Adv Dbase Sys
Adv Dbase Sys EECS 584
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This 8 page Class Notes was uploaded by Ophelia Ritchie on Thursday October 29, 2015. The Class Notes belongs to EECS 584 at University of Michigan taught by Kristina Lefevre in Fall. Since its upload, it has received 72 views. For similar materials see /class/231522/eecs-584-university-of-michigan in Engineering Computer Science at University of Michigan.
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Date Created: 10/29/15
An Evaluation of Buffer Management Strategies for Relational Database Systems HongTai Chou David J Dewitt I Ijl I Presenter Anfal Ashkanani Instructor Kristen Lefevre umma EECSSN FallZDDE 1 Motivation I Conventional virtual memory page replacement algorithms are not suitable forthe relational database environment I Previous work gave limited results Extensive multi user testing and replacement policies is needed umma Escssao relzum 2 Why don t Virtual memory replacement algorithms work Buffer Size l5 4 Loop lolrl query lnner loop page accesses scanned lemes r l 2 3 4 5 LRU MRU First 4 accesses lmll mu 3 eesss mlss miss accessl mss acres access 3 access4 1 2 l5 miss access J 5 mm sscssmmzom 3 hIIIuud hImI ui hIIIId Another example Buffer SlZelS 3 Merge loin l Clusterl scanned twice ClusterZ scanned Mice r l 2 3 r 4 5 E First E accesses es 1 1 J inis access 5 miss access E quotH miss acci2554 ll 4 was access 5 miss access E miss mama EEcssm Faiizuua Previous Work Dumain Separatiuri Algurithms 7 Pages classified mm types each separately managed in its assuciated dumainufbulfevs e Piublems Dues nut a quoteventiate the relative impanance between a Nerethes atpages Memavvpamtianmg NEW Algurithm pviuvity e Pvublems Emmian Frialmavianvemembasedanmmman ta matinee mm natclui Ell set e lntegvales advance knuwledge ufvefevence patterns mm query behaviuv mudel r Pmblems mummiesleapinvsemmeem u cs Sat Fall 2qu hIIIId hImI ui Query Locality Set Model I Relational database operations have predictable pattern of page references I Separate model of referencing behavior from buffer management algorithm I Page reference pattern determined for each le instance umma EECSSE iFallZUUE ilnl QLSM l l I l Straight Idependt Straight Sequential r Lopin 88 IR SH LH Clustered Cluster Straight CS CR HSS Looping Clustered LS HICS 102708 EECS 584 Fall 2008 7 inn QLSM Policies ality Set Size SS 1 CS FIFO or LRU it ofrecords in clusterrecords per P LS MRU pages in le IR any 1 or b CR any t Ofrecords l largest cluster SH 1 HSS 1 HCS FIFO orLRU it ofrecords in cluste39rHtrecords per page LH LIFO if4 12le N4 0 estmated number or pages referenced 102708 EEcs 584 Fall 2008 8 Iml Buffer Manager DBMIN I Based on model of relational query behavior Query Locality Set Model QLSM I Buffers allocated and managed on a per le instance basis Locality set buffered pages associated with 39file I Data Sharing through global buffer table 102708 EECS 584 Fall 2008 ImInd DBMIN Algorithm I Initialize global table I On le openclose Locality Set Size l Selected by OLSM Replacement policy 0 Open Activate load controller I On query page request search global table Page found Page in memory not in locality set Page not in memory iumma EECSSE iFallZDDE 1D Performance Evaluation I Hybrid simulation model ace driven 7 Distribution driven I Performance measure 7 Throughput average number or queries per second I Buffer Management Algorithms 7 Glo al RAND FlFO CLOCK 7 Local DEMlN WS HOT i l iumma EECSSE iFellZDDE ii InnIII hImIId Simulation Model I Queries can run concurrently Round Robin used for allocating CPU cles I Queries selected CPU demand Disk demand Memory demand iumma EECSSE iFallZDDE 2 iImInq Simulation Model Query Types I Different workloads consisting of mixture of query types are run lm M EECS 584 Fall 2008 l02708 ll Simulation Results Test 1 no data sharing no load control mmumwur a 5n mm mg ml m inhuman u 12 m a mum m Ma no Huirams no rum alumna 20 a a 2 nu ma amass Nu pm smmc a cum mx l02708 EECS 584 Fall 2008 him Simulation Results Test 2 with data sharing no load control muuaum nM 39 29quot v W a 03m 3507 050 050 040 m and quotq n n n4aleuzazszaaz 04I12x520242532 QUERY MIX 1H X00 EUFFERS HALF DATA SHARiNG QUERY I x 1 OD ammms FULL DATA SHARING I Shows increase in throughput for all algorithms l02708 EECS 584 Fall 2008 l5 What Goes Around Comes Around Michael Stonebraker Joey Hellerstein I Iquot I Presenter Jim Steinberger Discussion Ashwin Professor Kristen Lefevre Msua Escssawalzuua l Paper Overview I Primary Contribution Survey of Data Models History amp Evolution I Also presents opinions for discussion Presents lessons to learn from past data models We ll brie y discuss important lessons Does XML repeat history in a bad way mm Escssawslzuua 2 Hierarchical Tree IMS 1968 I Hierarchical model I Overview Record types arranged as hierarchy Each type has single parent I Problems next 3 slides The DL1 acc ss language offers littleno logicalphysical data independence A record may only exist if its parent does Potential redundancies mm Escssawalzuua 3 InnInd hlmIui ilml Hierarchical Tree IMS 1968 I DL l Programming language for accessing IMS Different underlying storage formats different restrictions on commands Heavy coupling between storage format used sequentialBtreehashed and client applications Thus poor physical data independence Different sets of data different optimization opportunities Optimization is performed by programmer 11508 EECS 584 Fall 2008 4 him Lesson 1 Physical Logical data independence good I Lifespan of data lt Lifespan of apps I Changes to physicallogical data should not require changes to apps ideally should not require expensive changes to apps Hence independencequot 11508 EECS 584 Fall 2008 5 inn Lesson 2 Treestructured models are restrictive TreeRoot supplier Redundant pan entries TreeRoot Pan Supplier silo suamei sen ssmte Part 1110 puame pstze pco 01 Redundant supplier entries Part p110 pnnme psize pcolor qn Supplier o Suppliers cannot exist wrinout parts EECS 584 Fall 2008 6 Pans cannot exist vilhom suppliers 11508
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