Can I Have a Read Lock and a Write_lock in Two Different Transaction

Commercial demands for ensuring smooth functionality and highly efficient run-fourth dimension servers, make information technology highly prime for Database Designers to work out systems and code which cleverly avert any kinds of inconsistencies in multi-user transactions, if not incertitude the standard of memory management in read-heavy, write-heavy and all such commercial databases. This article shall give an adequate introduction to the classic locking architecture that was proposed and implemented for the database developer community.

We should try to overlook the techniques of locking in general, i.e., based on the granularity or level of the database. This is so we may bargain with it separately when looking at the feasibility of the types of locks.

Definition :
The formal definition of a lock is equally follows:

A Lock is a variable assigned to whatever data item in order to go along runway of the condition of that information item so that isolation and non-interference is ensured during concurrent transactions.

At its basic, a database lock exists to forbid two or more database users from performing any change on the same information item at the very same time. Therefore, it is correct to interpret this technique as a means of synchronizing access, which is in stark contrast to other sets of protocols such as those using timestamps and multiversion timestamps. In layman's terms, this may exist further simplified to the metaphorical 'lock' that is put on a information item so that no other user may unlock the ability to perform any update query.

Case i: Simultaneous access to transactions is non permitted. Case 2: putting a lock on other transactions is viable

In Case 2, which has been portrayed above, if the user/session on the right attempts an update, it will be met with a LOCK Await state or otherwise be STALLED until access to the data detail is unlocked. In some situations – if the stall exceeds a time limit – the session is terminated and an mistake statement is returned.

We shall look at the multiple ways these locks have been introduced in the industry as solutions to concurrency in transactions.

Binary Locks :
Remember that a lock is fundamentally a variable which holds a value. A binary lock is a variable capable of belongings only 2 possible values, i.e., a 1 (depicting a locked country) or a 0 (depicting an unlocked state). This lock is usually associated with every data item in the database ( perhaps at table level, row level or even the entire database level).

Should item Ten be unlocked, then a corresponding object lock(10) would return the value 0. So, the instant a user/session begins updating the contents of item Ten, lock(X) is set to a value of 1. Due to this, for as long as the update query lasts, no other user may access the detail Ten – fifty-fifty read or write to it!

At that place are two operations used to implement binary locks. They are lock_data( ) and unlock_data( ). The algorithms take been discussed below (merely algorithms have been entertained due to the diversity in DBMS scripts):

The locking performance :

lock_data(X):          label:          if lock(Ten) == 0         {             then lock(10) = ane;         }         else //when lock(X) == 1 or item 10 is locked         {                         wait (until item is unlocked or lock(X)=0) //wait for the user to finish the update query             go to          label          }

Notation that 'label:' is literally a label for the line which can be referred to at a later footstep to transfer execution to. The 'await' command in the else block basically puts all other transactions wanting to access X in a queue. Since it monitors or keeps other transactions scheduled until access to the item is unlocked, it is ofttimes taken to exist outside the lock_data(10) operation i.e., defined outside.

 The unlocking operation :

unlock_data(X):     lock(10) = 0 //we unlock access to item X     if (transactions are in queue)     {             then grant access or 'wake' the next transaction in line;     }

Merits of Binary Locks :

• They are uncomplicated to implement since they are effectively mutually exclusive and establish isolation perfectly.
• Binary Locks demand less from the arrangement since the organization must only proceed a tape of the locked items. The system is the lock manager subsystem which is a feature of all DBMSs today.

Drawbacks of Binary Locks :

• Binary locks are highly restrictive.
• They exercise not even permit reading of the contents of particular Ten. As a event, they are non used commercially.

Shared or Sectional Locks :
The incentive governing these types of locks is the restrictive nature of binary locks. Here nosotros await at locks which permit other transactions to make read queries since a READ query is non-alien. Nevertheless, if a transaction demands a write query on item X, and then that transaction must be given exclusive access to particular X. Ergo, we require a kind of multi-mode lock which is what shared/exclusive locks are. They are besides known as Read/Write locks.

Different binary locks, Read/Write locks may be set to 3 values, i.e., SHARED, Sectional or UNLOCKED. Hence, our lock, i.e., lock(10), may reflect either of the post-obit values:

1. READ-LOCKED –
   If a transaction only requires to read the contents of item X and the lock but permits reading. This is likewise known as a shared lock.
2. WRITE-LOCKED –
   If a transaction needs to update or write to item Ten, the lock must restrict all other transactions and provide exclusive access to the current transaction. Thus, these locks are also known equally exclusive locks.
3. UNLOCKED –
   Once a transaction has completed its read or update operations, no lock is held and the data item is unlocked. In this state, the particular may be accessed by any queued transactions.

A Shared/Exclusive lock may hold any of the 3 states.

The most pop mode of implementing these locks is by introducing a LOCK-Tabular array which keeps rail of the number of read-locks on the data items and the transactions with write-locks on different items. The tabular array has been described below.

Notation that if an item is write-locked, information technology is logically supposed to have no reads on account of the fact that it is now exclusive. As a effect, the 'Locking Transaction' column holds only one value – the transaction ID of the current transaction. If an item is read-locked, it is shared past multiple transactions and therefore, the 'Locking Transaction' column lists the transaction IDs of all the transactions. Since there are 3 states that the lock may hold, at that place must exist 3 operations which would execute the change to those states. These are as follows :

The read_lock operation –

read_lock(X):          label:          if lock(X) = "unlocked"         {             then lock(X) = "read-locked";             no_of_reads = 1; //since but the first transaction in queue is at present able to read detail X         }         else if lock(X) = "read-locked"         {             then no_of_reads +=1; //merely increment as a new transaction is at present reading the item X         }         else //lock(Ten) write-locked         {             wait (until lock(Ten) is "unlocked");//transactions notice a LOCK Await during this time             go to          characterization;         }

When the lock(Ten) is fix to "write-locked" (in the terminal else clause), the particular is exclusively being accessed by a transaction. In guild for other transactions to access it, the LOCK WAIT must end (updating process must finish) and lock(X) = "unlocked". This is what we wait for in the next line.

The write_lock functioning –

write_lock(X):          label:          if lock(X) = "unlocked"         {             then lock(X) = "write-locked"         }         else //if a read-lock is issued to particular X         {             expect (until lock(X) is "unlocked"); //and so that the lock managing director may wake upwards the next transaction             go to          characterization;         }

If an particular is unlocked, we simply write-lock it to grant exclusive admission to the current transaction. Now the lock manager system must put all other transactions in a queue. If the detail is in a read-lock state, the write-lock may Not be direct issued. The item must first be unlocked before it can be write-locked. In doing then, the lock manager arrangement also wakes upward the queued transactions.

The unlock performance –

unlock(X):     if lock(Ten) = "write-locked"     {         then lock(X) = "unlocked";         //the transactions in queue, if whatsoever, may now admission particular X in the manner they demand     }     else if lock(Ten) = "read-locked"     {         and then             no_of_reads-=i; //the transaction is washed reading.             if no_of_reads == 0 //no transactions reading the item             {                 lock(X) = "unlocked";                 //transactions in queue, if any, may now access item X in the manner they demand             }     }

The first case is straightforward enough. However, in the second instance, we must check for the status that at that place are no more electric current transactions sharing or reading item 10. If particular X is being read, we leave the situation and simply decrement the no_of_reads as the final transaction has terminated. The point here is that an particular may exist "unlocked only if:

• the 'write' operation terminates or is completed
• all 'read' operations cease or are completed

Here are a few rules that Shared/Exclusive Locks must obey:

1. A transaction T MUST issue the unlock(Ten) operation afterwards all read and write operations accept finished.
2. A transaction T may Not upshot a read_lock(X) or write_lock(X) performance on an particular which already has a read or write-lock issued to itself.
3. A transaction T is Not immune to upshot the unlock(Ten) operation unless it has been issued with a read_lock(X) or write_lock(X) operation.

When nosotros relax these rules, a new dimension of interchanging the status of locks on items can exist introduced. This has been explained in the following commodity: Lock Based Concurrency Command Protocol in DBMS

Drawbacks of Shared/Sectional Locks :

• Do not guarantee serializability of schedules on their own. A split up protocol must exist followed to ensure this.
• Commercially not optimized for speedy transactions; non the best solution due to lock contention issues.
• Performance overhead is not negligible.

Certify Locks :
The motivation backside introducing certify locks is the failure of previously mentioned locks to deliver an efficient and promising architecture which does not compromise on speed of processing transactions. Here we briefly await at a form of multiple-way locking scheme which allows for the lock to be characterized by 3 locked states and one unlocked state.

Transactions may effect whatsoever of 3 locked states or 1 unlocked land

The states an item may be issued are :

1. READ-LOCKED –
   same every bit the read-locked state explained before for Shared/Exclusive Locks
2. WRITE-LOCKED –
   same equally the write-locked land explained before for Shared/Sectional Locks
3. CERTIFY-LOCKED –
   This is an exclusive lock. This is used when 2 different transactions must be read and write respectively, to item Ten. In order for this to happen, a committed and a local version of the data item is created. The committed version is used by all transactions which have a read-lock issued to X. The local version of X is accessed by T simply when a write-lock has been caused past T. Once the writing or updating operation has been carried out by T on item X, T must obtain a certify-lock so that the committed version of data item X may be updated to the local version'south contents and the local version may exist discarded.
4. UNLOCKED –
   same as the write-locked state explained earlier for Shared/Sectional Locks

Here is how a certify lock is used in multi-version concurrency control techniques:

In Stride ii, two versions of Particular Ten are created i.e., the committed and local versions.In Stride iv, the transaction must issue a certify lock on all writes it has made. Just and then can we proceed to the next stride. The updates on Local version are now concluding.

Step 5

In club for multiple transactions to access the contents of information item X, a compatibility table must be fatigued so that whatever collision or mistake is not returned, which may filibuster the procedure.

Locks on X	Read	Write	Certify
Read	Yes	Yes	No
Write	Yep	No	No
Certify	No	No	No

The correct way of interpreting this table is as follows. Consider two transactions, T and T'. Assign transaction T to either the rows or the columns. Do the exact opposite for T'. At present the compatibility between locks issued to an item Ten by T and T' tin exist cross-referenced. For instance, assign T to rows and T' to the columns. If T problems a read-lock on X and T' problems a write-lock on X, the result is a 'Yes' – this scenario is feasible. However, if T intends a write-lock on X and T' intends a certify-lock on X, the result is a 'No' – implying an incommunicable scenario.

At that place are further topics which look at developing better and avant-garde techniques to handle concurrency control, such as timestamps, multiversion models of data items and snapshot isolation. However, comprehending the basicity of the idea is key when it comes to edifice a clear understanding of concepts which may exist as complex as concurrency control.

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Source: https://www.geeksforgeeks.org/types-of-locks-in-concurrency-control/

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