TarantoolReadRDD

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

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

final def asInstanceOf[T0]: T0

def barrier(): RDDBarrier[R]

def cache(): TarantoolReadRDD.this.type

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

def checkpoint(): Unit

def clearDependencies(): Unit

def clone(): AnyRef

def coalesce(numPartitions: Int, shuffle: Boolean, partitionCoalescer: Option[PartitionCoalescer])(implicit ord: Ordering[R]): RDD[R]

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

def collect(): Array[R]

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

val conditions: Conditions

tuple filtering conditions

def context: SparkContext

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[R]): Map[R, Long]

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

final def dependencies: Seq[Dependency[_]]

def distinct(): RDD[R]

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

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def filter(f: (R) ⇒ Boolean): RDD[R]

def first(): R

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

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

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

def foreach(f: (R) ⇒ Unit): Unit

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

def getCheckpointFile: Option[String]

final def getClass(): Class[_]

def getDependencies: Seq[Dependency[_]]

final def getNumPartitions: Int

def getOutputDeterministicLevel: org.apache.spark.rdd.DeterministicLevel.Value

def getPartitions: Array[Partition]

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

def getStorageLevel: StorageLevel

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

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

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

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

def hashCode(): Int

val id: Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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

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

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

lazy val isBarrier_: Boolean

def isCheckpointed: Boolean

def isEmpty(): Boolean

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

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

def keyBy[K](f: (R) ⇒ K): RDD[(K, R)]

def localCheckpoint(): TarantoolReadRDD.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: (R) ⇒ U)(implicit arg0: ClassTag[U]): RDD[U]

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

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

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

implicit val messagePackMapper: MessagePackMapper

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

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(): TarantoolReadRDD.this.type

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

def pipe(command: Seq[String], env: Map[String, String], printPipeContext: ((String) ⇒ Unit) ⇒ Unit, printRDDElement: (R, (String) ⇒ Unit) ⇒ Unit, separateWorkingDir: Boolean, bufferSize: Int, encoding: String): 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[R]]

val readConfig: ReadConfig

read request configuration

def reduce(f: (R, R) ⇒ R): R

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

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

def saveAsObjectFile(path: String): Unit

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

def saveAsTextFile(path: String): Unit

val sc: SparkContext

spark context

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

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

val space: String

Tarantool space name

def sparkContext: SparkContext

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

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

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

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

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

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

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

def toDebugString: String

def toJavaRDD(): JavaRDD[R]

def toLocalIterator: Iterator[R]

def toString(): String

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

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

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

val tupleConverter: TupleConverter[R]

converter from TarantoolTuple to type R

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

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

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

final def wait(arg0: Long): Unit

final def wait(): Unit

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

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

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

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

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

def finalize(): Unit