rdd

Type Members

1. class ADAMContext extends Serializable with Logging

2. trait ADAMParquetArgs extends AnyRef

3. class ADAMRDDFunctions[T] extends Serializable with Logging

4. trait ADAMSaveAnyArgs extends ADAMSaveArgs

5. trait ADAMSaveArgs extends ADAMParquetArgs

6. abstract class ADAMSequenceDictionaryRDDAggregator[T] extends Serializable with Logging

   A class that provides functions to recover a sequence dictionary from a generic RDD of records.

7. class ADAMSpecificRecordSequenceDictionaryRDDAggregator[T] extends ADAMSequenceDictionaryRDDAggregator[T]

   A class that provides functions to recover a sequence dictionary from a generic RDD of records that are defined in Avro.

8. class Coverage extends Serializable

   A base is 'covered' by a region set if any region in the set contains the base itself.

9. case class GenomeBins(binSize: Long, seqLengths: Map[String, Long]) extends Serializable with Product

   Partition a genome into a set of bins.

10. case class GenomicPositionPartitioner(numParts: Int, seqLengths: Map[String, Long]) extends Partitioner with Logging with Product with Serializable

    GenomicPositionPartitioner partitions ReferencePosition objects into separate, spatially-coherent regions of the genome.

11. case class GenomicRegionPartitioner[T](partitionSize: Long, seqLengths: Map[String, Long], start: Boolean = true)(implicit evidence$1: ReferenceMapping[T]) extends Partitioner with Logging with Product with Serializable

12. class InstrumentedADAMAvroParquetOutputFormat extends InstrumentedOutputFormat[Void, IndexedRecord]

13. class MultiContigNonoverlappingRegions extends Serializable

    Creates a multi-reference-region collection of NonoverlappingRegions -- see the scaladocs to NonoverlappingRegions.

14. class NonoverlappingRegions extends Serializable

    The evaluation of a regionJoin takes place with respect to a complete partition on the total space of the genome.

15. class PairingRDD[T] extends Serializable

    PairingRDD provides some simple helper methods, allowing us take an RDD (presumably an RDD whose values are in some reasonable or intelligible order within and across partitions) and get paired or windowed views on that list of items.