Rによる大規模データの処理

2022年12月17日に開催された「R研究集会2022」の発表資料です。

当日の投影内容から、メモリの消費量の算出方法に誤りがあったため一部内容を変更しています。
リポジトリ: https://github.com/uribo/talk_221217_rjpusers

Transcript

1. ӝੜਅ໵ʢಙౡେֶσβΠϯܕ"*ڭҭݚڀηϯλʔʣ
   
   
   ʹΑΔେن໛σʔλͷॲཧ 
   ౷ܭ਺ཧݚڀॴڞಉར༻ݚڀूձʮσʔλղੳ؀ڥ3ͷ੔උͱར༻ʯ V@SJCP  IUUQTHJUIVCDPNVSJCPUBML@@SKQVTFST   
2. Ұԡ͠ϙΠϯτ େن໛σʔληοτͷޮ཰తͳॲཧͱసૹͷͨΊʹઃܭ "QBDIF
   "SSPX \BSSPX^
   ύοέʔδ ΠϯϝϞϦͷΧϥϜܕσʔλΛऔΓѻ͏ʢγϦΞϥΠζෆཁʣ ଟݴޠπʔϧϘοΫεͱͯ͠ɺ͞·͟·ͳϓϩάϥϛϯάݴޠͰ࣮૷ $
   3
   1ZUIPO
   3VTU
   +VMJB
   %VDL%#
   ͳͲ EQMZSόοΫΤϯυΛఏڙɻύΠϓԋࢉࢠʹΑΔॲཧΛద༻Մೳ QBSRVFUʹରԠɻύʔςΟγϣχϯάʹΑΔ؅ཧ MVCSJEBUFɺSMBOHɺTUSJOHSɺUJEZTFMFDUͳͲͷؔ਺ʹ΋ରԠ ະରԠͳؔ਺Λ\EVDLEC^ύοέʔδ͕Χόʔ ଎͍ খ͍͞ ಡΈࠐΈɾूܭՃ޻ॲཧ͕ ϑΝΠϧɾϝϞϦαΠζ͕ ޮ཰త DTWϑΝΠϧ͔ΒͷEQMZS΍EBUBUBCMFͰͷॲཧͱൺֱͯ͠ɺ͔ͳΓߴ଎ σʔλͷૢ࡞ɾ؅ཧ͕
3. ࣗݾ঺հ ӝੜ
   ਅ໵ ͏ΓΎ͏
   ͠Μ΍ ஍ཧۭؒσʔλղੳ ೥݄ʙಙౡ ౷ܭɺσʔλαΠΤϯε Ծ $  Ҋ Χόʔɿϓϩηε $ ࢖༻ $(ɿετοΫϑΥτͷ 3' ը૾ʢ  ԁʣ σʔλՄࢹԽ 3ݴޠ aདྷ೥݄ग़൛
4. େ͖͍σʔλͷॲཧɺͲ͏͍ͯ͠·͔͢ʁ ͜͜Ͱ͸ʮେ͖͍σʔλʯΛʮݱ࣮తʹѻ͑ͦ͏ͳ෺ʯͱ͠·͢ ୯ҰͷςΩετɾόΠφϦϑΝΠϧ ҰͭͷϑΝΠϧ͕࠷େͰ਺(#ɺશମͰ(#Ҏ಺ఔ౓ 
   σʔλج൫ʢ%#ɺ)BEPPQɺ"NB[PO
   "UIFOBɺ#JH2VFSZʣ౳Λར༻͠ͳ͍ 
   BXLͳͲͰલॲཧΛ͠ͳ͍ఔ౓ͷେ͖͞ ϩʔΧϧɾΫϥ΢υͰॲཧʜ ͳΔ΂҆͘Ձɾ௿ੑೳͷ؀ڥͰࡁ·͍ͤͨ  ฒྻԽ ϝϞϦΛͨ͘͞ΜੵΜͩίϯϐϡʔλʔͰॲཧͤ͞Δ
5. େ͖͍σʔλͷॲཧɺͲ͏͍ͯ͠·͔͢ʁ 3ɺ34UVEJP͋Δ͋Δ ॲཧͷաఔͰϝϞϦΛ࢖͍੾Δ 34UVEJP͕രൃ͢Δ
6. "QBDIF
   "SSPX
7. "QBDIF
   "SSPX 
   ɹɹɹɹɹɹ
   ͷσʔλ෼ੳπʔϧͷϓϥοτϑΥʔϜ ڞ௨ͷ࣮૷ΛݴޠΛ௒͑ͯڞ༗Ͱ͖Δ ϝϞϦ಺ͷσʔλΛޮ཰తʹߏ଄Խͯ͠ॲཧʢγϦΞϥΠζෆཁɺߴ଎ʣ σʔλަ׵࣌ͷੑೳվળʹΑΔߴ଎ͳॲཧΛ࣮ݱ  "QBDIF
   "SSPXܗࣜʜ
   BSSPX QBSRVFU ྻࢦ޲ͷσʔλʢΧϥϜܕσʔλʣΛѻ͏͜ͱʹಛԽ ෳ਺ݴޠରԠ ΠϯϝϞϦͰͷॲཧΛ࣮ݱ
8. ΧϥϜܕσʔλ
   σʔλ෼ੳʹಛԽ IUUQTBSSPXBQBDIFPSHPWFSWJFX ৯೑ྨ ྶ௕ྨ ྶ௕ྨ       Ϩοαʔύϯμ νϯύϯδʔ Ϛϯτώώ ৯೑ྨ ௗྨ ϥΠΦϯ ϑϯϘϧτϖϯΪϯ     ߦ୯ҐͰσʔλΛอ࣋ɾऔΓग़͠ $47΍.Z42-ͳͲͷσʔλϕʔε ߦࢦ޲ ಛఆྻͷ஋΁ͷૢ࡞ ˠશ෦ͷߦɾྻ΁ͷΞΫηεΛ൐͏ ྻ୯ҐͰσʔλΛอ࣋ɾऔΓग़͠ ྻࢦ޲ ৯೑ྨ ྶ௕ྨ ྶ௕ྨ       Ϩοαʔύϯμ νϯύϯδʔ Ϛϯτώώ ৯೑ྨ ௗྨ ϥΠΦϯ ϑϯϘϧτϖϯΪϯ     ˠࢦఆ͞ΕͨྻͷΈಡΈࠐΈ େྔͷߦʹର͢Δू໿ॲཧ͕ޮ཰త
9. \BSSPX^ύοέʔδ
10. \BSSPX^ύοέʔδͷಛ௃ 
    "SSPX
    $ ϥΠϒϥϦ΁ͷΠϯλʔϑΣʔεΛఏڙ "SSPX
    "SSPX͕ѻ͏BSSPX
    QBSRVFUܗࣜͷσʔλ 
    \EVDLEC^ύοέʔδɺ1ZUIPOͱͷ࿈ܞ 
    ʢϝϞϦʹ৐Γ੾Βͳ͍ن໛ͷʣෳ਺ͷϑΝΠϧΛಡΈࠐΈɺॲཧ \EQMZS^Λ͸͡Ίͱͯ͠\MVCSJEBUF^ɺ\TUSJOHS^ɺ\UJEZTFMFDU^ͳͲͷؔ਺ʹ΋ରԠ ˠ\EQMZS^ʹΑΔύΠϓॲཧ΍3ͷؔ਺Ͱେن໛σʔλͷૢ࡞͕࣮ݱ σʔλͷίϐʔΛ͢ΔաఔͰ΋ Ϋϥ΢υ؀ڥΛؚΊͨɺ \BSSPX^ͰରԠ͠ͳ͍ॲཧΛ࣮ߦ͢ΔͨΊɺผͷύοέʔδͱݴޠͰσʔλΛڞ༗ ෳ਺ϑΝΠϧ΁ͷߴ଎ͳಡΈॻ͖ ΠϯϝϞϦͰॲཧ
11. \BSSPX^Λ࢖ͬͨॲཧͷྲྀΕ 
    σʔλͷಡΈࠐΈ QBSRVFU GFBUIFS UYU DTW KTPO UTW 📄 
    σʔλϑϨʔϜͱͯ͠ฦΓ஋ΛಘΔ 
    \EQMZS^ͳͲͷؔ਺ʹΑΔॲཧ d <- read_parquet("data/zoo.parquet.parquet", as_data_frame = FALSE) result <- d |> select(name, taxon, body_length_cm) |> filter(taxon %in% c("霊長類", "齧歯類", "鳥類")) |> group_by(taxon) |> summarise(body_length_mean = mean(body_length_cm)) result |> collect() 
    ू໿͞ΕͨσʔλΛ෼ੳɾՄࢹԽ σʔλΛϝϞϦ্ʹಡΈࠐΉ ஗ԆධՁ
12. \EVDLEC^ύοέʔδ \BSSPX^ଆͰ\EVDLEC^ͱͷ࿈ܞͷͨΊʹto_duckdb() Λఏڙ ಈ࡞͢ΔίϯϐϡʔλʔͷϝϞϦ্Ͱಈ࡞͢ΔܰྔσʔλϕʔεγεςϜ Φϥϯμͷࠃཱݚڀॴͷϝϯόʔ͕த৺ʹͳͬͯ։ൃ $ Ͱॻ͔Εͨ"1*Λଟݴޠʹϥοϓͯ͠ఏڙ \EVDLEC^͸ͦͷ͏ͪͷ3ݴޠ޲͚ϥούʔύοέʔδ ˠ\BSSPX^ଆͰରԠ͠ͳ͍Ұ෦ͷؔ਺Λ࣮ߦͰ͖Δ \%#*^ʹΑͬͯσʔλϑϨʔϜΛૢ࡞
13. \BSSPX^͕ରԠ͠ͳ͍ؔ਺ʁ list_compute_functions() "SSPX
    RVFSZ
    FOHJOF લड़ͷͱ͓Γɺ\BSSPX^Ͱ͸"SSPX
    $ ΁ͷΠϯλʔϑΣΠεΛఏڙ \EQMZS^ͷؔ਺΋ར༻Մೳ ?acero ˠ͢΂ͯͷ3ͷؔ਺͕\BSSPX^Ͱ࣮ߦՄೳͳΘ͚Ͱ͸ͳ͍ d <- read_parquet(here::here("data/typeB/36_tokushima/year=2022/month=10/part-0.parquet"), as_data_frame = FALSE) ࣍ͷεϥΠυͰྫΛࣔͨ͢ΊʹBSSPXΦϒδΣΫτΛ༻ҙ EBUBGSBNFʹม׵ͯ͠ॲཧ
    PS
    Τϥʔ
14. 
    EBUBGSBNFʹม׵ͯ͠ॲཧ d |> select(datetime) |> mutate(is_jholiday = zipangu::is_jholiday(datetime)) #> Warning: Expression #> zipangu::is_jholiday(datetime) not supported in Arrow; #> pulling data into R #> datetime is_jholiday #> 1 2022-10-01 FALSE #> 2 2022-10-01 FALSE #> 3 2022-10-01 FALSE #> 4 2022-10-01 FALSE #> 5 2022-10-01 FALSE #> 6 2022-10-01 FALSE େ͖͍σʔλͷ··ͩͱॲཧʹ͕͔͔࣌ؒΔ͔΋
15. 
    ΤϥʔͰॲཧΛఀࢭ ˠ\EVDLEC^΁ͷม׵ͰରԠ d |> group_by(location_no) |> slice_min(order_by = traffic, n = 1) |> collect() #> Error: Slicing grouped data not supported in Arrow d |> group_by(location_no) |> to_duckdb() |> slice_min(order_by = traffic, n = 1) |> collect() #> # A tibble: 25,237 × 10 #> # Groups: location_no [274] #> datetime source_…¹ locat…² locat…³ meshc…⁴ link_…⁵ link_no traffic #> <dttm> <chr> <int> <chr> <chr> <int> <int> <int> #> 1 2022-10-29 17:50:00 3028 54 西ノ丸… 513404 2 662 2 #> 2 2022-10-29 19:50:00 3028 54 西ノ丸… 513404 2 662 2
16. \BSSPX^ύοέʔδͰͷ
    1BSRVFUϑΝΠϧͷѻ͍
17. "QBDIF
    1BSRVFU େن໛σʔλΛѻ͏ͨΊʹ޿͘࢖ΘΕ͍ͯΔඪ४తͳܗࣜΛఏڙ ྻࢦ޲σʔλΛѹॖ͞ΕͨόΠφϦܗࣜͰอଘɺ$47ͳͲͷඇѹॖςΩετܗࣜ ͱൺֱͯ͠ϑΝΠϧαΠζ͕খ͘͞ͳΔ IUUQTQBSRVFUBQBDIFPSH ޮ཰తͳྻσʔλදݱͷར఺Λར༻Ͱ͖ΔΑ͏ʹઃܭ ݩ͸)BEPPQΤίγεςϜͷதͰػೳ͢ΔΑ͏ʹ։ൃ
18. QBSRVSUͷಡΈࠐΈ
    
    ୯ҰϑΝΠϧ "84
    4ɺ(PPHMF
    $MPVE
    4UPSBHF
    (4$ ͔ΒͷಡΈࠐΈ΋0, read_parquet("data/typeB/36_tokushima/year=2022/month=10/part-0.parquet") σʔλϑϨʔϜͱͯ͠ಡΈࠐΈʢσϑΥϧτʣ "SSPX5BCMFͱͯ͠ಡΈࠐΈˠΠϯϝϞϦͰॲཧՄೳ read_parquet("s3://[access_key:secret_key@]bucket/path[?region=]") read_parquet("gs://anonymous@bucket/path") IUUQTBSSPXBQBDIFPSHEPDTSBSUJDMFTGTIUNM read_parquet("data/typeB/36_tokushima/year=2022/month=10/part-0.parquet", as_data_frame = FALSE, # tidyselectでの列選択 col_select = c(datetime, ends_with("no")))
19. QBSRVSUͷಡΈࠐΈ
    
    ෳ਺ϑΝΠϧ ڞ௨ͷྻ഑ྻΛ΋ͭෳ਺ͷQBSRVFUϑΝΠϧΛಡΈࠐΉʢ͜ͷஈ֊Ͱ͸εΩʔϚͷΈʣ open_dataset(here::here("data/typeB/13_tokyo/year=2021/")) #> FileSystemDataset with 12 Parquet files #> datetime: timestamp[us, tz=Asia/Tokyo] #> source_code: string #> location_no: int32 #> location_name: string #> meshcode10km: string #> link_type: int32 #> link_no: int32 #> traffic: int32 #> to_link_end_10m: string #> link_ver: int32 #> month: int32 #> #> See $metadata for additional Schema metadata ݄ຖʹ෼͔ΕͨݸͷϑΝΠϧ DTWͰ΋0, open_dataset(..., format = "csv")
20. ύʔςΟγϣχϯά Ұͭͷେ͖ͳσʔληοτΛෳ਺ͷࡉ͔ͳϑΝΠϧʹ෼ׂ͢Δઓུ )JWFܗࣜʜ
    LFZWBMVF ඞཁͳσʔλʹૉૣ͘ΞΫηεɺॲཧͷෛ୲͕ܰݮ ෼ׂΛత֬ʹߦ͏͜ͱ͕ॏཁ ྫ͑͹ʜ
    ೥ɺ݄ʢʣɺ౎ಓ෎ݝʢʣ d |> write_dataset(path = "data", partitioning = c("year", "month")) σʔληοτΛ ೥ɺ݄ʹ෼͚ͯอଘ EBUBZFBSNPOUIQBSUQBSRVFU NPOUIQBSUQBSRVFU NPOUIQBSUQBSRVFU ʜ EBUBZFBSNPOUIQBSUQBSRVFU NPOUIQBSUQBSRVFU NPOUIQBSUQBSRVFU
21. εΩʔϚʢܕͷࢦఆʣ ྻࢦ޲ͷσʔλܗࣜʜ
    ྻ͝ͱʹܾ·ͬͨܕʢ·ͱ·ͬͨ഑ஔʣ͕͋Δ ๛෋ͳσʔλλΠϓͰྻ഑ྻͷ஋Λఆٛ͢Δ Ϗοτ੔਺ʢJOUʣͱϏοτ੔਺ JOU ͸۠ผ͞ΕΔ open_dataset("data", schema = schema( datetime = timestamp(unit = "ms", timezone = "Asia/Tokyo"), source_code = utf8(), location_no = int32(), …)) #> FileSystemDataset with 12 Parquet files #> datetime: timestamp[ms, tz=Asia/Tokyo] #> source_code: string #> location_no: int32 #> location_name: string #> ... IUUQTBSSPXBQBDIFPSHEPDTSSFGFSFODFEBUBUZQFIUNM
22. \BSSPX^ύοέʔδʹΑΔ
    େن໛σʔλͷॲཧ
23. Ұൠಓ࿏ͷஅ໘ަ௨ྔ৘ใσʔλ ެӹࡒஂ๏ਓ೔ຊಓ࿏ަ௨৘ใηϯλʔ͕Φʔϓϯσʔλͱͯ͠ެ։ ֤౎ಓ෎ݝܯ࡯͕ं྆ײ஌ثͳͲͷܭଌػثͰऩूͨ͠அ໘ަ௨ྔʹؔ͢Δɹɹ ৘ใΛܯ࡯ிʹ͓͍ͯͱΓ·ͱΊͨ΋ͷ ΫϦΤΠςΟϒίϞϯζ
    දࣔ
    ࠃࡍ
    $$
    #:
     IUUQTXXXKBSUJDPSKQ ˞શࠃ͢΂ͯͷ࣍ϝογϡΛɹ ໢ཏ͢ΔΘ͚Ͱ͸ͳ͍
24. Ұൠಓ࿏ͷஅ໘ަ௨ྔ৘ใσʔλ [JQϑΝΠϧల։ޙͷDTWΛEBUBUBCMFͱͯ͠ಡΈࠐΉؔ਺Λ༻ҙ IUUQTHJUIVCDPNVSJCPKBSUJDS remotes::install_github("uribo/jarticr") dplyr::glimpse( jarticr::read_jartic_traffic("data-raw/typeB_tokushima_2022_10/徳島県警_202210.csv") ) #> Rows: 2,384,773 #> Columns: 10 #> $ datetime <dttm> 2022-10-01, 2022-10-01, 2022-10-01, 2022-10-01, 2022-… #> $ source_code <chr> "3028", "3028", "3028", "3028", "3028", "3028", "3028"… #> $ location_no <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,… #> $ location_name <chr> "徳島本町→県庁前", "県庁前→徳島本町", "新助任橋北詰→徳… #> $ meshcode10km <chr> "513404", "513404", "513404", "513404", "513404", "513… #> $ link_type <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, … #> $ link_no <int> 710, 705, 681, 676, 679, 678, 11, 375, 6, 5, 6, 5, 842… #> $ traffic <int> 21, 24, 25, 27, 25, 28, 30, 16, 42, 42, 27, 25, 16, 26… #> $ to_link_end_10m <chr> "6", "6", "11", "27", "21", "29", "26", "8", "7", "92"… #> $ link_ver <int> 202100, 202100, 202100, 202100, 202100, 202100, 202100…
25. ݕূ
    σʔλ αΠζͷҟͳΔσʔλΛछ༻ҙ -BSHF 4NBMM શࠃ .FEJVN )VHF શࠃ ೥ؒ ೥ؒ ౦ژ౎ ೥ؒ ౦ژ౎ ϲ݄ؒ ߦ਺ ྻ਺ σʔλαΠζ QBSRVFU ஍Ҭ ظؒ ϑΝΠϧαΠζ DTW ສ  ԯສ (# .#  (# (#   ԯສ (# ԯສ (# (# (# -BSHFɺ)VHFͷDTWϑΝΠϧαΠζ͸[JQѹॖ࣌ͷେ͖͞ ʢల։ޙ͸͞Βʹେ͖͍ʣ
26. ݕূ
    ؀ڥ "QQMF
    .
    .BD 3
     ϝϞϦ
    (#ʢݱߦͷ.#1Ͱ͸࠷େʣ library(arrow) # 10.0.1 library(readr) # 2.1.3 library(data.table) # 1.14.6 library(dplyr) # 1.0.10 library(dtplyr) # 1.2.2 library(duckdb) # 0.6.1 ͍ͣΕͷύοέʔδ΋$3"/࠷৽൛
27. ݕূ
    ͭͷॲཧΛൺֱ 
    άϧʔϓԽͱूܭ 
    ಡΈࠐΈ 
    ݁߹ DTWϑΝΠϧͷಡΈࠐΈ଎౓ readr::read_csv() data.table::fread() arrow::read_csv_arrow() \BSSPX^ \EQMZS^ \EBUBUBCMF^ \EVDLEC^ʜ
    BSSPXΦϒδΣΫτ͔Βม׵ \EUQMZS^
    ʜ
    EBUBUBCMFΦϒδΣΫτΛEQMZSͷؔ਺Ͱॲཧ όοΫΤϯυͰ\EBUBUBCMF^͕ػೳ
28. ݁Ռ
    ϑΝΠϧͷಡΈࠐΈ 4NBMM EBUBUBCMF 🏅
29. ݁Ռ
    ϑΝΠϧͷಡΈࠐΈ .FEJVN EBUBUBCMF 🏅
30. ݁Ռ
    ϑΝΠϧͷಡΈࠐΈ -BSHF
    )VHFͷDTW༻ҙͰ͖ͣ ಉن໛ͷQBSRVSUϑΝΠϧΛ ͰಡΈࠐΉʜ
    0, arrow::open_dataset() # 全国1年分(2021年) traffic_large <- open_dataset(here::here("data/typeB/"), schema = jartic_typeB_schema) |> filter(year == 2021) dim(traffic_large) #> [1] 3923767686 12 lobstr::obj_size(traffic_large) #> 487.10 kB # 全国4年分 traffic_huge <- open_dataset(here::here("data/typeB/"), schema = jartic_typeB_schema) dim(traffic_huge) #> [1] 15677276121 12 lobstr::obj_size(traffic_huge) #> 261.59 kB -BSHF )VHF ॲཧͷ಺༰ʹΑͬͯ͸݁ՌΛಘΒΕΔঢ়ଶ
31. ݁Ռ
    άϧʔϓԽͱूܭ BSSPX 🏅 4NBMM
32. ݁Ռ
    άϧʔϓԽͱूܭ BSSPX 🏅 .FEJVN
33. ݁Ռ
    άϧʔϓԽͱूܭ छͷσʔλαΠζͷ݁ՌΛൺֱ σʔλαΠζʹԠ࣮ͯ͡ߦ࣌ؒ΋૿Ճ
34. ݁Ռ
    ݁߹ EQMZS 🏅 4NBMM
35. ݁Ռ
    ݁߹ BSSPX 🏅 .FEJVN
36. ݁Ռ
    ݁߹ -BSHF
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