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Is WFG a scam?
If WFG were a scam. Why would it be backed by AEGON a Dutch company that has been around for over 160 years.
What does the acronym WFG stand for?
Have you ever found yourself questioning what the acronym WFG stands for? WFG is an acronym standing for the following phrases "World Financial Group", "WoodWind Fingering Guide", "World Freight Group", "Wait-For-Graph" and many others.
Wfg hfh gt?
No it wouldn't as copyright is not imposed.
How much do they take if you earn 500 per week?
wfg
What songs did john Bonham right-Bonzo the drummer from led zeppelin?
wfg
Wait for graph and resource allocation graph in deadlocks?
yes,wait for graph=WFG,crazy wait!
What are some risks on joining WFG Online?
Some risks that may be encountered include losing money or losing your identity because you have to put personal information out on the internet which is not wise.
Who is the World largest financial group in the world?
Based on the National Information Center, a website sponsored by the government, J.P. Morgan Chase and Company is in first place of the top 50 holding companies as of 03/31/2013. Their place is supported by the amount of their assets which exceed 3.3 billion dollars, the highest in this top 50 category.
How many six figure income earners does world financial group have?
There are currently 22 six figure income earners, Average income of these 22 is about 160k a year. Hope that helps. 8 Yr WFG accountant.
Can you consider waiting for godot a kind of tragedy?
"Waiting for Godot" does not really have any genre. Barely any stage directions are given, and so it is hard for any actor to interpret the scene, i.e. how the stage is set, or what genre the play is. The only stage directions we are given is "A country road. A tree. Evening". However, Beckett himself said that WFG is a tragic comedy. I believe this is because they never get what they are waiting for, but learn a lot about themsleves.
What happened in hundreds of cities after Martin luther king assassination?
There are a number of things that happened in hundreds of cities immediately after the assassination of Martin Luther King Jr. Riots and arsons were witnessed on so many places as a way of protest for the assassination.
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
