Talk on Database (ja)

筑波大学の2013年度の情報システム特別講義Dのスライド

Transcript

1. σʔλϕʔεͷ͸ͳ͠
   Basho Japan KK
   Kota UENISHI
   2014/1/31
   

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2. ͲͪΒ༷Ͱ͔͢ʁ
   •  @kuenishi
   
   •  NTTݚڀॴ ˠ Basho
   
   •  Erlang/OTPΛॻ͍ͯ࢓ࣄΛ͍ͯ͠·͢
   
   •  ෼ࢄσʔλϕʔεɾ෼ࢄγεςϜͷ঎༻։ൃྺ 6೥
   
   •  ϛυϧ΢ΣΞతͳ΋ͷ͕ൺֱతಘҙͰ͢
   
   

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3. •  Riakͱ͍͏OSSͷ෼ࢄσʔλϕʔε
   Λ࡞ͬͯച͍ͬͯ·͢
   
   •  Riak CSͱ͍͏OSSͷΫϥ΢υετ
   ϨʔδΛ࡞ͬͯଧ͍ͬͯ·͢
   
   •  ʮ෼ࢄਥʯΧϯϑΝϨϯεRicon.io
   
   •  Basho.com
   
   3
   
   

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4. ͖͔͚ͬ
   4
   
   தུ
   
   ʮ಺༰ͱͯ͠͸riakͱ
   
   ɹNoSQLΛؚΊͯ
   
   ɹ௖͚ͨΒʯ
   
   

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5. ࠓ೔͓΅͑ͯ΋Β͏͜ͱ
   •  NoSQL͸όζϫʔυͰ͋Γɺఆٛ͸ͳ͍
   
   •  ͍Ζ͍ΖͳσʔλετΞͱͦͷ෼ྨɺ࢖͍෼͚ͷίπ
   
   •  ෼ࢄγεςϜ΍σʔλϕʔεपลͷ໰୊ɺ၆ᛌਤ
   
   •  Riak͸ૉ੖Β͍͠σʔλϕʔεͰ͋Δ
   
   

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6. ͦ΋ͦ΋
   σʔλϕʔεͱ͸Կʁ
   •  ΞϓϦέʔγϣϯͷσʔλΛίϯϐϡʔλʹอଘ͢Δ
   ͨΊͷιϑτ΢ΣΞʢϥΠϒϥϦ or αʔόʔʣ
   
   6
   
   01010110100001001011
   11001010101010100101
   01001010101001010100
   10101010010111111110
   00000101111100101010
   00000010010101001001
   01001010010010100
   
   

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7. อଘ͢Δͱ͖ͷཁٻ
   •  σʔλΛਖ਼͘͠ॻ͖ࠐΉ͜ͱɺσʔλͷߋ৽͕த్൒
   ୺ͳঢ়ଶͰࣦഊ͠ͳ͍͜ͱ
   
   •  ॻ͖ࠐΜͩσʔλΛਖ਼͘͠ಡΈग़͢͜ͱ
   
   •  ॻ͖ࠐΜͩσʔλΛผܗࣜʹม׵ͯ͠ಡΈͩ͢͜ͱ
   
   •  ϋʔυ΢ΣΞੑೳͷݶք·Ͱߴ଎ʹอଘ͢Δ͜ͱ
   
   •  ϋʔυ΢ΣΞੑೳͷݶք·Ͱߴ଎ʹಡΈग़͢͜ͱ
   
   •  σʔλ͕ফ͑Δ৚͕݅ਖ਼֬ʹ൑໌͍ͯ͠Δ͜ͱ
   
   7
   
   

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8. ྺ্࢙ͷσʔλϕʔε
   •  IDS (GE, 1963)
   
   •  ֊૚ܕDB
   
   •  IMS (IBM, 1966 -),
   
   •  ωοτϫʔΫܕDB
   
   •  CODASYL (1969, COBOL),
   
   •  ࠓ΋ಈ͍͍ͯΔ੡඼΋͋Δ
   
   8
   
   

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9. 1977೥ System R (IBM)
   •  ؔ܎୅਺ͷཧ࿦ʹج͍ͮͨσʔλૢ࡞ݴޠ
   SQLΛ࣮૷ͨ͠ੈքॳͷσʔλϕʔε
   
   •  Ұ؏ͨ͠σʔλʹର͢Δෳ਺ͷૢ࡞Λશͯ
   ੒ޭɾશࣦͯഊʹ·ͱΊɺෳ਺ͷߋ৽ཁٻ
   Λฒߦ੍ޚ͠ɺσʔλΛӬଓԽ͢Δτϥϯ
   βΫγϣϯॲཧΛ࣮૷ͨ͠ੈքॳͷσʔλ
   ϕʔε
   
   •  ۀ຿ॲཧͷϞσϧʹඇৗʹΑ͘Ϛονͨ͠
   ͨΊɺരൃతʹීٴɹˠISOͰඪ४Խ
   
   •  1983೥ Oracle v3
   
   •  1987೥ Sybase SQL Server (ݱMicrosoft SQL
   Server)
   9
   
   

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10. ͸͡Ί͔ΒSQLͩͬͨΘ͚Ͱ΋ϦϨʔγϣφϧ
    ͩͬͨΘ͚Ͱ΋ͳ͍
    ͭ·Γ…
    
    10
    
    

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11. RDBMSͷ࣌୅
    •  ACIDಛੑʹج͍ͮͨτϥϯβΫγϣϯ؅ཧ
    •  SQLͱ͍͏౷Ұ͞ΕͨΠϯλʔϑΣʔε
    
    •  ੈքதͷΤϯλʔϓϥΠζͷσʔλ؅ཧ͸ΦϑΟεͷOA
    ԽɾγεςϜͷΦʔϓϯԽʹ൐͍RDBMS͕ओྲྀʹ
    
    •  εέʔϧΞοϓͷ࣌୅Ͱ΋͋Δ
    
    •  1995೥ͷHDDͷGB୯Ձ: ~7.5ສԁ/ GB
    
    11
    
    

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12. •  2003೥ʙɹITόϒϧ่յޙ
    
    •  Ոఉ༻ίϯϐϡʔλɺϒϩʔυόϯυͷීٴ
    
    •  Web 2.0ɺϒϩάɺWikipediaɺEϝʔϧɺWebݕࡧɺEC
    
    •  1998೥ Google૑ۀ
    
    •  1995೥ Amazon૑ۀ
    
    •  “Web Scale” ͷσʔλྔ
    
    12
    
    Webͷ࣌୅
    

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13. •  ٻΊΒΕΔ͜ͱ͕มԽ: ߏ଄͸؆୯Ͱ΋ɺྔ΍τϥ
    ϑΟοΫɺϨεϙϯεɺՄ༻ੑͳͲͷཁٻ͕ଟ༷
    Խɾߴ౓Խ
    
    •  σʔλͷ୯Ձ͕͍҆etc
    
    •  RDBMSͰ͸ղܾͰ͖ͳ͍Φʔμʔ·Ͱσʔλྔ͕
    ૿Ճ͢ΔʹैͬͯɺͦΕΛղܾ͢Δٕज़͕ొ৔
    
    •  ؔ܎ϞσϧɺSQLͰ͸ѻ͍ʹ͍͘σʔλϞσϧʢ୯
    ७͕ͩΑ͘มԽ͢Δσʔλߏ଄ʣ
    
    •  2003೥ͷHDDͷGB୯Ձ: 100ԁ / GBɹ(120GB)
    
    13
    
    “Web Scale”
    

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14. Web Scale΁ͷΞϓϩʔν
    •  Ոఉ༻ίϯϐϡʔλͱಉ͡HW
    
    •  LAMP + Memcached(2003)
    
    •  Redis (2009)
    
    •  Google: GFS(2003), BigTable(2006)
    
    •  Hadoop (2006), HBase (2006)
    
    •  Amazon: Dynamo(2006)
    
    •  Cassandra (2008), Riak (2009)
    
    14
    
    

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15. ຊ౰ʹղ͖͍ͨ໰୊
    15
    
    

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16. εέʔϦϯάͷ໰୊
    16
    
    

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17. εέʔϦϯάͷํ๏
    •  ෳ਺୆ͷϊʔυʹσʔλΛ෼ࢄอ࣋ͯ͠ྔΛՔ͙
    
    •  ʮͲͷσʔλ͕Ͳͷαʔόʔʹೖ͍ͬͯΔ͔ʁʯ
    
    17
    
    

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19. ϋογϡతϧʔςΟϯά
    •  Riak, Cassie,
    DynamoͳͲ
    
    •  Կ͕Ͳ͜ʹ͋Δ͔
    Θ͔Γʹ͍͘
    
    •  εέʔϧΞ΢τɺ
    ෛՙ෼ࢄ͕؆୯
    
    19
    
    node1
    node2
    node3
    node4
    

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20. “ϋογϡత”
    •  ΩʔͱϊʔυIDΛϋογϡԽͯ͠ಉ໊͡લۭؒʹஔ͘
    
    •  ϋογϡͷ୯ҐͰσʔλΛ෼ׂͯ͠഑ஔ
    
    •  ϊʔυ௥Ճɾ࡟আͷͱ͖ͷσʔλ࠶഑ஔΛ࠷খݶʹͰ
    ͖Δ
    
    20
    
    {foo, SomeData}!
    Hash(foo)%N!
    Hash(node1)%N!
    

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21. 21
    
    Locality vs Load
    Balancing - Use Cases
    • ઌಡΈΛޮ͔ͤͯόϧΫͰγʔέϯγϟϧΞ
    Ϋηε
    • - HBase, BigTable, etc
    • ϋογϡͰ෼ࢄͤͯ͞ෛՙ෼ࢄͯ͠ϥϯμϜ
    ΞΫηε
    • - Riak, Cassie, etc
    

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22. ੔߹ੑͷ໰୊
    22
    
    

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23. Q. ੔߹ੑͬͯͳΜͩͱ
    ͓΋͍·͔͢ʁ
    23
    
    

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24. ੔߹ੑʹ͸2ͭͷจ຺͕͋Δ
    •  ڞ௨͢Δͷ͸ʮ୭͕ݟͯ΋ಉ͡Α͏ʹݟ͑Δ͜ͱʯ
    
    •  ෳ਺छྨͷσʔλؒͷInvariant͕कΒΕ͍ͯΔ͜ͱ
    
    •  “ACID” తͳAnomaly͕ൃੜ͠ͳ͍͜ͱ
    
    •  Phantom Read, Write Skew, etc etc…
    
    •  ෳ਺ͷσʔλͷίϐʔ͕ಉ͡Ͱ͋Δ͜ͱ
    
    •  ෳ਺ͷίϐʔΛ҆શʹߋ৽Ͱ͖Δ͜ͱ
    
    •  ผʑͷਓͰ΋ಉ͡σʔλΛݟΕ͍ͯΔ͜ͱ
    
    

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25. 25
    
    Consistent Replication
    is Difficult
    • ϨϓϦέʔγϣϯ͸ॱ൪͕ೖΕସΘΔ
    • CPUͷΞ΢τΦϒΦʔμʔ࣮ߦͱಉ͡
    w1
    w1
    w1
    w2
    w2
    w2
    Actor 0
    Actor 1
    Actor 2
    w2
    w2
    w1
    

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26. ෼ࢄ߹ҙ໰୊
    •  ʮෳ੡͕͢΂ͯಉ͡Ͱ͋Δʯ
    
    •  ʹʮશһ͕ͻͱͭͷ஋ʹ߹ҙͰ͖͍ͯΔঢ়ଶʯ
    
    •  ΞϠγ͍ಈ࡞Λ͢ΔՄೳੑ͕͋Δ΋ͷ
    
    •  ωοτϫʔΫ
    
    •  ߹ҙ͢Δ૬ख
    
    •  ੍ݶ࣌ؒɿແݶ
    
    26
    
    

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27. ·͡Ίʹॻ͘ͱ…
    •  ͍ͭͰ΋յΕΔՄೳੑͷ͋Δෳ਺ͷϊʔυ͕ɺ
    
    •  յΕͯ·ͨ෮ؼ͢ΔՄೳੑ΋͋Δ
    
    •  ฦࣄ͕஗͍͚ͩͷ৔߹΋
    
    •  ৴པੑͷ௿͍ϊʔυؒ௨৴Λ࢖ͬͯ
    
    •  ΋ͷ͘͢͝஗Ԇ͍ͯ͠Δ͚Ͳ࣮͸ಧ͘
    
    •  ͻͱͭͷ஋Λ߹ҙ͢ΔʢͷʹͲͷΑ͏ͳ৚݅ͱϓϩτ
    ίϧ͕͋Ε͹Α͍͔ʁʣ
    
    27
    
    

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28. ͳͥ೉͍͠ͷ͔
    •  ࢮ׆؂ࢹ͕೉͍͠
    
    •  ϦʔμʔΛఘΊΔɺϚελʔΛఘΊΔɺetc
    
    •  ࢳి࿩Ͱࢮ׆؂ࢹ͢Δ࿅श
    
    •  ނোϞσϧͷ͸ͳ͕͍͠Ζ͍Ζ͋Δ
    
    28
    
    

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29. ࢮ׆؂ࢹ͸೉͍͠
    •  ʮࢮΜͩ͜ͱʯΛਖ਼͘͠ݟ͚ͭΔͷ͸೉͍͠
    
    •  ࣮ݧʢ͕࣌ؒ͋Ε͹ʣ
    
    29
    
    

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30. ʮࢮΜͰ͍Δʯ is Կ
    30
    
    © ʮ๺ేͷݓʯݪ఩෉ɺ෢࿦ଚ
    
    
    
    

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31. ނোతࠔΔ͜ͱͷ෼ྨ
    Crash Failure
    
    ɹ (fail-stop, fail-safe)
    
    ނোͨ͠Βࢭ·Δɺࢭ·ͬͨ͜ͱ͕͢
    ͙ʹ෼͔Δ
    
    Crash Failure (fail-silent)
    ໧ͬͯࢮ͵
    
    Crash Recovery
    ނোͨ͠ϑϦͯ͠஌ΒΜ΀Γͯ͠ؼͬͯ
    ͘Δ
    
    Omission Failure
    (receive / send)
    
    ϝοηʔδܽམ
    
    Timing Failure
    ·ͱ΋ͳ଎౓Ͱಈ͔ͳ͘ͳΔ
    
    Response Failure
    Ϩεϙϯε͕͓͔͍͠ʢσʔλ͕յΕͯ
    ͍Δetcʣ
    
    Arbitrary Failure
    Ϗβϯνϯނোɺѱҙͷ͋ΔϠπ͕͍Δ
    
    31
    
    

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32. ෼ࢄ߹ҙͷछྨ
    •  ʮΞτϛοΫϒϩʔυΩϟετϓϩτίϧʯ
    
    •  ͓͓·͔ʹ͍ͬͯ෼ࢄ߹ҙ͢ΔͨΊͷϓϩτίϧΛ
    ૯শͯ͠
    
    •  ΞτϛοΫ͡Όͳ͍ϒϩʔυΩϟετ΋୔ࢁ͋ͬͯͦ
    ΕͳΓʹಈ͍͍ͯΔ
    
    •  ୅දతͳ΋ͷPaxos, Rafter, ZAB
    
    32
    
    

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33. 33
    
    Consensus Based
    Replication
    • ϨϓϦέʔγϣϯͷϦʔμʔΛଟ਺ܾͰબग़
    • or ϨϓϦέʔγϣϯຖʹଟ਺ܾ
    w1
    w1
    w1 w2
    w2
    w2
    Actor 0
    Actor 1
    Actor 2
    w2
    w2
    w1
    

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34. 34
    
    What is PAXOS? – Example
      Two phase election – phase 1
     Larger n is prior
    21:32
    8ß: ¼
    ÛËÙêîĝ
    21:36
    O2Ě
    21:35
    [_ÕðJK
    21:36
    O2ÙÐÄorz
    21:38
    O2ÙÐÞorz
    n=3
    n=1
    n=2
    8
    

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35. 35
    
    What is PAXOS? – Example
      Two phase election – phase 2
     confirmation
    21:42
    Ãğ
    21:41
    O2ÙÀÀ
    ëÞĝĚ
    21:43
    a~Å…
    21:44
    Ãğ 21:43
    GJ
    proposer
    21:43
    ÀêO2ÚyÁËÚ
    Ù|N`çÜßÙ
    n=4
    9
    

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36. Մ༻ੑͷ໰୊
    •  σʔλΛ͍͟ॻ͖ࠐ΋͏ͱࢥͬͨॠؒʹσʔλ͕σʔλϕʔε
    ͕མ͍ͪͯͨΓݻ·͍ͬͯͯ͸ϏδωενϟϯεΛಀ͢
    
    36
    
    

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37. CAPఆཧ
    ͲΜͳނোʹରͯ͠΋ QBSUJUJPOUPMFSBODF
    
    σʔλ͸ৗʹ੔߹͓ͯ͠Γ DPOTJTUFODZ
    
    γεςϜ͕ࢭ·Δ͜ͱ͸ͳ͍ BWBJMBCJMJUZ
    
    • ͜ͷ3ͭΛಉ࣌ʹຬͨ͢γεςϜ͸ଘࡏ͠ͳ͍
    
    • ͜Ε·ͰͷRDBMS͸CAॏࢹ
    
    37
    
    

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38. CAPఆཧʢCॏࢹͷ৔߹ʣ
    •  n1ͱn2ͷϨϓϦΧΛৗʹ੔߹͓ͤͯ͘͞
    
    •  ωοτϫʔΫ͕੾ΕͨΓނোͨ͠ΒࢭΊΔˠՄ༻ੑˣ
    
    38
    
    w1
    w2
    
    n1
    n2
    
    

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39. CAPఆཧʢAॏࢹͷ৔߹ʣ
    •  n1ͱn2ͷϨϓϦΧΛৗʹ࢖͑ΔΑ͏ʹ͢Δ
    
    •  ωοτϫʔΫ͕੾ΕͨΓނোͯ͠΋ॻ͚Δˠ੔߹ੑˣ
    
    39
    
    w1
    w2
    
    n1
    n2
    
    

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40. CAPఆཧʢPॏࢹͷ৔߹ʣ
    •  n1ͱn2ͷϨϓϦΧΛΤεύʔʹ͢Δ
    
    •  ωοτϫʔΫ͕੾ΕͨΒਖ਼͍͠ํ͕Θ͔ΔˠՄ༻ੑͪ
    ΐͬͱˣ
    
    40
    
    w1
    w2
    
    n1
    n2
    
    

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41. Amazon’s Dynamo
    •  ʮσʔλϕʔε͸ϦϨʔγϣφϧ͚ͩ͡Όͳ͍ɺ੔߹
    ੑ͚ͩ͡Όͳ͍ɺՄ༻ੑ͕େࣄͳ৔߹΋͋ΔΜͩʯ
    
    •  ΞϚκϯͷγϣοϐϯάΧʔτʹ࢖ΘΕ͍ͯͨ
    
    •  Vector Clocks
    
    •  Handoff
    
    •  (CRDT in Riak)
    
    41
    
    

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42. ʮͱΓ͋͑ͣॻ͘ʯͱ͍͏ߟ͑
    •  “Hinted Handoff” Ϧϯάͷ࣍ͷਓ
    ʹͱΓ͋͑ͣ౉͓ͯ͘͠
    
    •  ނো͔Β໭͖ͬͯͨΒฦ͢
    
    •  ॻ͖ࠐΈ͕ॏෳͨ͠Βʁ
    
    42
    
    w1
    
    

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43. ͱΓ͋͑ͣॻ͍͓͍ͯͯ
    ॻ͖ࠐΈ͕িಥͨ͠Βʁ
    •  ྆ํ͓͍࣋ͬͯͯɺিಥͨ͠σʔ
    λͷʮҼՌؔ܎ʯΛ໌Β͔ʹ͢Δ
    
    •  “Vector Clock”
    
    •  {a: 1, b:2, c:1} ͱ {a: 2, b:2, c:1}
    
    •  {a: 1, b:2, c:1} ͱ {a: 1, c:1, d:1}
    
    •  িಥͨ͠΋ͷ͸ΞϓϦͰղܾ
    
    43
    
    w1
    
    w2
    
    r
    
    

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44. 44
    
    CRDT
    • CRDT (Conflict-Free Replicated Data Types
    • “AP” Λαϙʔτ
    • Counter, Register, Sets, Maps
    • →ผεϥΠυʁ
    

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45. 45
    
    CRDTͰͷRead
    • ॱ൪͕ೖΕସΘͬͯ΋݁Ռ͕มΘΒͳ͍ܕ
    • update(w1, update(w2, Data0) =
    update(w2, update(w1, Data0) = Data
    w1
    w1
    w1
    w2
    w2
    w2
    Actor 0
    Actor 1
    Actor 2
    w1(w2(Data0)) => Data
    w1(w2(Data0)) => Data
    w2(w1(Data0)) => Data
    

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46. ACID vs BASE
    ACID
    BASE
    
    ੔߹͍ͯ͠ͳͯ͘΋
    ৗʹσʔλʹΞΫη
    εͰ͖Δ
    
    Basically Avaiable
    
    Atomicity
    ෳ਺ͷૢ࡞ͷ੒ޭɾ
    ࣦഊΛ·ͱΊΔ
    
    Consistency
    ৑௕Խ͞Εͨσʔλ
    ΍ෳ਺ͷϦϨʔγϣ
    ϯ͕ৗʹ੔߹͍ͯ͠
    Δ
    
    ࠷ऴతʹ੔߹ͨ͠ঢ়
    ଶʹͳΔ͜ͱ͕อূ
    ͞Ε͍ͯΕ͹Α͍
    
    Eventually Consistent
    
    Isolation
    ฒߦ؅ཧͯ͠ߋ৽్
    தͷঢ়ଶΛݟͤͳ͍
    
    Durability
    σʔλΛӬଓԽͯ͠
    ࣦΘͳ͍
    
    ϨϓϦΧ͸ܾఆ࿦త
    Ͱ͸ͳ͘ɺ֬཰తͰ
    ͋ͬͨΓɺάϩʔό
    ϧʹҰ؏͍ͯ͠ͳ͘
    ͯ΋Α͍
    
    Soft-state
    
    46
    
    

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47. σʔλετΞͷ෼ྨ࣠
    47
    
    

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48. ΫΠζɿͲ͜·Ͱ͕DB?
    Ͳ͔͜Β͕NoSQL?
    ACIDͳτϥϯβΫγϣϯ
    τϥϯβΫγϣϯͳ͠
    
    SQLΠϯλʔϑ
    Σʔε
    
    Oracle
    
    MySQL
    
    PostgreSQL
    
    SQL Server, DB2
    
    Cassandra (CQL)
    
    Hive,
    
    Presto
    
    Impala
    
    ಠࣗAPI
    InnoDB
    
    BerkeleyDB
    
    FoundationDB
    
    Riak
    
    MongoDB
    
    Redis
    
    48
    
    

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49. ςετʹग़ͳ͍ຊ౰ͷ͜ͱ
    49
    
    

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50. CAPఆཧ͔ΒΈͨ੡඼ͷ෼ྨ
    •  CAॏࢹ
    
    •  RDBMS, MongoDB, HBase, etc…
    
    •  ੔߹ੑҡ࣋ͷͨΊͷ෼ࢄ߹ҙʢਖ਼͘͠ϑΣΠϧΦʔ
    όʔ͢ΔͨΊʣͷ࢓૊Έ͕ඞཁ
    
    •  APॏࢹ
    
    •  Cassandra, Riak, CouchDB
    
    •  ෼ࢄ߹ҙͷ࢓૊Έ͕ෆཁʹ࣮૷΋ӡ༻΋؆୯
    
    50
    
    

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51. ͜͜·Ͱͷ·ͱΊ:
    ͱͯ΋ᐆດͳද
    CAॏࢹ
    APॏࢹ
    
    RDBMS
    
    HBase
    MongoDB
    
    Cassandra
    
    CouchDB
    
    Riak
    
    51
    
    

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52. ϦϨʔγϣφϧϞσϧΛఘΊΔ
    52
    
    •  ςʔϒϧߏ଄ => KVS (Mapߏ଄)
    
    •  Pkey͸ΧϥϜͷͻͱ͔ͭΒબͿ΋ͷ=> ඞਢͷ΋ͷ
    
    •  JOINΛͤ͞ͳ͍
    
    •  ͜ΕʹΑΓεέʔϧΞ΢τܕͷ෼ࢄ͕Մೳʹ
    
    •  εΩʔϚΛࣄલఆٛ͠ͳ͍
    
    

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53. εΩʔϚ:
    σʔλϕʔεͷσʔλߏ଄ΛܾΊΔ΋ͷ
    •  εΩʔϚΛࣄલʹఆٛ: ϦϨʔγϣφϧϞσϧʹԊͬͨ࢖͍ํ
    
    •  Pros: σʔλߏ଄ʹڧྗͳ੍໿Λ՝ͨ͢Ί࠷దԽ͠΍͍͢ˍΞϓϦ
    Λ։ൃ͠΍͍͢
    
    •  Cons: ΞϓϦͷมߋίετ͕ߴ͍ˍ࠷ॳʹద੾ʹઃܭ͠ͳ͍ͱ͔ͳ
    Γมߋʹऑ͍
    
    •  εΩʔϚΛࣄલʹܾΊΔඞཁ͕ͳ͍৔߹
    
    •  Pro: σʔλߏ଄Λޙ͔ΒͰ΋͔ͳΓॊೈʹมߋͰ͖Δ
    
    •  Con: ςετ͕ͳ͍ͱόά͕ग़΍͍͢ɺσʔλߏ଄͕ෳࡶͩͱ࠷ద
    Խ͠ʹ͍͘
    
    53
    
    

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54. ৽͍͠σʔλϞσϧ
    ΧϥϜࢦ޲
    
    •  ΧϥϜΛ͍͘ΒͰ΋૿΍
    ͢͜ͱ͕Ͱ͖Δ
    
    •  Query LanguageΛ࡞Δ
    
    •  ʮΧϥϜϑΝϛϦʔʯ
    
    •  HBase, Cassandra
    
    υΩϡϝϯτࢦ޲
    
    •  ݸʑͷϨίʔυ͕ࣗ༝ͳ
    ܗࣜΛ࣋ͭ
    
    •  MapReduceͰΫΤϦ
    
    •  XML, JSON, etc …
    
    •  CouchDB, MongoDB
    
    54
    
    

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55. ͜͜·Ͱͷ·ͱΊ:
    ͱͯ΋ᐆດͳද2
    CAॏࢹ
    APॏࢹ
    
    SQL
    RDBMS
    -
    
    ΧϥϜࢦ޲
    HBase
    Cassandra
    
    υΩϡϝϯτࢦ޲
    MongoDB
    CouchDB
    
    (blob)
    Riak
    
    55
    
    

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56. ΋͏ͻͱͭσʔλϞσϧ
    Graph
    •  Semantic Webతͳσʔλߏ଄Λѻ͏ͨΊͷDB
    
    •  ;ͨͭͷํ޲ੑ
    
    •  ϊʔυͱΤοδΛਂ͘୳ࡧ͍ͨ͠
    
    •  ϊʔυͱΤοδ͕ଟ͗͢Δ
    
    56
    
    

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57. σʔλϕʔε͕ಈ͘ॲཧܥ
    •  ωΠςΟϒ
    
    •  ଎͍ɺϝϞϦ؅ཧɺGC͕ͳ͍
    
    •  JVM
    
    •  ଎͍ɺϝϞϦ؅ཧ͠ͳ͍͍ͯ͘ɺGC͕ى͖Δ
    
    •  Erlang VM
    
    •  ͦͦ͜͜଎͍ɺϝϞϦ؅ཧ͠ͳ͍͍ͯ͘ɺGCͰࢭ
    ·Βͳ͍
    
    57
    
    

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58. View Slide

59. ͍··Ͱઆ໌͖ͯͨ͠ͷͰ؆୯
    ໰୊
    Riak͸Ͳ͏͍ͯ͠Δ͔
    
    εέʔϦϯά
    ϋογϡతϧʔςΟϯάͰGossipͳਫฏ෼ࢄ
    
    ੔߹ੑͷ؅ཧ
    Vector Clocks, CRDTͳͲRead࣌ʹղܾ
    
    2.0Ͱ͸Paxos΋ೖΔ
    
    Մ༻ੑͷอূ
    Hinted HandoffΛ࢖ͬͯৗʹॻ͖ࠐΈ͕Ͱ͖ΔΑ͏
    ʹ͍ͯ͠Δ
    
    σʔλϞσϧ
    Blob + Document Based
    
    ΠϯσοΫεΛ͸ΕΔ
    
    MapReduce͕Ͱ͖Δ
    
    ॲཧܥ
    Erlang VM
    
    59
    
    

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60. ࣮૷໘ͰͷRiakͷಛ௃
    •  ʮ໷தʹΞϥʔτͰى͜͞Εͳ͍ʯ͜ͱΛ໨ࢦͨ͠
    
    •  Erlang VMΛ࢖༻
    
    •  GCʹΑΔఀࢭ͕࣌ؒͳ͍
    
    •  ແఀࢭͰͷύονద༻ɺղੳɺૢ࡞͕Մೳ
    
    •  ίϚϯυମܥɾϑΝΠϧߏ଄ɾσʔλߏ଄ΛͳΔ΂͘γϯϓϧʹઃ
    ܭ͠ӡ༻ෛ୲Λ௿ݮ
    
    •  ҆ఆੑΛॏࢹͨ͠ઃܭ
    
    •  ίϯύΫγϣϯɺ༧ଌՄೳੑ
    
    60
    
    

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61. ݁ہɺͲ͏͍͏ͱ͖ʹͲΕΛ࢖͑͹Α͍ͷ͔ʁ
    61
    
    

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62. ࣮૷໘΋ߟྀͨ͠
    ੡඼બ୒ͷϙΠϯτ
    •  JOINͳͲσʔλͷਖ਼نԽ͕ඞཁͳͱ͖: RDBMS
    
    •  ΦϯϝϞϦͰ࠷৽ͷ࣌ܥྻσʔλΛݟ͍ͨͱ͖: MongoDB
    
    •  ΧϥϜΛ͍͘ΒͰ΋૿΍͍ͨ͠ͱ͖
    
    •  SQL෩ͷΫΤϦΛ͍ͨ͠ͱ͖ or Մ༻ੑ: Cassandra
    
    •  େྔσʔλʹޮ཰తʹόονॲཧΛ͍ͨ͠ͱ͖: Hbase
    
    •  σʔλΛͳ͘͞ͳ͍&μ΢ϯλΠϜΛͳ͍ͨ͘͠ͱ͖: Riak
    
    62
    
    

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63. ·ͱΊ
    •  σʔλϕʔεͷྺ࢙తʹNoSQL͸৽͘͠͸ͳ͍
    
    •  SQLͱACID͸ผͷ͸ͳ͠ɺNoSQLͱ͍͏ΑΓNoACID
    
    •  εέʔϦϯά͸ʢཧ۶͸ʣ೉͘͠ͳ͍
    
    •  ੔߹ੑ͸ཧ۶͔Βͯͦ͠΋ͦ΋೉͍͠
    
    •  Մ༻ੑ͸ͦΜͳʹ೉͘͠ͳ͍
    
    •  Riak͸Մ༻ੑͱεέʔϥϏϦςΟ͕ಘҙ
    
    63
    
    

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64. Questions?
    64
    
    ࢀߟจݙϦετ: https://gist.github.com/kuenishi/8296883#refs
    
    

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