ICOM 6005 – Database Management Systems Design Dr. Manuel Rodríguez-Martínez Electrical and Computer Engineering Department Lecture 16 – Intro. to Transactions Processing and Concurrency Control

ICOM 6005Dr. Manuel Rodriguez Martinez2 Transaction Processing Read : –Chapter 16, sec –Chapter 17 –ARIES papers Purpose: –Study different algorithms to support transactions and concurrency control in a DBMS

ICOM 6005Dr. Manuel Rodriguez Martinez3 Introduction DBMS software and supporting server machine are a big investment Enterprise wishes to maximize its use If each users get to use the DBMS by itself for a short period of time, it takes a lot of time to run the tasks Multiple user must be allowed to access the DBMS at the same time –Concurrent access DBMS might crash –Power fails, software bugs appears, hardware fails, soda is spilled … –Need recovery mechanism to recover loss data

ICOM 6005Dr. Manuel Rodriguez Martinez4 Multiple-Users using a DBMS DBMS T1 T4 T3 T2 Waiting Queue Users wait to get a hold on DBMS to run their tasks. Context switches make this inefficient

ICOM 6005Dr. Manuel Rodriguez Martinez5 Multiple-Users using a DBMS (2) DBMS T1 T4 T3 T2 DBMS executes different Tasks at the same time. Maximizes system throughput

ICOM 6005Dr. Manuel Rodriguez Martinez6 System Crash T1 T2 Data Disk is gone Updates are lost

ICOM 6005Dr. Manuel Rodriguez Martinez7 System Crash (2) T1 T2 Data Disk is gone Updates are lost How to recover?

ICOM 6005Dr. Manuel Rodriguez Martinez8 Concurrency and Recovery DBMS must support –Concurrency Allow different users to access DBMS at the same time Control access to data to prevent inconsistencies in DBMS –Recovery Track progress of operations by an users –Use a log for this If a crash occurs, must use this log to recover operations that were completed Log must be stored independently of data to prevent losing both Transactions – unit of work used by DBMS to support concurrency and recovery

ICOM 6005Dr. Manuel Rodriguez Martinez9 Relational DBMS Architecture Disk Space Management Buffer Management File and Access Methods Relational Operators Query Optimizer Query Parser Client API Client DB Execution Engine Concurrency and Recovery

ICOM 6005Dr. Manuel Rodriguez Martinez10 The need for concurrency Jil and Apu are married and share baking account A. Jil and Apu go to the bank at the same time and use to different ATMs –Jil asks to withdraw $300 from the $500 in A –Apu ask to withdraw $400 from the $500 in A The following might happen: –At ATM 1: System reads $500 in A –At ATM 2: System reads $500 in A –At ATM 1: System deducts $300 from A –At ATM 2: System deducts $400 from A –At ATM 1: Systems stored $200 as balance in A –At ATM 2: Systems stored $100 as balance in A Jil and Apu got $700 out of their $500 in account A! DBMS must prevent such events via concurrency control

ICOM 6005Dr. Manuel Rodriguez Martinez11 The need for recovery Tom goes to bank with a $1,000 deposit for this account A, which currently has $500 Tom talks with teller X. The following might happen: –Teller X reads A and finds $500 dollars –Tom gives $1,000 to teller X in an envelope –Teller X changes balance in A to $1,500 –Teller X sends a request to DBMS to update A to $1,500 –Power fails at this time What is the balance of A? –$500 or $1,500? How do we make sure it is $1,500? DBMS must support recovering correct balance via crash recover

ICOM 6005Dr. Manuel Rodriguez Martinez12 Transactions and ACID properties Transactions are the unit of work used to submit tasks to the DBMS –Selects, inserts, deletes, updates, create table, etc. Transactions must support ACID properties –Atomicity – all operations included in a transactions are either completed as a whole or aborted as whole –Consistency – each transactions reads a consistent DB and upon completion leaves DB in another consistent state –Isolation – transactions running concurrently have the same effect on the DB as if they had been run in serial fashion One at the other –Durability – changes made by committed (transactions) survive crashes and can be recovered. Changes made by aborted transactions are undone

ICOM 6005Dr. Manuel Rodriguez Martinez13 Supporting Transactions at DBMS Transaction Manager –Module in charge of supporting transaction at DBMS Sub-components –Lock Manager Deals with granting locks to transaction to get access to DB objects such as records, data pages, tables or whole databases –Log/Recovery Manager Deals with tracking operations done by transactions as well as determining which ones commit and which ones abort. After a crash, it recovers work done by committed transactions. Implementing Transaction Manager –Modules integrated with DBMS –Separate process from DBMS TP Monitor

ICOM 6005Dr. Manuel Rodriguez Martinez14 Schedules We can model operations done by a transaction with a schedule –List of operations done: read, write, plus logical operations –Often, we just care about Reads Writes Abort requests Commit requests Changes to individual objects (optional, just for clarity). –Assumptions: Only inter-transaction interaction is via reads/writes of shared objects

ICOM 6005Dr. Manuel Rodriguez Martinez15 Example Schedules T1T2 R(A) R(B) W(A) R(C) W(B) Commit W(C) Commit T1T2 R(A) R(B) W(A) R(C) W(B) Abort W(C) Commit Each row represent an action take a some point In time. DBMS make one action at a time Schedule 1 Schedule 2

ICOM 6005Dr. Manuel Rodriguez Martinez16 Serialization of Schedules Serial schedule: –A schedule in which each transaction T1, T2, …, Tk is executed one after the other without interleaving Key idea: –Transactions that interleave operations are ok as long as their schedule is equivalent to a serial schedule Serializable schedule on transactions T1, T2, …, Tk –Its effect are equivalent to a serial schedule –Performance is better Interleaving of operations Not all schedules are serializable System throughput – number of transactions completed per unit of time –Increases with serializable transactions

ICOM 6005Dr. Manuel Rodriguez Martinez17 Example of serializability T1T2 R(A) R(B) W(A) R(C) W(B) Commit W(C) Commit Schedule 1 T1T2 R(A) W(A) R(C) W(C) Commit R(B) W(B) Commit Serial equivalent

ICOM 6005Dr. Manuel Rodriguez Martinez18 Anomalies due to interleaving You want your schedules to be serializable Otherwise, the following things (considered bad) could happen –Write-read (WR) conflicts –Read-write (RW) conflicts –Write-write (WW) conflicts SQL allows you to decide the level of concurrency you need –By default you get serializable support

ICOM 6005Dr. Manuel Rodriguez Martinez19 Write-Read conflicts Transaction T1 reads uncommitted data produced by transaction T2. –Called a dirty read –Now, if T2 aborts, the work done by T1 is inconsistent Example: T1 and T2 access Bank account A –T1 reads A with balance $1000 –T1 substract $100 from A –T2 reads A with balance $900 –T1 aborts –T2 substract $200 from A –T2 stores A with balance $700 –T2 commits Problem: Balance should be $800 not $700

ICOM 6005Dr. Manuel Rodriguez Martinez20 Read-write conflicts Transaction T1 reads some object A, which is also read and modified by T2. When T1 reads A, the value has changed!!! –Called unrepeatable read Example: T1 and T2 access Bank account A –T1 reads A with balance $1000 –T1 checks balance > $500, goes to do other checks –T2 reads A with balance $1000 –T2 subtracts $700 –T2 writes A –T2 commits –T1 reads A again –T1 subtracts $500 from A –T1 writes A –T1 commits Balance is - $300.

ICOM 6005Dr. Manuel Rodriguez Martinez21 Write-Write Conflicts Transactions T1 reads object A, and T2 writes a new value to object A. T1 then writes A to the DB –Called a blind write Example: T1 and T2 access Bank account A –T1 reads A with balance $1000 –T2 sets A to $2000 –T2 writes A –T2 commits –T1 subtracts $500 from A –T1 writes A –T1 commits Balance is $500, but update from T2 is lost