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Zapisywanie pojedynczej kolumny obiektu R w istniejącej tabeli db bazy danych Postgres

2015-05-26 8 views
13

Posiadam praktyczną wiedzę na temat R, ale nie korzystałem z niej zbyt często w połączeniu z bazami danych. Moje pytanie wydaje się bardzo podobna do tej kwestii: update table in postgresql database through rZapisywanie pojedynczej kolumny obiektu R w istniejącej tabeli db bazy danych Postgres

Ale nie mogę dostać ten kod do pracy i pakiet doMC nie jest dostępny dla ostatnich wersjach R.

jestem w stanie połączyć się z geobaza, odczytaj dane i manipuluj nimi. Mogę również napisać obiekt R do geobazy jako całą tabelę. Mam jednak problem, dołączając istniejącą tabelę geobazy za pomocą obiektu R. Niestety jest to bezpieczna baza danych, więc nie mogę podać informacji o połączeniu.

- „ubrana”, „dzień tygodnia” i „dni” są puste kolumny w istniejącym wcześniej tabeli w geobazie

- „participant_id”, „date_id” i „gps_time” są wypełniane kolumn w wcześniej istniejący stół, który chciałbym scalić.

-ucsd to nazwa schematu i sage_choi jest istniejąca nazwa tabeli

choifnl <- structure(list(wearing = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("nw", 
"w"), class = "factor"), weekday = c("Saturday", "Saturday", 
"Saturday", "Saturday", "Saturday", "Saturday"), days = c(1, 
1, 1, 1, 1, 1), participant_id = c("0adf37c4-f950-40ad-9370-6bee2f93e935", 
"0adf37c4-f950-40ad-9370-6bee2f93e935", "0adf37c4-f950-40ad-9370-6bee2f93e935", 
"0adf37c4-f950-40ad-9370-6bee2f93e935", "0adf37c4-f950-40ad-9370-6bee2f93e935", 
"0adf37c4-f950-40ad-9370-6bee2f93e935"), date = c("20130202", 
"20130202", "20130202", "20130202", "20130202", "20130202"), 
    time = structure(1:6, .Label = c("00:00:00", "00:01:00", 
    "00:02:00", "00:03:00", "00:04:00", "00:05:00", "00:06:00", 
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    "23:57:00", "23:58:00", "23:59:00"), class = "factor")), .Names = c("wearing", 
"weekday", "days", "participant_id", "date", "time"), row.names = c(NA, 
6L), class = "data.frame") 


update <- function(i) { 
     drv <- dbDriver("PostgreSQL") 
     con <- dbConnect(drv, dbname = "", host = "",port <- , user = "", password = "") ##connect w/username and password 
     txt <- paste("UPDATE ucsd.sage_choi SET wearing=",choifnl$wearing[i],",weekday=", 
     choifnl$weekday[i],",days=",choifnl$days[i],",where participant_id=", 
     choifnl$participant_id[i],",AND date_id=", choifnl$date[i], 
     "AND gps_time=", choifnl$time[i]) 
     dbGetQuery(con, txt) 
     dbDisconnect(con) 
    } 

    library("foreach") 

    registerDoMC() 

    foreach(i = 1:length(choifnl$wearing), .inorder=FALSE,.packages="RPostgreSQL")%dopar%{ 
     update(i) 
    }
#### EDIT

Jest to ostateczne rozwiązanie (info Połączenie pominięte), że działa dobrze. Miałem pewne problemy z kodowaniem, a także odpowiednie rodzaje cytatów (pojedyncze).

update <- function(con,i) { 
     txt <- paste("UPDATE ucsd.sage_final_choi SET wearing=", paste("'",choifnl$wearing[i],"'",sep=""), 
        ", weekday=", paste("'",choifnl$weekday[i],"'",sep=""), 
        ", days=", choifnl$days[i], 
        "WHERE participant_id=",paste("'",choifnl$participant_id[i],"'",sep=""), 
        "AND date_id=", paste("'",choifnl$date[i],"'",sep=""), 
        "AND gps_time=", paste("'",choifnl$time[i],"'",sep=""), ";") 
     dbSendQuery(con, txt) # edit 2 

    } 


drv <- dbDriver("PostgreSQL") 
con <- dbConnect(drv, dbname = "", host = "", 
port <- 5432, user = "", password = "",options="-c search_path= schemaName") ##connect w/username and password 
foreach(i = 1:length(choifnl$wearing), .inorder=FALSE,.packages="RPostgreSQL")%do%{ 
    update(con,i) # passing in the open connection as an argument 
}

Źródło

2015-05-26 Misc

Odpowiedz

5

Jestem zakładając tutaj używasz RPostgreSQL biblioteki CRAN i że pytanie jest

„Jak mogę zaktualizować istniejący rekord postgresql użyciu R?”

Jeśli poprawnie zinterpretowałem twoje pytanie, mam dobre wieści i wprowadzę drobne mody do twojego istniejącego kodu, aby uruchomić go poniżej. Teraz dobra wiadomość:

  1. Błąd jest w SQL i
  2. Nie trzeba doMC (ani foreach, o to chodzi).
  3. Jesteś już podłączony do bazy danych - to zwykle jest bardziej uciążliwa część!

Jeśli naprawdę potrzebujesz paralelizmu, możesz zobaczyć podstawowy format inicjowania wielu pracowników za pomocą doSNOW. Tak czy inaczej, znacznie łatwiej jest debugować aplikację z jednym wątkiem, więc powinieneś po prostu zmienić pętlę na pętlę jednowątkową, zmieniając%% dopar% na końcu instrukcji foreach na% do%, a następnie zarejestruj twój równoległy backend PO POZYCIE SQL działa.

foreach(i = 1:length(choifnl$wearing),.inorder=FALSE,.packages="RPostgreSQL") %do% { 
    update(i) 
}

Następnie możesz zobaczyć, że twój SQL ma błąd składni, szczególnie w tym "gdzie" i twoim pierwszym "i" błędnie podąża przecinkami. Zwykle dzielę duże wypowiedzi na bardziej czytelne dla człowieka formy, jak poniżej, aby łatwiej było dostrzec niespójności w formie. Usunąłem przypadkowemu przecinki w tym fragmencie poniżej:

### SQL error resolved 
update <- function(i) { 
    drv <- dbDriver("PostgreSQL") 
    con <- dbConnect(drv, dbname = "", host = "",port <- , user = "", password = "") ##connect w/username and password 
    txt <- paste("UPDATE ucsd.sage_choi SET wearing=", choifnl$wearing[i], 
     ", weekday=", choifnl$weekday[i], 
     ", days=", choifnl$days[i], 
     "where participant_id=",choifnl$participant_id[i], 
     "AND date_id=", choifnl$date[i], 
     "AND gps_time=", choifnl$time[i]) 
    dbGetQuery(con, txt) 
    dbDisconnect(con) 
}

Z punktu widzenia wydajności, masz zamiar zrobić znacznie lepiej, jeśli zainicjować połączenie z zewnątrz do pętli, ponieważ nie trzeba zatopić czas i koszt ponownie ustanowić połączenie dla każdego rekordu.

### SQL error resolved, connection made outside loop 
update <- function(con,i) { 
    txt <- paste("UPDATE ucsd.sage_choi SET wearing=", choifnl$wearing[i], 
     ", weekday=", choifnl$weekday[i], 
     ", days=", choifnl$days[i], 
     "where participant_id=",choifnl$participant_id[i], 
     "AND date_id=", choifnl$date[i], 
     "AND gps_time=", choifnl$time[i]) 
    dbSendQuery(con, txt) # edit 2 

} 

drv <- dbDriver("PostgreSQL") 
con <- dbConnect(drv, dbname = "", host = "",port <- , user = "", password = "") ##connect w/username and password 
foreach(i = 1:length(choifnl$wearing), .inorder=FALSE,.packages="RPostgreSQL")%dopar%{ 
    update(con,i) # passing in the open connection as an argument 
} 
dbDisconnect(con)

Źródło

2015-06-01 22:47:48 aaryno

+1

To jest świetna Aaryn i dziękuję za dodatkowe wskazówki! – Misc

+0

Cześć Aaryn. Po uruchomieniu tego z moimi danymi i poprawnymi informacjami o połączeniu otrzymuję ten błąd: Błąd w {: zadanie 1 nie powiodło się - "brak argumentu" i ", bez wartości domyślnej". Nie jestem pewien, czego mi brakuje. Nie mam dużego doświadczenia z funkcją foreach(). Czy to też można zrobić z czymś w rodzinie stosującej? Używam również% do%, zgodnie z sugestią, ponieważ nie potrzebuję równoległości. – Misc

+0

Moja zła. Zapomniałem uwzględnić połączenie jako argument w wywołaniu funkcji aktualizacji (...). Dokonałem edycji. więc 'update' jest wywoływana z' con' i 'i' jako argumentami – aaryno

2

Gdybym zrozumiał pytanie poprawnie, to jest dość łatwe przy użyciu zdolności dplyr „s do połączenia z bazami danych

library(dplyr) 
library(RPostgreSQL) 

my_db <- src_postgres(host="<HOST>", 
         user="<USER>", 
         password="<PASS>", 
         db = "ucsd") 


sage_choi <- tbl(my_db,"sage_choi") 

sage_choi %>% 
    select(participant_id, date_id, gps_time) %>% 
    left_join(choifnl, copy=TRUE, by=c("participant_id"="participant_id", 
             "date_id"="date", 
             "gps_time"="time")) %>% 
    compute(name="sage_choi2", temporary=FALSE)

Po uruchomieniu kodu, stół sage_choi2 zawierałby zaludnionych kolumn.

Źródło

2015-06-03 00:15:16 akhmed

+1

To również działa. Chociaż podoba mi się to, jak odpowiedź @Aaryna Olssona dołącza do istniejącej tabeli i nie tworzy nowej. – Misc

+0

Tak, masz rację! 'dplyr' jest oparty na paradygmacie programowania funkcjonalnego:' f (x) 'nigdy nie zmienia' x', zamiast tego zwraca zmodyfikowaną kopię 'x':' y <- f (x) '. Zaletą jest to, że nie tworzymy osobnego zapytania do aktualizacji dla każdego '(identyfikator uczestnika, data_id, godzina_gps)'. Jeśli 'choifnl' jest duże, zaktualizowanie każdego rekordu za pomocą osobnego zapytania może trochę potrwać. – akhmed

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