Added support for Hdfs as deep storage

[vivek-balakrishnan-rovio]

PR for HDFS deep storage support.

[fabricebaranski]

It can be great also to change the version of spark and druid.
Currently I use spark 3.4.1 and druid 27.0.0
When using these versions, you need to change IndexIO and getBitmapSerdeFactory in TaskDataWriter.java.
Also, timestamp can be defined as long, so it can be great to adapt scala code of DruidDatasetExtensions
like that

      // if we're partitioning by day and the time column is of DateType we can simplify
      if (granularityString == GranularityType.DAY.name() &&  dataset.schema(timeColumn).dataType == DateType) {
        df = df.withColumn("__PARTITION_TIME__", col(timeColumn).cast(TimestampType))
      }
      else {
        if (dataset.schema(timeColumn).dataType == LongType) {
          df = df.withColumn("__PARTITION_TIME__",
            normalize_udf(column(timeColumn))
              .divide(1000)
              .cast(DataTypes.TimestampType))
            .withColumn(
              timeColumn,
            (col(timeColumn)/1000).cast(DataTypes.TimestampType))
        } else {
          df = df.withColumn("__PARTITION_TIME__",
            normalize_udf(unix_timestamp(column(timeColumn))
              .multiply(1000)
              .cast(DataTypes.LongType))
              .divide(1000)
              .cast(DataTypes.TimestampType))
        }
      }

[vivek-balakrishnan-rovio]

@fabricebaranski thanks, we plan to migrate to latest Druid version soon and I will include those changes you had suggested.