org.bdgenomics.adam.rdd

# ADAMContext

###
Related Docs: object ADAMContext | package rdd

#### class ADAMContext extends Serializable with Logging

The ADAMContext provides functions on top of a SparkContext for loading genomic data.

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### Instance Constructors

1. #### new ADAMContext(sc: SparkContext)

   sc

     The SparkContext to wrap.

### Value Members

1. #### final def !=(arg0: Any): Boolean

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2. #### final def ##(): Int

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4. #### final def asInstanceOf[T0]: T0

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5. #### def clone(): AnyRef

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8. #### def finalize(): Unit

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9. #### final def getClass(): Class[_]

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10. #### def getFiles(path: Path, fs: FileSystem): Array[Path]

    Elaborates out a directory/glob/plain path.

    Elaborates out a directory/glob/plain path.

    path

      Path to elaborate.

    fs

      The underlying file system that this path is on.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown

      `FileNotFoundException` if the path does not match any files.

    See also

      getFsAndFiles

11. #### def getFsAndFiles(path: Path): Array[Path]

    Elaborates out a directory/glob/plain path.

    Elaborates out a directory/glob/plain path.

    path

      Path to elaborate.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown

      `FileNotFoundException` if the path does not match any files.

    See also

      getFiles

12. #### def getFsAndFilesWithFilter(filename: String, filter: PathFilter): Array[Path]

    Elaborates out a directory/glob/plain path.

    Elaborates out a directory/glob/plain path.

    filename

      Path to elaborate.

    filter

      Filter to discard paths.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown

      `FileNotFoundException` if the path does not match any files.

    See also

      getFiles

13. #### def hashCode(): Int

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14. #### final def isInstanceOf[T0]: Boolean

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15. #### def isTraceEnabled(): Boolean

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16. #### def loadAlignments(filePath: String, projection: Option[Schema] = None, filePath2Opt: Option[String] = None, recordGroupOpt: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Loads alignments from a given path, and infers the input type.

    Loads alignments from a given path, and infers the input type.

    This method can load:

    * AlignmentRecords via Parquet (default) * SAM/BAM/CRAM (.sam, .bam, .cram) * FASTQ (interleaved, single end, paired end) (.ifq, .fq/.fastq) * FASTA (.fa, .fasta) * NucleotideContigFragments via Parquet (.contig.adam)

    As hinted above, the input type is inferred from the file path extension.

    filePath

      Path to load data from.

    projection

      The fields to project; ignored if not Parquet.

    filePath2Opt

      The path to load a second end of FASTQ data from. Ignored if not FASTQ.

    recordGroupOpt

      Optional record group name to set if loading FASTQ.

    stringency

      Validation stringency used on FASTQ import/merging.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    See also

      loadFasta

      loadFastq

      loadInterleavedFastq

      loadParquetAlignments

      loadBam

17. #### def loadBam(filePath: String, validationStringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Loads a SAM/BAM file.

    Loads a SAM/BAM file.

    This reads the sequence and record group dictionaries from the SAM/BAM file header. SAMRecords are read from the file and converted to the AlignmentRecord schema.

    filePath

      Path to the file on disk.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    See also

      loadAlignments

18. #### def loadBed(filePath: String, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), minPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD

    Loads features stored in BED6/12 format.

    Loads features stored in BED6/12 format.

    filePath

      The path to the file to load.

    optStorageLevel

      Optional storage level to use for cache before building the SequenceDictionary. Defaults to StorageLevel.MEMORY_ONLY.

    minPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism.

    stringency

      Optional stringency to pass. LENIENT stringency will warn when a malformed line is encountered, SILENT will ignore the malformed line, STRICT will throw an exception.

    returns

      Returns a FeatureRDD.

19. #### def loadCoverage(filePath: String): CoverageRDD

    Loads file of Features to a CoverageRDD.

    Loads file of Features to a CoverageRDD. Coverage is stored in the score attribute of Feature.

    filePath

      File path to load coverage from.

    returns

      CoverageRDD containing an RDD of Coverage

20. #### def loadFasta(filePath: String, fragmentLength: Long): NucleotideContigFragmentRDD

    Loads a FASTA file.

    Loads a FASTA file.

    filePath

      The path to load from.

    fragmentLength

      The length to split contigs into. This sets the parallelism achievable.

    returns

      Returns a NucleotideContigFragmentRDD containing the contigs.

21. #### def loadFastq(filePath1: String, filePath2Opt: Option[String], recordGroupOpt: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Loads (possibly paired) FASTQ data.

    Loads (possibly paired) FASTQ data.

    filePath1

      The path where the first set of reads are.

    filePath2Opt

      The path where the second set of reads are, if provided.

    recordGroupOpt

      The optional record group name to associate to the reads.

    stringency

      The validation stringency to use when validating the reads.

    returns

      Returns the reads as an unaligned AlignmentRecordRDD.

    See also

      loadUnpairedFastq

      loadPairedFastq

22. #### def loadFeatures(filePath: String, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), projection: Option[Schema] = None, minPartitions: Option[Int] = None): FeatureRDD

    Loads Features from a file, autodetecting the file type.

    Loads Features from a file, autodetecting the file type.

    Loads files ending in .bed as BED6/12, .gff3 as GFF3, .gtf/.gff as GTF/GFF2, .narrow[pP]eak as NarrowPeak, and .interval_list as IntervalList. If none of these match, we fall back to Parquet.

    filePath

      The path to the file to load.

    optStorageLevel

      Optional storage level to use for cache before building the SequenceDictionary. Defaults to StorageLevel.MEMORY_ONLY.

    projection

      An optional projection to push down.

    minPartitions

      An optional minimum number of partitions to use. For textual formats, if this is None, we fall back to the Spark default parallelism.

    returns

      Returns a FeatureRDD.

    See also

      loadParquetFeatures

      loadIntervalList

      loadNarrowPeak

      loadGff3

      loadGtf

      loadBed

23. #### def loadFragments(filePath: String): FragmentRDD

    Auto-detects the file type and loads a FragmentRDD.

    Auto-detects the file type and loads a FragmentRDD.

    This method can load:

    * Fragments via Parquet (default) * SAM/BAM/CRAM (.sam, .bam, .cram) * FASTQ (interleaved only --> .ifq) * Autodetects AlignmentRecord as Parquet with .reads.adam extension.

    filePath

      Path to load data from.

    returns

      Returns the loaded data as a FragmentRDD.

24. #### def loadGenotypes(filePath: String, projection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): GenotypeRDD

    Auto-detects the file type and loads a GenotypeRDD.

    Auto-detects the file type and loads a GenotypeRDD.

    If the file has a .vcf/.vcf.gz/.vcf.bgzf/.vcf.bgz extension, loads as VCF. Else, falls back to Parquet.

    filePath

      The path to load.

    projection

      An optional subset of fields to load.

    stringency

      The validation stringency to use when validating the VCF.

    returns

      Returns a GenotypeRDD.

    See also

      loadParquetGenotypes

      loadVcf

25. #### def loadGff3(filePath: String, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), minPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD

    Loads features stored in GFF3 format.

    Loads features stored in GFF3 format.

    filePath

      The path to the file to load.

    optStorageLevel

      Optional storage level to use for cache before building the SequenceDictionary. Defaults to StorageLevel.MEMORY_ONLY.

    minPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism.

    stringency

      Optional stringency to pass. LENIENT stringency will warn when a malformed line is encountered, SILENT will ignore the malformed line, STRICT will throw an exception.

    returns

      Returns a FeatureRDD.

26. #### def loadGtf(filePath: String, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), minPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD

    Loads features stored in GFF2/GTF format.

    Loads features stored in GFF2/GTF format.

    filePath

      The path to the file to load.

    optStorageLevel

      Optional storage level to use for cache before building the SequenceDictionary. Defaults to StorageLevel.MEMORY_ONLY.

    minPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism.

    stringency

      Optional stringency to pass. LENIENT stringency will warn when a malformed line is encountered, SILENT will ignore the malformed line, STRICT will throw an exception.

    returns

      Returns a FeatureRDD.

27. #### def loadIndexedBam(filePath: String, viewRegions: Iterable[ReferenceRegion])(implicit s: DummyImplicit): AlignmentRecordRDD

    Functions like loadBam, but uses bam index files to look at fewer blocks, and only returns records within the specified ReferenceRegions.

    Functions like loadBam, but uses bam index files to look at fewer blocks, and only returns records within the specified ReferenceRegions. Bam index file required.

    filePath

      The path to the input data. Currently this path must correspond to a single Bam file. The bam index file associated needs to have the same name.

    viewRegions

      Iterable of ReferenceRegions we are filtering on

28. #### def loadIndexedBam(filePath: String, viewRegion: ReferenceRegion): AlignmentRecordRDD

    Functions like loadBam, but uses bam index files to look at fewer blocks, and only returns records within a specified ReferenceRegion.

    Functions like loadBam, but uses bam index files to look at fewer blocks, and only returns records within a specified ReferenceRegion. Bam index file required.

    filePath

      The path to the input data. Currently this path must correspond to a single Bam file. The bam index file associated needs to have the same name.

    viewRegion

      The ReferenceRegion we are filtering on

29. #### def loadIndexedVcf(filePath: String, viewRegions: Iterable[ReferenceRegion], stringency: ValidationStringency = ValidationStringency.STRICT)(implicit s: DummyImplicit): VariantContextRDD

    Loads a VCF file indexed by a tabix (tbi) file into an RDD.

    Loads a VCF file indexed by a tabix (tbi) file into an RDD.

    filePath

      The file to load.

    viewRegions

      Iterator of ReferenceRegions we are filtering on.

    stringency

      The validation stringency to use when validating the VCF.

    returns

      Returns a VariantContextRDD.

30. #### def loadIndexedVcf(filePath: String, viewRegion: ReferenceRegion): VariantContextRDD

    Loads a VCF file indexed by a tabix (tbi) file into an RDD.

    Loads a VCF file indexed by a tabix (tbi) file into an RDD.

    filePath

      The file to load.

    viewRegion

      ReferenceRegions we are filtering on.

    returns

      Returns a VariantContextRDD.

31. #### def loadInterleavedFastq(filePath: String): AlignmentRecordRDD

    Loads reads from interleaved FASTQ.

    Loads reads from interleaved FASTQ.

    In interleaved FASTQ, the two reads from a paired sequencing protocol are interleaved in a single file. This is a zipped representation of the typical paired FASTQ.

    filePath

      Path to load.

    returns

      Returns the file as an unaligned AlignmentRecordRDD.

32. #### def loadInterleavedFastqAsFragments(filePath: String): FragmentRDD

    Loads interleaved FASTQ data as Fragments.

    Loads interleaved FASTQ data as Fragments.

    Fragments represent all of the reads from a single sequenced fragment as a single object, which is a useful representation for some tasks.

    filePath

      The path to load.

    returns

      Returns a FragmentRDD containing the paired reads grouped by sequencing fragment.

33. #### def loadIntervalList(filePath: String, minPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD

    Loads features stored in IntervalList format.

    Loads features stored in IntervalList format.

    filePath

      The path to the file to load.

    minPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism.

    stringency

      Optional stringency to pass. LENIENT stringency will warn when a malformed line is encountered, SILENT will ignore the malformed line, STRICT will throw an exception.

    returns

      Returns a FeatureRDD.

34. #### def loadNarrowPeak(filePath: String, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), minPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD

    Loads features stored in NarrowPeak format.

    Loads features stored in NarrowPeak format.

    filePath

      The path to the file to load.

    optStorageLevel

      Optional storage level to use for cache before building the SequenceDictionary. Defaults to StorageLevel.MEMORY_ONLY.

    minPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism.

    stringency

      Optional stringency to pass. LENIENT stringency will warn when a malformed line is encountered, SILENT will ignore the malformed line, STRICT will throw an exception.

    returns

      Returns a FeatureRDD.

35. #### def loadPairedFastq(filePath1: String, filePath2: String, recordGroupOpt: Option[String], stringency: ValidationStringency): AlignmentRecordRDD

    Loads paired FASTQ data from two files.

    Loads paired FASTQ data from two files.

    filePath1

      The path where the first set of reads are.

    filePath2

      The path where the second set of reads are.

    recordGroupOpt

      The optional record group name to associate to the reads.

    stringency

      The validation stringency to use when validating the reads.

    returns

      Returns the reads as an unaligned AlignmentRecordRDD.

    See also

      loadFastq

36. #### def loadParquet[T](filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None)(implicit ev1: (T) ⇒ SpecificRecord, ev2: Manifest[T]): RDD[T]

    This method will create a new RDD.

    This method will create a new RDD.

    T

      The type of records to return

    filePath

      The path to the input data

    predicate

      An optional pushdown predicate to use when reading the data

    projection

      An option projection schema to use when reading the data

    returns

      An RDD with records of the specified type

37. #### def loadParquetAlignments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): AlignmentRecordRDD

    Loads alignment data from a Parquet file.

    Loads alignment data from a Parquet file.

    filePath

      The path of the file to load.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional schema designating the fields to project.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    Note

      The sequence dictionary is read from an avro file stored at filePath/_seqdict.avro and the record group dictionary is read from an avro file stored at filePath/_rgdict.avro. These files are pure avro, not Parquet.

    See also

      loadAlignments

38. #### def loadParquetContigFragments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): NucleotideContigFragmentRDD

    Loads NucleotideContigFragments stored in Parquet, with metadata.

    Loads NucleotideContigFragments stored in Parquet, with metadata.

    filePath

      The path to load files from.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional projection to use for reading.

    returns

      Returns a NucleotideContigFragmentRDD.

39. #### def loadParquetCoverage(filePath: String, predicate: Option[FilterPredicate] = None): CoverageRDD

    Loads Parquet file of Features to a CoverageRDD.

    Loads Parquet file of Features to a CoverageRDD. Coverage is stored in the score attribute of Feature.

    filePath

      File path to load coverage from.

    predicate

      An optional predicate to push down into the file.

    returns

      CoverageRDD containing an RDD of Coverage

40. #### def loadParquetFeatures(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): FeatureRDD

    Loads Features stored in Parquet, with accompanying metadata.

    Loads Features stored in Parquet, with accompanying metadata.

    filePath

      The path to load files from.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional projection to use for reading.

    returns

      Returns a FeatureRDD.

41. #### def loadParquetFragments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): FragmentRDD

    Loads Fragments stored in Parquet, with accompanying metadata.

    Loads Fragments stored in Parquet, with accompanying metadata.

    filePath

      The path to load files from.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional projection to use for reading.

    returns

      Returns a FragmentRDD.

42. #### def loadParquetGenotypes(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): GenotypeRDD

    Loads Genotypes stored in Parquet with accompanying metadata.

    Loads Genotypes stored in Parquet with accompanying metadata.

    filePath

      The path to load files from.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional projection to use for reading.

    returns

      Returns a GenotypeRDD.

43. #### def loadParquetVariants(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): VariantRDD

    Loads Variants stored in Parquet with accompanying metadata.

    Loads Variants stored in Parquet with accompanying metadata.

    filePath

      The path to load files from.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional projection to use for reading.

    returns

      Returns a VariantRDD.

44. #### def loadReferenceFile(filePath: String, fragmentLength: Long): ReferenceFile

    Auto-detects the file type and loads a broadcastable ReferenceFile.

    Auto-detects the file type and loads a broadcastable ReferenceFile.

    If the file type is 2bit, loads a 2bit file. Else, uses loadSequences to load the reference as an RDD, which is then collected to the driver.

    filePath

      The path to load.

    fragmentLength

      The length of fragment to use for splitting.

    returns

      Returns a broadcastable ReferenceFile.

    See also

      loadSequences

45. #### def loadSequences(filePath: String, projection: Option[Schema] = None, fragmentLength: Long = 10000): NucleotideContigFragmentRDD

    Auto-detects the file type and loads contigs as a NucleotideContigFragmentRDD.

    Auto-detects the file type and loads contigs as a NucleotideContigFragmentRDD.

    Loads files ending in .fa/.fasta/.fa.gz/.fasta.gz as FASTA, else, falls back to Parquet.

    filePath

      The path to load.

    projection

      An optional subset of fields to load.

    fragmentLength

      The length of fragment to use for splitting.

    returns

      Returns a NucleotideContigFragmentRDD.

    See also

      loadReferenceFile

      loadParquetContigFragments

      loadFasta

46. #### def loadUnpairedFastq(filePath: String, recordGroupOpt: Option[String] = None, setFirstOfPair: Boolean = false, setSecondOfPair: Boolean = false, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Loads unpaired FASTQ data from two files.

    Loads unpaired FASTQ data from two files.

    filePath

      The path where the first set of reads are.

    recordGroupOpt

      The optional record group name to associate to the reads.

    setFirstOfPair

      If true, sets the read as first from the fragment.

    setSecondOfPair

      If true, sets the read as second from the fragment.

    stringency

      The validation stringency to use when validating the reads.

    returns

      Returns the reads as an unaligned AlignmentRecordRDD.

    See also

      loadFastq

47. #### def loadVariants(filePath: String, projection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): VariantRDD

    Auto-detects the file type and loads a VariantRDD.

    Auto-detects the file type and loads a VariantRDD.

    If the file has a .vcf/.vcf.gz/.vcf.bgzf/.vcf.bgz extension, loads as VCF. Else, falls back to Parquet.

    filePath

      The path to load.

    projection

      An optional subset of fields to load.

    stringency

      The validation stringency to use when validating the VCF.

    returns

      Returns a VariantRDD.

    See also

      loadParquetVariants

      loadVcf

48. #### def loadVcf(filePath: String, stringency: ValidationStringency = ValidationStringency.STRICT): VariantContextRDD

    Loads a VCF file into an RDD.

    Loads a VCF file into an RDD.

    filePath

      The file to load.

    stringency

      The validation stringency to use when validating the VCF.

    returns

      Returns a VariantContextRDD.

    See also

      loadVcfAnnotations

49. #### def log: Logger

    Attributes
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50. #### def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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51. #### def logDebug(msg: ⇒ String): Unit

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52. #### def logError(msg: ⇒ String, throwable: Throwable): Unit

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53. #### def logError(msg: ⇒ String): Unit

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54. #### def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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55. #### def logInfo(msg: ⇒ String): Unit

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56. #### def logName: String

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57. #### def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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58. #### def logTrace(msg: ⇒ String): Unit

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59. #### def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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60. #### def logWarning(msg: ⇒ String): Unit

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61. #### final def ne(arg0: AnyRef): Boolean

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62. #### final def notify(): Unit

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63. #### final def notifyAll(): Unit

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64. #### val sc: SparkContext

    The SparkContext to wrap.

65. #### final def synchronized[T0](arg0: ⇒ T0): T0

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66. #### def toString(): String

    Definition Classes
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67. #### final def wait(): Unit

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      @throws( ... )

68. #### final def wait(arg0: Long, arg1: Int): Unit

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69. #### final def wait(arg0: Long): Unit

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### Inherited from Logging

### Inherited from Serializable

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