Writing DataFrame as parquet creates empty files

I am trying to do some performance optimization for Spark job using bucketing technique. I am reading .parquet and .csv files and do some transformations. After I am doing bucketing and join two DataFrames. Then I am writing joined DF to parquet but I have an empty file of ~500B instead of 500Mb.

• Cloudera (cdh5.15.1)
• Spark 2.3.0

• Blob

  val readParquet = spark.read.parquet(inputP)
  readParquet
      .write
      .format("parquet")
      .bucketBy(23, "column")
      .sortBy("column")
      .mode(SaveMode.Overwrite)
      .saveAsTable("bucketedTable1")
  
  val firstTableDF = spark.table("bucketedTable1")
  
  val readCSV = spark.read.csv(inputCSV)
  readCSV
      .filter(..)
      .ordrerBy(someColumn)
  
      .write
      .format("parquet")
      .bucketBy(23, "column")
      .sortBy("column")
      .mode(SaveMode.Overwrite)
      .saveAsTable("bucketedTable2")
  
  val secondTableDF = spark.table("bucketedTable2")
  
  val resultDF = secondTableDF
      .join(firstTableDF, Seq("column"), "fullouter")
      .
      .
  resultDF
      .coalesce(1)
      .write
      .mode(SaveMode.Overwrite)
      .parquet(output)
  

When I launch Spark job in command line using ssh I have correct result, ~500Mb parquet file which I can see using Hive. If I run the same job using oozie workflow I have an empty file (~500 Bytes). When I do .show() on my resultDF I can see the data but I have empty parquet file.

+-----------+---------------+----------+
|       col1|          col2 |      col3|
+-----------+---------------+----------+
|33601234567|208012345678910|       LOL|
|33601234567|208012345678910|       LOL|
|33601234567|208012345678910|       LOL|

There is no problem writing to parquet when I am not saving data as a table. It occurs only with DF created from table.

Any suggestions ?

Thanks in advance for any thoughts!

I figured it out for my case I just added an option .option("path", "/sources/tmp_files_path"). Now I can use bucketing and I have a data in my output files.

readParquet
  .write
  .option("path", "/sources/tmp_files_path")
  .mode(SaveMode.Overwrite)
  .bucketBy(23, "column")
  .sortBy("column")
  .saveAsTable("bucketedTable1")