title: Spark partitionBy | save by column value rather than columnName={value}
body: <p>I am using scala and spark, my spark version is 2.4.3</p>
  
  <p>My dataframe looks like this, there are other columns which i have not put and is not relavent.</p>
  
  <pre><code>+-----------+---------+---------+
  |ts_utc_yyyy|ts_utc_MM|ts_utc_dd|
  +-----------+---------+---------+
  |2019       |01       |20       |
  |2019       |01       |13       |
  |2019       |01       |12       |
  |2019       |01       |19       |
  |2019       |01       |19       |
  +-----------+---------+---------+
  </code></pre>
  
  <p>Basically i want to store the data in a bucketed format like</p>
  
  <blockquote>
    <p>2019/01/12/<em>data</em></p>
    
    <p>2019/01/13/<em>data</em>  </p>
    
    <p>2019/01/19/<em>data</em></p>
    
    <p>2019/01/20/<em>data</em></p>
  </blockquote>
  
  <p>I am using following code snippet </p>
  
  <blockquote>
  <pre><code>  df.write
    .partitionBy("ts_utc_yyyy","ts_utc_MM","ts_utc_dd")
      .format("csv")
      .save(outputPath)
  </code></pre>
  </blockquote>
  
  <p>But the problem is it is getting stored along with the column name like below.</p>
  
  <blockquote>
    <p>ts_utc_yyyy=2019/ts_utc_MM=01/ts_utc_dd=12/<em>data</em></p>
    
    <p>ts_utc_yyyy=2019/ts_utc_MM=01/ts_utc_dd=13/<em>data</em></p>
    
    <p>ts_utc_yyyy=2019/ts_utc_MM=01/ts_utc_dd=19/<em>data</em></p>
    
    <p>ts_utc_yyyy=2019/ts_utc_MM=01/ts_utc_dd=20/<em>data</em></p>
  </blockquote>
  
  <p>how do i save without column name in the folder name ?</p>
  
  <p>Thanks.</p>