, then redo operations.

اسلاید 20: Immediate DB 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 (T0): B is restored to 2000 and A to 1000.(b) undo (T1) and redo (T0): C is restored to 700, and then A and B are set to 950 and 2050 respectively.(c) redo (T0) and redo (T1): A and B are set to 950 and 2050 respectively. Then C is set to 600

اسلاید 21: CheckpointsProblems in recovery procedure as discussed earlier :searching the entire log is time-consumingwe might unnecessarily redo transactions which have alreadyoutput their updates to the database.Streamline recovery procedure by periodically performing checkpointing Output all log records currently residing in main memory onto stable storage.Output all modified buffer blocks to the disk.Write a log record < checkpoint> onto stable storage.

اسلاید 22: Checkpoints (Cont.)During recovery we need to consider only the most recent transaction Ti that started before the checkpoint, and transactions that started after Ti. Scan backwards from end of log to find the most recent <checkpoint> record Continue scanning backwards till a record <Ti start> is found. Need only consider the part of log following above start record. Earlier part of log can be ignored during recovery, and can be erased whenever desired.For all transactions (starting from Ti or later) with no <Ti commit>, execute undo(Ti). (Done only in case of immediate modification.)Scanning forward in the log, for all transactions starting from Ti or later with a <Ti commit>, execute redo(Ti).

اسلاید 23: Example of CheckpointsT1 can be ignored (updates already output to disk due to checkpoint)T2 and T3 redone.T4 undoneTcTfT1T2T3T4checkpointsystem failure

اسلاید 24: Shadow PagingShadow paging is an alternative to log-based recovery; this scheme is useful if transactions execute seriallyIdea: maintain two page tables during the lifetime of a transaction –the current page table, and the shadow page tableStore the shadow page table in nonvolatile storage, such that state of the database prior to transaction execution may be recovered. Shadow page table is never modified during executionTo start with, both the page tables are identical. Only current page table is used for data item accesses during execution of the transaction.Whenever any page is about to be written for the first timeA copy of this page is made onto an unused page. The current page table is then made to point to the copyThe update is performed on the copy

اسلاید 25: Sample Page Table

اسلاید 26: Example of Shadow PagingShadow and current page tables after write to page 4

اسلاید 27: Shadow Paging (Cont.)To commit a transaction : 1. Flush all modified pages in main memory to disk 2. Output current page table to disk 3. Make the current page table the new shadow page table, as follows:keep a pointer to the shadow page table at a fixed (known) location on disk.to make the current page table the new shadow page table, simply update the pointer to point to current page table on diskOnce pointer to shadow page table has been written, transaction is committed.No recovery is needed after a crash — new transactions can start right away, using the shadow page table.Pages not pointed to from current/shadow page table should be freed (garbage collected).

اسلاید 28: Show Paging (Cont.)Advantages of shadow-paging over log-based schemesno overhead of writing log recordsrecovery is trivialDisadvantages :Copying the entire page table is very expensiveCan be reduced by using a page table structured like a B+-treeNo need to copy entire tree, only need to copy paths in the tree that lead to updated leaf nodesCommit overhead is high even with above extensionNeed to flush every updated page, and page tableData gets fragmented (related pages get separated on disk)After every transaction completion, the database pages containing old versions of modified data need to be garbage collected Hard to extend algorithm to allow transactions to run concurrentlyEasier to extend log based schemes

اسلاید 29: Recovery With Concurrent TransactionsWe modify the log-based recovery schemes to allow multiple transactions to execute concurrently.All transactions share a single disk buffer and a single logA buffer block can have data items updated by one or more transactionsWe assume concurrency control using strict two-phase locking;i.e. the updates of uncommitted transactions should not be visible to other transactionsOtherwise how to perform undo if T1 updates A, then T2 updates A and commits, and finally T1 has to abort?Logging is done as described earlier. Log records of different transactions may be interspersed in the log.The checkpointing technique and actions taken on recovery have to be changedsince several transactions may be active when a checkpoint is performed.

اسلاید 30: Recovery With Concurrent Transactions (Cont.)Checkpoints are performed as before, except that the checkpoint log record is now of the form < checkpoint L> where L is the list of transactions active at the time of the checkpointWe assume no updates are in progress while the checkpoint is carried out (will relax this later)When the system recovers from a crash, it first does the following:Initialize undo-list and redo-list to emptyScan the log backwards from the end, stopping when the first <checkpoint L> record is found. For each record found during the backward scan:if the record is <Ti commit>, add Ti to redo-listif the record is <Ti start>, then if Ti is not in redo-list, add Ti to undo-listFor every Ti in L, if Ti is not in redo-list, add Ti to undo-list

اسلاید 31: Recovery With Concurrent Transactions (Cont.)At this point undo-list consists of incomplete transactions which must be undone, and redo-list consists of finished transactions that must be redone.Recovery now continues as follows:Scan log backwards from most recent record, stopping when <Ti start> records have been encountered for every Ti in undo-list.During the scan, perform undo for each log record that belongs to a transaction in undo-list.Locate the most recent <checkpoint L> record.Scan log forwards from the <checkpoint L> record till the end of the log.During the scan, perform redo for each log record that belongs to a transaction on redo-list

اسلاید 32: Example of RecoveryGo over the steps of the recovery algorithm on the following log:<T0 start><T0, A, 0, 10><T0 commit><T1 start><T1, B, 0, 10><T2 start> /* Scan in Step 4 stops here */<T2, C, 0, 10><T2, C, 10, 20><checkpoint {T1, T2}><T3 start><T3, A, 10, 20><T3, D, 0, 10><T3 commit>

اسلاید 33: Log Record BufferingLog 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.

اسلاید 34: 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 Ti enters the commit state only when the log record <Ti commit> 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 ruleStrictly speaking WAL only requires undo information to be output

اسلاید 35: Database BufferingDatabase maintains an in-memory buffer of data blocksWhen a new block is needed, if buffer is full an existing block needs to be removed from bufferIf the block chosen for removal has been updated, it must be output to diskAs a result of the write-ahead logging rule, 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.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 itemLock can be released once the write is completed. Such locks held for short duration are called latches.Before a block is output to disk, the system acquires an exclusive latch on the blockEnsures no update can be in progress on the block

اسلاید 36: Buffer Management (Cont.)Database buffer can be implemented eitherin an area of real main-memory reserved for the database, orin virtual memoryImplementing 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.

اسلاید 37: 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, to make space for another page, 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 swapping out a database buffer page, operating system should pass control to database, which in turn outputs page to database instead of to swap space (making sure to output log records first)Dual paging can thus be avoided, but common operating systems do not support such functionality.

اسلاید 38: Failure with Loss of Nonvolatile StorageSo far we assumed no loss of non-volatile storageTechnique similar to checkpointing used to deal with loss of non-volatile storagePeriodically dump the entire content of the database to stable storageNo transaction may be active during the dump procedure; a procedure similar to checkpointing must take placeOutput 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.To recover from disk failurerestore database from most recent dump. Consult the log and redo all transactions that committed after the dumpCan be extended to allow transactions to be active during dump; known as fuzzy dump or online dumpWill study fuzzy checkpointing later

اسلاید 39: Advanced Recovery Algorithm

اسلاید 40: Advanced Recovery TechniquesSupport high-concurrency locking techniques, such as those used for B+-tree concurrency controlOperations 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 called logical undo logging, in contrast to physical undo logging.Redo information is logged physically (that is, new value for each write) even for such operationsLogical redo is very complicated since database state on disk may not be “operation consistent”

اسلاید 41: Advanced Recovery Techniques (Cont.)Operation logging is done as follows:When operation starts, log <Ti, Oj, operation-begin>. Here Oj is a unique identifier of the operation instance.While operation is executing, normal log records with physical redo and physical undo information are logged. When operation completes, <Ti, Oj, operation-end, U> is logged, where U contains information needed to perform a logical undo information.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 caselogical undo is performed using U; the physical undo information for the operation is ignored.Redo of operation (after crash) still uses physical redo information.

اسلاید 42: Advanced Recovery Techniques (Cont.)Rollback of transaction Ti is done as follows: Scan the log backwards If a log record <Ti, X, V1, V2> is found, perform the undo and log a special redo-only log record <Ti, X, V1>.If a <Ti, Oj, operation-end, U> record is foundRollback 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 <Ti, Oj, operation-abort>.Skip all preceding log records for Ti until the record <Ti, Oj operation-begin> is found

اسلاید 43: Advanced Recovery Techniques (Cont.)Scan the log backwards (cont.):If a redo-only record is found ignore itIf a <Ti, Oj, operation-abort> record is found:skip all preceding log records for Ti until the record <Ti, Oj, operation-begin> is found.Stop the scan when the record <Ti, start> is foundAdd a <Ti, abort> record to the logSome 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.

اسلاید 44: Advanced Recovery Techniques(Cont,)The following actions are taken when recovering from system crashScan log forward from last < checkpoint L> recordRepeat history by physically redoing all updates of all transactions, Create an undo-list during the scan as followsundo-list is set to L initiallyWhenever <Ti start> is found Ti is added to undo-listWhenever <Ti commit> or <Ti abort> is found, Ti is deleted from undo-listThis 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.

اسلاید 45: Advanced Recovery Techniques (Cont.)Recovery from system crash (cont.)Scan log backwards, performing undo on log records of transactions found in undo-list. Transactions are rolled back as described earlier.When <Ti start> is found for a transaction Ti in undo-list, write a <Ti abort> log record.Stop scan when <Ti start> records have been found for all Ti in undo-listThis undoes the effects of incomplete transactions (those with neither commit nor abort log records). Recovery is now complete.

اسلاید 46: Advanced Recovery Techniques (Cont.)Checkpointing is done as follows:Output all log records in memory to stable storageOutput to disk all modified buffer blocksOutput to log on stable storage a < checkpoint L> record. Transactions are not allowed to perform any actions while checkpointing is in progress.Fuzzy checkpointing allows transactions to progress while the most time consuming parts of checkpointing are in progressPerformed as described on next slide

اسلاید 47: Advanced Recovery Techniques (Cont.)Fuzzy checkpointing is done as follows:Temporarily stop all updates by transactionsWrite a <checkpoint L> log record and force log to stable storageNote list M of modified buffer blocksNow permit transactions to proceed with their actionsOutput to disk all modified buffer blocks in list Mblocks should not be updated while being outputFollow WAL: all log records pertaining to a block must be output before the block is outputStore a pointer to the checkpoint record in a fixed position last_checkpoint on diskWhen recovering using a fuzzy checkpoint, start scan from the checkpoint record pointed to by last_checkpointLog 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

اسلاید 48: ARIES Recovery Algorithm

اسلاید 49: ARIESARIES is a state of the art recovery method Incorporates numerous optimizations to reduce overheads during normal processing and to speed up recovery The “advanced recovery algorithm” we studied earlier is modeled after ARIES, but greatly simplified by removing optimizationsUnlike the advanced recovery algorithm, ARIES Uses log sequence number (LSN) to identify log recordsStores LSNs in pages to identify what updates have already been applied to a database pagePhysiological redoDirty page table to avoid unnecessary redos during recoveryFuzzy checkpointing that only records information about dirty pages, and does not require dirty pages to be written out at checkpoint timeMore coming up on each of the above …

اسلاید 50: ARIES OptimizationsPhysiological redoAffected page is physically identified, action within page can be logicalUsed to reduce logging overheads e.g. when a record is deleted and all other records have to be moved to fill holePhysiological redo can log just the record deletion Physical redo would require logging of old and new values for much of the pageRequires page to be output to disk atomicallyEasy to achieve with hardware RAID, also supported by some disk systemsIncomplete page output can be detected by checksum techniques, But extra actions are required for recovery Treated as a media failure

اسلاید 51: ARIES Data StructuresLog sequence number (LSN) identifies each log recordMust be sequentially increasingTypically an offset from beginning of log file to allow fast accessEasily extended to handle multiple log filesEach page contains a PageLSN which is the LSN of the last log record whose effects are reflected on the pageTo update a page:X-latch the pag, and write the log record Update the pageRecord the LSN of the log record in PageLSNUnlock pagePage flush to disk S-latches pageThus page state on disk is operation consistentRequired to support physiological redoPageLSN is used during recovery to prevent repeated redo Thus ensuring idempotence

اسلاید 52: ARIES Data Structures (Cont.)Each log record contains LSN of previous log record of the same transaction LSN in log record may be implicitSpecial redo-only log record called compensation log record (CLR) used to log actions taken during recovery that never need to be undoneAlso serve the role of operation-abort log records used in advanced recovery algorithmHave a field UndoNextLSN to note next (earlier) record to be undoneRecords in between would have already been undoneRequired to avoid repeated undo of already undone actionsLSN TransId PrevLSN RedoInfo UndoInfoLSN TransID UndoNextLSN RedoInfo

اسلاید 53: ARIES Data Structures (Cont.)DirtyPageTableList of pages in the buffer that have been updatedContains, for each such pagePageLSN of the pageRecLSN is an LSN such that log records before this LSN have already been applied to the page version on diskSet 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 workCheckpoint log recordContains: DirtyPageTable and list of active transactionsFor each active transaction, LastLSN, the LSN of the last log record written by the transactionFixed position on disk notes LSN of last completed checkpoint log record

اسلاید 54: ARIES Recovery AlgorithmARIES recovery involves three passesAnalysis pass: DeterminesWhich transactions to undoWhich pages were dirty (disk version not up to date) at time of crashRedoLSN: LSN from which redo should startRedo 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 transactionsTransactions whose abort was complete earlier are not undoneKey idea: no need to undo these transactions: earlier undo actions were logged, and are redone as required

اسلاید 55: ARIES Recovery: AnalysisAnalysis passStarts from last complete checkpoint log recordReads in DirtyPageTable from log recordSets RedoLSN = min of RecLSNs of all pages in DirtyPageTableIn case no pages are dirty, RedoLSN = checkpoint record’s LSNSets undo-list = list of transactions in checkpoint log recordReads LSN of last log record for each transaction in undo-list from checkpoint log recordScans forward from checkpoint.. On next page …

اسلاید 56: ARIES Recovery: Analysis (Cont.)Analysis pass (cont.)Scans forward from checkpointIf any log record found for transaction not in undo-list, adds transaction to undo-listWhenever an update log record is foundIf page is not in DirtyPageTable, it is added with RecLSN set to LSN of the update log recordIf transaction end log record found, delete transaction from undo-listKeeps track of last log record for each transaction in undo-listMay be needed for later undoAt end of analysis pass:RedoLSN determines where to start redo passRecLSN for each page in DirtyPageTable used to minimize redo workAll transactions in undo-list need to be rolled back

اسلاید 57: ARIES Redo PassRedo 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: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 recordOtherwise 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 recordNOTE: 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!

اسلاید 58: ARIES Undo ActionsWhen an undo is performed for an update log recordGenerate 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 belowSet UndoNextLSN of the CLR to the PrevLSN value of the update log recordArrows indicate UndoNextLSN valueARIES supports partial rollbackUsed e.g. to handle deadlocks by rolling back just enough to release reqd. locksFigure indicates forward actions after partial rollbacks records 3 and 4 initially, later 5 and 6, then full rollback123443565216

اسلاید 59: ARIES: Undo PassUndo pass Performs backward scan on log undoing all transaction in undo-listBackward 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 recordFor ordinary log records, set next LSN to be undone for transaction to PrevLSN noted in the log recordFor compensation log records (CLRs) set next LSN to be undo to UndoNextLSN noted in the log recordAll intervening records are skipped since they would have been undo alreadyUndos performed as described earlier

اسلاید 60: Other ARIES FeaturesRecovery IndependencePages can be recovered independently of othersE.g. if some disk pages fail they can be recovered from a backup while other pages are being usedSavepoints:Transactions can record savepoints and roll back to a savepointUseful for complex transactionsAlso used to rollback just enough to release locks on deadlock

اسلاید 61: Other ARIES Features (Cont.)Fine-grained locking:Index concurrency algorithms that permit tuple level locking on indices can be usedThese require logical undo, rather than physical undo, as in advanced recovery algorithmRecovery optimizations: For example:Dirty page table can be used to prefetch pages during redoOut 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

اسلاید 62: Remote Backup Systems

اسلاید 63: Remote Backup SystemsRemote backup systems provide high availability by allowing transaction processing to continue even if the primary site is destroyed.

اسلاید 64: 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.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 primaryTo transfer control back to old primary when it recovers, old primary must receive redo logs from the old backup and apply all updates locally.

اسلاید 65: 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 dataRemote backup is faster and cheaper, but less tolerant to failure more on this in Chapter 19

اسلاید 66: 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 primaryProblem: 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 backupReduces 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. Better availability than two-very-safe; avoids problem of lost transactions in one-safe.

اسلاید 67: End of Chapter

اسلاید 68: Block Storage Operations

اسلاید 69: Portion of the Database Log Corresponding to T0 and T1

اسلاید 70: State of the Log and Database Corresponding to T0 and T1

اسلاید 71: Portion of the System Log Corresponding to T0 and T1

اسلاید 72: State of System Log and Database Corresponding to T0 and T1