MongoRDD

final def !=(arg0: Any): Boolean

final def ##(): Int

def ++(other: RDD[D]): RDD[D]

final def ==(arg0: Any): Boolean

def aggregate[U](zeroValue: U)(seqOp: (U, D) ⇒ U, combOp: (U, U) ⇒ U)(implicit arg0: ClassTag[U]): U

final def asInstanceOf[T0]: T0

def cache(): MongoRDD.this.type

def cartesian[U](other: RDD[U])(implicit arg0: ClassTag[U]): RDD[(D, U)]

def checkpoint(): Unit

def clearDependencies(): Unit

def clone(): AnyRef

def coalesce(numPartitions: Int, shuffle: Boolean)(implicit ord: Ordering[D]): RDD[D]

def collect[U](f: PartialFunction[D, U])(implicit arg0: ClassTag[U]): RDD[U]

def collect(): Array[D]

def compute(split: Partition, context: TaskContext): Iterator[D]

def context: SparkContext

def copy(connector: Broadcast[MongoConnector] = connector, readConfig: ReadConfig = readConfig, pipeline: Seq[Bson] = pipeline): MongoRDD[D]

Allows to copying of this RDD with changing some of the properties

def count(): Long

def countApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]

def countApproxDistinct(relativeSD: Double): Long

def countApproxDistinct(p: Int, sp: Int): Long

def countByValue()(implicit ord: Ordering[D]): Map[D, Long]

def countByValueApprox(timeout: Long, confidence: Double)(implicit ord: Ordering[D]): PartialResult[Map[D, BoundedDouble]]

final def dependencies: Seq[Dependency[_]]

def distinct(): RDD[D]

def distinct(numPartitions: Int)(implicit ord: Ordering[D]): RDD[D]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def filter(f: (D) ⇒ Boolean): RDD[D]

def finalize(): Unit

def first(): D

def firstParent[U](implicit arg0: ClassTag[U]): RDD[U]

def flatMap[U](f: (D) ⇒ TraversableOnce[U])(implicit arg0: ClassTag[U]): RDD[U]

def fold(zeroValue: D)(op: (D, D) ⇒ D): D

def foreach(f: (D) ⇒ Unit): Unit

def foreachPartition(f: (Iterator[D]) ⇒ Unit): Unit

def getCheckpointFile: Option[String]

final def getClass(): Class[_]

def getDependencies: Seq[Dependency[_]]

final def getNumPartitions: Int

def getPartitions: Array[Partition]

def getPreferredLocations(split: Partition): Seq[String]

def getStorageLevel: StorageLevel

def glom(): RDD[Array[D]]

def groupBy[K](f: (D) ⇒ K, p: Partitioner)(implicit kt: ClassTag[K], ord: Ordering[K]): RDD[(K, Iterable[D])]

def groupBy[K](f: (D) ⇒ K, numPartitions: Int)(implicit kt: ClassTag[K]): RDD[(K, Iterable[D])]

def groupBy[K](f: (D) ⇒ K)(implicit kt: ClassTag[K]): RDD[(K, Iterable[D])]

def hashCode(): Int

val id: Int

def intersection(other: RDD[D], numPartitions: Int): RDD[D]

def intersection(other: RDD[D], partitioner: Partitioner)(implicit ord: Ordering[D]): RDD[D]

def intersection(other: RDD[D]): RDD[D]

def isCheckpointed: Boolean

def isEmpty(): Boolean

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

final def iterator(split: Partition, context: TaskContext): Iterator[D]

def keyBy[K](f: (D) ⇒ K): RDD[(K, D)]

def localCheckpoint(): MongoRDD.this.type

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

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

def logError(msg: ⇒ String): Unit

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

def logInfo(msg: ⇒ String): Unit

def logName: String

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

def logTrace(msg: ⇒ String): Unit

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

def logWarning(msg: ⇒ String): Unit

def map[U](f: (D) ⇒ U)(implicit arg0: ClassTag[U]): RDD[U]

def mapPartitions[U](f: (Iterator[D]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]

def mapPartitionsWithIndex[U](f: (Int, Iterator[D]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]

def max()(implicit ord: Ordering[D]): D

def min()(implicit ord: Ordering[D]): D

var name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def parent[U](j: Int)(implicit arg0: ClassTag[U]): RDD[U]

val partitioner: Option[Partitioner]

final def partitions: Array[Partition]

def persist(): MongoRDD.this.type

def persist(newLevel: StorageLevel): MongoRDD.this.type

def pipe(command: Seq[String], env: Map[String, String], printPipeContext: ((String) ⇒ Unit) ⇒ Unit, printRDDElement: (D, (String) ⇒ Unit) ⇒ Unit, separateWorkingDir: Boolean): RDD[String]

def pipe(command: String, env: Map[String, String]): RDD[String]

def pipe(command: String): RDD[String]

final def preferredLocations(split: Partition): Seq[String]

def randomSplit(weights: Array[Double], seed: Long): Array[RDD[D]]

def reduce(f: (D, D) ⇒ D): D

def repartition(numPartitions: Int)(implicit ord: Ordering[D]): RDD[D]

def sample(withReplacement: Boolean, fraction: Double, seed: Long): RDD[D]

def saveAsObjectFile(path: String): Unit

def saveAsTextFile(path: String, codec: Class[_ <: CompressionCodec]): Unit

def saveAsTextFile(path: String): Unit

val sc: SparkContext

def setName(_name: String): MongoRDD.this.type

def sortBy[K](f: (D) ⇒ K, ascending: Boolean, numPartitions: Int)(implicit ord: Ordering[K], ctag: ClassTag[K]): RDD[D]

def sparkContext: SparkContext

val sqlContext: SQLContext

def subtract(other: RDD[D], p: Partitioner)(implicit ord: Ordering[D]): RDD[D]

def subtract(other: RDD[D], numPartitions: Int): RDD[D]

def subtract(other: RDD[D]): RDD[D]

final def synchronized[T0](arg0: ⇒ T0): T0

def take(num: Int): Array[D]

def takeOrdered(num: Int)(implicit ord: Ordering[D]): Array[D]

def takeSample(withReplacement: Boolean, num: Int, seed: Long): Array[D]

def toDF(schema: StructType): DataFrame

Creates a DataFrame based on the provided schema.

def toDF[T](beanClass: Class[T]): DataFrame

Creates a DataFrame based on the schema derived from the bean class.

def toDF[T <: Product]()(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[T]): DataFrame

Creates a DataFrame based on the schema derived from the optional type.

def toDS[T](beanClass: Class[T]): Dataset[T]

Creates a Dataset from the RDD strongly typed to the provided java bean.

def toDS[T <: Product]()(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[T], arg1: NotNothing[T]): Dataset[T]

Creates a Dataset from the collection strongly typed to the provided case class.

def toDebugString: String

def toJavaRDD(): JavaMongoRDD[D]

def toLocalIterator: Iterator[D]

def toString(): String

def top(num: Int)(implicit ord: Ordering[D]): Array[D]

def treeAggregate[U](zeroValue: U)(seqOp: (U, D) ⇒ U, combOp: (U, U) ⇒ U, depth: Int)(implicit arg0: ClassTag[U]): U

def treeReduce(f: (D, D) ⇒ D, depth: Int): D

def union(other: RDD[D]): RDD[D]

def unpersist(blocking: Boolean): MongoRDD.this.type

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def withPipeline[B <: Bson](pipeline: Seq[B]): MongoRDD[D]

Returns a copy with the specified aggregation pipeline

def zip[U](other: RDD[U])(implicit arg0: ClassTag[U]): RDD[(D, U)]

def zipPartitions[B, C, D, V](rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D])(f: (Iterator[D], Iterator[B], Iterator[C], Iterator[D]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[D], arg3: ClassTag[V]): RDD[V]

def zipPartitions[B, C, D, V](rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D], preservesPartitioning: Boolean)(f: (Iterator[D], Iterator[B], Iterator[C], Iterator[D]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[D], arg3: ClassTag[V]): RDD[V]

def zipPartitions[B, C, V](rdd2: RDD[B], rdd3: RDD[C])(f: (Iterator[D], Iterator[B], Iterator[C]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[V]): RDD[V]

def zipPartitions[B, C, V](rdd2: RDD[B], rdd3: RDD[C], preservesPartitioning: Boolean)(f: (Iterator[D], Iterator[B], Iterator[C]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[V]): RDD[V]

def zipPartitions[B, V](rdd2: RDD[B])(f: (Iterator[D], Iterator[B]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[V]): RDD[V]

def zipPartitions[B, V](rdd2: RDD[B], preservesPartitioning: Boolean)(f: (Iterator[D], Iterator[B]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[V]): RDD[V]

def zipWithIndex(): RDD[(D, Long)]

def zipWithUniqueId(): RDD[(D, Long)]

def filterWith[A](constructA: (Int) ⇒ A)(p: (D, A) ⇒ Boolean): RDD[D]

def flatMapWith[A, U](constructA: (Int) ⇒ A, preservesPartitioning: Boolean)(f: (D, A) ⇒ Seq[U])(implicit arg0: ClassTag[U]): RDD[U]

def foreachWith[A](constructA: (Int) ⇒ A)(f: (D, A) ⇒ Unit): Unit

def mapPartitionsWithContext[U](f: (TaskContext, Iterator[D]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]

def mapPartitionsWithSplit[U](f: (Int, Iterator[D]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]

def mapWith[A, U](constructA: (Int) ⇒ A, preservesPartitioning: Boolean)(f: (D, A) ⇒ U)(implicit arg0: ClassTag[U]): RDD[U]

def toArray(): Array[D]