Maneira eficiente de inserir data frame de R para SQL

1. 
   único insert declarações , como na pergunta:
   
   INSERT INTO test (col1,col2,col3) VALUES (1,2,3)
   
2. 
   vários insert declarações , formatado assim:
   
   INSERT INTO test (col1,col2,col3) VALUES (1,2,3),(4,5,6),(7,8,9)
   
3. 
   load data infile declaração , ou seja, carregar um arquivo CSV escrito anteriormente em mysql :
   
   LOAD DATA INFILE 'the_dump.csv' INTO TABLE test
   

CREATE TABLE `test` (
  `col1` double, `col2` double, `col3` double, `col4` double, `col5` double
) ENGINE=MyISAM;

library(RMySQL)
con = dbConnect(MySQL(),
                user = 'the_user',
                password = 'the_password',
                host = '127.0.0.1',
                dbname='test')

n_rows = 1000000 # number of tuples
n_cols = 5 # number of fields
dump = matrix(runif(n_rows*n_cols), ncol=n_cols, nrow=n_rows)
colnames(dump) = paste0('col',1:n_cols)

before = Sys.time()
for (i in 1:nrow(dump)) {
  query = paste0('INSERT INTO test (',paste0(colnames(dump),collapse = ','),') VALUES (',paste0(dump[i,],collapse = ','),');')
  dbExecute(con, query)
}
time_naive = Sys.time() - before 

before = Sys.time()
chunksize = 10000 # arbitrary chunk size
for (i in 1:ceiling(nrow(dump)/chunksize)) {
  query = paste0('INSERT INTO test (',paste0(colnames(dump),collapse = ','),') VALUES ')
  vals = NULL
  for (j in 1:chunksize) {
    k = (i-1)*chunksize+j
    if (k <= nrow(dump)) {
      vals[j] = paste0('(', paste0(dump[k,],collapse = ','), ')')
    }
  }
  query = paste0(query, paste0(vals,collapse=','))
  dbExecute(con, query)
}
time_chunked = Sys.time() - before 

before = Sys.time()
write.table(dump, 'the_dump.csv',
          row.names = F, col.names=F, sep='\t')
query = "LOAD DATA INFILE 'the_dump.csv' INTO TABLE test"
dbSendStatement(con, query)
time_infile = Sys.time() - before