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What is 2pl ink droplet?
Printing upto 4800 dpi it use only 2 pikolitre ink
Explain the strict two-phase locking protocal in dbms?
The strict two-phase locking (S2PL) class of schedules is the intersection of the 2PL class with the class of schedules possessing the Strictness property. To comply with the S2PL protocol a transaction needs to comply with 2PL, and release its write (exclusive) locks only after it has ended, i.e., being either committed or aborted. On the other hand, read (shared) locks are released regularly during phase 2. Implementing general S2PL requires explicit support of phase-1 end, separate from transaction end, and no such widely utilized product implementation is known. S2PL is a special case of 2PL, i.e., the S2PL class is a proper subclass of 2PL
What is the surface area formula for a pyramid?
one half of the perimeter of the base times the slant height plus the area of the base or: 1/2Pl + B
How to find the surface area of a triangular based pyramid?
Surface area of any pyramid is 1/2Pl + B; where P=perimeter of the base, l=slant height and B= Area of the base.
What is two phase locking and how does it guarantee serializabilityin dbms?
Two-phase locking (2PL) is a concurrency control protocol used in database management systems to ensure that transactions are executed in a serializable manner. It operates in two phases: the growing phase, where a transaction can acquire locks but cannot release them, and the shrinking phase, where it can release locks but cannot acquire new ones. This locking mechanism prevents conflicts between transactions and ensures that the final result is the same as if the transactions were executed serially. By adhering to this protocol, 2PL guarantees that the interleaving of transactions does not lead to anomalies, thus preserving the integrity of the database.
What is the postal address of Prestwick Airport?
The postal address of Prestwick Aiport is, Shaw Rd Ayr, South Ayrshire KA9 2PL, United Kingdom. The phone number is +44 871 223 0700. Prestwick Airport serves the greater Glasgow area.
What is 2 phase locking potocol?
A transaction that follows the 2PL protocol can be divided in to 2 phases. * Expanding phase-new lock on items can acquire but NONE can be released * shrinking phase-existing locks can be released but no new locks can acquire 2 Phase Lock may limit the amount of concurrency that can occur in a schedule.
Difference between 2-phase locking and 2-phase commit?
2PC and 2PL are protocols used in conjunction with distributed databases. Both together are The two phase lock protocol (2PL) deals uniquely with the fact how are locks are acquired during a transaction whereas the two phase commit (2PC) protocol deals with the fact how do multiple hosts decide wether one specific transaction is written (commited) or not (abort). 2PL sais that first there is a phase where locks are (during a transaction) acquired (growth phase) and then there is a phase where the locks are beeing removed (shrinking phase). Once the shrinking phase started no more locks can be acquired during this transaction. The shrinking phase usually takes place after an abort or a commit phase in a typical database system. The essence of 2PC is that after a transaction is complete and should be commited a vote starts. Each node which is part of the transaction is asked to "prepare to commit". The node will then check wether a local commit is possible and if yes it votes with "ready to commit" (RTC) [Important: changes are not beeing written to the database at that point]. Once a node signaled RTC the system must be kept in a state where the transaction is allways commitable. If all nodes signal RTC the transaction the transaction master signals them a commit. If one of the nodes does not signal RTC the transaction master will signal abort to all local transactions.
How long does it take to drive from MA to PA?
Mapquest list the drive as followsTotal Est. Time: 7 hours, 23 minutesTotal Est. Distance: 435.57 mileshttp://www.mapquest.com/directions/main.adp?go=1&do=nw&rmm=1&un=m&cl=EN&ct=NA&rsres=1&1ffi=&1l=&1g=&1pl=&1v=&1n=&2ffi=&2l=&2g=&2pl=&2v=&2n=&1pn=&1a=&1c=&1s=MA&1z=&2pn=&2a=&2c=&2s=PA&2z=&r=f
How long does it take to drive from Bristol to Chester?
It takes 17 hours
8 Explain concurrency control issues in real time systems?
• Concurrency control is the problem of synchronizing concurrent transactions (i.e., order the operations of concurrent transactions) such that the following two propertiesare achieved: - the consistency of the DB is maintained - the maximum degree of concurrency of operations is achieved • Obviously, the serial execution of a set of transaction achieves consistency, if each single transaction is consistent Conflicts • Conflicting operations: Two operations Oij (x) and Okl(x) of transactions Ti and Tk are in conflict iff at least one of the operations is a write, i.e., - Oij = read(x) and Okl = write(x) - Oij = write(x) and Okl = read(x) - Oij = write(x) and Okl = write(x) • Intuitively, a conflict between two operations indicates that their order of execution is important. • Read operations do not conflict with each other, hence the ordering of read operations does not matter. • Example: Consider the following two transactions T1: Read(x) x ← x + 1 Write(x) Commit T2: Read(x) x ← x + 1 Write(x) Commit - To preserve DB consistency, it is important that the read(x) of one transaction is not between read(x) and write(x) of the other transaction. Schedules • A schedule (history) specifies a possibly interleaved order of execution of the operations O of a set of transactions T = {T1, T2, . . . , Tn}, where Ti is specified by a partial order (Σi , ≺i). A schedule can be specified as a partial order over O, where - ΣT =Sn i=1 Σi - ≺T ⊇ Sn i=1 ≺I - For any two conflicting operations Oij , Okl ∈ ΣT , either Oij ≺T Okl or Okl ≺T Oij • A schedule is serial if all transactions in T are executed serially. • Example: Consider the following two transactions T1: Read(x) x ← x + 1 Write(x) Commit T2: Read(x) x ← x + 1 Write(x) Commit - The two serial schedules are S1 = {Σ1, ≺1} and S2 = {Σ2, ≺2}, where Σ1 = Σ2 = {R1(x), W1(x), C1, R2(x), W2(x), C2} ≺1= {(R1, W1),(R1, C1),(W1, C1),(R2, W2),(R2, C2),(W2, C2), (C1, R2), . . . } ≺2= {(R1, W1),(R1, C1),(W1, C1),(R2, W2),(R2, C2),(W2, C2), (C2, R1), . . . } • We will also use the following notation: - {T1, T2} = {R1(x), W1(x), C1, R2(x), W2(x), C2} - {T2, T1} = {R2(x), W2(x), C2, R1(x), W1(x), C1} Serializability • Two schedules are said to be equivalent if they have the same effect on the DB. • Conflict equivalence: Two schedules S1 and S2 defined over the same set of transactions T = {T1, T2, . . . , Tn} are said to be conflict equivalent if for each pair of conflicting operations Oij and Okl , whenever Oij <1 Okl then Oij <2 Okl. - i.e., conflicting operations must be executed in the same order in both transactions. • A concurrent schedule is said to be (conflict-)serializable iff it is conflict equivalent to a serial schedule • A conflict-serializable schedule can be transformed into a serial schedule by swapping non-conflicting operations • Example: Consider the following two schedules T1: Read(x) x ← x + 1 Write(x) Write(z) Commit T2: Read(x) x ← x + 1 Write(x) Commit - The schedule {R1(x), W1(x), R2(x), W2(x), W1(z), C2, C1} is conflict-equivalent to {T1, T2} but not to {T2, T1} Concurrency Control Algorithms • Taxonomy of concurrency control algorithms - Pessimistic methods assume that many transactions will conflict, thus the concurrent execution of transactions is synchronized early in their execution life cycle ∗ Two-Phase Locking (2PL) · Centralized (primary site) 2PL · Primary copy 2PL · Distributed 2PL ∗ Timestamp Ordering (TO) · Basic TO · Multiversion TO · Conservative TO ∗ Hybrid algorithms - Optimistic methods assume that not too many transactions will conflict, thus delay the synchronization of transactions until their termination ∗ Locking-based ∗ Timestamp ordering-based DDB 2008/09 J. Gamper Page 10Locking Based Algorithms • Locking-based concurrency algorithms ensure that data items shared by conflicting operations are accessed in a mutually exclusive way. This is accomplished by associating a "lock" with each such data item. • Two types of locks (lock modes) - read lock (rl) - also called shared lock - write lock (wl) - also called exclusive lock • Compatibility matrix of locks rli(x) wli(x) rlj (x) compatible not compatible wlj (x) not compatible not compatible • General locking algorithm 1. Before using a data item x, transaction requests lock for x from the lock manager 2. If x is already locked and the existing lock is incompatible with the requested lock, the transaction is delayed 3. Otherwise, the lock is granted Locking Based Algorithms • Example: Consider the following two transactions T1: Read(x) x ← x + 1 Write(x) Read(y) y ← y − 1 Write(y) T2: Read(x) x ← x ∗ 2 Write(x) Read(y) y ← y ∗ 2 Write(y) - The following schedule is a valid locking-based schedule (lri(x) indicates the release of a lock on x): S = {wl1(x), R1(x), W1(x), lr1(x) wl2(x), R2(x), W2(x), lr2(x) wl2(y), R2(y), W2(y), lr2(y) wl1(y), R1(y), W1(y), lr1(y)} - However, S is not serializable ∗ S cannot be transformed into a serial schedule by using only non-conflicting swaps ∗ The result is different from the result of any serial execution Two-Phase Locking (2PL) • Two-phase locking protocol - Each transaction is executed in two phases ∗ Growing phase: the transaction obtains locks ∗ Shrinking phase: the transaction releases locks - The lock point is the moment when transitioning from the growing phase to the shrinking phase Two-Phase Locking (2PL) . . . • Properties of the 2PL protocol - Generates conflict-serializable schedules - But schedules may cause cascading aborts ∗ If a transaction aborts after it releases a lock, it may cause other transactions that have accessed the unlocked data item to abort as well • Strict 2PL locking protocol - Holds the locks till the end of the transaction - Cascading aborts are avoided DDB 2008/09 J. Gamper Page 14Two-Phase Locking (2PL) . . . • Example: The schedule S of the previous example is not valid in the 2PL protocol: S = {wl1(x), R1(x), W1(x), lr1(x) wl2(x), R2(x), W2(x), lr2(x) wl2(y), R2(y), W2(y), lr2(y) wl1(y), R1(y), W1(y), lr1(y)} - e.g., after lr1(x) (in line 1) transaction T1 cannot request the lock wl1(y) (in line 4). - Valid schedule in the 2PL protocol S = {wl1(x), R1(x), W1(x), wl1(y), R1(y), W1(y), lr1(x), lr1(y) wl2(x), R2(x), W2(x), wl2(y), R2(y), W2(y), lr2(x), lr2(y)} Timestamp Ordering . . . • Basic timestamp ordering is "aggressive": It tries to execute an operation as soon as it receives it • Conservative timestamp ordering delays each operation until there is an assurance that it will not be restarted, i.e., that no other transaction with a smaller timestamp can arrive - For this, the operations of each transaction are buffered until an ordering can be established so that rejections are not possible • If this condition can be guaranteed, the scheduler will never reject an operation • However, this delay introduces the possibility for deadlocks • Multiversion timestamp ordering - Write operations do not modify the DB; instead, a new version of the data item is created: x1, x2, . . . , xn - Ri(x) is always successful and is performed on the appropriate version of x, i.e., the version of x (say xv) such that wts(xv) is the largest timestamp less than ts(Ti) - Wi(x) produces a new version xw with ts(xw) = ts(Ti) if the scheduler has not yet processed any Rj (xr) on a version xr such that ts(Ti) < rts(xr) i.e., the write is too late. - Otherwise, the write is rejected. • The previous concurrency control algorithms are pessimistic • Optimistic concurrency control algorithms - Delay the validation phase until just before the write phase - Ti run independently at each site on local copies of the DB (without updating the DB) - Validation test then checks whether the updates would maintain the DB consistent: ∗ If yes, all updates are performed ∗ If one fails, all Ti 's are rejected • Potentially allow for a higher level of concurrency Deadlock Management • Deadlock: A set of transactions is in a deadlock situation if several transactions wait for each other. A deadlock requires an outside intervention to take place. • Any locking-based concurrency control algorithm may result in a deadlock, since there is mutual exclusive access to data items and transactions may wait for a lock • Some TO-based algorihtms that require the waiting of transactions may also cause deadlocks • A Wait-for Graph (WFG) is a useful tool to identify deadlocks - The nodes represent transactions - An edge from Ti to Tj indicates that Ti is waiting for Tj - If the WFG has a cycle, we have a deadlock situation • Deadlock management in a DDBMS is more complicate, since lock management is not centralized • We might have global deadlock, which involves transactions running at different sites • A Local Wait-for-Graph (LWFG) may not show the existence of global deadlocks • A Global Wait-for Graph (GWFG), which is the union of all LWFGs, is needed Deadlock Prevention • Deadlock prevention: Guarantee that deadlocks never occur - Check transaction when it is initiated, and start it only if all required resources are available. - All resources which may be needed by a transaction must be predeclared • Advantages - No transaction rollback or restart is involved - Requires no run-time support • Disadvantages - Reduced concurrency due to pre-allocation - Evaluating whether an allocation is safe leads to added overhead - Difficult to determine in advance the required resources Conclusion • Concurrency orders the operations of transactions such that two properties are achieved: (i) the database is always in a consistent state and (ii) the maximum concurrency of operations is achieved • A schedule is some order of the operations of the given transactions. If a set of transactions is executed one after the other, we have a serial schedule. • There are two main groups of serializable concurrency control algorithms: locking based and timestamp based • A transaction is deadlocked if two or more transactions are waiting for each other. A Wait-for graph (WFG) is used to identify deadlocks • Centralized, distributed, and hierarchical schemas can be used to identify deadlocks
Give an example where strict 2 phase locking is followed but the resulting schedule leads to deadlock Explain why the 2PL being followed here is strict and explain why there is deadlock?
T1: Write X // This acquires an exclusive lock: LockXT2: Write Y // This acquires an exclusive lock: LockYT2: Read X // This attempts to acquire a shared lock on X, but since X is locked already by T1, T2 is subsequently blocked by the system until X is freed.T1: Read Y // This attempts to acquire a shared lock on Y, but since Y is locked already by T2, T1 is subsequently blocked by the system until Y is free.T1: Commits // This should release all locks held by T1.T2: Commits // This should release all locks held by T2.* Note that "block" means the transaction will not proceed until the specified condition is met.Now, since T2 is waiting for T1 to free X AND T1 is waiting for T2 to free Y, we get into a cycle of condition checking. These conditions will never be met because both transactions are waiting for the other one to do something, in order to proceed itself. Therefore we have a deadlock between T1 and T2 trying to access the shared resources X and Y.The Wikipedia article on Two-phase locking may help you understand why this is strict 2-phase locking and what 2-phase locking is.
