Thanks! I got this to work.
val csvRdd = sc.parallelize(data.split("\n")) val df = new com.databricks.spark.csv.CsvParser().withUseHeader(true).withInferSchema(true).csvRdd(sqlContext, csvRdd) > On Apr 15, 2016, at 1:14 PM, Hyukjin Kwon <gurwls...@gmail.com> wrote: > > Hi, > > Would you try this codes below? > > val csvRDD = ...your processimg for csv rdd.. > val df = new CsvParser().csvRdd(sqlContext, csvRDD, useHeader = true) > > Thanks! > > On 16 Apr 2016 1:35 a.m., "Benjamin Kim" <bbuil...@gmail.com > <mailto:bbuil...@gmail.com>> wrote: > Hi Hyukjin, > > I saw that. I don’t know how to use it. I’m still learning Scala on my own. > Can you help me to start? > > Thanks, > Ben > >> On Apr 15, 2016, at 8:02 AM, Hyukjin Kwon <gurwls...@gmail.com >> <mailto:gurwls...@gmail.com>> wrote: >> >> I hope it was not too late :). >> >> It is possible. >> >> Please check csvRdd api here, >> https://github.com/databricks/spark-csv/blob/master/src/main/scala/com/databricks/spark/csv/CsvParser.scala#L150 >> >> <https://github.com/databricks/spark-csv/blob/master/src/main/scala/com/databricks/spark/csv/CsvParser.scala#L150>. >> >> Thanks! >> >> On 2 Apr 2016 2:47 a.m., "Benjamin Kim" <bbuil...@gmail.com >> <mailto:bbuil...@gmail.com>> wrote: >> Does anyone know if this is possible? I have an RDD loaded with rows of CSV >> data strings. Each string representing the header row and multiple rows of >> data along with delimiters. I would like to feed each thru a CSV parser to >> convert the data into a dataframe and, ultimately, UPSERT a Hive/HBase table >> with this data. >> >> Please let me know if you have any ideas. >> >> Thanks, >> Ben >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> <mailto:user-unsubscr...@spark.apache.org> >> For additional commands, e-mail: user-h...@spark.apache.org >> <mailto:user-h...@spark.apache.org> >> >