Transaction isolation levels relation with locks on table

Question

I have read about 4 levels of isolation   Isolation Level       Dirty Read    Nonrepeatable Read  Phantom Read   READ UNCOMMITTED      Permitted       Permitted           Permitted READ COMMITTED              --        Permitted           Permitted REPEATABLE READ             --             --             Permitted SERIALIZABLE                --             --              --   I want to understand the lock each transaction isolation takes on the table    READ UNCOMMITTED - no lock on table READ COMMITTED - lock on committed data REPEATABLE READ - lock on block of sql which is selected by using select query  SERIALIZABLE - lock on full table on which Select query is fired    below are the three phenomena which can occur in transaction isolation  Dirty Read- no lock  Nonrepeatable Read - no dirty read as lock on committed data  Phantom Read - lock on block of sql which is selected by using select query     I want to understand where we define these isolation levels   only at jdbc hibernate level or in DB also    PS  I have gone through the links in Isolation levels in oracle  but they looks clumsy and talk on database specific

User · Accepted Answer

I want to understand the lock each transaction isolation takes on the table   For example  you have 3 concurrent processes A  B and C  A starts a transaction  writes data and commit rollback  depending on results   B just executes a SELECT statement to read data  C reads and updates data  All these process work on the same table T    READ UNCOMMITTED - no lock on the table  You can read data in the table while writing on it  This means A writes data  uncommitted  and B can read this uncommitted data and use it  for any purpose   If A executes a rollback  B still has read the data and used it  This is the fastest but most insecure way to work with data since can lead to data holes in not physically related tables  yes  two tables can be logically but not physically related in real-world apps      READ COMMITTED - lock on committed data  You can read the data that was only committed  This means A writes data and B can t read the data saved by A until A executes a commit  The problem here is that C can update data that was read and used on B and B client won t have the updated data  REPEATABLE READ - lock on a block of SQL which is selected by using select query   This means B reads the data under some condition i e  WHERE aField  gt  10 AND aField  lt  20  A inserts data where aField value is between 10 and 20  then B reads the data again and get a different result  SERIALIZABLE - lock on a full table on which Select query is fired   This means  B reads the data and no other transaction can modify the data on the table  This is the most secure but slowest way to work with data  Also  since a simple read operation locks the table  this can lead to heavy problems on production  imagine that T table is an Invoice table  user X wants to know the invoices of the day and user Y wants to create a new invoice  so while X executes the read of the invoices  Y can t add a new invoice  and when it s about money  people get really mad  especially the bosses         I want to understand where we define these isolation levels  only at JDBC hibernate level or in DB also   Using JDBC  you define it using Connection setTransactionIsolation   Using Hibernate    lt property name  hibernate connection isolation  gt 2 lt  property gt    Where   1  READ UNCOMMITTED 2  READ COMMITTED 4  REPEATABLE READ 8  SERIALIZABLE   Hibernate configuration is taken from here  sorry  it s in Spanish    By the way  you can set the isolation level on RDBMS as well    MySQL isolation level   SQL Server isolation level Informix isolation level  Personal Note  I will never forget about SET ISOLATION TO DIRTY READ sentence     and on and on

User · Answer

As brb tea says  depends on the database implementation and the algorithm they use  MVCC or Two Phase Locking   CUBRID  open source RDBMS  explains the idea of this two algorithms         Two-phase locking  2PL          The first one is when the T2 transaction tries to change the A record    it knows that the T1 transaction has already changed the A record and   waits until the T1 transaction is completed because the T2 transaction   cannot know whether the T1 transaction will be committed or rolled   back  This method is called Two-phase locking  2PL           Multi-version concurrency control  MVCC          The other one is to allow each of them  T1 and T2 transactions  to   have their own changed versions  Even when the T1 transaction has   changed the A record from 1 to 2  the T1 transaction leaves the   original value 1 as it is and writes that the T1 transaction version   of the A record is 2  Then  the following T2 transaction changes the A   record from 1 to 3  not from 2 to 4  and writes that the T2   transaction version of the A record is 3       When the T1 transaction is rolled back  it does not matter if the 2    the T1 transaction version  is not applied to the A record  After   that  if the T2 transaction is committed  the 3  the T2 transaction   version  will be applied to the A record  If the T1 transaction is   committed prior to the T2 transaction  the A record is changed to 2    and then to 3 at the time of committing the T2 transaction  The final   database status is identical to the status of executing each   transaction independently  without any impact on other transactions    Therefore  it satisfies the ACID property  This method is called   Multi-version concurrency control  MVCC     The MVCC allows concurrent modifications at the cost of increased overhead in memory  because it has to maintain different versions of the same data  and computation  in REPETEABLE READ level you can t loose updates so it must check the versions of the data  like Hiberate does with Optimistick Locking    In 2PL Transaction isolation levels control the following         Whether locks are taken when data is read  and what type of locks are requested    How long the read locks are held    Whether a read operation referencing rows modified by another transaction          Block until the exclusive lock on the row is freed    Retrieve the committed version of the row that existed at the time the statement or transaction started    Read the uncommitted data modification             Choosing a transaction isolation level does not affect the locks that   are acquired to protect data modifications  A transaction always gets   an exclusive lock on any data it modifies and holds that lock until   the transaction completes  regardless of the isolation level set for   that transaction  For read operations  transaction isolation levels   primarily define the level of protection from the effects of   modifications made by other transactions       A lower isolation level increases the ability of many users to access   data at the same time  but increases the number of concurrency   effects  such as dirty reads or lost updates  that users might   encounter    Concrete examples of the relation between locks and isolation levels in SQL Server  use 2PL except on READ COMMITED with READ COMMITTED SNAPSHOT ON    READ UNCOMMITED  do not issue shared locks to prevent other transactions from modifying data read by the current transaction  READ UNCOMMITTED transactions are also not blocked by exclusive locks that would prevent the current transaction from reading rows that have been modified but not committed by other transactions        READ COMMITED     If READ COMMITTED SNAPSHOT is set to OFF  the default   uses shared locks to prevent other transactions from modifying rows while the current transaction is running a read operation  The shared locks also block the statement from reading rows modified by other transactions until the other transaction is completed         Row locks are released before the next row is processed        If READ COMMITTED SNAPSHOT is set to ON  the Database Engine uses row versioning to present each statement with a transactionally consistent snapshot of the data as it existed at the start of the statement  Locks are not used to protect the data from updates by other transactions   REPETEABLE READ  Shared locks are placed on all data read by each statement in the transaction and are held until the transaction completes  SERIALIZABLE  Range locks are placed in the range of key values that match the search conditions of each statement executed in a transaction        The range locks are held until the transaction completes

User · Answer

The locks are always taken at DB level -  Oracle official Document - To avoid conflicts during a transaction  a DBMS uses locks  mechanisms for blocking access by others to the data that is being accessed by the transaction   Note that in auto-commit mode  where each statement is a transaction  locks are held for only one statement   After a lock is set  it remains in force until the transaction is committed or rolled back  For example  a DBMS could lock a row of a table until updates to it have been committed  The effect of this lock would be to prevent a user from getting a dirty read  that is  reading a value before it is made permanent   Accessing an updated value that has not been committed is considered a dirty read because it is possible for that value to be rolled back to its previous value  If you read a value that is later rolled back  you will have read an invalid value    How locks are set is determined by what is called a transaction isolation level  which can range from not supporting transactions at all to supporting transactions that enforce very strict access rules   One example of a transaction isolation level is TRANSACTION READ COMMITTED  which will not allow a value to be accessed until after it has been committed  In other words  if the transaction isolation level is set to TRANSACTION READ COMMITTED  the DBMS does not allow dirty reads to occur  The interface Connection includes five values that represent the transaction isolation levels you can use in JDBC

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