Hi @Mark, Here are my suggestions: 1. Previous to saving the rdd, I recommend you transform it to a dataframe and use the dataframewriter: https://spark.apache.org/docs/2.3.1/api/scala/index.html#org.apache.spark.sql.DataFrameWriter As per your requirement to avoid the directory and part file names, I believe this is not possible out of the box. You can write a single part file but the directory will be created by default. You can read more here: https://community.hortonworks.com/questions/142479/pyspark-creating-directory-when-trying-to-rdd-as-s.html One of the possible solutions is to write to a temporary directory and then move the single file renaming it to the appropriate folder. You can have a single file created inside the temporary directory by using the coalesce method like this: df.coalesce(1).write.format("json").mode("overwrite").save("temp_dir/test.json") 2. For saving json to orc hive table unless you plan to store it as string column you will need to parse the json and use flatmap to get correct columns you like to store. You can review the dataframewriter api saveAsTable method and example: https://spark.apache.org/docs/2.3.1/api/scala/index.html#org.apache.spark.sql.DataFrameWriter@saveAsTable(tableName:String):Unit And also check out this article that shows how to append to an orc table: http://jugsi.blogspot.com/2017/12/append-data-with-spark-to-hive-oarquet.html As always if you found this answer addressed your question, please take a moment to login and click the "accept" link on the answer. Thanks! ... View more