java - Change output filename prefix for DataFrame.write()

Question

Output files generated via the Spark SQL DataFrame.write() method begin with the "part" basename prefix. e.g.

DataFrame sample_07 = hiveContext.table("sample_07");
sample_07.write().parquet("sample_07_parquet");

Results in:

hdfs dfs -ls sample_07_parquet/                                                                                                                                                             
Found 4 items
-rw-r--r--   1 rob rob          0 2016-03-19 16:40 sample_07_parquet/_SUCCESS
-rw-r--r--   1 rob rob        491 2016-03-19 16:40 sample_07_parquet/_common_metadata
-rw-r--r--   1 rob rob       1025 2016-03-19 16:40 sample_07_parquet/_metadata
-rw-r--r--   1 rob rob      17194 2016-03-19 16:40 sample_07_parquet/part-r-00000-cefb2ac6-9f44-4ce4-93d9-8e7de3f2cb92.gz.parquet

I would like to change the output filename prefix used when creating a file using Spark SQL DataFrame.write(). I tried setting the "mapreduce.output.basename" property on the hadoop configuration for the Spark context. e.g.

public class MyJavaSparkSQL {

  public static void main(String[] args) throws Exception {
    SparkConf sparkConf = new SparkConf().setAppName("MyJavaSparkSQL");
    JavaSparkContext ctx = new JavaSparkContext(sparkConf);
    ctx.hadoopConfiguration().set("mapreduce.output.basename", "myprefix");
    HiveContext hiveContext = new org.apache.spark.sql.hive.HiveContext(ctx.sc());
    DataFrame sample_07 = hiveContext.table("sample_07");
    sample_07.write().parquet("sample_07_parquet");
    ctx.stop();
  }

That did not change the output filename prefix for the generated files.

Is there a way to override the output filename prefix when using the DataFrame.write() method?

Answer 1

You cannot change the "part" prefix while using any of the standard output formats (like Parquet). See this snippet from ParquetRelation source code:

private val recordWriter: RecordWriter[Void, InternalRow] = {
  val outputFormat = {
    new ParquetOutputFormat[InternalRow]() {
      // ...
      override def getDefaultWorkFile(context: TaskAttemptContext, extension: String): Path = {
        // ..
        //  prefix is hard-coded here:
        new Path(path, f"part-r-$split%05d-$uniqueWriteJobId$bucketString$extension")
    }
  }
}

If you really must control the part file names, you'll probably have to implement a custom FileOutputFormat and use one of Spark's save methods that accept a FileOutputFormat class (e.g. saveAsHadoopFile).