advanced database systems
play

ADVANCED DATABASE SYSTEMS Transaction Models & Concurrency - PowerPoint PPT Presentation

Nov 16, 2022 •108 likes •1.49k views

Lect ure # 02 ADVANCED DATABASE SYSTEMS Transaction Models & Concurrency Control @ Andy_Pavlo // 15- 721 // Spring 2019 CMU 15-721 (Spring 2019) 2 Background Transaction Models Concurrency Control Protocols Isolation Levels CMU

  1. CMU 15-721 (Spring 2019) 17 N ESTED TRAN SACTIO NS Txn #1 BEGIN Sub-Txn #1.1 WRITE(A) BEGIN BEGIN Sub-Txn #1.1.1 WRITE(B) BEGIN BEGIN WRITE(C) COMMIT WRITE(D) ROLLBACK COMMIT

  2. CMU 15-721 (Spring 2019) 17 N ESTED TRAN SACTIO NS Txn #1 BEGIN Sub-Txn #1.1 WRITE(A) BEGIN BEGIN Sub-Txn #1.1.1 X WRITE(B) BEGIN BEGIN X WRITE(C) COMMIT X WRITE(D) ROLLBACK COMMIT

  3. CMU 15-721 (Spring 2019) 17 N ESTED TRAN SACTIO NS Txn #1 BEGIN Sub-Txn #1.1 ✓ WRITE(A) BEGIN BEGIN Sub-Txn #1.1.1 X WRITE(B) BEGIN BEGIN X WRITE(C) COMMIT X WRITE(D) ROLLBACK COMMIT

  4. CMU 15-721 (Spring 2019) 18 TRAN SACTIO N CH AIN S Multiple txns executed one after another. Combined COMMIT / BEGIN operation is atomic. → No other txn can change the state of the database as seen by the second txn from the time that the first txn commits and the second txn begins. Differences with savepoints: → COMMIT allows the DBMS to free locks. → Cannot rollback previous txns in chain.

  5. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 COMMIT BEGIN WRITE(C) ROLLBACK

  6. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 COMMIT BEGIN A WRITE(C) ROLLBACK

  7. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 COMMIT BEGIN A WRITE(C) ROLLBACK

  8. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 COMMIT BEGIN A B WRITE(C) ROLLBACK

  9. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 COMMIT BEGIN A B WRITE(C) ROLLBACK

  10. CMU 15-721 (Spring 2019) 19 TRAN SACTIO N CH AIN S Txn #1 BEGIN WRITE(A) Txn #2 COMMIT BEGIN READ(A) WRITE(B) Txn #3 ✓ ✓ COMMIT X BEGIN A B C WRITE(C) ROLLBACK

  11. CMU 15-721 (Spring 2019) 20 BULK UPDATE PRO BLEM These other txn models are nice, but they still do not solve our bulk update problem. Chained txns seems like the right idea but they require the application to handle failures and maintain its own state. → Has to be able to reverse changes when things fail.

  12. CMU 15-721 (Spring 2019) 21 CO M PEN SATIN G TRAN SACTIO N S A special type of txn that is designed to semantically reverse the effects of another already committed txn. Reversal has to be logical instead of physical. → Example: Decrement a counter by one instead of reverting to the original value.

  13. CMU 15-721 (Spring 2019) 22 SAGA TRAN SACTIO N S A sequence of chained txns T 1 – T n and compensating txns C 1 – C n-1 where one of the following is guaranteed: → The txns will commit in the order T 1 … T j ,C j …C 1 (where j < n) This allows the DBMS to support long-running, multi-step txns without application-managed logic SAGAS SIGMOD 1987

  14. CMU 15-721 (Spring 2019) 23 SAGA TRAN SACTIO N S Txn #1 Txn #2 Txn #3 BEGIN BEGIN BEGIN WRITE(A+1) WRITE(B+1) WRITE(C+1) COMMIT COMMIT

  15. CMU 15-721 (Spring 2019) 23 SAGA TRAN SACTIO N S Txn #1 Txn #2 Txn #3 BEGIN BEGIN BEGIN WRITE(A+1) WRITE(B+1) WRITE(C+1) COMMIT COMMIT

  16. CMU 15-721 (Spring 2019) 23 SAGA TRAN SACTIO N S Txn #1 Txn #2 Txn #3 BEGIN BEGIN BEGIN WRITE(A+1) WRITE(B+1) WRITE(C+1) COMMIT COMMIT Comp Txn #2 BEGIN WRITE(B-1) COMMIT

  17. CMU 15-721 (Spring 2019) 23 SAGA TRAN SACTIO N S Txn #1 Txn #2 Txn #3 BEGIN BEGIN BEGIN WRITE(A+1) WRITE(B+1) WRITE(C+1) COMMIT COMMIT Comp Txn #1 Comp Txn #2 BEGIN BEGIN WRITE(A-1) WRITE(B-1) COMMIT COMMIT

  18. CMU 15-721 (Spring 2019) 24 CO N CURREN CY CO N TRO L The protocol to allow txns to access a database in a multi-programmed fashion while preserving the illusion that each of them is executing alone on a dedicated system. → The goal is to have the effect of a group of txns on the database’s state is equivalent to any serial execution of all txns. Provides A tomicity + I solation in ACID

  19. CMU 15-721 (Spring 2019) 25 TXN IN TERN AL STATE Status → The current execution state of the txn. Undo Log Entries → Stored in an in-memory data structure. → Dropped on commit. Redo Log Entries → Append to the in-memory tail of WAL. → Flushed to disk on commit. Read/Write Set → Depends on the concurrency control scheme.

  20. CMU 15-721 (Spring 2019) 26 CO N CURREN CY CO N TRO L SCH EM ES Two-Phase Locking (2PL) → Assume txns will conflict so they must acquire locks on database objects before they are allowed to access them. Timestamp Ordering (T/O) → Assume that conflicts are rare so txns do not need to first acquire locks on database objects and instead check for conflicts at commit time.

  21. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Growing Phase Shrinking Phase

  22. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  23. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  24. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  25. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  26. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  27. CMU 15-721 (Spring 2019) 27 TWO - PH ASE LO CKIN G Txn #1 COMMIT BEGIN LOCK(A ) LOCK(A) READ(A) LOCK(B) LOCK(B) WRITE(B) UNLOCK(A) UNLOCK(B) Txn #2 COMMIT BEGIN LOCK(B) WRITE(B) LOCK(A) WRITE(A) UNLOCK(A) UNLOCK(B)

  28. CMU 15-721 (Spring 2019) 28 TWO - PH ASE LO CKIN G Deadlock Detection → Each txn maintains a queue of the txns that hold the locks that it waiting for. → A separate thread checks these queues for deadlocks. → If deadlock found, use a heuristic to decide what txn to kill in order to break deadlock. Deadlock Prevention → Check whether another txn already holds a lock when another txn requests it. → If lock is not available, the txn will either (1) wait, (2) commit suicide, or (3) kill the other txn.

  29. CMU 15-721 (Spring 2019) 29 TIM ESTAM P O RDERIN G Basic T/O → Check for conflicts on each read/write. → Copy tuples on each access to ensure repeatable reads. Optimistic Currency Control (OCC) → Store all changes in private workspace. → Check for conflicts at commit time and then merge.

  30. CMU 15-721 (Spring 2019) 30 BASIC T/ O Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A)

  31. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A)

  32. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10000 10000 B 10000 10000

  33. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10000 10000 B 10000 10000

  34. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10001 10000 B 10000 10000

  35. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10001 10000 B 10000 10000

  36. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10001 10000 B 10000 10001

  37. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10001 10005 B 10000 10001

  38. CMU 15-721 (Spring 2019) 30 BASIC T/ O 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(B) WRITE(A) Read Write Record Timestamp Timestamp A 10001 10005 B 10000 10001

  39. CMU 15-721 (Spring 2019) 31 O PTIM ISTIC CO N CURREN CY CO N TRO L Timestamp-ordering scheme where txns copy data read/write into a private workspace that is not visible to other active txns. When a txn commits, the DBMS verifies that there are no conflicts. First proposed in 1981 at CMU by H.T. Kung. ON OPTIMISTIC METHODS FOR CONCURRENCY C CONTROL ACM T TRANSACTIONS ON DATABASE S SYSTEMS 1981

  40. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Write Record Value Timestamp A 123 10000 B 456 10000

  41. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Read Phase Write Record Value Timestamp A 123 10000 B 456 10000

  42. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Write Record Value Timestamp A 123 10000 B 456 10000

  43. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Workspace Write Write Record Value Record Value Timestamp Timestamp A 123 10000 A 123 10000 B 456 10000

  44. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Workspace Write Write Record Value Record Value Timestamp Timestamp A 123 10000 A 123 10000 B 456 10000

  45. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 123 888 10000 A 123 10000 B 456 10000

  46. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 888 123 10000 A 123 10000 B 456 10000 B 456 10000

  47. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 123 888 10000 A 123 10000 ∞ 999 B 456 10000 B 456 10000

  48. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) VALIDATE PHASE WRITE PHASE Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 888 123 10000 A 123 10000 ∞ 999 B 456 10000 B 456 10000

  49. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) VALIDATE PHASE WRITE PHASE Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 888 123 10000 A 123 10000 ∞ 999 B 456 10000 B 456 10000

  50. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) VALIDATE PHASE WRITE PHASE Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 888 123 10000 A 123 10000 ∞ 999 B 456 10000 B 456 10000

  51. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) VALIDATE PHASE WRITE PHASE Workspace Write Write Record Value Record Value Timestamp Timestamp ∞ A 888 123 10000 A 123 888 10000 10001 ∞ 999 999 10001 B 456 10000 B 456 10000

  52. CMU 15-721 (Spring 2019) 32 O PTIM ISTIC CO N CURREN CY CO N TRO L 10001 Txn #1 COMMIT BEGIN READ(A) WRITE(A) WRITE(B) VALIDATE PHASE WRITE PHASE Write Record Value Timestamp A 123 888 10000 10001 999 10001 B 456 10000

  53. CMU 15-721 (Spring 2019) 33 O BSERVATIO N When there is low contention, optimistic protocols perform better because the DBMS spends less time checking for conflicts. At high contention, the both classes of protocols degenerate to essentially the same serial execution.

  54. CMU 15-721 (Spring 2019) 34 CO N CURREN CY CO N TRO L EVALUATIO N Compare in-memory concurrency control protocols at high levels of parallelism. → Single test-bed system. → Evaluate protocols using core counts beyond what is available on today's CPUs. Running in extreme environments exposes what are the main bottlenecks in the DBMS. STARING INTO THE ABYSS: AN EVALUATION OF CONCURRENCY CONTROL W WITH ONE THOUSAND CORES VLDB 2014

  55. CMU 15-721 (Spring 2019) 35 10 0 0 - CO RE CPU SIM ULATO R DBx1000 Database System → In-memory DBMS with pluggable lock manager. → No network access, logging, or concurrent indexes MIT Graphite CPU Simulator → Single-socket, tile-based CPU. → Shared L2 cache for groups of cores. → Tiles communicate over 2D-mesh network.

  56. CMU 15-721 (Spring 2019) 36 TARGET WO RKLOAD Yahoo! Cloud Serving Benchmark (YCSB) → 20 million tuples → Each tuple is 1KB (total database is ~20GB) Each transactions reads/modifies 16 tuples. Varying skew in transaction access patterns. Serializable isolation level.

Recommend

Lect ure # 11 ADVANCED DATABASE SYSTEMS System Catalogs and Database Compression @

Lect ure # 11 ADVANCED DATABASE SYSTEMS System Catalogs and Database Compression @

Lect ure # 11 ADVANCED DATABASE SYSTEMS System Catalogs and Database Compression @ Andy_Pavlo // 15- 721 // Spring 2018 DATABASE TALK Oracle In-Memory Database Engine Monday February 26 th @ 4:30pm GHC 4401

709 views • 60 slides
Lect ure # 01 ADVANCED DATABASE SYSTEMS Course Introduction &amp; History of Database Systems

Lect ure # 01 ADVANCED DATABASE SYSTEMS Course Introduction &amp; History of Database Systems

Lect ure # 01 ADVANCED DATABASE SYSTEMS Course Introduction &amp; History of Database Systems @ Andy_Pavlo // 15- 721 // Spring 2018 2 WH Y YO U SH O ULD TAKE TH I S CO URSE DBMS developers are in demand and there are many challenging

912 views • 66 slides
15-721 ADVANCED DATABASE SYSTEMS Lecture #01 Course Introduction &amp; History of Database

15-721 ADVANCED DATABASE SYSTEMS Lecture #01 Course Introduction &amp; History of Database

15-721 ADVANCED DATABASE SYSTEMS Lecture #01 Course Introduction &amp; History of Database Systems @Andy_Pavlo // Carnegie Mellon University // Spring 2017 Who are the richest people in the world? 3 WHY YOU SHOULD TAKE THIS COURSE

1.21k views • 67 slides
Advanced Database Management Systems Database Management Systems Alvaro A A Fernandes School of

Advanced Database Management Systems Database Management Systems Alvaro A A Fernandes School of

Advanced Database Management Systems Database Management Systems Alvaro A A Fernandes School of Computer Science, University of Manchester AAAF (School of CS, Manchester) Advanced DBMSs 2011-2012 1 / 144 Outline Database Management Systems:

2.09k views • 144 slides
Advanced Database CS 525: Organization? Advanced Database =Database Implementation

Advanced Database CS 525: Organization? Advanced Database =Database Implementation

Advanced Database CS 525: Organization? Advanced Database =Database Implementation Organization =How to implement a database system and have fun doing it ;-) 01: Introduction Boris Glavic Slides: adapted from a course taught by

199 views • 7 slides
ADVANCED DATABASE SYSTEMS Database Compression @ Andy_Pavlo // 15- 721 // Spring 2019 CMU

ADVANCED DATABASE SYSTEMS Database Compression @ Andy_Pavlo // 15- 721 // Spring 2019 CMU

Lect ure # 10 ADVANCED DATABASE SYSTEMS Database Compression @ Andy_Pavlo // 15- 721 // Spring 2019 CMU 15-721 (Spring 2019) 2 UPCO M IN G DATABASE EVEN TS Splice Machine Tech Talk Thursday Feb 21 st @ 12:00pm CIC 4 th Floor

1.11k views • 73 slides
CSE 736: Advanced Topics in Database Systems YINGJING YAN

CSE 736: Advanced Topics in Database Systems YINGJING YAN

CSE 736: Advanced Topics in Database Systems YINGJING YAN INTRODUCTION Chabot is a picture retrieval system for a database that will eventually

811 views • 47 slides
CS 61: Database Systems Advanced SQL Adapted from https://www.mysqltutorial.org/ unless

CS 61: Database Systems Advanced SQL Adapted from https://www.mysqltutorial.org/ unless

CS 61: Database Systems Advanced SQL Adapted from https://www.mysqltutorial.org/ unless otherwise noted Review: database schema has tables for Restaurants and Inspections (and others) use nyc_inspections; One entry for each restaurant One

392 views • 23 slides
DATABASE SYSTEMS Database programming in a web environment Database System Course AGENDA FOR

DATABASE SYSTEMS Database programming in a web environment Database System Course AGENDA FOR

DATABASE SYSTEMS Database programming in a web environment Database System Course AGENDA FOR TODAY The final project Advanced Mysql Database programming Recap: DB servers in the web Web programming architecture HTTP on a need-to-know basis.

688 views • 54 slides
ADVANCED DATABASE SYSTEMS Optimizer Implementation (Part III) @ Andy_Pavlo // 15- 721 //

ADVANCED DATABASE SYSTEMS Optimizer Implementation (Part III) @ Andy_Pavlo // 15- 721 //

Lect ure # 21 ADVANCED DATABASE SYSTEMS Optimizer Implementation (Part III) @ Andy_Pavlo // 15- 721 // Spring 2020 2 O BSERVATIO N The best plan for a query can change as the database evolves over time. Physical design changes.

517 views • 47 slides
ADVANCED DATABASE SYSTEMS Self-Driving Database Management Systems @ Andy_Pavlo // 15- 721 //

ADVANCED DATABASE SYSTEMS Self-Driving Database Management Systems @ Andy_Pavlo // 15- 721 //

Lect ure # 25 ADVANCED DATABASE SYSTEMS Self-Driving Database Management Systems @ Andy_Pavlo // 15- 721 // Spring 2019 CMU 15-721 (Spring 2019) 2 Autonomous DBMS History Self-Driving DBMSs Learned Components CMU 15-721 (Spring 2019) 3

918 views • 55 slides
DATABASE SYSTEMS Database programming in a web environment Database System Course, 2016-2017

DATABASE SYSTEMS Database programming in a web environment Database System Course, 2016-2017

DATABASE SYSTEMS Database programming in a web environment Database System Course, 2016-2017 AGENDA FOR TODAY The final project Advanced Mysql Database programming Recap: DB servers in the web Web programming architecture HTTP on a

845 views • 53 slides
ADVANCED DATABASE SYSTEMS Recovery Protocols @ Andy_Pavlo // 15- 721 // Spring 2019 CMU

ADVANCED DATABASE SYSTEMS Recovery Protocols @ Andy_Pavlo // 15- 721 // Spring 2019 CMU

Lect ure # 12 ADVANCED DATABASE SYSTEMS Recovery Protocols @ Andy_Pavlo // 15- 721 // Spring 2019 CMU 15-721 (Spring 2019) 2 DATABASE RECOVERY Recovery algorithms are techniques to ensure database consistency , atomicity and durability

1.05k views • 50 slides
Lect ure # 24 ADVANCED DATABASE SYSTEMS Databases on New Hardware @ Andy_Pavlo // 15- 721 //

Lect ure # 24 ADVANCED DATABASE SYSTEMS Databases on New Hardware @ Andy_Pavlo // 15- 721 //

Lect ure # 24 ADVANCED DATABASE SYSTEMS Databases on New Hardware @ Andy_Pavlo // 15- 721 // Spring 2018 2 ADM IN ISTRIVIA Snowflake Guest: May 2 th @ 3:00pm Final Exam Handout: May 2 nd Code Review #2: May 2 nd @ 11:59pm We will use the

1.01k views • 73 slides
ADVANCED DATABASE SYSTEMS Multi-Version Concurrency Control (Garbage Collection) @ Andy_Pavlo

ADVANCED DATABASE SYSTEMS Multi-Version Concurrency Control (Garbage Collection) @ Andy_Pavlo

Lect ure # 05 ADVANCED DATABASE SYSTEMS Multi-Version Concurrency Control (Garbage Collection) @ Andy_Pavlo // 15- 721 // Spring 2020 2 M VCC GARBAGE CO LLECTIO N A MVCC DBMS needs to remove reclaimable physical versions from the database

1.46k views • 57 slides
15-721 ADVANCED DATABASE SYSTEMS Lecture #11 Database Compression Andy Pavlo / / Carnegie

15-721 ADVANCED DATABASE SYSTEMS Lecture #11 Database Compression Andy Pavlo / / Carnegie

15-721 ADVANCED DATABASE SYSTEMS Lecture #11 Database Compression Andy Pavlo / / Carnegie Mellon University / / Spring 2016 @Andy_Pavlo // Carnegie Mellon University // Spring 2017 2 TODAYS AGENDA Background Nave Compression

827 views • 57 slides
ADVANCED DATABASE SYSTEMS Parallel Join Algorithms (Sorting) @ Andy_Pavlo // 15- 721 //

ADVANCED DATABASE SYSTEMS Parallel Join Algorithms (Sorting) @ Andy_Pavlo // 15- 721 //

Lect ure # 18 ADVANCED DATABASE SYSTEMS Parallel Join Algorithms (Sorting) @ Andy_Pavlo // 15- 721 // Spring 2020 2 PRO J ECT # 2 This Week Status Meetings Wednesday April 8 th Code Review Submission Update Presentation

819 views • 65 slides
Distributed Transaction Management Advanced Topics in Database Management (INFSCI 2711) Some

Distributed Transaction Management Advanced Topics in Database Management (INFSCI 2711) Some

Distributed Transaction Management Advanced Topics in Database Management (INFSCI 2711) Some materials are from Database Management Systems, Ramakrishnan and Gehrke and Database System Concepts, Siberschatz, Korth and Sudarshan and Data

515 views • 24 slides
Advanced Database Management Systems Distributed DBMS:Introduction and Architectures Alvaro A A

Advanced Database Management Systems Distributed DBMS:Introduction and Architectures Alvaro A A

Advanced Database Management Systems Distributed DBMS:Introduction and Architectures Alvaro A A Fernandes School of Computer Science, University of Manchester AAAF (School of CS, Manchester) Advanced DBMSs 2011-2012 1 / 121 Outline

1.35k views • 121 slides
ADVANCED DATABASE SYSTEMS Query Execution &amp; Processing @ Andy_Pavlo // 15- 721 // Spring

ADVANCED DATABASE SYSTEMS Query Execution &amp; Processing @ Andy_Pavlo // 15- 721 // Spring

Lect ure # 13 ADVANCED DATABASE SYSTEMS Query Execution &amp; Processing @ Andy_Pavlo // 15- 721 // Spring 2020 2 ARCHITECTURE OVERVIEW Networking Layer SQL Query SQL Parser Planner Binder Rewriter Optimizer / Cost Models Compiler

881 views • 51 slides
Overview of Database Systems CS3860 - Jay Urbain, PhD Introduction to Database Systems 1 2 UFR

Overview of Database Systems CS3860 - Jay Urbain, PhD Introduction to Database Systems 1 2 UFR

Overview of Database Systems CS3860 - Jay Urbain, PhD Introduction to Database Systems 1 2 UFR Uniform Financial Report (I think) What is a database? 3 What is a database? Collection of data Files, notes, to do list, patient records,

1.13k views • 26 slides
Advanced Database Technologies Advanced Database Technologies in a Diabetic Healthcare System in

Advanced Database Technologies Advanced Database Technologies in a Diabetic Healthcare System in

Advanced Database Technologies Advanced Database Technologies in a Diabetic Healthcare System in a Diabetic Healthcare System Wynne Hsu, Mong Li Lee, Beng Chin Ooi, Pranab Kumar Mohanty, Keng Lik Teo, Chenyi Xia National University of

444 views • 7 slides
Advanced Database Management Systems Query Processing: Query Evaluation Alvaro A A Fernandes

Advanced Database Management Systems Query Processing: Query Evaluation Alvaro A A Fernandes

Advanced Database Management Systems Query Processing: Query Evaluation Alvaro A A Fernandes School of Computer Science, University of Manchester AAAF (School of CS, Manchester) Advanced DBMSs 2012-2013 1 / 111 Outline Algorithmic

1.23k views • 111 slides
Data Linkage Advanced Topics in Database Management (INFSCI 2711) Some materials are from

Data Linkage Advanced Topics in Database Management (INFSCI 2711) Some materials are from

Data Linkage Advanced Topics in Database Management (INFSCI 2711) Some materials are from Similarity Joins in Relational Database Systems, Augsten and Bohlen and Semantic Web for Working Ontologists, Allemang and Hendler Vladimir Zadorozhny,

277 views • 14 slides

More recommend