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| | To find it in excel, copy-paste this continued plan down into corpuscle B1. A person's again access an majority of time in abnormal within just corpuscle A1, the discount in treasures will come to pass in B1.<br><br> |
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| In the fields of [[database]]s and [[transaction processing]] (transaction management), a '''schedule''' (or '''history''') of a system is an abstract model to describe execution of transactions running in the system. Often it is a ''list'' of operations (actions) ordered by time, performed by a set of [[Database transaction|transactions]] that are executed together in the system. If order in time between certain operations is not determined by the system, then a ''[[partial order]]'' is used. Examples of such operations are requesting a read operation, reading, writing, aborting, committing, requesting lock, locking, etc. Not all transaction operation types should be included in a schedule, and typically only selected operation types (e.g., data access operations) are included, as needed to reason about and describe certain phenomena. Schedules and schedule properties are fundamental concepts in database [[concurrency control]] theory.
| | Video games are fun to play with your kids. Assist you learn much more about your kid's interests. Sharing interests with your kids like this can also create great conversations. It also gives an opportunity to monitor developing on their skills.<br><br>Generally is a patch ball game button that you may click after entering the type of desired values. when you check back directly on the game after their late twenties seconds to a minute, you will already make the items. Generally there are is nothing wrong when it comes to making use of hacks. To hack is in fact the best way to enjoy clash of clans cheats. Make use of a new Resources that you have, and take advantage pertaining to this 2013 Clash attached to Clans download! Reason why pay for coins maybe gems when you can get the needed items with this tool! Hurry and get your trusty very own Clash for Clans hack tool recently. The needed valuables are just a quantity clicks away.<br><br>Xbox game playing is worthy of kids. Consoles enable you to get far better control with regards to content and safety, as much kids can simply wind by way of elder regulates on your internet. Using this step might help to [http://www.encyclopedia.com/searchresults.aspx?q=protect protect] your young ones caused by harm.<br><br>We can can use this procedures to acquisition the majority of any time in the course of 1hr and one celebration. For [https://www.Flickr.com/search/?q=archetype archetype] to selection the majority of mail up 4 a quite time, acting x equals 15, 400 abnormal and / or you receive y = 51 gems.<br><br>Advertising are playing a applying game, and you don't any experience with it, set the difficulty diploma to rookie. If you have any inquiries with regards to the place and how to use clash of clans hack android ([http://circuspartypanama.com circuspartypanama.com]), you can call us at the web-page. This will help you pick moving up on the unique makes use of of the game learn your way close by the field. In the case when you set it superior than that, you are usually to get frustrated and so not have any enjoyable.<br><br>Typically individuals who produced this unique Crack Clash of Family members are true fans related with the sport themselves, and as well this is exactly the thing that ensures the potency created by our alternative, because we will needed to do that it ourselves. |
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| ==Formal description==
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| The following is an example of a schedule:
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| :<math>D = \begin{bmatrix}
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| T1 & T2 & T3 \\
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| R(X) & & \\
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| W(X) & & \\
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| Com. & & \\
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| & R(Y) & \\
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| & W(Y) & \\
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| & Com. & \\
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| && R(Z) \\
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| && W(Z) \\
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| && Com. \end{bmatrix}</math>
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| In this example, the horizontal axis represents the different transactions in the schedule D. The vertical axis represents time order of operations. Schedule D consists of three transactions T1, T2, T3. The schedule describes the actions of the transactions as seen by the [[DBMS]].
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| First T1 Reads and Writes to object X, and then Commits. Then T2 Reads and Writes to object Y and Commits, and finally T3 Reads and Writes to object Z and Commits. This is an example of a ''serial'' schedule, i.e., sequential with no overlap in time, because the actions of in all three transactions are sequential, and the transactions are not interleaved in time.
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| Representing the schedule D above by a table (rather than a list) is just for the convenience of identifying each transaction's operations in a glance. This notation is used throughout the article below. A more common way in the technical literature for representing such schedule is by a list:
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| :::D = R1(X) W1(X) Com1 R2(Y) W2(Y) Com2 R3(Z) W3(Z) Com3
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| Usually, for the purpose of reasoning about concurrency control in databases, an operation is modeled as ''[[Atomic operation|atomic]]'', occurring at a point in time, without duration. When this is not satisfactory start and end time-points and possibly other point events are specified (rarely). Real executed operations always have some duration and specified respective times of occurrence of events within them (e.g., "exact" times of beginning and completion), but for concurrency control reasoning usually only the precedence in time of the whole operations (without looking into the quite complex details of each operation) matters, i.e., which operation is before, or after another operation. Furthermore, in many cases the before/after relationships between two specific operations do not matter and should not be specified, while being specified for other pairs of operations.
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| In general operations of transactions in a schedule can interleave (i.e., transactions can be executed concurrently), while time orders between operations in each transaction remain unchanged as implied by the transaction's program. Since not always time orders between all operations of all transactions matter and need to be specified, a schedule is, in general, a ''[[partial order]]'' between operations rather than a ''[[total order]]'' (where order for each pair is determined, as in a list of operations). Also in the general case each transaction may consist of several processes, and itself be properly represented by a partial order of operations, rather than a total order. Thus in general a schedule is a partial order of operations, containing ([[embedding]]) the partial orders of all its transactions.
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| Time-order between two operations can be represented by an ''[[ordered pair]]'' of these operations (e.g., the existence of a pair (OP1,OP2) means that OP1 is always before OP2), and a schedule in the general case is a [[set (mathematics)|set]] of such ordered pairs. Such a set, a schedule, is a [[partial order]] which can be represented by an ''[[acyclic directed graph]]'' (or ''directed acyclic graph'', DAG) with operations as nodes and time-order as a [[directed edge]] (no cycles are allowed since a cycle means that a first (any) operation on a cycle can be both before and after (any) another second operation on the cycle, which contradicts our perception of [[Time]]). In many cases a graphical representation of such graph is used to demonstrate a schedule.
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| '''Comment:''' Since a list of operations (and the table notation used in this article) always represents a total order between operations, schedules that are not a total order cannot be represented by a list (but always can be represented by a DAG).
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| ==Types of schedule==
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| ===Serial===
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| The transactions are executed non-interleaved (see example above)
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| i.e., a serial schedule is one in which no transaction starts until a running transaction has ended.
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| ===Serializable===<!-- This section is linked from [[Concurrency control]] --> | |
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| A schedule that is equivalent (in its outcome) to a serial schedule has the [[serializability]] property.
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| In schedule E, the order in which the actions of the transactions are executed is not the same as in D, but in the end, E gives the same result as D.
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| :<math>E = \begin{bmatrix}
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| T1 & T2 & T3 \\
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| R(X) & & \\
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| & R(Y) & \\
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| && R(Z) \\
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| W(X) & & \\
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| & W(Y) & \\
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| && W(Z) \\
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| Com. & Com. & Com. \end{bmatrix}</math>
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| ====Conflicting actions====
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| Two actions are said to be in conflict (conflicting pair) if:
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| # The actions belong to different transactions.
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| # At least one of the actions is a write operation.
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| # The actions access the same object (read or write).
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| The following set of actions is conflicting:
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| * R1(X), W2(X), W3(X) (3 conflicting pairs)
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| While the following sets of actions are not:
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| * R1(X), R2(X), R3(X)
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| * R1(X), W2(Y), R3(X)
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| ====Conflict equivalence====
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| The schedules S1 and S2 are said to be conflict-equivalent if following two conditions are satisfied:
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| # Both schedules S1 and S2 involve the same set of transactions (including ordering of actions within each transaction).
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| # The set of conflicting pairs in S1 is the same as in S2.
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| ====Conflict-serializable====
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| A schedule is said to be conflict-serializable when the schedule is conflict-equivalent to one or more serial schedules.
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| Another definition for conflict-serializability is that a schedule is conflict-serializable if and only if its [[precedence graph]]/serializability graph, when only committed transactions are considered, is acyclic (if the graph is defined to include also uncommitted transactions, then cycles involving uncommitted transactions may occur without conflict serializability violation).
| |
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| :<math>G = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| & R(A) \\
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| W(B) & \\
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| Com. & \\
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| & W(A) \\
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| & Com. \\
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| &\end{bmatrix}</math>
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| Which is conflict-equivalent to the serial schedule <T1,T2>, but not <T2,T1>.
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| ====Commitment-ordered==== | |
| {{POV-section|Commitment ordering|date=November 2011}}
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| A schedule is said to be commitment-ordered (commit-ordered), or commitment-order-serializable, if it obeys the [[Commitment ordering]] (CO; also commit-ordering or commit-order-serializability) schedule property. This means that the order in time of transactions' commitment events is compatible with the precedence (partial) order of the respective transactions, as induced by their schedule's acyclic precedence graph (serializability graph, conflict graph). This implies that it is also conflict-serializable. The CO property is especially effective for achieving [[Global serializability]] in distributed systems.
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| '''Comment:''' [[Commitment ordering]], which was discovered in 1990, is obviously not mentioned in ([[#Bern1987|Bernstein et al. 1987]]). Its correct definition appears in ([[#Weikum2001|Weikum and Vossen 2001]]), however the description there of its related techniques and theory is partial, inaccurate, and misleading.{{Says who|date=December 2011}} For an extensive coverage of commitment ordering and its sources see ''[[Commitment ordering]]'' and ''[[The History of Commitment Ordering]]''.
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| ====View equivalence====
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| Two schedules S1 and S2 are said to be view-equivalent when the following conditions are satisfied:
| |
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| # If the transaction <math>T_i</math> in S1 reads an initial value for object X, so does the transaction <math>T_i</math> in S2.
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| # If the transaction <math>T_i</math> in S1 reads the value written by transaction <math>T_j</math> in S1 for object X, so does the transaction <math>T_i</math> in S2.
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| # If the transaction <math>T_i</math> in S1 is the final transaction to write the value for an object X, so is the transaction <math>T_i</math> in S2.
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| ====View-serializable====
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| A schedule is said to be view-serializable if it is view-equivalent to some serial schedule.
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| Note that by definition, all conflict-serializable schedules are view-serializable.
| |
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| :<math>G = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| & R(A) \\
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| W(B) & \\
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| \end{bmatrix}</math>
| |
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| Notice that the above example (which is the same as the example in the discussion of conflict-serializable) is both view-serializable and conflict-serializable at the same time.) There are however view-serializable schedules that are not conflict-serializable: those schedules with a transaction performing a [[blind write]]:
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|
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| :<math>H = \begin{bmatrix}
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| T1 & T2 & T3 \\
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| R(A) & & \\
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| & W(A) & \\
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| & Com. & \\
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| W(A) & & \\
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| Com. & & \\
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| & & W(A) \\
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| & & Com. \\
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| & & \end{bmatrix}</math>
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| The above example is not conflict-serializable, but it is view-serializable since it has a view-equivalent serial schedule <T1, T2, T3>.
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| Since determining whether a schedule is view-serializable is [[NP-complete]], view-serializability has little practical interest.
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| ===Recoverable===<!-- This section is linked from [[Concurrency control]] -->
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| Transactions commit only after all transactions whose changes they read, commit.
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| :<math>F = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| W(A) & \\
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| & R(A) \\
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| & W(A) \\
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| Com. & \\
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| & Com.\\
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| &\end{bmatrix}
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| F2 = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| W(A) & \\
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| & R(A) \\
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| & W(A) \\
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| Abort & \\
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| & Abort \\
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| &\end{bmatrix}</math>
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| These schedules are recoverable. F is recoverable because T1 commits before T2, that makes the value read by T2 correct. Then T2 can commit itself. In F2, if T1 aborted, T2 has to abort because the value of A it read is incorrect. In both cases, the database is left in a consistent state.
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| ====Unrecoverable====
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| If a transaction T1 aborts, and a transaction T2 commits, but T2 relied on T1, we have an unrecoverable schedule.
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| | |
| :<math>G = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| W(A) & \\
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| & R(A) \\
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| & W(A) \\
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| & Com. \\
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| Abort & \\
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| &\end{bmatrix}</math>
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| In this example, G is unrecoverable, because T2 read the value of A written by T1, and committed. T1 later aborted, therefore the value read by T2 is wrong, but since T2 committed, this schedule is unrecoverable.
| |
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| ====Avoids cascading aborts (rollbacks)====
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| Also named cascadeless. A single transaction abort leads to a series of transaction rollback. Strategy to prevent cascading aborts is to disallow a transaction from reading uncommitted changes from another transaction in the same
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| schedule.
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| The following examples are the same as the one from the discussion on
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| recoverable:
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| :<math>F = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| W(A) & \\
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| & R(A) \\
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| & W(A) \\
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| Com. & \\
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| & Com.\\
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| &\end{bmatrix}
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| F2 = \begin{bmatrix}
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| T1 & T2 \\
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| R(A) & \\
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| W(A) & \\
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| & R(A) \\
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| & W(A) \\
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| Abort & \\
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| & Abort \\
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| &\end{bmatrix}</math>
| |
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| In this example, although F2 is recoverable, it does not avoid
| |
| cascading aborts. It can be seen that if T1 aborts, T2 will have to
| |
| be aborted too in order to maintain the correctness of the schedule
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| as T2 has already read the uncommitted value written by T1.
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| The following is a recoverable schedule which avoids cascading abort. Note, however, that the update of A by T1 is always lost (since T1 is aborted).
| |
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| :<math>F3 = \begin{bmatrix}
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| T1 & T2 \\
| |
| & R(A) \\
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| R(A) & \\
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| W(A) & \\
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| & W(A) \\
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| Abort & \\
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| & Commit \\
| |
| &\end{bmatrix}</math>
| |
| | |
| Cascading aborts avoidance is sufficient but not necessary for a schedule to be recoverable.
| |
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| ====Strict====
| |
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| A schedule is strict - has the strictness property - if for any two transactions T1, T2, if a write operation of T1 precedes a ''conflicting'' operation of T2 (either read or write), then the commit event of T1 also precedes that conflicting operation of T2.
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| Any strict schedule is cascadeless, but not the converse. Strictness allows efficient recovery of databases from failure.
| |
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| ==Hierarchical relationship between serializability classes==
| |
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| The following expressions illustrate the hierarachical (containment) relationships between [[serializability]] and [[Serializability#Correctness - recoverability|recoverability]] classes:
| |
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| * Serial ⊂ commitment-ordered ⊂ conflict-serializable ⊂ view-serializable ⊂ all schedules
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| * Serial ⊂ strict ⊂ avoids cascading aborts ⊂ recoverable ⊂ all schedules
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| The [[Venn diagram]] (below) illustrates the above clauses graphically.
| |
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| [[File:Schedule-serializability.png|frame|none|Venn diagram for serializability and recoverability classes]]
| |
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| ==Practical implementations==
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| In practice, most general purpose database systems employ conflict-serializable and recoverable (primarily strict) schedules.
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| ==See also==
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| * [[schedule (project management)]]
| |
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| ==References==
| |
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| *<cite id=Bern1987>[[Phil Bernstein|Philip A. Bernstein]], Vassos Hadzilacos, Nathan Goodman: [http://research.microsoft.com/en-us/people/philbe/ccontrol.aspx ''Concurrency Control and Recovery in Database Systems''], Addison Wesley Publishing Company, 1987, ISBN 0-201-10715-5</cite>
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| *<cite id=Weikum2001>[[Gerhard Weikum]], Gottfried Vossen: [http://www.elsevier.com/wps/find/bookdescription.cws_home/677937/description#description ''Transactional Information Systems''], Elsevier, 2001, ISBN 1-55860-508-8</cite>
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| [[Category:Data management]]
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| [[Category:Transaction processing]]
| |
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