class
ExasolRDD extends RDD[Row] with Logging
Instance Constructors
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Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
aggregate[U](zeroValue: U)(seqOp: (U, Row) ⇒ U, combOp: (U, U) ⇒ U)(implicit arg0: ClassTag[U]): U
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final
def
asInstanceOf[T0]: T0
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def
barrier(): RDDBarrier[Row]
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def
cache(): ExasolRDD.this.type
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def
cartesian[U](other: RDD[U])(implicit arg0: ClassTag[U]): RDD[(Row, U)]
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def
checkpoint(): Unit
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def
clearDependencies(): Unit
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def
clone(): AnyRef
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def
closeMainResources(): Unit
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def
coalesce(numPartitions: Int, shuffle: Boolean, partitionCoalescer: Option[PartitionCoalescer])(implicit ord: Ordering[Row]): RDD[Row]
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def
collect(): Array[Row]
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def
compute(split: Partition, context: TaskContext): Iterator[Row]
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def
count(): Long
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def
countApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]
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def
countApproxDistinct(relativeSD: Double): Long
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def
countApproxDistinct(p: Int, sp: Int): Long
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def
countByValue()(implicit ord: Ordering[Row]): Map[Row, Long]
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def
countByValueApprox(timeout: Long, confidence: Double)(implicit ord: Ordering[Row]): PartialResult[Map[Row, BoundedDouble]]
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def
createMainConnection(): EXAConnection
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final
def
dependencies: Seq[Dependency[_]]
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def
distinct(): RDD[Row]
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def
distinct(numPartitions: Int)(implicit ord: Ordering[Row]): RDD[Row]
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def
finalize(): Unit
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def
first(): Row
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def
firstParent[U](implicit arg0: ClassTag[U]): RDD[U]
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def
flatMap[U](f: (Row) ⇒ TraversableOnce[U])(implicit arg0: ClassTag[U]): RDD[U]
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def
fold(zeroValue: Row)(op: (Row, Row) ⇒ Row): Row
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def
foreach(f: (Row) ⇒ Unit): Unit
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def
foreachPartition(f: (Iterator[Row]) ⇒ Unit): Unit
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def
getCheckpointFile: Option[String]
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final
def
getClass(): Class[_]
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def
getDependencies: Seq[Dependency[_]]
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final
def
getNumPartitions: Int
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def
getOutputDeterministicLevel: org.apache.spark.rdd.DeterministicLevel.Value
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def
getPreferredLocations(split: Partition): Seq[String]
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def
groupBy[K](f: (Row) ⇒ K, p: Partitioner)(implicit kt: ClassTag[K], ord: Ordering[K]): RDD[(K, Iterable[Row])]
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def
groupBy[K](f: (Row) ⇒ K, numPartitions: Int)(implicit kt: ClassTag[K]): RDD[(K, Iterable[Row])]
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def
groupBy[K](f: (Row) ⇒ K)(implicit kt: ClassTag[K]): RDD[(K, Iterable[Row])]
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def
hashCode(): Int
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val
id: Int
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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def
intersection(other: RDD[Row], numPartitions: Int): RDD[Row]
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def
intersection(other: RDD[Row], partitioner: Partitioner)(implicit ord: Ordering[Row]): RDD[Row]
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def
intersection(other: RDD[Row]): RDD[Row]
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lazy val
isBarrier_: Boolean
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def
isCheckpointed: Boolean
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def
isEmpty(): Boolean
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final
def
isInstanceOf[T0]: Boolean
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def
isTraceEnabled(): Boolean
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final
def
iterator(split: Partition, context: TaskContext): Iterator[Row]
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def
keyBy[K](f: (Row) ⇒ K): RDD[(K, Row)]
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def
localCheckpoint(): ExasolRDD.this.type
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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def
logError(msg: ⇒ String): Unit
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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def
logInfo(msg: ⇒ String): Unit
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def
logName: String
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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def
logTrace(msg: ⇒ String): Unit
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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def
logWarning(msg: ⇒ String): Unit
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def
map[U](f: (Row) ⇒ U)(implicit arg0: ClassTag[U]): RDD[U]
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def
mapPartitions[U](f: (Iterator[Row]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]
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def
mapPartitionsWithIndex[U](f: (Int, Iterator[Row]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassTag[U]): RDD[U]
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def
max()(implicit ord: Ordering[Row]): Row
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def
min()(implicit ord: Ordering[Row]): Row
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var
name: String
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
parent[U](j: Int)(implicit arg0: ClassTag[U]): RDD[U]
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def
persist(): ExasolRDD.this.type
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def
pipe(command: Seq[String], env: Map[String, String], printPipeContext: ((String) ⇒ Unit) ⇒ Unit, printRDDElement: (Row, (String) ⇒ Unit) ⇒ Unit, separateWorkingDir: Boolean, bufferSize: Int, encoding: String): RDD[String]
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def
pipe(command: String, env: Map[String, String]): RDD[String]
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def
pipe(command: String): RDD[String]
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final
def
preferredLocations(split: Partition): Seq[String]
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def
repartition(numPartitions: Int)(implicit ord: Ordering[Row]): RDD[Row]
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def
sample(withReplacement: Boolean, fraction: Double, seed: Long): RDD[Row]
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def
saveAsObjectFile(path: String): Unit
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def
saveAsTextFile(path: String, codec: Class[_ <: CompressionCodec]): Unit
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def
saveAsTextFile(path: String): Unit
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def
setName(_name: String): ExasolRDD.this.type
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def
sortBy[K](f: (Row) ⇒ K, ascending: Boolean, numPartitions: Int)(implicit ord: Ordering[K], ctag: ClassTag[K]): RDD[Row]
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def
subtract(other: RDD[Row], p: Partitioner)(implicit ord: Ordering[Row]): RDD[Row]
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def
subtract(other: RDD[Row], numPartitions: Int): RDD[Row]
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def
subtract(other: RDD[Row]): RDD[Row]
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
takeOrdered(num: Int)(implicit ord: Ordering[Row]): Array[Row]
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def
takeSample(withReplacement: Boolean, num: Int, seed: Long): Array[Row]
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def
toDebugString: String
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def
toJavaRDD(): JavaRDD[Row]
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def
toLocalIterator: Iterator[Row]
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def
toString(): String
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def
top(num: Int)(implicit ord: Ordering[Row]): Array[Row]
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def
treeAggregate[U](zeroValue: U)(seqOp: (U, Row) ⇒ U, combOp: (U, U) ⇒ U, depth: Int)(implicit arg0: ClassTag[U]): U
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def
treeReduce(f: (Row, Row) ⇒ Row, depth: Int): Row
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def
unpersist(blocking: Boolean): ExasolRDD.this.type
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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def
zip[U](other: RDD[U])(implicit arg0: ClassTag[U]): RDD[(Row, U)]
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def
zipPartitions[B, C, D, V](rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D])(f: (Iterator[Row], Iterator[B], Iterator[C], Iterator[D]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[D], arg3: ClassTag[V]): RDD[V]
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def
zipPartitions[B, C, D, V](rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D], preservesPartitioning: Boolean)(f: (Iterator[Row], Iterator[B], Iterator[C], Iterator[D]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[D], arg3: ClassTag[V]): RDD[V]
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def
zipPartitions[B, C, V](rdd2: RDD[B], rdd3: RDD[C])(f: (Iterator[Row], Iterator[B], Iterator[C]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[V]): RDD[V]
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def
zipPartitions[B, C, V](rdd2: RDD[B], rdd3: RDD[C], preservesPartitioning: Boolean)(f: (Iterator[Row], Iterator[B], Iterator[C]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[C], arg2: ClassTag[V]): RDD[V]
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def
zipPartitions[B, V](rdd2: RDD[B])(f: (Iterator[Row], Iterator[B]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[V]): RDD[V]
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def
zipPartitions[B, V](rdd2: RDD[B], preservesPartitioning: Boolean)(f: (Iterator[Row], Iterator[B]) ⇒ Iterator[V])(implicit arg0: ClassTag[B], arg1: ClassTag[V]): RDD[V]
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def
zipWithIndex(): RDD[(Row, Long)]
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def
zipWithUniqueId(): RDD[(Row, Long)]
An org.apache.spark.rdd.RDD reads / writes data from an Exasol tables.
The com.exasol.spark.rdd.ExasolRDD holds data in parallel from each Exasol physical nodes.