我对 R 有一定的了解，但我并没有过多地将它与数据库结合使用。我的问题似乎与这个问题非常相似:
update table in postgresql database through r
但是我无法使该代码正常工作，并且 doMC 包不适用于 R 的最新版本。
我能够连接到地理数据库，读取数据并对其进行操作。我还可以将 R 对象作为整个表写入地理数据库。但是，我遇到了麻烦，将现有的地理数据库表附加到 R 对象。不幸的是，它是一个安全的数据库，所以我不能提供我的连接信息。
-“wearing”、“weekday”和“days”是地理数据库中预先存在的表中的空白列
-“participant_id”、“date_id”和“gps_time”是我想要合并的预先存在的表中的填充列。
-ucsd 是架构名称，sage_choi 是现有表名称
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",
"00:07:00", "00:08:00", "00:09:00", "00:10:00", "00:11:00",
"00:12:00", "00:13:00", "00:14:00", "00:15:00", "00:16:00",
"00:17:00", "00:18:00", "00:19:00", "00:20:00", "00:21:00",
"00:22:00", "00:23:00", "00:24:00", "00:25:00", "00:26:00",
"00:27:00", "00:28:00", "00:29:00", "00:30:00", "00:31:00",
"00:32:00", "00:33:00", "00:34:00", "00:35:00", "00:36:00",
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"16:57:00", "16:58:00", "16:59:00", "17:00:00", "17:01:00",
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"17:12:00", "17:13:00", "17:14:00", "17:15:00", "17:16:00",
"17:17:00", "17:18:00", "17:19:00", "17:20:00", "17:21:00",
"17:22:00", "17:23:00", "17:24:00", "17:25:00", "17:26:00",
"17:27:00", "17:28:00", "17:29:00", "17:30:00", "17:31:00",
"17:32:00", "17:33:00", "17:34:00", "17:35:00", "17:36:00",
"17:37:00", "17:38:00", "17:39:00", "17:40:00", "17:41:00",
"17:42:00", "17:43:00", "17:44:00", "17:45:00", "17:46:00",
"17:47:00", "17:48:00", "17:49:00", "17:50:00", "17:51:00",
"17:52:00", "17:53:00", "17:54:00", "17:55:00", "17:56:00",
"17:57:00", "17:58:00", "17:59:00", "18:00:00", "18:01:00",
"18:02:00", "18:03:00", "18:04:00", "18:05:00", "18:06:00",
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"18:12:00", "18:13:00", "18:14:00", "18:15:00", "18:16:00",
"18:17:00", "18:18:00", "18:19:00", "18:20:00", "18:21:00",
"18:22:00", "18:23:00", "18:24:00", "18:25:00", "18:26:00",
"18:27:00", "18:28:00", "18:29:00", "18:30:00", "18:31:00",
"18:32:00", "18:33:00", "18:34:00", "18:35:00", "18:36:00",
"18:37:00", "18:38:00", "18:39:00", "18:40:00", "18:41:00",
"18:42:00", "18:43:00", "18:44:00", "18:45:00", "18:46:00",
"18:47:00", "18:48:00", "18:49:00", "18:50:00", "18:51:00",
"18:52:00", "18:53:00", "18:54:00", "18:55:00", "18:56:00",
"18:57:00", "18:58:00", "18:59:00", "19:00:00", "19:01:00",
"19:02:00", "19:03:00", "19:04:00", "19:05:00", "19:06:00",
"19:07:00", "19:08:00", "19:09:00", "19:10:00", "19:11:00",
"19:12:00", "19:13:00", "19:14:00", "19:15:00", "19:16:00",
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"19:22:00", "19:23:00", "19:24:00", "19:25:00", "19:26:00",
"19:27:00", "19:28:00", "19:29:00", "19:30:00", "19:31:00",
"19:32:00", "19:33:00", "19:34:00", "19:35:00", "19:36:00",
"19:37:00", "19:38:00", "19:39:00", "19:40:00", "19:41:00",
"19:42:00", "19:43:00", "19:44:00", "19:45:00", "19:46:00",
"19:47:00", "19:48:00", "19:49:00", "19:50:00", "19:51:00",
"19:52:00", "19:53:00", "19:54:00", "19:55:00", "19:56:00",
"19:57:00", "19:58:00", "19:59:00", "20:00:00", "20:01:00",
"20:02:00", "20:03:00", "20:04:00", "20:05:00", "20:06:00",
"20:07:00", "20:08:00", "20:09:00", "20:10:00", "20:11:00",
"20:12:00", "20:13:00", "20:14:00", "20:15:00", "20:16:00",
"20:17:00", "20:18:00", "20:19:00", "20:20:00", "20:21:00",
"20:22:00", "20:23:00", "20:24:00", "20:25:00", "20:26:00",
"20:27:00", "20:28:00", "20:29:00", "20:30:00", "20:31:00",
"20:32:00", "20:33:00", "20:34:00", "20:35:00", "20:36:00",
"20:37:00", "20:38:00", "20:39:00", "20:40:00", "20:41:00",
"20:42:00", "20:43:00", "20:44:00", "20:45:00", "20:46:00",
"20:47:00", "20:48:00", "20:49:00", "20:50:00", "20:51:00",
"20:52:00", "20:53:00", "20:54:00", "20:55:00", "20:56:00",
"20:57:00", "20:58:00", "20:59:00", "21:00:00", "21:01:00",
"21:02:00", "21:03:00", "21:04:00", "21:05:00", "21:06:00",
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"21:27:00", "21:28:00", "21:29:00", "21:30:00", "21:31:00",
"21:32:00", "21:33:00", "21:34:00", "21:35:00", "21:36:00",
"21:37:00", "21:38:00", "21:39:00", "21:40:00", "21:41:00",
"21:42:00", "21:43:00", "21:44:00", "21:45:00", "21:46:00",
"21:47:00", "21:48:00", "21:49:00", "21:50:00", "21:51:00",
"21:52:00", "21:53:00", "21:54:00", "21:55:00", "21:56:00",
"21:57:00", "21:58:00", "21:59:00", "22:00:00", "22:01:00",
"22:02:00", "22:03:00", "22:04:00", "22:05:00", "22:06:00",
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"22:27:00", "22:28:00", "22:29:00", "22:30:00", "22:31:00",
"22:32:00", "22:33:00", "22:34:00", "22:35:00", "22:36:00",
"22:37:00", "22:38:00", "22:39:00", "22:40:00", "22:41:00",
"22:42:00", "22:43:00", "22:44:00", "22:45:00", "22:46:00",
"22:47:00", "22:48:00", "22:49:00", "22:50:00", "22:51:00",
"22:52:00", "22:53:00", "22:54:00", "22:55:00", "22:56:00",
"22:57:00", "22:58:00", "22:59:00", "23:00:00", "23:01:00",
"23:02:00", "23:03:00", "23:04:00", "23:05:00", "23:06:00",
"23:07:00", "23:08:00", "23:09:00", "23:10:00", "23:11:00",
"23:12:00", "23:13:00", "23:14:00", "23:15:00", "23:16:00",
"23:17:00", "23:18:00", "23:19:00", "23:20:00", "23:21:00",
"23:22:00", "23:23:00", "23:24:00", "23:25:00", "23:26:00",
"23:27:00", "23:28:00", "23:29:00", "23:30:00", "23:31:00",
"23:32:00", "23:33:00", "23:34:00", "23:35:00", "23:36:00",
"23:37:00", "23:38:00", "23:39:00", "23:40:00", "23:41:00",
"23:42:00", "23:43:00", "23:44:00", "23:45:00", "23:46:00",
"23:47:00", "23:48:00", "23:49:00", "23:50:00", "23:51:00",
"23:52:00", "23:53:00", "23:54:00", "23:55:00", "23:56:00",
"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$wearing), .inorder=FALSE,.packages="RPostgreSQL")%dopar%{
update(i)
}
＃＃＃＃编辑
这是运行良好的最终解决方案(省略了连接信息)。我在编码方面遇到了一些问题，还包括正确类型的引号(单引号)。
update <- function(con,i) {
txt <- paste("UPDATE ucsd.sage_final_choi SET wearing=", paste("'",choifnl$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
}
最佳答案
我在这里假设您使用的是 CRAN 库 RPostgreSQL 并且您的问题是，
“如何使用 R 更新现有的 postgresql 记录？”
如果我正确解释了您的问题，我有个好消息，我将对您现有的代码进行小修改以使其在下面工作。现在，好消息是:
如果您确实需要并行性，您可以查看使用 doSNOW 初始化多个 worker 的基本格式。无论哪种方式，调试单线程应用程序都容易得多，因此您应该直接将循环更改为单线程循环，方法是将 foreach 语句末尾的 %dopar% 参数更改为 %do% 然后注册使 SQL 工作后的并行后端。
foreach(i = 1:length(choifnl$wearing),.inorder=FALSE,.packages="RPostgreSQL") %do% {
update(i)
}
然后你可能会看到你的 SQL 有一个语法错误，特别是在“where”和你的第一个“and”错误地跟在逗号之后。我通常将大型语句分解为更易于阅读的形式，如下所示，以便更容易发现形式上的不一致。我删除了下面这段代码中无意中的逗号:
### SQL error resolved
update <- function(i) {
drv <- dbDriver("PostgreSQL")
con <- dbConnect(drv, dbname = "", host = "",port <- , user = "", password = "") ##connect w/username and password
txt <- paste("UPDATE ucsd.sage_choi SET wearing=", choifnl$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$time[i])
dbGetQuery(con, txt)
dbDisconnect(con)
}
从性能的角度来看，如果在 for 循环之外初始化连接，您会做得更好，因为您不需要花费时间和成本来为每个记录重新建立连接。
### SQL error resolved, connection made outside loop
update <- function(con,i) {
txt <- paste("UPDATE ucsd.sage_choi SET wearing=", choifnl$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)
关于database - 将一列 R 对象写入预先存在的 postgres db 表，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/30470589/