frameless.TypedDatasetForwarded
deserialized
Related Doc:
package TypedDatasetForwarded
Returns a new TypedDataset that only contains elements where func returns true.
Returns a new TypedDataset that only contains elements where func returns true.
apache/spark
Returns a new TypedDataset by first applying a function to all elements of this TypedDataset, and then flattening the results.
Returns a new TypedDataset by first applying a function to all elements of this TypedDataset, and then flattening the results.
apache/spark
Returns a new TypedDataset that contains the result of applying func to each element.
Returns a new TypedDataset that contains the result of applying func to each element.
apache/spark
Returns a new TypedDataset that contains the result of applying func to each partition.
Returns a new TypedDataset that contains the result of applying func to each partition.
apache/spark
Optionally reduces the elements of this TypedDataset using the specified binary function.
Optionally reduces the elements of this TypedDataset using the specified binary function. The given
func must be commutative and associative or the result may be non-deterministic.
Differs from Dataset#reduce by wrapping its result into an Option and an effect-suspending F.
Methods on
TypedDataset[T]that go through a full serialization and deserialization ofT, and execute outside of the Catalyst runtime.The correct way to do a projection on a single column is to use the
selectmethod as follows:Spark provides an alternative way to obtain the same resulting
Dataset, using themapmethod:This second approach is however substantially slower than the first one, and should be avoided as possible. Indeed, under the hood this
mapwill deserialize the entireTuple3to an full JVM object, call the apply method of the_._2closure on it, and serialize the resulting String back to its Catalyst representation.