Distributed Database Management System UNIT-2. Concurrency Control. Transaction ACID rules. MCA 325, Distributed DBMS And Object Oriented Databases

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1 Distributed Database Management System UNIT-2 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. U2.1 Concurrency Control Concurrency control is a method used to ensure that database transactions are executed in a safe manner (i.e., without data loss). Concurrency control is especially applicable to database management system (DBMS), which must ensure that transactions are executed safely and that they follow the ACID rules. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.2 Transaction ACID rules A transaction = sequence of statements that either all succeed, or all fail Transactions have the ACID properties: A = atomicity (a transaction should be done or undone completely ) C = consistency (a transaction should transform a system from one consistent state to another consistent state) Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.3 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.1

2 Transaction ACID rules Cont I = isolation (each transaction should happen independently of other transactions ) D = durability (completed transactions should remain permanent) Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.4 Distributed Concurrency Control Objectives: All concurrency control (CC) mechanisms must ensure consistency of data items is preserved. Each atomic action completes in finiteit time Distribution of Processing power. Havelowest storage overheads Perform in network without communication delays. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.5 Locks The most common way in which access to items is controlled is by locks. Lock manager is the part of a DBMS that records, for each item I, whether one or more transactions are reading or writing any part of I. If so, the manager will forbid another transaction from gaining i access to I, provided d the type of access (read or write) could cause a conflict, such as the duplicate selling of an airline seat. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.6 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.2

3 Example of locks Lets consider two transaction T1 and T2. Each accesses an item A, which we assume has an integer value, and adds one to A. Read A; A:=A+1;Write A; T1: Read A A:=A+1 Write A T2: Read A A:=A+1 Write A Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.7 Example of locks (cont ) The most common solution to this problem is to provide a lock on A. Before reading A, a transaction T must lock A, which prevents another transaction from accessing A until T is finished with A. Furthermore, the need for T to set a lock on A prevents T from accessing A if some other transaction is already using A. T must wait until the other transaction unlocks A, which it should do only after finishing with A. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.8 Concurrent access with transaction Agent A Agent B begin transaction read account 754 ($314.60) Begin transaction wait update account 754 ($264.60) wait commit wait read account 754 ($264.60) update account 754 ($214.60) commit Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.9 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.3

4 Transaction Management with SQL Transaction support is provided by two SQL statements: COMMIT and ROLLBACK. A COMMIT statement is reached, in which case all changes are permanently recorded within the database. The COMMIT statement automatically ends the SQL transaction. A ROLLBACK statement is reached in which case all changes are aborted and the database is rolled back to its previous consistent state. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.10 Two-Phase Locking Techniques Two-phase locking, (2PL) is a concurrency control locking protocol, or mechanism, which guarantees Serializability. It is also the name of the resulting class (set) of transaction schedules. Using locks that block processes, 2PL may be subject to deadlocks that result from the mutual blocking of two transactions or more. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.11 Two-Phase Locking Techniques Cont Check these two condition before granting a lock on transaction 1. There is no other transaction holding a lock on Q in a mode that conflict with M. 2. There is no other transaction that is waiting for a lock on Q and that made its lock request before Ti. Two Phases: (a) Locking (Growing) (b) Unlocking (Shrinking) Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.12 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.4

5 Two-Phase Locking Techniques Cont Locking (Growing) Phase: A transaction applies locks (read or write) on desired data items one at a time. A transaction may obtain locks, but may not release any lock. Unlocking (Shrinking) Phase: A transaction unlocks its locked data items one at a time. A transaction may release locks, but may not obtain any new locks. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.13 Putting Locks on Transaction Transaction View in 2 phase locking Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.14 Types of 2PL We Can employ one of the following 4 protocols (based on 2PL) to ensure serializability for DDBMSs Centralized 2PL: single site maintains all locking information. Primary Copy 2PL: For data copies, one copy chosen as primary copy, others are slave copies, Only need to write-lock primary copy of data item that is to be updated. Changes can be propagated to slaves Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.15 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.5

6 Types of 2PL Cont Distributed 2PL: Lock managers distributed to every site. Each lock manager responsible for locks for data at that site. If data is not replicated, equivalent to primary copy 2PL. Otherwise, implements a Read-One-Write-All (ROWA) replica control protocol. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.16 Types of 2PL Cont Majority Locking: Extension of distributed 2PL. To read/write data replicated at n sites, sends lock request to>1/2n sites Transaction cannot proceed until majority of locks obtained. Overly strong in case of read locks. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.17 Deadlock Adeadlock is a situation wherein two or more competing actions are waiting for the other to finish, and thus neither ever does In the computing world deadlockdl refers to a specific condition when two or more processes are each waiting for another to release a resource. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.18 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.6

7 Deadlock Situation Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.19 Necessary conditions 1. Mutual exclusion condition: a resource is either assigned to one process or it is available 2. Hold and wait condition: processes already holding resources may request new resources 3. No preemption condition: only a process holding a resource may release it 4. Circular wait condition: two or more processes formacircularchainwhereeachprocesswaitsfor a resource that the next process in the chain holds Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.20 Distributed Deadlock Detection Researchers works on detecting the occurrence of deadlocks in distributed system. The presence of atomic transaction in some distributed systems makes a major conceptual difference. When a deadlock is detected in a conventional system, we kill one or more processes to break the deadlock --- one or more unhappy users. When deadlock is detected in a system based on atomic transaction, it is resolved by aborting one or more transactions. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.21 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.7

8 Distributed Deadlock Detection Cont But transactions have been designed to with stand being aborted. When a transaction is aborted, the system is first restored to the state it had before the transaction began, at which point the transaction can start again. With a bit of luck, it will succeed the second time. Thus the difference is that the consequences of killing off a process are much less severe when transactions are used. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.22 Centralized approach for Deadlock Detection Under this approach there is some coordinator process which is endowed with the responsibility of collecting the information about the local wait for graphs constructing a global wait for graph and to check for the existence of a dead lock. The draw back with the centralized approach is given below: Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.23 Distributed Deadlock Detection 1. The coordinator process cannot always construct a consistent global wait for graph based on the information collected from the various sites at different times therefore the probability of detection of phantom or false Deadlock is always there. 2. Another major draw back is the existence of a single-point of failure of coordinator process. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.24 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.8

9 Distributed Deadlock Detection Cont The Chandy-Misra-Haas algorithm: Processes are allowed to request multiple resources at once -- the growing phase of a transaction can be speeded up. The consequence of this change is a process may now wait on two or more resources at the same time. When a process has to wait for some resources, a problem message is generated and sent to the process holding the resources. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.25 Distributed Deadlock Detection Cont The message consists of three numbers: -> The process being blocked, -> The process sending the message, -> and the process receiving the message. When message arrived, the recipient checks to see it it itself is waiting for any processes. If so, the message is updated, keeping the first number unchanged, and replaced the second and third field by the corresponding process number. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.26 Distributed Deadlock Detection Cont The message is then send to the process holding the needed resources. If a message goes all the way around and comes back to the original sender -- the process that initiate the probe, a cycle exists and the system is deadlocked. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.27 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.9

10 Time stamp protocol Time stamp = Assigning time to a transaction Or Assigning logical counter to any new transaction. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.28 Time stamp protocol Cont Wait-Die and Wound-Wait Propose in the context of a distributed system, but could be used in a centralized system as well comes in two version (Wait-die and Wound-wait) work as follows: Every transaction is timestamped with its start time (which must be unique) Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.29 Time stamp protocol Cont When transaction A requests a lock on some item that is already locked by transaction B, then Wait-Die: A waits if it is older than B; otherwise, it dies - that is, A is rolled back and restarted. Wound-Wait: A waits if it is younger than B; otherwise, it wounds B that is, B is rolled back and restarted. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.30 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.10

11 Wait-die Wait-die If (T i older than T j ) then T i allowed to wait Else Abort T i (rollback and restart later) End if Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.31 Wound-wait Wound-wait If (T i older than T j ) then Abort T j (T i wound T j ) (rollback and restart later) Else T i allowed to wait End if Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.32 No waiting algorithm If transaction is unable to obtain a lock, it is immediately aborted and then restarted after a certain time delay without checking whether a deadlock will actually occur or not. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.33 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.11

12 Quorum based protocol A quorum is the minimum number of votes that a distributed transaction has to obtain in order to be allowed to perform an operation in a distributed system. A quorum-based technique is implemented to enforce consistent operation in a distributed system. Quorum-based voting can be used as a replica control method, as well as a commit method to ensure transaction atomicity in the presence of network partitioning. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.34 Quorum based protocol Cont Each site i has associated with it a number of votes Vi, Vi being a positive integer. Let V indicate the sum of the votes of all sites of the network. A transaction must collect a commit quorum Vc before committing. A transaction must collect a abort quorum Va before aborting. hence the following rules must be obeyed in the implementation of the commit protocol: Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.35 Quorum based protocol Cont Va + Vc > V, where 0 <= Va, Vc <= V. Before a transaction commits, it must obtain a commit quorum Vc. Before a transaction aborts, it must obtain an abort quorum Va. The first rule ensures that a transaction cannot be committed and aborted at the same time. The next two rules indicate the votes that a transaction has to obtain before it can terminate one way or the Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.36 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.12

13 Quorum based protocol Cont In replicated databases, a data object has copies present at several sites. To ensure serializability, no two transactions should be allowed to read or write a data item concurrently. In case of replicated databases, a quorum-based replica control protocol can be used to ensure that no two copies of a data item are read or written by two transactions concurrently. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.37 Quorum based protocol Cont The quorum-based voting for replica control is due to [Gifford, 1979]. Each copy of a replicated data item is assigned a vote. Each operation then has to obtain a read quorum (Vr) or a write quorum (Vw) to read or write a data item, respectively. If a given data item has a total of V votes, the quorums have to obey the following rules: Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.38 Vr + Vw > V Vw > V/2 Quorum based protocol Cont The first rule ensures that a data item is not read and written by two transactions concurrently. The second rule ensures that two write operations from two transactions cannot occur concurrently on the same data item. The two rules ensure that onecopy serializability is maintained. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.39 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.13

14 Commit Protocols There are two kinds of commit protocols : Two-Phase Commit protocol - a blocking protocol Three-Phase Commit protocol - a nonblocking protocol Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U phase commit Commit-request phase 1. The coordinator sends a query to commit message to all cohorts. 2. The cohorts execute the transaction up to the point where they will be asked to commit. 3. Each cohort replies with an agreement message if the transaction succeeded, or an abort message if the transaction failed. 4. The coordinator waits until it has a message from each cohort. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.41 Commit phase If the coordinator received an agreement message from all cohorts during the commitrequest phase: The coordinator writes a commit record into its log. The coordinator sends a commit message to all the cohorts. Each cohort completes the operation, and releases all the locks and resources held during the transaction. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.42 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.14

15 Commit phase Cont Each cohort sends an acknowledgement to the coordinator. The coordinator completes the transaction when acknowledgements have been received. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.43 Commit phase Cont Ifany cohort sent an abort message during the commit-request phase: The coordinator sends a rollback message to all the cohorts. Each cohort undo the transaction using the undo log, and releases the resources and locks held during the transaction. Each cohort sends an acknowledgement to the coordinator. The coordinator completes the transaction when acknowledgements have been received. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.44 Commit phase Cont Disadvantages The greatest disadvantage of the two-phase commit protocol is the fact that it is a blocking protocol. A node will block while it is waiting for a message. Note: A commitment protocol is called Blocking if the occurrence of some kinds of failures forces some of the participating sites to wait until the failure is repaired before terminating the transaction. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.45 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.15

16 Non-blocking commitment protocol Three-phase commit protocol In databases the three-phase commit protocol (3PC) is a distributed algorithm which lets all nodes in a distributed system agree to commit a transaction. Unlike the two-phase commit protocol (2PC) however, 3PC is non-blocking. Specifically, 3PC places an upper bound on the amount of time required before a transaction either commits or aborts. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.46 Non-blocking commitment protocol Cont This property ensures that if a given transaction is attempting to commit via 3PC and holds some resource locks, it will release the locks after the timeout. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.47 Coordinator The coordinator receives a transaction request. If there is a failure at this point, the coordinator aborts the transaction (i.e. upon recovery, it will consider the transaction aborted). Otherwise, the coordinator sends a start transaction message to the cohorts and moves to the waiting state. If there is a failure, timeout, or if the coordinator receives a will not start transaction message in the waiting state, the coordinator aborts the transaction and sends an abort message to all cohorts. Otherwise the coordinator will receive will Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.48 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.16

17 Coordinator Cont start transaction messages from all cohorts within the time window, so it sends commit messages to all cohorts and moves to the prepared state. If the coordinator fails in the prepared p state, it will move to the commit state. However if the coordinator times out while waiting for an acknowledgement from a cohort, it will abort the transaction. In the case where all acknowledgements are received, the coordinator moves to the commit state as well. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.49 Cohort The cohort receives a start transaction message from the coordinator. If the cohort agrees it sends a will start transaction message to the coordinator and moves to the prepared state. Otherwise it sends a will not start transaction message and aborts. If there is a failure, it moves to the abort state. In the prepared state, if the cohort receives an abort message from the coordinator, fails, or times out waiting for a commit, it aborts. If the cohort receives a commit message, it sends an ack message back and commits. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.50 Partitioned Networks Partitioned Networks Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.51 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.17

18 Partitioned Networks Cont With modern communication networks, which are capable of routing messages, the following assumption about the network is also reasonable: If site X cannot communicate with site Y but can communicate with site Z, then site Z cannot communicate with site Y either. In this case, when two operating sites X and Y cannot communicate, this means that no communication path is available between them, and the network is partitioned into two or more completely disconnected sub networks, one including X, and the other one including Y. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.52 Partitioned Networks Cont All the operational sites which belong to the same sub network can communicate with each other however, they cannot communicate with the sites belong to a different sub network until the partition is repaired. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.53 Check Points & Cold Starts/Restarts Check points and Cold starts/restarts Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.54 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.18

19 Check Points Check Point- A previous consistent state is marked by a check point. Check points are very useful during the recovery procedure. Performing a check point requires the following operations: Writing to stable storage all log records and all database updates which are still volatile storage. Writing to the stable storage a check point record. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.55 Check Points Cont Check point is achieved in three steps: 1. write a begin checkpoint record into log. 2. Collect the checkpoint data into the log. 3. write a end checkpoint record into log. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.56 Cold starts/restarts Cold restarts should be extremely rare in a data base system, this is required if the log information is lost at a site of the network. In this case, the affected site is not capable of reconstructing its most recent state, thus a previous state is reconstructed, and The effect of some local sub transaction is lost, the whole distributed database must be reset to a globally consistent previous state. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.57 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.19

20 Short Questions What are checkpoints. How it is differ from save points. What is 2 phase locking technique? What is concurrency control in DDBMS? Explain quorum based protocol? What is distributed deadlock. How it occur in a DDBMS. How locks can be applied in transactions. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.58 Long Questions What is the difference between 2 phase and 3 phase locking technique. What is check point explain in detail and where we require cold restart. Why deadlock arise in DDBMS and how they can be recover? Explain the time based protocol in detail and write some advantages with example. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.59 References 1. S. Ceri, G. Pelagatti, Distributed Database: Principles and Systems, McGraw Hill, New York, M. Tamer Ozsu, Patrick Valduriez, Principles of Distributed Databases System, Pearson, 2nd Ed., Mario Piattini, Advanced Database Technology and Design, Artech House, UK, Shivendra Goel, Divya Goel, Distributed Database Management System, Sun India Publications, Chhanda Ray, Distributed Database System, Pearson, Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel. Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63 U2.60 Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63,By Shivendra Goel U2.20