Return the union of this RDD and another one.
Return the union of this RDD and another one. Any identical elements will appear multiple
times (use .distinct() to eliminate them).
Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value".
Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value". This function can return a different result type, U, than the type of this RDD, T. Thus, we need one operation for merging a T into an U and one operation for merging two U's, as in scala.TraversableOnce. Both of these functions are allowed to modify and return their first argument instead of creating a new U to avoid memory allocation.
Persist this RDD with the default storage level (MEMORY_ONLY).
Persist this RDD with the default storage level (MEMORY_ONLY).
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of
elements (a, b) where a is in this and b is in other.
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of
elements (a, b) where a is in this and b is in other.
Mark this RDD for checkpointing.
Mark this RDD for checkpointing. It will be saved to a file inside the checkpoint directory set with SparkContext.setCheckpointDir() and all references to its parent RDDs will be removed. This function must be called before any job has been executed on this RDD. It is strongly recommended that this RDD is persisted in memory, otherwise saving it on a file will require recomputation.
Clears the dependencies of this RDD.
Clears the dependencies of this RDD. This method must ensure that all references to the original parent RDDs is removed to enable the parent RDDs to be garbage collected. Subclasses of RDD may override this method for implementing their own cleaning logic. See UnionRDD for an example.
Return a new RDD that is reduced into numPartitions partitions.
Return a new RDD that is reduced into numPartitions partitions.
Return an RDD that contains all matching values by applying f.
Return an RDD that contains all matching values by applying f.
Return an array that contains all of the elements in this RDD.
Return an array that contains all of the elements in this RDD.
Implemented by subclasses to compute a given partition.
Implemented by subclasses to compute a given partition.
The SparkContext that this RDD was created on.
The SparkContext that this RDD was created on.
Return the number of elements in the RDD.
Return the number of elements in the RDD.
(Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.
(Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.
Return the count of each unique value in this RDD as a map of (value, count) pairs.
Return the count of each unique value in this RDD as a map of (value, count) pairs. The final combine step happens locally on the master, equivalent to running a single reduce task.
(Experimental) Approximate version of countByValue().
(Experimental) Approximate version of countByValue().
Get the list of dependencies of this RDD, taking into account whether the RDD is checkpointed or not.
Get the list of dependencies of this RDD, taking into account whether the RDD is checkpointed or not.
Return a new RDD containing the distinct elements in this RDD.
Return a new RDD containing the distinct elements in this RDD.
Return a new RDD containing only the elements that satisfy a predicate.
Return a new RDD containing only the elements that satisfy a predicate.
Return the first element in this RDD.
Return the first element in this RDD.
Returns the first parent RDD
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value".
Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value". The function op(t1, t2) is allowed to modify t1 and return it as its result value to avoid object allocation; however, it should not modify t2.
Applies a function f to all elements of this RDD.
Applies a function f to all elements of this RDD.
Gets the name of the file to which this RDD was checkpointed
Gets the name of the file to which this RDD was checkpointed
Implemented by subclasses to return how this RDD depends on parent RDDs.
Implemented by subclasses to return how this RDD depends on parent RDDs. This method will only be called once, so it is safe to implement a time-consuming computation in it.
Implemented by subclasses to return the set of partitions in this RDD.
Implemented by subclasses to return the set of partitions in this RDD. This method will only be called once, so it is safe to implement a time-consuming computation in it.
Optionally overridden by subclasses to specify placement preferences.
Optionally overridden by subclasses to specify placement preferences.
Get the RDD's current storage level, or StorageLevel.
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
Return an RDD created by coalescing all elements within each partition into an array.
Return an RDD created by coalescing all elements within each partition into an array.
Return an RDD of grouped items.
Return an RDD of grouped items.
Return an RDD of grouped elements.
Return an RDD of grouped elements. Each group consists of a key and a sequence of elements mapping to that key.
Return an RDD of grouped items.
Return an RDD of grouped items.
A unique ID for this RDD (within its SparkContext).
A unique ID for this RDD (within its SparkContext).
Return whether this RDD has been checkpointed or not
Return whether this RDD has been checkpointed or not
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
Internal method to this RDD; will read from cache if applicable, or otherwise compute it. This should not be called by users directly, but is available for implementors of custom subclasses of RDD.
Creates tuples of the elements in this RDD by applying f.
Creates tuples of the elements in this RDD by applying f.
Return a new RDD by applying a function to all elements of this RDD.
Return a new RDD by applying a function to all elements of this RDD.
Return a new RDD by applying a function to each partition of this RDD.
Return a new RDD by applying a function to each partition of this RDD.
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
A friendly name for this RDD
A friendly name for this RDD
Optionally overridden by subclasses to specify how they are partitioned.
Optionally overridden by subclasses to specify how they are partitioned.
Get the array of partitions of this RDD, taking into account whether the RDD is checkpointed or not.
Get the array of partitions of this RDD, taking into account whether the RDD is checkpointed or not.
Persist this RDD with the default storage level (MEMORY_ONLY).
Persist this RDD with the default storage level (MEMORY_ONLY).
Set this RDD's storage level to persist its values across operations after the first time it is computed.
Set this RDD's storage level to persist its values across operations after the first time it is computed. Can only be called once on each RDD.
Return an RDD created by piping elements to a forked external process.
Return an RDD created by piping elements to a forked external process.
Return an RDD created by piping elements to a forked external process.
Return an RDD created by piping elements to a forked external process.
Return an RDD created by piping elements to a forked external process.
Return an RDD created by piping elements to a forked external process.
Get the preferred location of a split, taking into account whether the RDD is checkpointed or not.
Get the preferred location of a split, taking into account whether the RDD is checkpointed or not.
Reduces the elements of this RDD using the specified commutative and associative binary operator.
Reduces the elements of this RDD using the specified commutative and associative binary operator.
Return a sampled subset of this RDD.
Return a sampled subset of this RDD.
Save this RDD as a SequenceFile of serialized objects.
Save this RDD as a SequenceFile of serialized objects.
Save this RDD as a text file, using string representations of elements.
Save this RDD as a text file, using string representations of elements.
Assign a name to this RDD
Assign a name to this RDD
Return an RDD with the elements from this that are not in other.
Return an RDD with the elements from this that are not in other.
Return an RDD with the elements from this that are not in other.
Return an RDD with the elements from this that are not in other.
Return an RDD with the elements from this that are not in other.
Return an RDD with the elements from this that are not in other.
Uses this partitioner/partition size, because even if other is huge, the resulting
RDD will be <= us.
Take the first num elements of the RDD.
Take the first num elements of the RDD. This currently scans the partitions *one by one*, so it will be slow if a lot of partitions are required. In that case, use collect() to get the whole RDD instead.
Return an array that contains all of the elements in this RDD.
Return an array that contains all of the elements in this RDD.
A description of this RDD and its recursive dependencies for debugging.
A description of this RDD and its recursive dependencies for debugging.
Return the union of this RDD and another one.
Return the union of this RDD and another one. Any identical elements will appear multiple
times (use .distinct() to eliminate them).
Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc.
Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc. Assumes that the two RDDs have the *same number of partitions* and the *same number of elements in each partition* (e.g. one was made through a map on the other).
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
(Since version scala.this.deprecated.init$default$2) use mapPartitionsWithIndex
Coalesce the partitions of a parent RDD (
prev) into fewer partitions, so that each partition of this RDD computes one or more of the parent ones. Will produce exactlymaxPartitionsif the parent had more than this many partitions, or fewer if the parent had fewer.This transformation is useful when an RDD with many partitions gets filtered into a smaller one, or to avoid having a large number of small tasks when processing a directory with many files.