As we know that, in order to maintain consistency in a database, it follows ACID properties. Among these four properties (Atomicity, Consistency, Isolation and Durability) Isolation determines how transaction integrity is visible to other users and systems. It means that a transaction should take place in a system in such a way that it is the only transaction that is accessing the resources in a database system.
Isolation levels defines the degree to which a transaction must be isolated from the data modifications made by any other transaction in the database system. A transaction isolation level are defined by the following phenomena –

  • Dirty Read – A Dirty read is the situation when a transaction reads a data that has not yet been commited.For example, Let’s say transaction 1 updates a row and leaves it uncommited, meanwhile Transaction 2 reads the updated row. If transaction 1 rolls back the change, transaction 2 will have read data that is considered never to have existed.
  • Non Repeatable read – Non Repeatable read occurs when a transaction reads same row twice, and get a different value each time. For example, suppose transaction T1 reads a data. Due to concurrency, another transaction T2 updates the same data and commit, Now if transaction T1 rereads the same data, it will retrieve a different value.
  • Phantom Read – Phantom Read occurs when two same queries are executed, but the rows retrieved by the two, are different. For example, suppose transaction T1 retrieves a set of rows that satisfy some search criteria. Now, Transaction T2 generates some new rows that matches the search criteria for transaction T1. If transaction T1 reexecutes the statement that reads the rows, it gets a different set of rows this time.

Based on these phenomena, The SQL standard defines four isolation levels :

  1. Read Uncommitted – Read Uncommitted is the lowest isolation level. In this level, one transaction may read not yet commited changes made by other transaction, thereby allowing dirty reads. In this level, transactions are not isolated from each other.
  2. Read Committed – This isolation level guarantees that any data read is committed at the moment it is read. Thus it does not allows dirty read. The transaction hold a read or write lock on the current row, and thus prevent other rows from reading, updating or deleting it.
  3. Repeatable Read – This is the most restrictive isolation level. The transaction holds read locks on all rows it references and write locks on all rows it inserts, updates, or deletes. Since other transaction cannot read, update or delete these rows, consequently it avoids non repeatable read.
  4. Serializable – This is the Highest isolation level. A serializable execution is guaranteed to be serializable. Serializable execution is defined to be an execution of operations in which concurrently executing transactions appears to be serially executing.

The Table given below clearly depicts the relationship between isolation levels, read phenomena and locks :


Anomaly Serializable is not the same as Serializable. That is, it is necessary, but not sufficient that a Serializable schedule should be free of all three phenomena types.


source - https://www.geeksforgeeks.org/transaction-isolation-levels-dbms/




In database systems, isolation determines how transaction integrity is visible to other users and systems. For example, when a user is creating a Purchase Order and has created the header, but not the Purchase Order lines, is the header available for other systems/users (carrying out concurrent operations, such as a report on Purchase Orders) to see?

A lower isolation level increases the ability of many users to access the same data at the same time, but increases the number of concurrency effects (such as dirty reads or lost updates) users might encounter. Conversely, a higher isolation level reduces the types of concurrency effects that users may encounter, but requires more system resources and increases the chances that one transaction will block another.[1]

Isolation is typically defined at database level as a property that defines how/when the changes made by one operation become visible to other. On older systems, it may be implemented systemically, for example through the use of temporary tables. In two-tier systems, a Transaction Processing (TP) manager is required to maintain isolation. In n-tier systems (such as multiple websites attempting to book the last seat on a flight), a combination of stored procedures and transaction management is required to commit the booking and send confirmation to the customer.[2]

Isolation is one of the ACID (Atomicity, Consistency, Isolation, Durability) properties.

Concurrency control[edit source]

Concurrency control comprises the underlying mechanisms in a DBMS which handle isolation and guarantee related correctness. It is heavily used by the database and storage engines (see above) both to guarantee the correct execution of concurrent transactions, and (different mechanisms) the correctness of other DBMS processes. The transaction-related mechanisms typically constrain the database data access operations' timing (transaction schedules) to certain orders characterized as the serializabilityand recoverability schedule properties. Constraining database access operation execution typically means reduced performance (rates of execution), and thus concurrency control mechanisms are typically designed to provide the best performance possible under the constraints. Often, when possible without harming correctness, the serializability property is compromised for better performance. However, recoverability cannot be compromised, since such typically results in a quick database integrity violation.

Two-phase locking is the most common transaction concurrency control method in DBMSs, used to provide both serializability and recoverability for correctness. In order to access a database object a transaction first needs to acquire a lock for this object. Depending on the access operation type (e.g., reading or writing an object) and on the lock type, acquiring the lock may be blocked and postponed, if another transaction is holding a lock for that object.

Read phenomena[edit source]

The ANSI/ISO standard SQL 92 refers to three different read phenomena when Transaction 1 reads data that Transaction 2 might have changed.

In the following examples, two transactions take place. In the first, Query 1 is performed. Then, in the second transaction, Query 2 is performed and committed. Finally, in the first transaction, Query 1 is performed again.

The queries use the following data table:

users
idnameage
1Joe20
2Jill25

Dirty reads[edit source]

dirty read (aka uncommitted dependency) occurs when a transaction is allowed to read data from a row that has been modified by another running transaction and not yet committed.

Dirty reads work similarly to non-repeatable reads; however, the second transaction would not need to be committed for the first query to return a different result. The only thing that may be prevented in the READ UNCOMMITTED isolation level is updates appearing out of order in the results; that is, earlier updates will always appear in a result set before later updates.

In our example, Transaction 2 changes a row, but does not commit the changes. Transaction 1 then reads the uncommitted data. Now if Transaction 2 rolls back its changes (already read by Transaction 1) or updates different changes to the database, then the view of the data may be wrong in the records of Transaction 1.

Transaction 1Transaction 2
/* Query 1 */
SELECT age FROM users WHERE id = 1;
/* will read 20 */
/* Query 2 */
UPDATE users SET age = 21 WHERE id = 1;
/* No commit here */
/* Query 1 */
SELECT age FROM users WHERE id = 1;
/* will read 21 */
ROLLBACK; /* lock-based DIRTY READ */

But in this case no row exists that has an id of 1 and an age of 21.

Non-repeatable reads[edit source]

non-repeatable read occurs, when during the course of a transaction, a row is retrieved twice and the values within the row differ between reads.

Non-repeatable reads phenomenon may occur in a lock-based concurrency control method when read locks are not acquired when performing a SELECT, or when the acquired locks on affected rows are released as soon as the SELECT operation is performed. Under the multiversion concurrency control method, non-repeatable reads may occur when the requirement that a transaction affected by a commit conflict must roll back is relaxed.

Transaction 1Transaction 2
/* Query 1 */
SELECT * FROM users WHERE id = 1;
/* Query 2 */
UPDATE users SET age = 21 WHERE id = 1;
COMMIT; /* in multiversion concurrency
   control, or lock-based READ COMMITTED */
/* Query 1 */
SELECT * FROM users WHERE id = 1;
COMMIT; /* lock-based REPEATABLE READ */

In this example, Transaction 2 commits successfully, which means that its changes to the row with id 1 should become visible. However, Transaction 1 has already seen a different value for age in that row. At the SERIALIZABLE and REPEATABLE READ isolation levels, the DBMS must return the old value for the second SELECT. At READ COMMITTED and READ UNCOMMITTED, the DBMS may return the updated value; this is a non-repeatable read.

There are two basic strategies used to prevent non-repeatable reads. The first is to delay the execution of Transaction 2 until Transaction 1 has committed or rolled back. This method is used when locking is used, and produces the serial schedule T1, T2. A serial schedule exhibits repeatable reads behaviour.

In the other strategy, as used in multiversion concurrency control, Transaction 2 is permitted to commit first, which provides for better concurrency. However, Transaction 1, which commenced prior to Transaction 2, must continue to operate on a past version of the database — a snapshot of the moment it was started. When Transaction 1 eventually tries to commit, the DBMS checks if the result of committing Transaction 1 would be equivalent to the schedule T1, T2. If it is, then Transaction 1 can proceed. If it cannot be seen to be equivalent, however, Transaction 1 must roll back with a serialization failure.

Using a lock-based concurrency control method, at the REPEATABLE READ isolation mode, the row with ID = 1 would be locked, thus blocking Query 2 until the first transaction was committed or rolled back. In READ COMMITTED mode, the second time Query 1 was executed, the age would have changed.

Under multiversion concurrency control, at the SERIALIZABLE isolation level, both SELECT queries see a snapshot of the database taken at the start of Transaction 1. Therefore, they return the same data. However, if Transaction 1 then attempted to UPDATE that row as well, a serialization failure would occur and Transaction 1 would be forced to roll back.

At the READ COMMITTED isolation level, each query sees a snapshot of the database taken at the start of each query. Therefore, they each see different data for the updated row. No serialization failure is possible in this mode (because no promise of serializability is made), and Transaction 1 will not have to be retried.

Phantom reads[edit source]

phantom read occurs when, in the course of a transaction, new rows are added or removed by another transaction to the records being read.

This can occur when range locks are not acquired on performing a SELECT ... WHERE operation. The phantom reads anomaly is a special case of Non-repeatable reads when Transaction 1 repeats a ranged SELECT ... WHERE query and, between both operations, Transaction 2 creates (i.e. INSERT) new rows (in the target table) which fulfill that WHERE clause.

Transaction 1Transaction 2
/* Query 1 */
SELECT * FROM users
WHERE age BETWEEN 10 AND 30;
/* Query 2 */
INSERT INTO users(id,name,age) VALUES ( 3, 'Bob', 27 );
COMMIT;
/* Query 1 */
SELECT * FROM users
WHERE age BETWEEN 10 AND 30;
COMMIT;

Note that Transaction 1 executed the same query twice. If the highest level of isolation were maintained, the same set of rows should be returned both times, and indeed that is what is mandated to occur in a database operating at the SQL SERIALIZABLE isolation level. However, at the lesser isolation levels, a different set of rows may be returned the second time.

In the SERIALIZABLE isolation mode, Query 1 would result in all records with age in the range 10 to 30 being locked, thus Query 2 would block until the first transaction was committed. In REPEATABLE READ mode, the range would not be locked, allowing the record to be inserted and the second execution of Query 1 to include the new row in its results.

Isolation levels[edit source]

Of the four ACID properties in a DBMS (Database Management System), the isolation property is the one most often relaxed. When attempting to maintain the highest level of isolation, a DBMS usually acquires locks on data which may result in a loss of concurrency or implements multiversion concurrency control. This requires adding logic for the application to function correctly.

Most DBMSs offer a number of transaction isolation levels, which control the degree of locking that occurs when selecting data. For many database applications, the majority of database transactions can be constructed to avoid requiring high isolation levels (e.g. SERIALIZABLE level), thus reducing the locking overhead for the system. The programmer must carefully analyze database access code to ensure that any relaxation of isolation does not cause software bugs that are difficult to find. Conversely, if higher isolation levels are used, the possibility of deadlock is increased, which also requires careful analysis and programming techniques to avoid.

The isolation levels defined by the ANSI/ISO SQL standard are listed as follows.

Serializable[edit source]

This is the highest isolation level.

With a lock-based concurrency control DBMS implementation, serializability requires read and write locks (acquired on selected data) to be released at the end of the transaction. Also range-locks must be acquired when a SELECT query uses a ranged WHEREclause, especially to avoid the phantom reads phenomenon.

When using non-lock based concurrency control, no locks are acquired; however, if the system detects a write collision among several concurrent transactions, only one of them is allowed to commit. See snapshot isolation for more details on this topic.

From : (Second Informal Review Draft) ISO/IEC 9075:1992, Database Language SQL- July 30, 1992: The execution of concurrent SQL-transactions at isolation level SERIALIZABLE is guaranteed to be serializable. A serializable execution is defined to be an execution of the operations of concurrently executing SQL-transactions that produces the same effect as some serial execution of those same SQL-transactions. A serial execution is one in which each SQL-transaction executes to completion before the next SQL-transaction begins.

Repeatable reads[edit source]

In this isolation level, a lock-based concurrency control DBMS implementation keeps read and write locks (acquired on selected data) until the end of the transaction. However, range-locks are not managed, so phantom reads can occur.

Write skew is possible at this isolation level, a phenomenon where two writes are allowed to the same column(s) in a table by two different writers (who have previously read the columns they are updating), resulting in the column having data that is a mix of the two transactions.[3][4]

Read committed[edit source]

In this isolation level, a lock-based concurrency control DBMS implementation keeps write locks (acquired on selected data) until the end of the transaction, but read locks are released as soon as the SELECT operation is performed (so the non-repeatable reads phenomenon can occur in this isolation level). As in the previous level, range-locks are not managed.

Putting it in simpler words, read committed is an isolation level that guarantees that any data read is committed at the moment it is read. It simply restricts the reader from seeing any intermediate, uncommitted, 'dirty' read. It makes no promise whatsoever that if the transaction re-issues the read, it will find the same data; data is free to change after it is read.

Read uncommitted[edit source]

This is the lowest isolation level. In this level, dirty reads are allowed, so one transaction may see not-yet-committed changes made by other transactions.

Since each isolation level is stronger than those below, in that no higher isolation level allows an action forbidden by a lower one, the standard permits a DBMS to run a transaction at an isolation level stronger than that requested (e.g., a "Read committed" transaction may actually be performed at a "Repeatable read" isolation level).

Default isolation level[edit source]

The default isolation level of different DBMS's varies quite widely. Most databases that feature transactions allow the user to set any isolation level. Some DBMS's also require additional syntax when performing a SELECT statement to acquire locks (e.g. SELECT ... FOR UPDATE to acquire exclusive write locks on accessed rows).

However, the definitions above have been criticized as being ambiguous, and as not accurately reflecting the isolation provided by many databases:

This paper shows a number of weaknesses in the anomaly approach to defining isolation levels. The three ANSI phenomena are ambiguous, and even in their loosest interpretations do not exclude some anomalous behavior ... This leads to some counter-intuitive results. In particular, lock-based isolation levels have different characteristics than their ANSI equivalents. This is disconcerting because commercial database systems typically use locking implementations. Additionally, the ANSI phenomena do not distinguish between a number of types of isolation level behavior that are popular in commercial systems.[5]

There are also other criticisms concerning ANSI SQL's isolation definition, in that it encourages implementors to do "bad things":

... it relies in subtle ways on an assumption that a locking schema is used for concurrency control, as opposed to an optimistic or multi-version concurrency scheme. This implies that the proposed semantics are ill-defined.[6]

Isolation levels, read phenomena, and locks[edit source]

Isolation levels vs read phenomena[edit source]

Isolation levelLost updatesDirty readsNon-repeatable readsPhantoms
Read Uncommitteddon't occurmay occurmay occurmay occur
Read Committeddon't occurdon't occurmay occurmay occur
Repeatable Readdon't occurdon't occurdon't occurmay occur
Serializabledon't occurdon't occurdon't occurdon't occur

Anomaly Serializable is not the same as Serializable. That is, it is necessary, but not sufficient that a Serializable schedule should be free of all three phenomena types.[5]

See also[edit source]


source - https://en.wikipedia.org/wiki/Isolation_(database_systems)




The transaction isolation level is a state within databases that specifies the amount of data that is visible to a statement in a transaction, specifically when the same data source is accessed by multiple transactions simultaneously.

Transaction isolation level is part of the isolation state of a database management system. Isolation is one of the ACID (atomicity, consistency, isolation, durability) properties.


The transaction isolation level is primarily used as a means to provide accurate and reliable access to data within concurrent transactions. For example, two different transactions might be accessing the same data simultaneously. Therefore, if the change made on the data by one transaction is not passed to the other transaction, it can affect database operations. To circumvent this, DBMS employs different transaction isolation levels that enforce read and write locks on the data. There are four different types of transaction isolation levels.

  1. Serializable: Implements read and writes locks until the transaction is finished. Also implements range locks.
  2. Repeatable Reads: Implements read and write locks until the transaction is completed. Doesn’t manage range locks.
  3. Read Committed: Implements write locks until the transaction is completed but releases read locks when a SELECT operation is performed.
  4. Read Uncommitted: One transaction can see the uncommitted changes made by the other transaction



source - https://www.techopedia.com/definition/24042/transaction-isolation-level







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A Hibernate Session is just a transactional write-behind cache that translate entity state transitionsinto DML statements. The Hibernate Session can be connected or disconnected from the database. When it is disconnected, it cannot flush current pending entity state changes to the underlying database.

There are multiple ways to associate a Hibernate Session to a database transaction:

  • session-per-request (the session is bound to the life-cycle of a single logical @Transaction and one physical database transaction)
  • long conversation (the session can span to multiple @Transaction operations, hence there are multiple database transactions involved)

When it comes to database transactions, there are two different approaches:

  • RESOURCE_LOCAL transactions, using a single DataSource will always bind a physical database transaction to a Hibernate Session (within the context of a single logical transaction, meaning that you can still implement long conversations to span over multiple such logical transactions).

  • JTA, using multiple DataSources. JTA state that connections should be aggressively releasedafter each statement, but it practice you still get the same JDBC Connection handle within the context of a single logical transaction.

Now back to your questions:

  1. Does beginning a new database transaction on an old session obtains a new connection and resumes the session?

Yes. The Hibernate session is reconnected and flushing/committing can proceed.

  1. Does committing a database transaction disconnects a session from the JDBC connection and returns the connection to the pool?

By default, when you commit a transaction, the Session is closed and the underlying connection is closed. If you use connection pooling, the database connection will indeed return to the pool.

  1. From Hibernate Documentation, earlier versions of Hibernate required explicit disconnection and reconnection of a Session. These methods are deprecated, as beginning and ending a transaction has the same effect. How do they have the same effect?

These methods are deprecated because the connection management is now controlled by the connection release modes.


source - https://stackoverflow.com/questions/28486850/what-is-the-difference-between-a-session-and-a-connection-in-hibernate




Hibernate Architecture


In the Hibernate we found the many of object like persistent object, session factory, transaction factory, connection factory, session, transaction all are include in the hibernate architecture.

In the Hibernate architecture we sees that it is a layer to keep you isolated from having to know the underlying APIs. Hibernate makes use of the database and configuration data to provide persistence services (and persistent objects) to the application.

There are 4 layers in hibernate architecture java application layer, hibernate framework layer, backhand api layer and database layer. Let's see the diagram of hibernate architecture:


This is the high level architecture of Hibernate with mapping file and configuration file.

Hibernate framework uses many objects session factory, session, transaction etc. alongwith existing Java API such as JDBC (Java Database Connectivity), JTA (Java Transaction API) and JNDI (Java Naming Directory Interface).

Elements of Hibernate Architecture

For creating the first hibernate application, we must know the elements of Hibernate architecture. They are as follows:

Session Factory

The SessionFactory is a factory of session and client of ConnectionProvider. It holds second level cache (optional) of data. The org.hibernate.SessionFactory interface provides factory method to get the object of Session.

Session

The session object provides an interface between the application and data stored in the database. It is a short-lived object and wraps the JDBC connection. It is factory of Transaction, Query and Criteria. It holds a first-level cache (mandatory) of data. The org.hibernate.Session interface provides methods to insert, update and delete the object. It also provides factory methods for Transaction, Query and Criteria.

Transaction

The transaction object specifies the atomic unit of work. It is optional. The org.hibernate.Transaction interface provides methods for transaction management.

ConnectionProvider

It is a factory of JDBC connections. It abstracts the application from DriverManager or DataSource. It is optional.

TransactionFactory

It is a factory of Transaction. It is optional.


source - http://r4r.co.in/java/hibernate/hibernate_tutorial/hibernate_architecture.shtml




Sessions

Sessions are a key component of the Oracle Application Server TopLink application--they provide OracleAS TopLink with access to the database. Sessions enable you to execute queries, and they return persistent objects and other results for client applications. This chapter introduces OracleAS TopLink sessions, and describes:

Introduction to Session Concepts

A session represents the connection between an application and the relational database that stores its persistent objects. OracleAS TopLink provides different session classes, each optimized for different design requirements and data access strategies. OracleAS TopLink session types range from a simple database session that gives one user one connection to the database, to the session broker that provides access to several databases for multiple clients.

To understand the OracleAS TopLink session, you must be familiar with several session concepts.

sessions.xml File

In most cases, the developer pre configures sessions for the application in a session configuration file. This file, known as the sessions.xml file, is an Extensible Markup Language (XML) file that contains all sessions that are associated with the application. The sessions.xml file can contain any number of sessions and session types.

Session Types

Several session types each provide a particular set of functionality to the application.

Server Session

A server session is the most common OracleAS TopLink session type, because it supports the three-tier architectures that are common to enterprise applications. Server sessions manage the server side of client-server communications. They work together with the client session to provide complete client-server communication.

The server session provides shared resources to a multithreaded environment, including a shared cache and connection pools. The server session also provides transaction isolation.

For more information about the server session, see "Server Session and Client Session".

Client Session

A client session is a client-side communications mechanism that works together with the server session to provide the client-server connection. Each client session serves one client.

For more information about the client session, see "Server Session and Client Session".

Remote Session

A remote session offers database access to clients that do not reside on the OracleAS TopLink Java virtual machine (JVM). The remote session connects to a client session, which, in turn, connects to the server session.

For more information, see "Remote Session".

Database Session

A database session is a unique session type because it provides both client and server communications. It is a relatively simple session type that supports only a single client and a single database connection. The database session is not scalable; however, if you have an application with a single client that requires only one database connection, the database session is usually your best choice.

For more information, see "Database Session".

Session Broker

The OracleAS TopLink session broker is a mechanism that enables client applications to communicate with multiple databases. A session broker makes multiple database access transparent to the client.

For more information, see "Session Broker".


source - https://docs.oracle.com/cd/B10463_01/web.904/b10313/sessions.htm

Oracle Application Server TopLink Application Developer's Guide





common concepts that get used with SQL Server thread management and scheduling

Sessions – when the client application connects to SQL Server the two sides establish a “session” on which to exchange information. Strictly speaking a session is not the same as the underlying physical connection, it is a SQL Server logical representation of a connection. But for practical purposes, you can think of this as being a connection (session =~ connection). See sys.dm_exec_sessions. This is the old SPID that existed in SQL Server 2000 and earlier. You may sometimes notice a single session repeating multiple times in a DMV output. This happens because of parallel queries. A parallel query uses the same session to communicate with the client, but on the SQL Server side multiple worker (threads) are assigned to service this request. So if you see multiple rows with the same session ID, know that the query request is being serviced by multiple threads.

Connections – this is the actual physical connection established at the lower protocol level with all of its characteristics sys.dm_exec_connections . There is a 1:1 mapping between a Session and a Connection.



Literally : Connection is Physical Communication Channel and Session is a state of information exchange. A Connection may have multiple sessions.

The connection is the physical communication channel between SQL Server and the application: the TCP socket, the named pipe, the shared memory region. The session in SQL Server corresponds to the Wikipedia definition of a session: a semi-permanent container of state for an information exchange. In other words the sessions stores settings like cache of your login information, current transaction isolation level, session level SET values etc etc.

Normally there is one session on each connection, but there could be multiple session on a single connection (Multiple Active Result Sets, MARS) and there are sessions that have no connection (SSB activated proceduressystem sessions). There are also connections w/o sessions, namely connections used for non-TDS purposes, like database mirroring sys.dm_db_mirroring_connections or Service Broker connections sys.dm_broker_connections.

I got the reference from here


source - https://stackoverflow.com/questions/39199173/difference-between-session-and-connection-in-sql-server




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REST

Web/HTTP 2019.01.20 08:41


Although REST is stateless, it has state transfer in its name. It's a little bit confusing to everyone.

Stateless

When you open a web page in the browser, you will act as a service consumer and the www server will act as a service provider to serve you with a webpage. If it is a normal connection, the client and the server will both perform a handshake and initiate a session (called a TCP connection).

After that, based on the server's and client's behavior, the state will change to either ESTABLISHED, IDLE, TIMEOUT, etc. But in REST, we are using the HTTP protocol which is a stateless, meaning the server will not store any session information about the client. The client is responsible for sending all of the details required by the server to get serviced, meaning when we invoke the URIhttp://somedomain:8080/senthil/services/page1 from the server, it has enough details about the client to serve page1 fully.

State Transfer

Using the same example, when you open a web page using some URL to view an image file (RESOURCE) on the server,the www server will show you (the client) the image in some format i.e a REPRESENTATION of the RESOURCE (image file).

During this process, the constant resource state of the server (i.e. the state of the image file which is stored in the server database) will be represented to client in an understandable format i.e. application state of the client. So, the resource state will remain constant in respect to clients, and only the representation of the resource will change, which in turn would change the application state.

Finally, the representation of the resource (how the image is displayed to the client), which implicitly changes the state of both the server and the client is called REST.


source - https://stackoverflow.com/questions/10418105/what-does-representational-state-mean-in-rest






Statelessness

As per the REST (REpresentational “State” Transfer) architecture, the server does not store any state about the client session on the server side. This restriction is called Statelessness. Each request from the client to server must contain all of the information necessary to understand the request, and cannot take advantage of any stored context on the server. Session state is therefore kept entirely on the client. client is responsible for storing and handling all application state related information on client side.

It also means that the client is responsible for sending any state information to the server whenever it is needed. There should not be any session affinity or sticky sessions on server.

Statelessness means that every HTTP request happens in complete isolation. When the client makes an HTTP request, it includes all information necessary for the server to fulfill that request. The server never relies on information from previous requests. If that information was important, the client would have sent it again in this request.

To enable clients to access these stateless APIs, its necessary that servers also should include every piece of information that the client may need to create the state on its side.

For becoming stateless, do not store even authentication/authorization details of client. Provide credentials with the request. Each request MUST stand alone and should not be affected by the previous conversation happened from the same client in past.

Application State vs Resource State

Please do not confuse between application state and resource state. Both are completely different things.

Application state is server-side data which servers store to identify incoming client requests, their previous interaction details, and current context information.

Resource state is the current state of a resource on a server at any point of time – and it has nothing to do with the interaction between client and server. It is what you get as a response from the server as API response. You refer to it as resource representation.

REST statelessness means being free on application state.

Advantages of Statelessness

There are some very noticeable advantages for having REST APIs stateless.

  1. Statelessness helps in scaling the APIs to millions of concurrent users by deploying it to multiple servers. Any server can handle any request because there is no session related dependency.
  2. Being stateless makes REST APIs less complex – by removing all server-side state synchronization logic.
  3. A stateless API is also easy to cache as well. A specific software can decide whether or not to cache the result of an HTTP request just by looking at that one request. There’s no nagging uncertainty that state from a previous request might affect the cacheability of this one. It improves the performance of applications.
  4. The server never loses track of “where” each client is in the application because the client sends all necessary information with each request.


source - https://restfulapi.net/statelessness/

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