| write.jdbc {SparkR} | R Documentation |
Save the content of the SparkDataFrame to an external database table via JDBC. Additional JDBC database connection properties can be set (...) You can find the JDBC-specific option and parameter documentation for writing tables via JDBC in https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option Data Source Option in the version you use.
write.jdbc(x, url, tableName, mode = "error", ...) ## S4 method for signature 'SparkDataFrame,character,character' write.jdbc(x, url, tableName, mode = "error", ...)
x |
a SparkDataFrame. |
url |
JDBC database url of the form |
tableName |
the name of the table in the external database. |
mode |
one of 'append', 'overwrite', 'error', 'errorifexists', 'ignore' save mode (it is 'error' by default) |
... |
additional JDBC database connection properties. |
Also, mode is used to specify the behavior of the save operation when data already exists in the data source. There are four modes:
'append': Contents of this SparkDataFrame are expected to be appended to existing data.
'overwrite': Existing data is expected to be overwritten by the contents of this SparkDataFrame.
'error' or 'errorifexists': An exception is expected to be thrown.
'ignore': The save operation is expected to not save the contents of the SparkDataFrame and to not change the existing data.
write.jdbc since 2.0.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
coltypes(),
createOrReplaceTempView(),
crossJoin(),
cube(),
dapplyCollect(),
dapply(),
describe(),
dim(),
distinct(),
dropDuplicates(),
dropna(),
drop(),
dtypes(),
exceptAll(),
except(),
explain(),
filter(),
first(),
gapplyCollect(),
gapply(),
getNumPartitions(),
group_by(),
head(),
hint(),
histogram(),
insertInto(),
intersectAll(),
intersect(),
isLocal(),
isStreaming(),
join(),
limit(),
localCheckpoint(),
merge(),
mutate(),
ncol(),
nrow(),
persist(),
printSchema(),
randomSplit(),
rbind(),
rename(),
repartitionByRange(),
repartition(),
rollup(),
sample(),
saveAsTable(),
schema(),
selectExpr(),
select(),
showDF(),
show(),
storageLevel(),
str(),
subset(),
summary(),
take(),
toJSON(),
unionAll(),
unionByName(),
union(),
unpersist(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D sparkR.session()
##D jdbcUrl <- "jdbc:mysql://localhost:3306/databasename"
##D write.jdbc(df, jdbcUrl, "table", user = "username", password = "password")
## End(Not run)