minne meets Hivemall/pepabo_minne_matrix_factorization_in_hivemall

第三回 Hivemall Meetup
https://eventdots.jp/event/597518

Transcript

1. 
   ϋϯυϝΠυϚʔέοτͰϨίϝϯσʔγϣϯ
    ࡾ୐༔հ
   
   (.0
   1&1"#0
   JOD
   
   ୈࡾճ
   )JWFNBMM
   .FFUVQ NJOOF
   NFFUT
   )JWFNBMM
2. ϓϦϯγύϧΤϯδχΞ ࡾ୐༔հ
   
   !NPOPDISPNFHBOF NJOOFࣄۀ෦ IUUQCMPHNPOPDISPNFHBOFDPN
3. ໨࣍ wϋϯυϝΠυϚʔέοτͱ͍͏αʔϏεͱɺͦͷಛ௃
   wڠௐϑΟϧλϦϯάͱ͸
   w.BUSJY
   'BDUPSJ[BUJPO
   ʹΑΔϨίϝϯσʔγϣϯ
   wNJOOFͰͷར༻ࣄྫ
4. ϋϯυϝΠυϚʔέοτͱ͍͏
   αʔϏεͱɺͦͷಛ௃
6. wݸਓ͕खܰʹϋϯυϝΠυ࡞඼ͷల ࣔ΍ചങ͕Ͱ͖Δɺࠃ಺࠷େͷϋϯ υϝΠυϚʔέοτ
   w࡞Ո਺ສਓಥഁ
   wΞΫηαϦʔ΍όοάɺࡒ෍ɺখ෺ ͳͲ NJOOF
7. NJOOF IUUQTNJOOFDPN
8. Ϟϊͮ͘ΓΛ͞ΕΔΈͳ͞·ͷ࡞඼ʹײಈͯ͠ɺ
   ͨ͘͞Μͷํʹ͍ͭͰ΋ݟͯ΋Β͑Δ৔ॴΛ࡞Γ͍ͨɺ
   ͦͯ͠ɺΈͳ͞·ͷϑΝϯΛ࡞Γ૿΍͓͢ख఻͍͕͍ͨ͠ l
9. ϋϯυϝΠυϚʔέοτͷಛ௃
10. ϋϯυϝΠυϚʔέοτͷಛ௃ ଟछଟ༷ͳ࡞Ո͞Μ͕ू͏
    ˠ
    ࡞඼਺͕ଟ͍
    ࡞඼͸ϋϯυϝΠυ
    ˠ
    ࡏݿ਺͕গͳ͍ɺ͍ΘΏΔҰ఺΋ͷ΍ɺड஫ੜ࢈
11. ࡞඼ͱͷग़ձ͍ ࡞඼਺͕ଟ͍
    ˠ
    ݸผϢʔβʔʹର͢ΔਓྗͰͷਪન͸ࣄ্࣮ෆՄೳ
    ࡏݿ਺͕গͳ͍
    ˠ
    શମϢʔβʔʹର͢Δ࣮੷͔Βબఆͨ͠ਓؾ࡞඼ͷ༗ޮظ͕ؒ୹͍
    ˠ
    ݸผͷϢʔβʔ޲͚ʹγεςϜ͕͓͢͢Ί࡞ՈΛબఆ͢Δ࢓૊Έ͕ඞཁ
12. ͓͢͢Ί࡞Ոͷબఆ wNJOOFʮ͋ͳͨʹ͓͢͢Ίͷ࡞Ոʯ
    wϢʔβʔͷߦಈΛجʹ࡞ՈΛϨʔςΟϯά Activity Filter and shuffle Users fav, follow etc… Matrix Factorization Recommendation import DB
13. ڠௐϑΟϧλϦϯάͱ͸
14. ڠௐϑΟϧλϦϯά lଟ͘ͷϢʔβͷᅂ޷৘ใΛ஝ੵ͠ɺ͋ΔϢʔβ ͱᅂ޷ͷྨࣅͨ͠ଞͷϢʔβͷ৘ใΛ༻͍ͯࣗ ಈతʹਪ࿦Λߦ͏ํ๏࿦z 8JLJQFEJB
    IUUQTKBXJLJQFEJBPSHXJLJڠௐϑΟϧλϦϯά
15. ڠௐϑΟϧλϦϯά 8JLJQFEJB
    IUUQTFOXJLJQFEJBPSHXJLJ$PMMBCPSBUJWF@pMUFSJOH
    #Z
    .PTIBOJO
    
    0XO
    XPSL
    $$
    #:4"
    
    IUUQTDPNNPOTXJLJNFEJBPSHXJOEFYQIQ DVSJE
16. ڠௐϑΟϧλϦϯά  ᅂ޷ͷऩू
     ϢʔβʔͱΞΠςϜʹΑΔධՁߦྻΛ࡞੒͢Δ
     ࣅ͍ͯΔϢʔβʔΛ୳ͩ͢͠
     ྫ͑͹ɺϢʔβʔؒͷධՁ఺਺ΛݩʹྨࣅੑείΞΛࢉग़͢Δ
     ϢʔΫϦουڑ཭ɺϐΞιϯ૬ؔɺ+BDDBSE܎਺ͳͲ
     ΞΠςϜΛਪન͢Δ
     ࣅ͍ͯΔϢʔβʔ͕ධՁ͍ͯͯ͠ɺࣗ෼͕ධՁ͍ͯ͠ͳ͍ΞΠςϜ
     ྫ͑͹ɺϢʔβʔྨࣅੑείΞʹج͍ͯධՁ༧ଌΛࢉग़͢Δ
17. ڠௐϑΟϧλϦϯά
    
    ՝୊ w௨ৗͷϏδωεͰ࢖͏σʔλ͸ɺϢʔβʔɺΞΠςϜͱ΋ʹ๲େ͔ͭɺૄͳσʔ λͰ͋Δ͜ͱ͕ଟ͍
    wྨࣅ౓ΛٻΊΔͨΊͷܭࢉྔ͕૿͑Δ
    w૬ؔؔ܎ͷநग़͕೉͘͠ͳΓਫ਼౓͕ग़ͳ͍
18. .BUSJY
    'BDUPSJ[BUJPOʹΑΔ
    Ϩίϝϯσʔγϣϯ
19. .BUSJY
    'BDUPSJ[BUJPO
20. .BUSJY
    'BDUPSJ[BUJPO wϢʔβʔ΍ΞΠςϜ͝ͱͷධՁͷภΓ͕͋ͬͯɺେྔ͔ͭૄͳσʔλʹର͢Δ ධՁ༧ଌ
    wLݸͷજࡏҼࢠΛ࣋ͭϢʔβʔߦྻͱΞΠςϜߦྻΛ༻͍ͯۙࣅʢ࣍ݩ࡟ݮʣ
    wϢʔβʔ΍ΞΠςϜʹର͢ΔόΠΞεͷߟྀ              Item User R = ≈ m P n n Q × m k k
21. ͓͞Β͍
    
    ߦྻͷੵ
     0 B B @ 1 3 1 4 2 1 1 3 1 C C A ✓ 4 1 2 2 4 2 ◆ = 0 B B @ 10 13 8 12 17 10 10 6 6 10 13 8 1 C C A
22. ͓͞Β͍
    
    ߦྻͷੵ
     w ߦͱྻ
    ͷ಺ੵ͕
    ߦྻ੒෼ 0 B B @ 1 3 1 4 2 1 1 3 1 C C A ✓ 4 1 2 2 4 2 ◆ = 0 B B @ 10 13 8 12 17 10 10 6 6 10 13 8 1 C C A (1 ⇤ 4) + (3 ⇤ 2) = 10
23. ͓͞Β͍
    
    ߦྻͷੵ
     w ߦͱྻ
    ͷ಺ੵ͕
    ߦྻ੒෼
    w N
    º
    L
    ͱ
    L
    º
    O
    ͷߦྻͷੵ͸
    N
    º
    O
    w ٯ΋·ͨ੒Γཱͭ 0 B B @ 1 3 1 4 2 1 1 3 1 C C A ✓ 4 1 2 2 4 2 ◆ = 0 B B @ 10 13 8 12 17 10 10 6 6 10 13 8 1 C C A 3 4 3 4 (4×2) ͱ (2×3) Ͱ (4×3)ͷߦྻ
24. .BUSJY
    'BDUPSJ[BUJPO
25. .BUSJY
    'BDUPSJ[BUJPO  ϥϯμϜͳ஋ͰॳظԽ͞Εͨ෼ղޙͷߦྻΛͭ༻ҙ͢Δ
     ݩͷධՁߦྻͰ஋͕ೖ͍ͬͯΔ੒෼શͯʹରͯ͠ɺ෼ղޙͷߦྻͷੵͷ݁Ռ ͱൺֱ͢Δ
     ޡࠩΛิਖ਼͢Δ
     ݩͷධՁߦྻͱۙࣅʹͳΔ·Ͱ 
    Λ܁Γฦ͢              Item User R = ≈ m P n n Q × m k k
26. ͭ·Γ R = m P n n Q × m k k LݸͷજࡏҼࢠΛ࣋ͭͭͷߦྻͷੵʹ ΑΓɺݩͷධՁߦྻͷ஋ʹۙͮ͘Α͏ ͳ
    A A
    ͷ૊Έ߹ΘͤΛ୳͢͜ͱ 0 B B @ ? ? ? ? ? ? ? ? 1 C C A ✓ ? ? ? ? ? ? ◆ = 0 B B @ 10 13 8 12 17 10 10 6 6 10 13 8 1 C C A ٻΊΒΕ֤ͨߦྻ͸ɺݩͷಛ௃Λ·ͱΊͨߦྻͱΈͳ ͢͜ͱ͕Ͱ͖Δ
    w 6TFSͷಛ௃ΛL࣍ݩʹ·ͱΊͨߦྻ
    w *UFNͷಛ௃ΛL࣍ݩʹ·ͱΊͨߦྻ
27. ͭ·Γ R = m P n n Q × m k k LݸͷજࡏҼࢠΛ࣋ͭͭͷߦྻͷੵʹ ΑΓɺݩͷධՁߦྻͷ஋ʹۙͮ͘Α͏ ͳ
    A A
    ͷ૊Έ߹ΘͤΛ୳͢͜ͱ 0 B B @ ? ? ? ? ? ? ? ? 1 C C A ✓ ? ? ? ? ? ? ◆ = 0 B B @ 10 13 8 12 17 10 10 6 6 10 13 8 1 C C A ˠ
    ϥϯμϜͳ
    A A
    ͷ૊Έ߹Θ͔ͤΒٻΊ ͨ஋ͱɺਖ਼ղͷ஋ͷޡࠩΛখͯ͘͞͠ ͍͚͹Α͍
    ˠ
    ޯ഑߱Լ๏
28. ޯ഑߱Լ๏ͱ͸ wػցֶशʹ͓͍ͯϞσϧʹରֶͯ͠शΛਐΊΔͨΊͷख๏ͷͻͱͭɻ
    wτϨʔχϯάର৅ͷσʔλʹରͯ͠Ϟσϧͱͷޡ͕ࠩ࠷খʹͳΔΑ͏ʹϞσϧ ಺ͷύϥϝλΛߋ৽͍ͯ͘͜͠ͱɻ
    wύϥϝλߋ৽͸ɺޡࠩΛఆٛͨؔ͠਺Λඍ෼ͯ͠࠷খʹ͚ۙͮΔૢ࡞Λ܁Γฦ ͢͜ͱͰߦ͏ɻ
29. ࢀߟ
    (PʹΑΔޯ഑߱Լ๏
    
    ཧ࿦ͱ࣮ફ
    
    IUUQTTQFBLFSEFDLDPNNPOPDISPNFHBOFHSBEJFOUEFTDFOUJOHPMBOH
30. .BUSJY
    'BDUPSJ[BUJPO w༧ଌ஋ ˆ rij = pT i qj = k X k=1 pikqkj e2 ij = (rij ˆ rij)2 = (rij k X k=1 pikqkj)2 p0 ik = pik + ↵ @ @pik e2 ij = pik + 2↵eijqkj q0 kj = qkj + ↵ @ @qkj e2 ij = qkj + 2↵eijpik wೋ৐ޡࠩͷ໨తؔ਺ wύϥϝλߋ৽ࣜ
31. .BUSJY
    'BDUPSJ[BUJPO
    
    3FHVMBSJ[BUJPO w༧ଌ஋ ˆ rij = pT i qj = k X k=1 pikqkj wೋ৐ޡࠩͷ໨తؔ਺ wύϥϝλߋ৽ࣜ e2 ij = (rij ˆ rij)2 + 2 ( P 2 + Q 2 ) p0 ik = pik + ↵ @ @pik e2 ij = pik + ↵(2eijqkj pik) q0 kj = qkj + ↵ @ @qkj e2 ij = qkj + ↵(2eijpik qkj)
32. .BUSJY
    'BDUPSJ[BUJPO
    
    #JBT w༧ଌ஋ wೋ৐ޡࠩͷ໨తؔ਺ wύϥϝλߋ৽ࣜ ˆ rij = µ + buser(i) + bitem(j) + k X k=1 pikqkj e2 ij = (rij ˆ rij)2 + 2 ( buser 2 + bitem 2 + P 2 + Q 2 ) p0 ik = pik + ↵ @ @pik e2 ij = pik + ↵(2eijqkj pik) q0 kj = qkj + ↵ @ @qkj e2 ij = qkj + ↵(2eijpik qkj) buser(i) = buser(i) + ↵ @ @buser(i) e2 ij = buser(i) + ↵(2eij buser(i)) bitem(j) = bitem(j) + ↵ @ @bitem(j) e2 ij = bitem(j) + ↵(2eij bitem(j))
33. :FT
    XF`SF
    HPQIFS
34. .BUSJY
    'BDUPSJ[BUJPO rows, cols := R.Dims() p := mat64.NewDense(rows, K, randomSlice(rows*K)) q := mat64.NewDense(K, cols, randomSlice(rows*K)) for step := 0; step < 5000; step++ { for i := 0; i < rows; i++ { for j := 0; j < cols; j++ { rij := R.At(i, j) if rij == 0.0 { continue } pi := p.RowView(i) qj := q.ColView(j) err := rij - mat64.Dot(pi, qj) for k := 0; k < K; k++ { pik := p.At(i, k) qkj := q.At(k, j) p.Set(i, k, pik+alpha*(2*err*qkj)) q.Set(k, j, qkj+alpha*(2*err*pik)) } } } } return p, q # R ⽷5 0 3⽹ ⾇0 2 2⾇ ⽸4 4 0⽺ # R^ ⽷ 4.867 4.489 3.194⽹ ⾇ 2.482 2.266 1.629⾇ ⽸ 4.155 3.834 2.726⽺
35. NJOOFͰͷར༻ࣄྫ
36. Ϩίϝϯυ wNJOOFʮ͋ͳͨʹ͓͢͢Ίͷ࡞Ոʯ
    wϢʔβʔͷߦಈΛجʹ࡞ՈΛϨʔςΟϯά Activity Filter and shuffle Users fav, follow etc… Matrix Factorization Recommendation import DB
37. ߦಈϩάͷϨʔςΟϯά
38. #JHGPPU wϖύϘͷ࣍ੈ୅ϩά
    l׆༻z
    ج൫
    wߦಈϩάͷऩूɺ෼ੳɺ׆༻ͷ֤ஈ֊ʹ͓͍ͯɺશࣾͰར༻Ͱ͖Δ൚༻ੑͱ۩ ମతͳ׆༻ํ๏Λఏڙ
    wࠃ಺࠷େڃϋϯυϝΠυϚʔέοτNJOOFΛࢧ͑Δϩάج൫
39. #JHGPPU IDFA/GAID UID rack-bigfoot Service Request Activity log Services DB Attribute Big Cube Cube https://icons8.com BI Recommendation Bandit algorithm Re-marketing Feedback Name identification Cookie Sync
40. ࢀߟ
    αʔϏεʹدΓఴ͏ϩάج൫
    
    ϩάऩूͷͦͷઌʹ
    
    IUUQTTQFBLFSEFDLDPNNPOPDISPNFHBOFQFQBCPMPHJOGSBTUSVDUVSFCJHGPPU
41. Ϩίϝϯυ wNJOOFʮ͋ͳͨʹ͓͢͢Ίͷ࡞Ոʯ
    wϢʔβʔͷߦಈΛجʹ࡞ՈΛϨʔςΟϯά Activity Filter and shuffle Users fav, follow etc… Matrix Factorization Recommendation import DB
42. .BUSJY
    'BDUPSJ[BUJPO
    CZ
    )JWFNBMM
43. .BUSJY
    'BDUPSJ[BUJPO
    CZ
    )JWFNBMM Activity Rating Ratings 20% 80% testings trainings sgd_model predictions evaluations MAE RMSE Bias P, Q Service fav, follow etc… Recommendation Matrix Factorization
44. SBUJOH wධՁߦྻΛ౤ೖ͢Δ޻ఔ
    wNJOOFͰ͸Ϣʔβʔʹ໌ࣔతͳධՁΛೖྗͯ͠΋Β͏ͷͰ͸ͳ͘ɺલड़ͷߦ ಈϩάΛݩʹ
    AߪೖऀA
    ͷ
    A࡞ՈA
    ʹର͢ΔධՁΛಋग़͍ͯ͠Δ Activity Filter and shuffle Users fav, follow etc… Matrix Factorization Recommendation import DB
45. SBUJOH INSERT OVERWRITE TABLE ratings SELECT r.account_id, r.creator_id, ( -- rating ) AS rating, rand(31) as rnd FROM ( ... 3FTVMU
    &YQPSUΑΓ*/4&35
    07&383*5&
    5"#-&
    ͷ΄͏͕ߴ଎ ޙ޻ఔͰτϨʔχϯάͱςετσʔλʹׂΓৼΔͨΊ
    ϥϯμϜ஋ΛׂΓৼ͓ͬͯ͘ͱศར
46. USBJOJOH
    UFTUJOH wϨʔςΟϯάޙͷσʔλΛτϨʔχϯά༻ɺݕূ༻ʹׂΓৼΔ޻ఔ
    wࠓճ͸ΛτϨʔχϯά༻σʔλɺΛݕূ༻σʔλͱ͢Δ
47. USBJOJOH
    UFTUJOH INSERT OVERWRITE TABLE training SELECT account_id, creator_id, rating, rnd FROM ratings WHERE rnd > 0.2 -- rnd <= 0.2 ; ΛτϨʔχϯά༻ USBJOJOH ʹɻ
    ಉ͡Α͏ʹͯ͠Λςετ༻ UFTUJOH ʹׂΓৼΔɻ
48. .BUSJY
    'BDUPSJ[BUJPO w.BUSJY
    'BDUPSJ[BUJPOΛ࢖ͬͯɺධՁߦྻ͔Β
    LݸͷજࡏҼࢠΛ࣋ͭϢʔβʔ ߦྻͱΞΠςϜߦྻʢNJOOFͷ৔߹ɺ࡞ՈߦྻʣΛಋ͘޻ఔ
    w)JWFNBMMͰ͸όΠΞε߲͖ͭͷߦྻΛಋग़͢Δ              Item User R = ≈ m P n n Q × m k k
49. .BUSJY
    'BDUPSJ[BUJPO INSERT OVERWRITE TABLE sgd_model SELECT idx, array_avg(u_rank) as Pu, array_avg(i_rank) as Qi, avg(u_bias) as Bu, avg(i_bias) as Bi, min(mu) as mu FROM ( SELECT train_mf_sgd(account_id, creator_id, rating, '- factor 20 -iter 50 -update_mu') AS (idx, u_rank, i_rank, u_bias, i_bias, mu) FROM training ) t GROUP BY idx;
50. .BUSJY
    'BDUPSJ[BUJPO INSERT OVERWRITE TABLE sgd_model SELECT idx, array_avg(u_rank) as Pu, array_avg(i_rank) as Qi, avg(u_bias) as Bu, avg(i_bias) as Bi, min(mu) as mu FROM ( SELECT train_mf_sgd(account_id, creator_id, rating, '- factor 20 -iter 50 -update_mu') AS (idx, u_rank, i_rank, u_bias, i_bias, mu) FROM training ) t GROUP BY idx; ޙ޻ఔͰධՁͷฏۉ஋Λ࢖͏͕ɺ5SFBTVSF%BUB্ Ͱ͸ม਺͕࢖͑ͳ͍ͷͰʢશͯಉ͡ʹͳΔ͕ʣ VQEBUFNVΦϓγϣϯΛ࢖ͬͯɺ͜͜ͰٻΊ͓ͯ͘ ࿦ཧߏ଄ͱͯ͠͸ߦྻ͕ͩJEY͸ڞ௨Խ͞Ε͓ͯΓ
    ͻͱͭͷςʔϒϧʹ֨ೲ͞ΕΔ 1V
    2J
    ͸ͦΕͧΕϢʔβʔɺΞΠςϜʢ࡞Ոʣ͋ͨ
    Γͷ
    LݸͷજࡏҼࢠΛ഑ྻͱͯ࣋ͭ͠ USBJO@NG@THEʹΑΓ֬཰తޯ഑߱Լ๏ʹΑΔ .BUSJY
    'BDUPSJ[BUJPO͕ߦΘΕΔɻ
    ଞʹ΋"EB(SBE࠷దԽΛ࢖͏USBJO@NG@BEBHSBE΋
    ࢖͏͜ͱ͕Ͱ͖Δ
51. FWBMVBUJPO wֶशͨ͠Ϟσϧ͕աֶश͍ͯ͠ͳ͍͔Λௐ΂Δ޻ఔ
    w࠷ॳͷ޻ఔͰ෼཭͓͍ͯͨ͠ςετσʔλΛ࢖ͬͯ༧ଌධՁΛߦ͏
    wશͯͷ݁ՌΛݟൺ΂Δ͜ͱ͸Ͱ͖ͳ͍ͨΊɺશޡࠩΛಛఆͷख๏ʹΑΓ൑ఆ ͢Δ
    w."&
    ޡࠩͷઈର஋ͷฏۉ
    w3.4&
    ޡࠩͷೋ৐ͷฏۉͷฏํࠜ
    wຖճͷ݁ՌΛςʔϒϧʹग़ྗͯ͠ਪҠΛ֬ೝ͍ͯ͠Δ
52. FWBMVBUJPO SELECT mae(t3.predicted, t3.actual) as mae, rmse(t3.predicted, t3.actual) as rmse FROM ( SELECT t2.actual, mf_predict(if(size(t2.Pu)=0, null, t2.Pu), if(size(p2.Qi)=0, null, Qi), t2.Bu, p2.Bi, t2.mu) as predicted FROM ( SELECT t1.account_id, t1.creator_id, t1.rating as actual, p1.Pu, p1.Bu, p1.mu FROM testing t1 LEFT OUTER JOIN sgd_model p1 ON (t1.account_id = p1.idx) WHERE p1.Bu IS NOT NULL AND p1.mu IS NOT NULL ) t2 LEFT OUTER JOIN sgd_model p2 ON (t2.creator_id = p2.idx) ) t3; ֶशࡁΈϞσϧΛ࢖ͬͯςετσʔλʹର͢Δ
    ."&
    3.4&ΛٻΊΔʢ஋͸খ͍͞΄ͲΑ͍ʣ
53. QSFEJDUJPO wֶश͕ऴΘͬͨϞσϧΛ࢖ͬͯධՁΛߦ͏޻ఔ
    wϢʔβʔߦྻͱΞΠςϜʢ࡞Ոʣߦྻͷੵ࿨ʢʹόΠΞεΛՃ͑ͨ΋ͷʣ͕༧ ଌϨʔςΟϯάͱͳΔ
    wྫ͑͹͋ΔϢʔβʔ͕ະධՁͷΞΠςϜʢ࡞Ոʣͷ͏ͪɺ༧ଌϨʔςΟϯά͕ ߴ͍΋ͷΛਪન͢Δ
54. QSFEJDUJPO INSERT OVERWRITE TABLE prediction SELECT t2.account_id, t2.creator_id, t2.rank, t2.predicted FROM ( SELECT ROW_NUMBER() OVER(PARTITION BY t1.account_id ORDER BY t1.predicted DESC) AS rank, t1.account_id, t1.creator_id, t1.predicted FROM ( SELECT accounts_creators.account_id, accounts_creators.creator_id, mf_predict(if(size(accounts.Pu)=0, null, accounts.Pu), if(size(creators.Qi)=0, null, creators.Qi), accounts.Bu, creators.Bi, accounts.mu) AS predicted FROM -- prediction for all accounts and creators ) t1 ) t2 WHERE t2.rank <= 100; ֤ΞΧ΢ϯτͷ༧ଌϨʔςΟϯά͕ߴ͍΋ͷΛ݅ NG@QSFEJDUʹΑΓֶशࡁΈͷϞσϧ͔Β֤ΞΠςϜʹର͢Δ
    ༧ଌϨʔςΟϯάΛٻΊΔ ΞΧ΢ϯτ͝ͱͷ༧ଌϨʔςΟϯάͰฒͼସ͑
55. ϫʔΫϑϩʔͷ؅ཧ
56. ϫʔΫϑϩʔͷ؅ཧ w5SFBTVSF%BUBͷεέδϡʔϧΫΤϦΛར༻
    wΫΤϦͷίʔυ؅ཧ༻ʹ
    1FOEVMVNΛ։ൃ
    wIUUQTHJUIVCDPNNPOPDISPNFHBOFQFOEVMVN
    w%4-ʹΑͬͯεέδϡʔϧΫΤϦΛهड़͠ɺίʔυ؅ཧ Scheduled queries Queries on GitHub Apply Pendulum
57. 1FOEVMVN schedule 'test-scheduled-job' do database 'db_name' query 'select time from access;' retry_limit 0 priority :normal cron '30 0 * * *' timezone 'Asia/Tokyo' delay 0 result_url 'td://@/db_name/table_name' end Schedfile Apply $ pendulum --apikey='...' -a --dry-run $ pendulum --apikey='...' -a
58. %JHEBHҠߦத
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59. "QQFOEJY
60. "QQFOEJY w'BDUPSJ[BUJPO
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    wϨʔςΟϯάͷ޻෉
    wಋೖͱධՁํ๏
61. ·ͱΊ
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    w)JWFΫΤϦͰ؆୯ʹ΍Δ͜ͱ͕Ͱ͖Δ͚Ͳɺ಺෦ͷϩδοΫ͸೺Ѳ͍ͯͨ͠΄ ͏͕Α͍
    wσʔλ͕͋Ε͹ྟΉ݁Ռ͕ग़ͯ͘ΔΘ͚Ͱ͸ͳ͍ͷͰɺϑΟϧλϦϯά΍νϡʔ χϯάɺϨʔςΟϯάͷௐ੔ͳͲ͸ͱͬͯ΋େࣄ
63. ͓ΘΓ
64. ܅΋ϖύϘͰಇ͔ͳ͍͔ʁ ࠷৽ͷ࠾༻৘ใΛνΣοΫˠ !QC@SFDSVJU