SparkContextEx

Instance Constructors

new SparkContextEx(sc: SparkContext)

sc
The active Spark context.

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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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final def eq(arg0: AnyRef): Boolean

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final def getClass(): Class[_]

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final def isInstanceOf[T0]: Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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def rdd[α](text: String, column: String, lo: Long, hi: Long, partitions: ℕ, format: Format[α])(implicit arg0: ClassTag[α]): RDD[α]

Executes a query on the default cluster to yield a suitably partitioned RDD whose elements are formatted by applying the given function to each row of the resulting JDBC result set.
Executes a query on the default cluster to yield a suitably partitioned RDD whose elements are formatted by applying the given function to each row of the resulting JDBC result set.
text
The text of a query to be executed on the cluster or the name of an existing table in the cluster to load.
column
The name of the integral valued column in the result set with which to further partition the query.
lo
The lower bound of the partitioning column.
hi
The upper bound of the partitioning column.
partitions
The number of partitions per instance to create.
format
Formats an element from a single row of a result set.
returns
The results of the query in the form of a suitably partitioned RDD.

Exceptions thrown
SQLException if a database access error occurs.
See also
JDBC to Other Databases for more on the semantics of the column, lo, hi, and partitions parameters.
def rdd[α](text: String, mfpi: ℕ, format: Format[α])(implicit arg0: ClassTag[α]): RDD[α]

Executes a query on the default cluster to yield a suitably partitioned RDD whose elements are formatted by applying the given function to each row of the resulting JDBC result set.
Executes a query on the default cluster to yield a suitably partitioned RDD whose elements are formatted by applying the given function to each row of the resulting JDBC result set.
text
The text of a query to be executed on the cluster or the name of an existing table in the cluster to load.
mfpi
The maximum number of factors per distinct instance to include in the factorization implicitly performed by the server, or 0 if no limit is necessary.
format
Formats an element from a single row of a result set.
returns
The results of the query in the form of a suitably partitioned RDD.

Exceptions thrown
SQLException if a database access error occurs.
final def synchronized[T0](arg0: ⇒ T0): T0

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def toString(): String

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final def wait(): Unit

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Related Doc: package spark

implicit class SparkContextEx extends AnyRef

Instance Constructors

new SparkContextEx(sc: SparkContext)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def rdd[α](text: String, column: String, lo: Long, hi: Long, partitions: ℕ, format: Format[α])(implicit arg0: ClassTag[α]): RDD[α]

def rdd[α](text: String, mfpi: ℕ, format: Format[α])(implicit arg0: ClassTag[α]): RDD[α]

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

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