title: Structured streaming writes Parquet files to Hadoop
body: <p>I was able to write the results of structured streaming to Parquet files. The thing is that those files are in local file system, and now I want to write them to Hadoop file system. Is there any way to do that?</p>
  
  <pre class="lang-java prettyprint-override"><code>StreamingQuery query = result //.orderBy("window")
              .repartition(1)
              .writeStream()
              .outputMode(OutputMode.Append())
              .format("parquet")
              .option("checkpointLocation", "hdfs://localhost:19000/data/checkpoints")
              .start("hdfs://localhost:19000/data/total");
  </code></pre>
  
  <p>I used this code, but it says:</p>
  
  <pre><code>Exception in thread "main" java.lang.IllegalArgumentException: Wrong FS: hdfs://localhost:19000/data/checkpoints/metadata, expected: file:///
  at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:649)
  at org.apache.hadoop.fs.RawLocalFileSystem.pathToFile(RawLocalFileSystem.java:82)
  at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:606)
  at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
  at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
  at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
  at org.apache.hadoop.fs.FileSystem.exists(FileSystem.java:1426)
  at org.apache.spark.sql.execution.streaming.StreamMetadata$.read(StreamMetadata.scala:51)
  at org.apache.spark.sql.execution.streaming.StreamExecution.&lt;init&gt;(StreamExecution.scala:100)
  at org.apache.spark.sql.streaming.StreamingQueryManager.createQuery(StreamingQueryManager.scala:232)
  at org.apache.spark.sql.streaming.StreamingQueryManager.startQuery(StreamingQueryManager.scala:269)
  at org.apache.spark.sql.streaming.DataStreamWriter.start(DataStreamWriter.scala:262)
  at org.apache.spark.sql.streaming.DataStreamWriter.start(DataStreamWriter.scala:206)
  </code></pre>
  
  <p>Thanks</p>