Concurrency control is a mechanism for managing simultaneous transactions in a shared database to ensure serializability and isolation of transactions. It utilizes locking protocols like two-phase locking to control access to database items during transactions and prevent issues like lost updates, dirty reads, and incorrect summaries that can occur without concurrency control when transactions' operations are interleaved.

2. Process of managing simultaneous execution of
transactions in a shared database, to ensure the
serializability of transactions, is known as
concurrency control. Concurrency Control Protocols
are mechanisms to control concurrency of
transactions to ensure isolation of transactions (or
serializable schedules
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3. 1-Lost Updates: This problem occurs when two transactions
that access the same database items have their operations
interleaved in a way that makes the value of some database
item incorrect. Successfully completed update is overridden by
another user.
2-The dirty read problem: Transactions read a value written by
a transaction that has been later aborted. This value
disappears from the database upon abort, and should not have
been read by any transaction ("dirty read"). The reading
transactions end with incorrect results.
3-The incorrect summary problem: While one transaction takes
a summary over the values of all the instances of a repeated
data-item, a second transaction updates some instances of
that data-item. The resulting summary does not reflect a
correct result for any (usually needed for correctness)
precedence order between the two transactions:
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4. In databases and transaction processing, two-phase
locking (2PL) is a concurrency control method that
guarantees serializability. It is also the name of the resulting
set of database transaction schedules (histories). The
protocol utilizes locks, applied by a transaction to data, which
may block (interpreted as signals to stop) other transactions
from accessing the same data during the transaction's life.
By the 2PL protocol locks are applied and removed in two
phases:
Expanding phase: locks are acquired and no locks are
released.
Shrinking phase: locks are released and no locks are
acquired.
Two types of locks are utilized by the basic
protocol: Shared and Exclusive locks. Refinements of the
basic protocol may utilize more lock types. Using locks that
block processes, 2PL may be subject to deadlocks that result
from the mutual blocking of two or more transactions.
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5.  Pessimistic concurrency control: Is an approach where
an entity is locked in the database for the entire time that
it is in application memory. A lock either limits or
prevents other users from working with the entity in the
database.
 Optimistic
concurrency
control:This
strategy
is
appropriate for single user systems, systems where the
system of record is guaranteed to be accessed by only
one user or system process at a time, or read-only
tables. These situations do occur. It is important to
recognize that this strategy is completely inappropriate
for multi-user systems
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6. By having concurrency control you avoid dirty writes (or
inconsistent data). It is like your traffic signal - allows one
set of users (drivers) to pass through at a time. In computer
terms, if a user wants to update some data then the
following steps are taken: (a) the data is fetched along with
the timestamp (the date, time when it was last modified) (b)
the data is modified by the user who then submits the data
for update / storage in the system (c) the system verifies
the original timestamp with the current timestamp. (i) If both
are same, the new data (including the new timestamp) is
updated/stored in the system. (ii) If they are different, then
obviously the data had changed between the time it was
fetched and now - meaning that someone else had updated
in the meanwhile. The system typically informs the user
that the data had been modified by a different user and
asks him/her to submit the modifications once again.
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7. Concurrency control is a type of management style
where employers or supervisors constantly monitor
how employees are working while the work is still in
progress. This kind of management makes
employees feel like slaves and lowers their morale
to work, which lowers production. It also creates a
sense of mistrust between the employer and the
employees.
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8. Concurrency control and locking
 The purpose of concurrency control is to prevent two
different users (or two different connections by the
same user) from trying to update the same data at the
same time. Concurrency control can also prevent one
user from seeing out-of-date data while another user
is updating the same data.
 The following examples explain why concurrency
control is needed. For both examples, suppose that
your checking account contains $1,000. During the
day you deposit $300 and spend $200 from that
account. At the end of the day your account should
have $1,100.
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9.  Example 1: No concurrency control
 At 11:00 AM, bank teller #1 looks up your account and
sees that you have $1,000. The teller subtracts the $200
check, but is not able to save the updated account
balance ($800) immediately.
 At 11:01 AM, another teller #2 looks up your account and
still sees the $1,000 balance. Teller #2 then adds your
$300 deposit and saves your new account balance as
$1,300.
 At 11:09 AM, bank teller #1 returns to the
terminal, finishes entering and saving the updated value
that is calculated to be $800. That $800 value writes over
the $1300.
 At the end of the day, your account has $800 when it
should have had $1,100 ($1000 + 300 - 200).
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10.  Example 2: Concurrency control
 When teller #1 starts working on your account,
a lock is placed on the account.
 When teller #2 tries to read or update your
account while teller #1 is updating your account,
teller #2 will not be given access and gets an
error message.
 After teller #1 has finished the update, teller #2
can proceed.
 At the end of the day, your account has $1,100
($1000 - 200 + 300).
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11. In Example 1, the account updates are
done simultaneously rather than in
sequence and one update write overwrites
another update.
In Example 2, to prevent two users from
updating the data simultaneously (and
potentially writing over each other's
updates), the system uses a concurrency
control mechanism
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