Download presentation
Presentation is loading. Please wait.
Published byNancy Strothers Modified over 9 years ago
1
4/16/20151 PSU’s CS 587 16. Concurrency Control and Recovery (only for DBs with updates…..!)- Review Concurrency Control Transaction ACID Isolation Schedules Guaranteeing isolation Serializability Serializability ⇔ Isolation Locking Strict Two Phase Locking Strict 2PL ⇒ Serializable
2
4/16/20152 PSU’s CS 587 Learning Objectives Define ACID, schedule, isolated, equivalent, serializable, S2PL, conflict serializable, precedence graph, recoverable. Know the implications on slide 25 and when the converses hold Explain lock management, multiple granularity locks, phantoms, locking in BTrees, optimistic concurrency control
3
4/16/20153 PSU’s CS 587 Example Transaction Transfer $100 from A to B Read A; Verify A; Write A-100; then Read B; Verify B; Write B+100 Are all 6 steps necessary? Which steps require disc access? When can an abort occur without damage? Write is as in a program’s write What damage can an abort cause? How can you avoid such damage?
4
4/16/20154 PSU’s CS 587 Transaction (cont.) User (application developer) must indicate: Begin transaction read/write/modify statements intermixed with other programming language statements plus either commit - indicates successful completion or abort - indicates program wants to roll back (erase the transaction) All or nothing! (Atomic)
5
4/16/20155 PSU’s CS 587 ACID Supporting the ACID Properties of Transactions A A tomicity: All actions in a transaction happen in their entirety or not at all. C C onsistency: If the DB starts in a consistent state, (this notion is defined by the user; some of it may be enforced by integrity constraints) and if a transaction executes with no other queries active, then the DB ends up in a consistent state. I I solation: Each transaction is isolated from other transactions. The effect on the DB is as if each transaction executed by itself. D D urability: If a transaction commits, its changes to the database state persist. Recovery System Recovery System Concurrency Control System Programmers
6
4/16/20156 PSU’s CS 587 Isolation/Concurrency Control T1:BEGIN A+=100, B-=100 END T2:BEGIN A=1.06*A, B=1.06*B END What is each of these transactions doing? A schedule of T1 and T2 is an interleaving of the steps of these transactions so that each transaction’s order is preserved.
7
4/16/20157 PSU’s CS 587 Which of these is a Schedule of T1 and T2? T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: B=1.06*B, A=1.06*A T1: A+=100, B-=100 T2: A=1.06*A,B=1.06*B
8
4/16/20158 PSU’s CS 587 Isolated Schedules A schedule is isolated if its effect on the DB is as if each transaction executed by itself, serially. Which of the schedules on the next page is isolated? Hint: Calculate the effect of the schedule on a sample state of the DB, for example A has $1,000, B has $500. This won’t tell you the effect on all states, but it’s helpful information.
9
4/16/20159 PSU’s CS 587 Which Schedules are Isolated? T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B Goal of Concurrency Control subsystem: Guarantee only isolated schedules. T1: A+=100, B-=100 T2: A=1.06*A,B=1.06*B T1: A+=100,B-=100 T2: A=1.06*A, B=1.06*B
10
4/16/201510 PSU’s CS 587 Equivalent Schedules Two schedules are equivalent if given any starting DB state, they produce the same result. Which of these schedules is equivalent? T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A,B=1.06*B
11
4/16/201511 PSU’s CS 587 Serializable Schedules A schedule is serializable if it is equivalent to a serial schedule. Which of these schedules is serializable? T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A, B=1.06*B T1: A+=100, B-=100 T2: A=1.06*A,B=1.06*B
12
4/16/201512 PSU’s CS 587 The goal of Concurrency Control Recall the goal of concurrency control: To ensure that all schedules are isolated Theorem: A schedule is Serializable ⇔ it is Isolated ⇒: Serializable ⇒ equivalent to some serial schedule, and in a serial schedule, each Xact. is isolated ⇐: If each xact runs alone, the schedule must be serial But serializability is hard to verify How can we, in real time, check each schedule? So the Concurrency Control Subsystem needs more work.
13
4/16/201513 PSU’s CS 587 Locking Transaction must get a lock – before it can read or update data There are two kinds of locks: shared (S) locks and exclusive (X) locks To read a record you MUST get an S lock To modify or delete a record you MUST get an X lock Lock info maintained by a “lock manager”
14
4/16/201514 PSU’s CS 587 How Locks Work If a Xact has an S lock on a data object, new transactions can get S locks on that object, but not X locks. If a Xact has an X lock, no other Xact can get any lock (S or X) on that data object. If a transaction can’t get a lock, it waits (in a queue). -- SX S X ok ok no no ok ok no Lock compatibility lock on data item lock you want
15
4/16/201515 PSU’s CS 587 Strict Two Phase Locking Protocol (S2PL) Strict 2PL is a way of managing locks during a transaction A Xact gets (S and X) locks gradually, as needed The Xact holds all locks until end of transaction (commit/abort) time # of locks held by a transaction T All locks are released at the end, upon commit or abort 0 2 1 4 3 5
16
4/16/201516 PSU’s CS 587 Strict 2PL guarantees serializability Idea of the Proof: a Strict 2PL schedule is equivalent to the serial schedule in which each transaction runs instantaneously at the time that it commits This is huge: A property of each transaction (S2PL) implies a property of any set of transactions (serializability) No need to check serializability of any schedules Real DBMSs use S2PL to enforce serializability In reality, users can and do choose lower levels of concurrency for all but the most sensitive transactions
17
4/16/201517 PSU’s CS 587 17. Concurrency Control Conflicts Conflicting Actions Conflict Equivalent Conflict Serializable Conf. Ser. ⇒ Serializable Precedence Graph Conf. Serializable ⇔ Precedence graph is acyclic Strict 2PL ⇒ Recoverable 2PL ¬ ⇒ Recoverable Locks Management Deadlocks Waits-for Multiple Granularity Phantoms Predicate, Index locking Locking in B+ Trees Optimistic CC Inefficiency of locking Optimistic CC idea
18
4/16/201518 PSU’s CS 587 17.1 Conflict Serializable Schedules Conflicting actions: Actions that access the same data and at least one of which is a write Note that changing the order of these two actions might yield different results. Two schedules are conflict equivalent if: They involve the same actions of the same transactions in the same order Every pair of conflicting actions is ordered the same way Schedule S is conflict serializable if S is conflict equivalent to some serial schedule 17. CC
19
4/16/201519 PSU’s CS 587 Which are conflict serializable? T1: R(A), W(A) T2: R(A), W (A), R(B) T1: R(B), W(A), W(B) T2: R(A), W (A), R(B) T1: R(A), W(A) T2: W(A) T3: W(A) 17. CC T1: R(A),W(A), R(B),W(B) T2: R(A),W(A), R(B),W(B)
20
4/16/201520 PSU’s CS 587 Conflict Serializable ⇒ Serializable If two actions do not conflict, then commuting them results in an equivalent schedule. Suppose S is conflict serializable. Then there is a sequence of commuting actions I = {I 1,…,I n } so that a)Each of the I i commutes nonconflicting actions b)I applied to S is a serial schedule Because of (a), I does not change the state of any database. Thus S, and I applied to S, are equivalent and I applied to S is serial (b), so S is serializable.
21
4/16/201521 PSU’s CS 587 Serializable does NOT imply Conflict Serializable Equivalent to what serial schedule? Therefore it is a serializable schedule Why is it not conflict serializable? (for now just give an intuitive reason, later we will have a proof) T1: R(A), W(A) T2: W(A) T3: W(A)
22
4/16/201522 PSU’s CS 587 Precedence graphs Why is this graph not conflict serializable? The cycle in the graph illustrates the problem. T1 must precede T2, and T2 must precede T1, in any conflict equivalent serial schedule. T1: R(A), W(A), R(B), W(B) T2: R(A), W(A), R(B), W(B) T1T2 A B Precedence graph 17. CC
23
4/16/201523 PSU’s CS 587 Precedence Graph Precedence graph : One node per Xact; edge from Ti to Tj if an action of Ti precedes and conflicts with an action of Tj. Theorem: Schedule is conflict serializable if and only if its precedence graph is acyclic ⇒ If there is a cycle in the graph, it cannot be serializable (see previous page & generalize) ⇐ If the graph is acyclic, the schedule is equivalent to a topologically sorted order of the actions. 17. CC
24
4/16/201524 PSU’s CS 587 Example of acyclic graph Is this graph acyclic? What is a topological sort of it? Is a schedule, for which this is a precedence graph, equivalent to a serial schedule? Can we move all actions of T4 to occur before T2, without reversing conflicting actions? How about T1 before T4? T1T2 T4T3
25
4/16/201525 PSU’s CS 587 Summary Each Xact in a schedule is Isolated Isolated Xact: same results as if it ran alone The schedule is Serializable Serializable Schedule: Same result as a serial schedule The schedule is Conflict Serializable Conflict Serializable : Conflict Equivalent to a Serializable Schedule The Schedule’s Precedence Graph is Acyclic The schedule is consistent with Strict 2PL. Strict 2PL: There is a locking schedule where all locks are held until EOT Deadlock is possible Deadlock: There is a cycle in the Waitsfor graph.
26
4/16/201526 PSU’s CS 587 Strict 2PL ⇒ Recoverable A schedule is recoverable if, during it, all transactions commit only after all transactions whose data they have read commit. Why is recoverability desirable? Otherwise, T1 may read the data of T2 ( a so-called dirty read ), then T1 commit, then T2 abort and roll back. Then T1 has read a value that does not exist.
27
4/16/201527 PSU’s CS 587 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. 2PL implies that all schedules have acyclic precedence graphs, so are serializable. However, they are not recoverable, so Strict 2PL is used in practice. 17. CC
28
4/16/201528 PSU’s CS 587 Lock Management Lock and unlock requests are handled by the lock manager Lock table entry: IDs of transactions currently holding a lock Type of lock held (shared or exclusive) Pointer to queue of lock requests If there is an S lock on an object O and T1 requests an X lock, what happens? What if then T2 requests an S lock? Locking and unlocking have to be atomic operations How is this enforced? Lock upgrade: transaction that holds a shared lock can be upgraded to hold an exclusive lock if no one else has a shared lock. 17. CC
29
4/16/201529 PSU’s CS 587 New Lock Type of lock? Queue empty? S EnQ lock? NY Grant S lock N Type of lock? Y S EnQ X lock? X Grant X lock N EnQ Y Managing a new lock (simplified)
30
4/16/201530 PSU’s CS 587 Managing a lock release (simplified) Release Lock Other locks? Y Exit N DeQ xact from Q, give it a lock What type of lock was it? Exit X Is there an S lock on top of the Q? Y S N
31
4/16/201531 PSU’s CS 587 Deadlocks Deadlock: Cycle of transactions waiting for locks to be released by each other. Two ways of dealing with deadlocks: Deadlock prevention Deadlock detection 17. CC
32
4/16/201532 PSU’s CS 587 Deadlock Prevention Theory Assign priorities based on timestamps. Older transactions get higher priority. Assume Ti wants a lock that Tj holds. Two policies are possible: Wait-Die: It Ti has higher priority, Ti waits for Tj; otherwise Ti aborts Wound-wait: If Ti has higher priority, Tj aborts; otherwise Ti waits If a transaction re-starts, make sure it has its original timestamp Practice: http://dev.mysql.com/doc/refman/5.0/en/innodb- deadlocks.html http://dev.mysql.com/doc/refman/5.0/en/innodb- deadlocks.html 17. CC
33
4/16/201533 PSU’s CS 587 Deadlock Detection Create a waits-for graph: Nodes are transactions There is an edge from Ti to Tj if Ti is waiting for Tj to release a lock Periodically check for cycles in the waits-for graph Note that waits-for graph is opposite direction of precedence graph. 17. CC
34
4/16/201534 PSU’s CS 587 Deadlock Detection (Continued) Example: T1: S(A), R(A), S(B) T2: X(B),W(B) X(C) T3: S(C), R(C) X(A) T4: X(B) T1T2 T4T3 T1T2 T4T3 17. CC
35
4/16/201535 PSU’s CS 587 Multiple-Granularity Locks Hard to decide what granularity to lock (tuples vs. pages vs. tables). Shouldn’t have to decide! Data “containers” are nested: Tuples Tables Pages Database contains 17. CC
36
4/16/201536 PSU’s CS 587 Solution: New Lock Modes, Protocol Allow Xacts to lock at each level, but with a special protocol using new “intention” locks: v Before locking an item, Xact must set “intention locks” on all its ancestors. v IX(IS): Intend to X(S) lock a subset. v SIX: S & IX at the same time. Used to scan and update selected records. -- ISIX -- IS IX SX S X 17. CC
37
4/16/201537 PSU’s CS 587 Multiple Granularity Lock Protocol Each Xact starts from the root of the hierarchy. To get S or IS lock on a node, must hold IS or IX on parent node. To get X or IX or SIX on a node, must hold IX or SIX on parent node. Must release locks in bottom-up order. Sometimes hard to decide granularity of locks. Can start small and use lock escalation. 17. CC
38
4/16/201538 PSU’s CS 587 Examples T1 scans R, and updates a few tuples: T1 gets an SIX lock on R, then repeatedly gets an S lock on tuples of R, and occasionally upgrades to X on the tuples. T2 uses an index to read only part of R: T2 gets an IS lock on R, and repeatedly gets an S lock on tuples of R. T3 reads all of R: T3 gets an S lock on R. OR, T3 could behave like T2; can use lock escalation to decide which. -- ISIX -- IS IX SX S X 17. CC
39
4/16/201539 PSU’s CS 587 Dynamic Databases: Phantoms If we allow updates, even Strict 2PL will not assure serializability: T1 finds oldest sailor in each rank T2 inserts(Rohi,1,27) and deletes John Schedule is This schedule is Strict 2PL, but not serializable! Result of this schedule is (1,Pehr)(2,Lorr) Result of T1;T2 is (1,Pehr)(2,John) Result of T2;T1 is (1,Rohi)(2,Lorr) 17. CC NameRankAge Pehr125 John226 Lorr223 T1 rank 1 T1 rank 2 T2 inserts Rohi, deletes John
40
4/16/201540 PSU’s CS 587 The Problem When T1 retrieved the oldest sailor of rank 1, it locked each sailor of rank 1 with a read lock. None of these locks applied to the new record (a phantom) inserted by T2. We need a mechanism to prevent phantoms; to allow T1 to lock present and future sailors with rank 1. There are two such mechanisms, index locking and predicate locking. 17. CC
41
4/16/201541 PSU’s CS 587 Index Locking If there is a dense index on the rating field using Alternative (2), T1 should lock the index page(s) containing the data entries with rating = 1. If there are no records with rating = 1, T1 must lock the index page where such a data entry would be, if it existed! If there is no suitable index, T1 must lock all pages, and lock the file/table to prevent new pages from being added, to ensure that no new records with rating = 1 are added. r=1 Data Index
42
4/16/201542 PSU’s CS 587 Predicate Locking Grant lock on all records that satisfy some logical predicate, e.g. age > 2*salary. Index locking is a special case of predicate locking for which an index supports efficient implementation of the predicate lock. What is the predicate in the sailor example? In general, predicate locking has a lot of locking overhead. 17. CC
43
4/16/201543 PSU’s CS 587 Locking in B+ Trees How can we efficiently lock a B+ tree? Btw, don’t confuse this with multiple granularity locking! One solution: Ignore the tree structure, just lock pages while traversing the tree, following 2PL. This has terrible performance! Root node (and many higher level nodes) become bottlenecks because every tree access begins at the root. This single threads all updates to the tree. 17. CC
44
4/16/201544 PSU’s CS 587 Two Useful Observations Higher levels of the tree only direct searches for leaf pages. For inserts/deletes, a node on a path from root to modified leaf must be locked (in X mode, of course), only if a split can propagate up to it from the modified leaf. We can exploit these observations to design efficient locking protocols that guarantee serializability even though they violate 2PL. 17. CC
45
4/16/201545 PSU’s CS 587 A Tree Locking Algorithm Search: Start at root and go down; repeatedly, S lock child then unlock parent. Insert/Delete: Start at root and go down, obtaining X locks as needed. Once child is locked, check if it is safe: If child is safe, release all locks on ancestors. Safe node: Node such that the change will not propagate up beyond this node. Inserts: Node is not full. Deletes: Node is not half-empty. 17. CC
46
4/16/201546 PSU’s CS 587 Example ROOT A B C DE F G H I 35 20* 3844 22*23*24*35*36*38*41*44* Do: 1) Search 38* 2) Delete 38* 3) Insert 45* 4) Insert 25* 23 20 35 23 35 38 44
47
4/16/201547 PSU’s CS 587 Optimistic CC (Kung-Robinson) Locking is a conservative approach in which conflicts are prevented. Disadvantages: Lock management overhead. Deadlock detection/resolution. Lock contention for heavily used objects. If conflicts are rare, we might be able to gain concurrency by not locking, and instead checking for conflicts before Xacts commit. A version of this optimistic approach is used by PostgreSQL and Oracle 17. CC
48
4/16/201548 PSU’s CS 587 Kung-Robinson Model Xacts have three phases: READ: Xacts read from the database, but make changes to private copies of objects. VALIDATE: Check for conflicts. WRITE: Make local copies of changes public. ROOT old new modified objects 17. CC
49
4/16/201549 PSU’s CS 587 Validation Each Xact is assigned a numeric id. Just use a timestamp. Xact ids assigned at end of READ phase, just before validation begins. ReadSet(Ti): Set of objects read by Xact Ti. WriteSet(Ti): Set of objects modified by Ti. 17. CC
50
4/16/201550 PSU’s CS 587 Test 1 For all i and j such that TSi < TSj, check that Ti completes before Tj begins. Ti Tj RVW RVW 17. CC
51
4/16/201551 PSU’s CS 587 Test 2 For all i and j such that Ti < Tj, check that: Ti completes before Tj begins its Write phase + WriteSet(Ti) ReadSet(Tj) is empty. Ti Tj RVW RVW Does Tj read dirty data? Does Ti overwrite Tj’s writes? 17. CC
52
4/16/201552 PSU’s CS 587 Test 3 For all i and j such that Ti < Tj, check that: Ti completes Read phase before Tj does + WriteSet(Ti) ReadSet(Tj) is empty + WriteSet(Ti) WriteSet(Tj) is empty. Tj Ti RVW RVW Does Tj read dirty data? Does Ti overwrite Tj’s writes? 17. CC
53
4/16/201553 PSU’s CS 587 Overheads in Optimistic CC Must record read/write activity in ReadSet and WriteSet per Xact. Must create and destroy these sets as needed. Must check for conflicts during validation, and must make validated writes ``global’’. Critical section can reduce concurrency. Scheme for making writes global can reduce clustering of objects. Optimistic CC restarts Xacts that fail validation. Work done so far is wasted; requires clean-up. 17. CC
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.