Save the content of the SparkDataFrame to an external database table via JDBC. Additional JDBC database connection properties can be set (...)
write.jdbc(x, url, tableName, mode = "error", ...)# S4 method for SparkDataFrame,character,character
write.jdbc(x, url, tableName, mode = "error", ...)
a SparkDataFrame.
JDBC database url of the form jdbc:subprotocol:subname
.
the name of the table in the external database.
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.
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 {
sparkR.session()
jdbcUrl <- "jdbc:mysql://localhost:3306/databasename"
write.jdbc(df, jdbcUrl, "table", user = "username", password = "password")
# }
Run the code above in your browser using DataLab