What is 2 phase locking with respect to database concurrency control?

2PL or Two – phase locking is the most widely used concurrency control method. This method is used for implementing the serializability theory. The protocol makes use of two types of locks that the transactions apply to data which leads to blocking of the other transactions from accessing the same data item during the execution period of that transaction.
The 2PL protocol works in the following 2 phases:
- The expanding phase: In this phase the locks are only acquired and there is no releasing.
- The shrinking phase: In this phase the locks are only released and not acquired.

Shared locks (S) and exclusive locks (X) are the two types of lock used by this protocol. However many refinements have been produced of this protocol which utilize more than one type of lock. Since 2PL blocks processes using locks, it can lead to deadlocks as a result of the blocked transactions. SS2PL (strong strict two – phase locking) is combined to form the 2PL and is also known as rigorousness. It is mostly used for maintaining concurrency control in the database systems. The protocol has a number of variants, the most common being the strict 2PL, which is a combination of 2PL and strictness. A schedule that obeys the protocol is said to be serializable.
In a typical transaction, when the phase – 1 of transaction ends and there is no explicit information available, it is said to be in a ready state i.e., it can commit now without requiring any more locks. In such cases, we can end the phase-2 immediately or sometimes it might not even be required. In other cases where more than one processes are involved, we determining the end of phase – 1 and begin releasing of the locks with the help of a synchronization point. If this is not done, we violate the serializability and strict 2PL rules. But, determining such a transaction point is very costly and therefore the transaction end is merged with the end of phase – 1 eliminating the need of phase – 2.
Thus 2PL is turned in to SS2PL. In S2PL, the transactions must release their locks (X locks) after they have completed their write operation either by aborting or committing. The read locks (S) on the other hand are released on regular basis in phase 2.  Explicit phase – 1 end support is required for implementation of the general S2PL.
Strong strict 2Pl is also known as rigorous two – phase locking, rigorousness or rigorous scheduling and so on. Both the read and write locks are released after the completion of the transaction by the protocol. A transaction that complies with SS2PL is the one having only phase – 1 during its entire life time and no phase – 2. The class of schedules exhibiting the SS2PL property is called rigorousness. S2PL is a superset of SS2PL classes. This one has been the concurrency control mechanism choice for most of the database designers. The main advantage is that it provides strictness apart from serializability.
These two properties are very much necessary for an efficient recovery of the database as well as in commitment ordering. Global serializability and distributed serializability solutions are used for distributed environments. The down side of 2PL protocol is deadlocks. The data access operations are blocked by the locks resulting in a deadlock.  In this situation none of the blocked transactions can reach completion. Thus resolving the deadlocks effectively is a major issue. It can be resolved by aborting one of the locked transactions, thus eliminating the cycle in the precedence graph. The wait -  for -  graphs are used for detecting deadlocks. 

Purpose of Volume Testing and what are its features.

Volume testing belongs to the group of non-functional tests. Huge amount of data is processed through the application (which is being tested) in order to check the extreme limitations of the system.
- Volume testing refers to testing a software application for a certain data volume.
- Volume testing can (and should) be used in component testing.
- Volume testing will also be undertaken (normally) as part of the User Acceptance test.
- Volume testing is used to find faults and give credible information about the state of the component, on which business decisions can be taken.
- Volume testing might take place to confirm that the central core architecture is the one to proceed with.
- Developers across customers & finish users can do. The tests can be outsourced to a testing laboratory that specializes in performance testing.

Examples:
- Online system: Input fast, but not necessarily fastest possible, from different input channels.
- Database system: The database should be very large. Every object occurs with maximum number of instances.
- File exchange: Especially long files. Maximal lengths. Lengths longer than typical
maximum values in communication protocols.
- Disk space: Try to fill disk space everywhere there are disks.

Volume test is interesting if
• The volume test is not executed before.
• Does the system always has the necessary memory resources?
• Can we guarantee this if several systems share the hardware?
• Is it guaranteed that no larger data volumes than specified will occur?
• Is there a low risk if data volume turn greater than specified anyway but the
system does not work well enough then?

Database System Concepts - Data Model, Schemas and Database state

A data model is a collection of concepts that can be used to describe the structure of a database. By structure of the database we mean the data types, relationships, and constraints that should hold on the data. Most data models also include a set of basic operations for specifying retrievals and updates on database.

Categories of Data Models:
- High level or Conceptual data models : These models provide concepts that are close to the way many users perceive data. They use concepts such as entities, attributes, and relationships. An entity represents a real-world object or concept such as an employee or a project. An attribute represents property of interest that describes an entity such as employee's salary or name. A relationship represents an interaction among the entities.
- Representational data models : These models provides concept that may be understood by end users but that are not too far removed from the way data is organized within the computer. They are used most frequently in traditional commercial DBMSs and they include the widely used relational model as well as the network and hierarchical models. These models represent data by using record structures and hence are sometimes called record-based data models.
- Low level or Physical data models : These models provide concepts that describe the details of how the data is stored in the computer by representing information such as record formats, record orderings, and access paths. An access path is a structure that makes the search for particular database records efficient.

Schemas:
The description of a database in any data model is called the database schema which is specified during the database design and is not expected to change frequently. A displayed is called a schema diagram.


A schema diagram displays only some aspects of a schema, such as names of record types and data items, and some types of constraints.

Database State or Iinstance: The actual data in a database changes every time data is inserted, deleted, or modified. The data in the database at a particular moment in time is called a database state or a snapshot. It is also called the current set of occurrences or instances in the database.

Distinguish between Database State and Database Schema:
When a new database is defined, we specify its database schema only to the DBMS. At this point, the corresponding database state is empty state. The initial state of the database is got when the database is first populated or loaded with the initial data. From then on, every time an update operation is applied to the database, we get another database state.