Transaction control and isolation levels in Oracle

Transaction control and isolation levels in Oracle

Contents Transaction control Data Concurrency and Consistency in a Multiuser Environment Locking

A Banking Transaction

Transactions - Rationale Consider two clients booking airline tickets There are 2 seats left on a flight Client A wants 2 seats: – time 12:02 makes initial request – 12:06 confirms purchase through booking form – 12:08 authorises credit card payment Client B wants 2 seats: – time 12:03 makes initial request – 12:05 confirms purchase through booking form – 12:09 authorises credit card payment Situation needs careful control 08/26/2023 4

Some Possibilities Clients A and B are both told 2 seats are free in initial enquiries B confirms purchase before A – But A may still proceed A attempts credit card debit first – If successful A secures tickets at 12:08 B then attempts credit card debit – If successful B secures tickets at 12:09 potentially over-writing A’s tickets A has paid for tickets no longer his/hers 08/26/2023 5

Requirements 1 When client A beats B in the initial enquiry: – they should form a queue (serialisability) – B must wait for A to finish Different kinds of finish for A: – successful completes booking form makes credit card debit store results (commit) – number of seats available is now zero write transaction log and finish B cannot proceed with purchase as no tickets left 08/26/2023 6

Requirements 2 – unsuccessful may not complete booking form may not have funds on credit card undo any database changes (rollback) and finish – number of seats available is still 2 B can now proceed to attempt to purchase the 2 tickets left Techniques required to emulate business practice 08/26/2023 7

Structure of a DBMS Query Optimization and Execution Relational Operators Files and Access Methods Buffer Management Disk Space Management These layers must consider concurrency control and recovery (Transaction, Lock, Recovery Managers)

Transactions and Concurrent Execution Transaction - DBMS’s abstract view of a user program (or activity): – A sequence of reads and writes of database objects. – Unit of work that must commit or abort as an atomic unit Transaction Manager controls the execution of transactions. User’s program logic is invisible to DBMS! – Arbitrary computation possible on data fetched from the DB – The DBMS only sees data read/written from/to the DB. Challenge: provide atomic transactions to concurrent users! – Given only the read/write interface.

Concurrency: Why bother? The latency argument The throughput argument Both are critical!

Example of a Fund Transfer Isolation requirement — if between steps 3 and 6, another transaction T2 is allowed to access the partially updated database, it will see an inconsistent database (the sum A B will be less than it should be). T1 T2 1. read(A) 2. A : A – 50 3. write(A) read(A), read(B), print(A B) 4. read(B) 5. B : B 50 6. write(B Isolation can be ensured trivially by running transactions serially that is, one after the other. However, executing multiple transactions concurrently has significant benefits, as we will see later.

ACID Properties A transaction is a unit of program execution that accesses and possibly updates various data items.To preserve the integrity of data the database system must ensure: Atomicity. Either all operations of the transaction are properly reflected in the database or none are. Consistency. Execution of a transaction in isolation preserves the consistency of the database. Isolation. Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions. Intermediate transaction results must be hidden from other concurrently executed transactions. – That is, for every pair of transactions Ti and Tj, it appears to Ti that either Tj, finished execution before Ti started, or Tj started execution after Ti finished. Durability. After a transaction completes successfully, the changes it has made to the database persist, even if there are system failures.

Transaction State Active – the initial state; the transaction stays in this state while it is executing Partially committed – after the final statement has been executed. Failed -- after the discovery that normal execution can no longer proceed. Aborted – after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted: – restart the transaction can be done only if no internal logical error – kill the transaction Committed – after successful completion.

Transaction State (Cont.)

A.C.I.D. Atomicity and Durability A transaction ends in one of two ways: – commit after completing all its actions “commit” is a contract with the caller of the DB – abort (or be aborted by the DBMS) after executing some actions. Or system crash while the xact is in progress; treat as abort. Two important properties for a transaction: – Atomicity : Either execute all its actions, or none of them – Durability : The effects of a committed xact must survive failures. DBMS ensures the above by logging all actions: – – Undo the actions of aborted/failed transactions. Redo actions of committed transactions not yet propagated to disk when system crashes.

SQL Transaction commands DBMS does not have an inbuilt way of knowing which commands are grouped to form a single logical transaction. Some commands, e.g. COMMIT and ROLLBACK can provide boundaries of transaction. Commit; – saves current database state – releases resources, locks & savepoints held – equivalent to Save and Exit in MS Word Rollback; – returns database state to that at start of transaction – releases resources, locks & savepoints held – equivalent to dismiss/ do not save changes in MS Word By default, every SQL statement also commits implicitly if it executes successfully – Implicit commit can be turned off by a database directive 08/26/2023 E.g. in JDBC, connection.setAutoCommit(false); 16

Transactions in SQL A transaction is a logical unit of work on a database. A group of related operations that – typically comprises a collection of individual actions e.g. in SQL INSERT, UPDATE, DELETE, SELECT – must be performed successfully before any changes to the database are finalised. Variable size: – entire run on SQL*Plus e.g. spend 2 hours inserting data – single command in SQL*Plus e.g. one insert command – one execution of a procedure e.g. one run of add patient 08/26/2023 17

Database Transaction A database transaction consists of one of the following: DML statements which constitute one consistent change to the data One DDL statement One DCL statement

Oracle Transaction Types Type Data manipulation language (DML) Data definition language (DDL) Description Consists of any number of DML statements that the Oracle server treats as a single entity or a logical unit of work Consists of only one DDL statement Data control language Consists of only one DCL (DCL) statement

Transaction boundaries A transaction ends beginswith withone theoffirst theexecutable following events: SQL statement. A COMMIT or ROLLBACK statement is issued A DDL or DCL statement executes (automatic commit) The user exits iSQL*Plus The system crashes

Advantages of COMMIT and ROLLBACK With COMMIT and ROLLBACK statements, you can: Ensure data consistency Preview data changes before making changes permanent Group logically related operations

Concurrent Executions Multiple transactions are allowed to run concurrently in the system. Advantages are: increased processor and disk utilization, leading to better transaction throughput E.g. one transaction can be using the CPU while another is reading from or writing to the disk reduced average response time for transactions: short transactions need not wait behind long ones. Concurrency control schemes – mechanisms to achieve isolation Control the interaction among the concurrent transactions in order to prevent them from destroying the consistency of the database

Schedules Schedule – a sequences of instructions that specify the chronological order in which instructions of concurrent transactions are executed a schedule for a set of transactions must consist of all instructions of those transactions must preserve the order in which the instructions appear in each individual transaction. A transaction that successfully completes its execution will have a commit instructions as the last statement by default transaction assumed to execute commit instruction as its last step A transaction that fails to successfully complete its execution will have an abort instruction as the last statement

Schedule 1 Let T transfer 50 from A to B, and T transfer 10% of the 1 2 balance from A to B. Goal: A B is “preserved”. A serial schedule in which T is followed by T : 1 2

Schedule 2 A serial schedule where T2 is followed by T1

Schedule 3 Let T1 and T2 be the transactions defined previously. The following schedule is not a serial schedule, but it is equivalent to Schedule 1. A 100 A 50 Write A 50 A 50 temp 5 A 45 Write A 45 B 10 B 60 Write B 60 B 60 B 65 Write B 65 A B 110 In Schedules 1, 2 and 3, the sum A B is preserved.

Schedule 4 The following concurrent schedule does not preserve the value of (A B ). A 100 A 50 A 100 temp 10 A 90 Write A 90 B 10 Write A 50 B 10 B 60 Write B 60 B 10 10 20 Write B 20 A B 70

Serializability Basic Assumption – Each transaction preserves database consistency. Thus serial execution of a set of transactions preserves database consistency. A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule. Different forms of schedule equivalence give rise to the notions of: 1. conflict serializability 2. view serializability

Simplified view of transactions We ignore operations other than read and write instructions We assume that transactions may perform arbitrary computations on data in local buffers in between reads and writes. Our simplified schedules consist of only read and write instructions.

Conflicting Instructions Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q. 1. li read(Q), lj read(Q). 2. li read(Q), lj write(Q). 3. li write(Q), lj read(Q). 4. li write(Q), lj write(Q). li and lj don’t conflict. They conflict. They conflict They conflict Intuitively, a conflict between li and lj forces a (logical) temporal order between them. If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule.

Conflict Serializability If a schedule S can be transformed into a schedule S by a series of swaps of nonconflicting instructions, we say that S and S are conflict equivalent. We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule

Conflict Serializability (Cont.) Schedule 3 can be transformed into Schedule 6, a serial schedule where T2 follows T1, by series of swaps of nonconflicting instructions. Therefore Schedule 3 is conflict serializable. Schedule 3 Schedule 6

Conflict Serializability (Cont.) Example of a schedule that is not conflict serializable: We are unable to swap instructions in the above schedule to obtain either the serial schedule T3, T4 , or the serial schedule T4, T3 .

View Serializability Let S and S be two schedules with the same set of transactions. S and S are view equivalent if the following three conditions are met, for each data item Q, 1. If in schedule S, transaction Ti reads the initial value of Q, then in schedule S’ also transaction Ti must read the initial value of Q. 2. If in schedule S transaction Ti executes read(Q), and that value was produced by transaction Tj (if any), then in schedule S’ also transaction Ti must read the value of Q that was produced by the same write(Q) operation of transaction Tj . 3. The transaction (if any) that performs the final write(Q) operation in schedule S must also perform the final write(Q) operation in schedule S’. As can be seen, view equivalence is also based purely on reads and writes alone.

View Serializability (Cont.) A schedule S is view serializable if it is view equivalent to a serial schedule. Every conflict serializable schedule is also view serializable. But, a view serializable schedule may not be conflict serializable. Below is a schedule which is view-serializable but not conflict serializable. What serial schedule is above equivalent to? Every view serializable schedule that is not conflict serializable has blind writes.

Testing for Serializability Consider some schedule of a set of transactions T1, T2, ., Tn Precedence graph — a directed graph where the vertices are the transactions (names). We draw an arc from Ti to Tj if the two transaction conflict, and Ti accessed the data item on which the conflict arose earlier. We may label the arc by the item that was accessed. Example 1

Test for Conflict Serializability A schedule is conflict serializable if and only if its precedence graph is acyclic. Cycle-detection algorithms exist which take order n2 time, where n is the number of vertices in the graph. If precedence graph is acyclic, the serializability order can be obtained by a topological sorting of the graph. This is a linear order consistent with the partial order of the graph. For example, a serializability order for Schedule A would be T5 T1 T3 T2 T4 Are there others?

Examples Schedule 1: T2:R(A),T1:R(B), T2:W(A), T3:R(A), T1:W(B), T3:W(A), T2:R(B), T2:W(B) T1 B T2 A T3 Schedule 2: T2:R(A),T1:R(B), T2:W(A), T2:R(B), T3:R(A), T1:W(B), T3:W(A), T2:W(B) B T1 B T2 A T3

Test for View Serializability The precedence graph test for conflict serializability cannot be used directly to test for view serializability. Extension to test for view serializability has cost exponential in the size of the precedence graph. The problem of checking if a schedule is view serializable falls in the class of NP-complete problems. Thus existence of an efficient algorithm is extremely unlikely. However practical algorithms that just check some sufficient conditions for view serializability can still be used.

Recoverable Schedules Need to address the effect of transaction failures on concurrently running transactions. Recoverable schedule — if a transaction Tj reads a data item previously written by a transaction Ti , then the commit operation of Ti appears before the commit operation of Tj. The following schedule (Schedule 11) is not recoverable if T9 commits immediately after the read If T8 should abort, T9 would have read (and possibly shown to the user) an inconsistent database state. Hence, database must ensure that schedules are recoverable.

Cascading Rollbacks Cascading rollback – a single transaction failure leads to a series of transaction rollbacks. Consider the following schedule where none of the transactions has yet committed (so the schedule is recoverable) If T10 fails, T11 and T12 must also be rolled back. Can lead to the undoing of a significant amount of work

Cascadeless Schedules Cascadeless schedules — cascading rollbacks cannot occur; for each pair of transactions Ti and Tj such that Tj reads a data item previously written by Ti, the commit operation of Ti appears before the read operation of Tj. Every cascadeless schedule is also recoverable It is desirable to restrict the schedules to those that are cascadeless

Concurrency Control A database must provide a mechanism that will ensure that all possible schedules are either conflict or view serializable, are recoverable and preferably cascadeless A policy in which only one transaction can execute at a time generates serial schedules, but provides a poor degree of concurrency Q: Are serial schedules recoverable/cascadeless? Testing a schedule for serializability after it has executed is a little too late! Goal – develop concurrency control protocols that will assure serializability.

Concurrency Control (Cont.) Concurrency-control schemes tradeoff between the amount of concurrency they allow and the amount of overhead that they incur. Some schemes allow only conflict-serializable schedules to be generated, while others allow view-serializable schedules that are not conflictserializable.

Concurrency Control vs. Serializability Tests Concurrency-control protocols allow concurrent schedules, but ensure that the schedules are conflict/view serializable, and are recoverable and cascadeless . Concurrency control protocols generally do not examine the precedence graph as it is being created Instead a protocol imposes a discipline that avoids nonseralizable schedules. Different concurrency control protocols provide different tradeoffs between the amount of concurrency they allow and the amount of overhead that they incur. Tests for serializability help us understand why a concurrency control protocol is correct.

Weak Levels of Consistency Some applications are willing to live with weak levels of consistency, allowing schedules that are not serializable E.g. a read-only transaction that wants to get an approximate total balance of all accounts E.g. database statistics computed for query optimization can be approximate (why?) Such transactions need not be serializable with respect to other transactions Tradeoff accuracy for performance

Levels of Consistency in SQL-92 Serializable — default Repeatable read — only committed records to be read, repeated reads of same record must return same value. However, a transaction may not be serializable – it may find some records inserted by a transaction but not find others. Read committed — only committed records can be read, but successive reads of record may return different (but committed) values. Read uncommitted — even uncommitted records may be read. Lower degrees of consistency useful for gathering approximate information about the database Warning: some DBMSes do not ensure serializable schedules by default E.g. Oracle and PostgreSQL by default support a level of consistency called snapshot isolation (not part of the SQL standard)

A Briefer on Oracle Internals

Oracle Memory Structures

Overview of the System Global Area A system global area (SGA) is a group of shared memory structures that contain data and control information for one Oracle database instance. If multiple users are concurrently connected to the same instance, then the data in the instance's SGA is shared among the users. – the SGA is sometimes called the shared global area. An SGA and Oracle processes constitute an Oracle instance. Oracle automatically allocates memory for an SGA when you start an instance, – the OS reclaims the memory when you shut down the instance. Each instance has its own SGA. The SGA is read/write.

Log Writer Process (LGWR) Log writer process (LGWR) is responsible for redo log buffer management – writing the redo log buffer to a redo log file on disk. LGWR writes all redo entries that have been copied into the buffer since the last time it wrote – A commit record when a user process commits a transaction – Redo log buffers When a user commits a transaction, the transaction is assigned a system change number (SCN) – Oracle records it along with the transaction's redo entries in the redo log. – SCNs are recorded in the redo log so that recovery operations can be synchronized in Real Application Clusters and distributed databases.

COMMIT transaction After COMMIT Before COMMIT The generated internal rollback transaction segment tablerecords for theinassociated buffers in rollback the SGA updated SCN segment generatedrecords redo log entrieswith in the redo log buffer of the SGA. LGWR writes have SGA redo entries to database the onlinebuffers redo log The changes beenlog made to the of file the Oracle SGA. releases locks Oracle marks the transaction complete.

ROLLBACK transaction ROLLBACK to SAVEPOINT Oracle rolls undoes back allonly transaction the statements changesrun using after thethe undo savepoint. or rollback segments tablespace Oracle preserves the specified savepoint, but all savepoints that Oracle were releases established all the after transaction’s the specified locksone of data are lost Oracle The transaction releases all ends table and row locks acquired since that savepoint

State of the Data Before COMMIT or ROLLBACK The previous state of the data can be recovered. The current user can review the results of the DML operations by using the SELECT statement. Other users cannot view the results of the DML statements by the current user. The affected rows are locked Other users cannot change the data within the affected rows.

State of the Data after COMMIT Data changes are made permanent in the database. The previous state of the data is permanently lost. All users can view the results. Locks on the affected rows are released; those rows are available for other users to manipulate. All savepoints are erased.

Data Concurrency and Consistency Data concurrency means that many users can access data at the same time. Data consistency means that each user sees a consistent view of the data, including visible changes made by the user’s own transactions and transactions of other users.

The isolation models prevents Dirty reads Nonrepeatable (fuzzy) reads Phantom reads

Isolation levels (SQL92) controls Isolation Level Dirty Read Nonrepeatable Phantom Read Read Read uncommitted Y Y Y Read committed N Y Y Repeatable read N N Y Serializable N N N

Oracle isolation levels Read committed Each query executed by a transaction sees only data that was committed before the query began (Oracle default isolation level) Serializable Serializable transactions see only those changes that were committed at the time the transaction began, plus its own changes Read-only The transaction sees only those changes that were committed at the time the transaction began and do not allow any DML statement

Multiversion Concurrency Control Statement-level read consistency The data returned by a single query comes from a single point in time — the time that the query began Transaction-level read consistency When a transaction executes in serializable mode, all data accesses reflect the state of the database as of the time the transaction began

Common recommendations Keep transactions as fast as possible Increase the size/number of rollback segments Avoid executing long-running queries when transactions which update the table are also executing.

Set the Isolation Level You can set the isolation level of a transaction by using one of these statements at the beginning of a transaction: SET TRANSACTION ISOLATION LEVEL READ COMMITTED; SET TRANSACTION ISOLATION LEVEL SERIALIZABLE; SET TRANSACTION ISOLATION LEVEL READ ONLY;

Serializable Transaction Failure

Modes of Locking Exclusive lock The mode prevents the associates resource from being shared Share lock The mode allows the associated resource to be shared, depending on the operations involved

Deadlock

Types of Locks Lock DML locks (data locks) Description DML locks protect data For example, table locks lock entire tables, rowlocks lock selected rows. DDL locks (dictionary locks) DDL locks protect the structure of schema objects Internal locks and latches Internal locks and latches protect internal database structures such as datafiles