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Crash Recovery

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  1. Crash Recovery

  2. Review: The ACID properties • Atomicity: All actions in the Xaction happen, or none happen. • Consistency: If each Xaction is consistent, and the DB starts consistent, it ends up consistent. • Isolation: Execution of one Xaction is isolated from that of other Xacts. • D urability: If a Xaction commits, its effects persist. • CC guarantees Isolation and Atomicity. • The Recovery Manager guarantees Atomicity & Durability.

  3. Transaction failure : Logical errors: application errors (e.g. div by 0, segmentation fault) System errors: deadlocks System crash: hardware/software failure causes the system to crash. Disk failure: head crash or similar disk failure destroys all or part of disk storage Why is recovery system necessary? • The data we will lose can be in main memory or in disk

  4. 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 Stable storage: a “mythical” form of storage that survives all failures approximated by maintaining multiple copies on distinct nonvolatile media Storage Media

  5. Recovery and Durability • To achieve Durability: Put data on stable storage • To approximate stable storage make two copies of data • Problem: data transfer failure

  6. Solution: Write to the first disk Write to the second disk when the first disk completes The process is complete only after the second write completes successfully Recovery (from disk failures, etc): Detect bad blocks with the checksum (e.g. parity) Two good copies, equal blocks: done One good, one bad : copy good to bad Two bad copies: ignore write Two good, unequal blocks? Stable-Storage Implementation • Ans: Copy the second to the first

  7. Recovery and Atomicity • Durability is achieved by making 2 copies of data • What about atomicity… • Crash may cause inconsistencies…

  8. Example: transfer $50 from account A to account B goal is either to perform all database modifications made by Tior none at all. Requires several inputs (reads) and outputs (writes) Failure after output to account A and before output to B…. DB is corrupted! Recovery and Atomicity

  9. Recovery Algorithms • Recovery algorithms are techniques to ensure database consistency and transaction atomicity and durability despite failures • Recovery algorithms have two parts • Actions taken during normal transaction processing to ensure enough information exists to recover from failures • Actions taken after a failure to recover the database contents to a state that ensures atomicity, consistency and durability

  10. Physical blocks: blocks on disk. Buffer blocks: blocks in main memory. Data transfer: 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 Tihas its private work-area in which local copies of all data items accessed and updated by it are kept. Ti's local copy of a data item X is called xi. Background: Data Access Assumption: each data item fits in and is stored inside, a single block.

  11. 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 xito 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. Data Access (Cont.)

  12. buffer input(A) Buffer Block A X A Buffer Block B Y output(B) B read(X) write(Y) disk x2 x1 y1 work area of T2 work area of T1 memory

  13. Recovery and Atomicity (Cont.) • To ensure atomicity, first output information about modifications to stable storage without modifying the database itself. • We study : • log-based recovery • Database Files storing the actual data • Log • Another file storing the actions of transactions

  14. Simplifying assumptions: Transactions run serially logs are written directly on the stable stogare Log: a sequence of log records; maintains a record of update activities on the database. (Write Ahead Log, W.A.L.) Log records for transaction Tj: <Tistart > <Ti, X, V1, V2> <Ticommit > Two approaches using logs Deferred database modification Immediate database modification Log-Based Recovery

  15. Log example Log <T1, start> <T1, A, 1000, 950> <T1, B, 2000, 2050> <T1, commit> Transaction T1 Read(A) A =A-50 Write(A) Read(B) B = B+50 Write(B)

  16. Write the modifications to a log And Defer execution of write operations till database commits Example Ti starts: write a <Tistart> record to log. Tiwrite(X) write <Ti, X, V> to log: V is the new value for X The write is deferred Note: old value is not needed for this scheme Tipartially commits: Write <Ticommit> to the log DB updates by reading and executing the log: <Tistart> …… <Ticommit> Deferred Database Modification

  17. How to use the log for recovery after a crash? Redo: if both <Tistart> and <Ti commit> are there in the log. Ignore otherwise. Crashes can occur while the transaction is executing the original updates, or while recovery action is being taken REDO should be idempotent (i.e., executing several times should be the same as once) example transactions T0and T1(T0executes before T1): T0: read (A) T1: read (C) A: - A - 50C:- C- 100 Write (A) write (C) read (B) B:- B + 50 write (B) Deferred Database Modification

  18. Below we show the log as it appears at three instances of time. Deferred Database Modification (Cont.) <T0, start> <T0, A, 950> <T0, B, 2050> <T0, commit> <T1, start> <T1, C, 600> (b) <T0, start> <T0, A, 950> <T0, B, 2050> (a) <T0, start> <T0, A, 950> <T0, B, 2050> <T0, commit> <T1, start> <T1, C, 600> <T1, commit> (c) - Only new values of an item are recorded in the log (old values can be omitted). - At partial commit time, after the log records are on stable storage, the items are written to the database.

  19. Allow database modifications to be OUTPUT to the database before transaction commits. Tighter logging rules are needed to ensure transaction are undoable Write records must be of the form: <Ti, X, Vold, Vnew > Both old and new values Log record must be written before database item is written/output Output of DB items can occur: Before or after commit In any order But Log record should be written prior to Output of an item to database Immediate Database Modification

  20. Log Database <T0start> <T0, A, 1000, 950> <To, B, 2000, 2050> A = 950 B = 2050 <T0commit> <T1start> <T1, C, 700, 600> C = 600 <T1commit> Immediate Database Modification Example

  21. Recovery procedure : Undo : <Ti, start > is in the log but <Ticommit> is not. Undo: restore the value of all data items updated by Ti to their old values, going backwards from the last log record for Ti Redo: <Tistart> and <Ticommit> are both in the log. Redo: sets the value of all data items updated by Tito the new values, going forward from the first log record for Ti Both operations must be idempotent: even if the operation is executed multiple times the effect is the same as if it is executed once Undo operations are performed first, then redo operations. Why? Immediate Database Modification (Cont.)

  22. I M Recovery Example <T0, start> <T0, A, 1000, 950> <T0, B, 2000, 2050> <T0, commit> <T1, start> <T1, C, 700, 600> <T1, commit> (c) <T0, start> <T0, A, 1000, 950> <T0, B, 2000, 2050> <T0, commit> <T1, start> <T1, C, 700, 600> (b) <T0, start> <T0, A, 1000, 950> <T0, B, 2000, 2050> (a) 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

  23. Problems in recovery procedure as discussed earlier : searching the entire log is time-consuming we might unnecessarily redo transactions which have already output their updates to the database. How to avoid redundant redoes? Put marks in the log indicating that at that point DB and log are consistent. Checkpoint! Checkpoints

  24. Checkpoints • At a checkpoint: • 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.

  25. Recovering from log with checkpoints: 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. Why? After that, recover from log with the rules that we had before. Checkpoints (Cont.)

  26. Example of Checkpoints Tc Tf T1 T2 T3 T4 checkpoint system failure checkpoint • T1 can be ignored (updates already output to disk due to checkpoint) • T2 and T3 redone. • T4 undone

  27. To permit concurrency: All transactions share a single disk buffer and a single log Concurrency control: Strict 2PL :i.e. Release eXclusive locks only after commit. Why? Logging is done as described earlier. The checkpointing technique and actions taken on recovery have to be changed (based on ARIES) since several transactions may be active when a checkpoint is performed. Recovery With Concurrent Transactions

  28. Checkpoints for concurrent transactions: < checkpointL>L: the list of transactions active at the time of the checkpoint We assume no updates are in progress while the checkpoint is carried out Recovery for concurrent transactions, 3 phases Analysis: Construction of Undo, Redo-Lists Perform Undo Perform Redo Recovery With Concurrent Transactions (Cont.)

  29. 1. ANALYSIS: Construction of Undo, Redo-lists a. Initialize undo-list and redo-list to empty b. Scan the log backwards from the end, stopping when the first <checkpointL> record is found. For each record found during the backward scan: if the record is <Ticommit>, add Tito redo-list if the record is <Ti start>, then if Ti is not in redo-list, add Ti to undo-list c. For every Ti in L, if Ti is not in redo-list, add Tito undo-list  This will add txns to undo-list that started prior to L but did not commit Recovery With Concurrent Transactions (Cont.) ANALYSIS

  30. Perform UNDO: Scan log backwards Perform undo(T) for every transaction in undo-list Stop when reach <T, start> for every T in undo-list. Perform REDO: Locate the most recent <checkpoint L> record. Scan log forwards from the <checkpoint L> record till the end of the log. perform redo for each log record that belongs to a transaction on redo-list Recovery With Concurrent Transactions UNDO REDO

  31. Go over the steps of the recovery algorithm on the following log: <T0start> <T0, A, 0, 10> <T0commit> <T1start> <T1, B, 0, 10> <T2start> <T2, C, 0, 10> <T2, C, 10, 20> <checkpoint {T1, T2}> <T3start> <T3, A, 10, 20> <T3, D, 0, 10> <T3commit> <T4, start> Example of Recovery Redo-list{T3} Undo-list{T4, T1, T2} Undo: Set C to 10 Set C to 0 Set B to 0 Redo: Set A to 20 Set D to 10 DB A B C D Initial 0 0 0 0 At crash 20 10 20 10 After rec. 20 0 0 10

  32. Recovery Summary • Durability • Duplicate copies • Ensuring Atomicity • Deferred Logging --- Only Redo • Immediate Logging -- Undo and Redo • Checkpoints : to limit log size • Recovery of concurrent txns with checkpoints • 3 phases

  33. What we covered • Relational model - SQL • Formal & commercial query languages • Functional Dependencies • Normalization • Interfacing with Databases: PL/SQL, JDBC… Physical Design • File storage • Indexing • Query Processing and Optimization • Txns • Concurrency Control • Recovery