package mutable
- Source
- package.scala
- Alphabetic
- By Inheritance
- mutable
- AnyRef
- Any
- Hide All
- Show All
- Public
- All
Type Members
-
trait
LazyCombiner[Elem, +To, Buff <: Growable[Elem] with Sizing] extends Combiner[Elem, To]
Implements combining contents of two combiners by postponing the operation until
result
method is called.Implements combining contents of two combiners by postponing the operation until
result
method is called. It chains the leaf results together instead of evaluating the actual collection.- Elem
the type of the elements in the combiner
- To
the type of the collection the combiner produces
- Buff
the type of the buffers that contain leaf results and this combiner chains together
-
class
ParArray[T] extends ParSeq[T] with GenericParTemplate[T, ParArray] with ParSeqLike[T, ParArray[T], ArraySeq[T]] with Serializable
Parallel sequence holding elements in a linear array.
Parallel sequence holding elements in a linear array.
ParArray
is a parallel sequence with a predefined size. The size of the array cannot be changed after it's been created.ParArray
internally keeps an array containing the elements. This means that bulk operations based on traversal ensure fast access to elements.ParArray
uses lazy builders that create the internal data array only after the size of the array is known. In the meantime, they keep the result set fragmented. The fragments are copied into the resulting data array in parallel using fast array copy operations once all the combiners are populated in parallel.- T
type of the elements in the array
- Annotations
- @SerialVersionUID()
- Since
2.9
- See also
Scala's Parallel Collections Library overview section on
ParArray
for more information.
- type ParArrayCombiner[T] = ResizableParArrayCombiner[T]
-
trait
ParFlatHashTable[T] extends FlatHashTable[T]
Parallel flat hash table.
Parallel flat hash table.
- T
type of the elements in the table.
-
class
ParHashMap[K, V] extends ParMap[K, V] with GenericParMapTemplate[K, V, ParHashMap] with ParMapLike[K, V, ParHashMap[K, V], HashMap[K, V]] with ParHashTable[K, DefaultEntry[K, V]] with Serializable
A parallel hash map.
A parallel hash map.
ParHashMap
is a parallel map which internally keeps elements within a hash table. It uses chaining to resolve collisions.- K
type of the keys in the parallel hash map
- V
type of the values in the parallel hash map
- Annotations
- @SerialVersionUID()
-
class
ParHashSet[T] extends ParSet[T] with GenericParTemplate[T, ParHashSet] with ParSetLike[T, ParHashSet[T], HashSet[T]] with ParFlatHashTable[T] with Serializable
A parallel hash set.
A parallel hash set.
ParHashSet
is a parallel set which internally keeps elements within a hash table. It uses linear probing to resolve collisions.- T
type of the elements in the parallel hash set .
- Annotations
- @SerialVersionUID()
-
trait
ParHashTable[K, Entry >: Null <: HashEntry[K, Entry]] extends HashTable[K, Entry]
Provides functionality for hash tables with linked list buckets, enriching the data structure by fulfilling certain requirements for their parallel construction and iteration.
-
trait
ParIterable[T] extends GenIterable[T] with parallel.ParIterable[T] with GenericParTemplate[T, ParIterable] with ParIterableLike[T, ParIterable[T], Iterable[T]] with Mutable
A template trait for mutable parallel iterable collections.
A template trait for mutable parallel iterable collections.
This is a base trait for Scala parallel collections. It defines behaviour common to all parallel collections. Concrete parallel collections should inherit this trait and
ParIterable
if they want to define specific combiner factories.Parallel operations are implemented with divide and conquer style algorithms that parallelize well. The basic idea is to split the collection into smaller parts until they are small enough to be operated on sequentially.
All of the parallel operations are implemented as tasks within this trait. Tasks rely on the concept of splitters, which extend iterators. Every parallel collection defines:
def splitter: IterableSplitter[T]
which returns an instance of
IterableSplitter[T]
, which is a subtype ofSplitter[T]
. Splitters have a methodremaining
to check the remaining number of elements, and methodsplit
which is defined by splitters. Methodsplit
divides the splitters iterate over into disjunct subsets:def split: Seq[Splitter]
which splits the splitter into a sequence of disjunct subsplitters. This is typically a very fast operation which simply creates wrappers around the receiver collection. This can be repeated recursively.
Tasks are scheduled for execution through a scala.collection.parallel.TaskSupport object, which can be changed through the
tasksupport
setter of the collection.Method
newCombiner
produces a new combiner. Combiners are an extension of builders. They provide a methodcombine
which combines two combiners and returns a combiner containing elements of both combiners. This method can be implemented by aggressively copying all the elements into the new combiner or by lazily binding their results. It is recommended to avoid copying all of the elements for performance reasons, although that cost might be negligible depending on the use case. Standard parallel collection combiners avoid copying when merging results, relying either on a two-step lazy construction or specific data-structure properties.Methods:
def seq: Sequential def par: Repr
produce the sequential or parallel implementation of the collection, respectively. Method
par
just returns a reference to this parallel collection. Methodseq
is efficient - it will not copy the elements. Instead, it will create a sequential version of the collection using the same underlying data structure. Note that this is not the case for sequential collections in general - they may copy the elements and produce a different underlying data structure.The combination of methods
toMap
,toSeq
ortoSet
along withpar
andseq
is a flexible way to change between different collection types.Since this trait extends the
GenIterable
trait, methods likesize
must also be implemented in concrete collections, whileiterator
forwards tosplitter
by default.Each parallel collection is bound to a specific fork/join pool, on which dormant worker threads are kept. The fork/join pool contains other information such as the parallelism level, that is, the number of processors used. When a collection is created, it is assigned the default fork/join pool found in the
scala.parallel
package object.Parallel collections are not necessarily ordered in terms of the
foreach
operation (seeTraversable
). Parallel sequences have a well defined order for iterators - creating an iterator and traversing the elements linearly will always yield the same order. However, bulk operations such asforeach
,map
orfilter
always occur in undefined orders for all parallel collections.Existing parallel collection implementations provide strict parallel iterators. Strict parallel iterators are aware of the number of elements they have yet to traverse. It's also possible to provide non-strict parallel iterators, which do not know the number of elements remaining. To do this, the new collection implementation must override
isStrictSplitterCollection
tofalse
. This will make some operations unavailable.To create a new parallel collection, extend the
ParIterable
trait, and implementsize
,splitter
,newCombiner
andseq
. Having an implicit combiner factory requires extending this trait in addition, as well as providing a companion object, as with regular collections.Method
size
is implemented as a constant time operation for parallel collections, and parallel collection operations rely on this assumption.The higher-order functions passed to certain operations may contain side-effects. Since implementations of bulk operations may not be sequential, this means that side-effects may not be predictable and may produce data-races, deadlocks or invalidation of state if care is not taken. It is up to the programmer to either avoid using side-effects or to use some form of synchronization when accessing mutable data.
- T
the element type of the collection
- Since
2.9
-
trait
ParMap[K, V] extends GenMap[K, V] with parallel.ParMap[K, V] with ParIterable[(K, V)] with GenericParMapTemplate[K, V, ParMap] with ParMapLike[K, V, ParMap[K, V], mutable.Map[K, V]]
A template trait for mutable parallel maps.
A template trait for mutable parallel maps.
The higher-order functions passed to certain operations may contain side-effects. Since implementations of bulk operations may not be sequential, this means that side-effects may not be predictable and may produce data-races, deadlocks or invalidation of state if care is not taken. It is up to the programmer to either avoid using side-effects or to use some form of synchronization when accessing mutable data.
- K
the key type of the map
- V
the value type of the map
- Since
2.9
-
trait
ParMapLike[K, V, +Repr <: ParMapLike[K, V, Repr, Sequential] with ParMap[K, V], +Sequential <: mutable.Map[K, V] with mutable.MapLike[K, V, Sequential]] extends GenMapLike[K, V, Repr] with parallel.ParMapLike[K, V, Repr, Sequential] with Growable[(K, V)] with Shrinkable[K] with mutable.Cloneable[Repr]
A template trait for mutable parallel maps.
A template trait for mutable parallel maps. This trait is to be mixed in with concrete parallel maps to override the representation type.
The higher-order functions passed to certain operations may contain side-effects. Since implementations of bulk operations may not be sequential, this means that side-effects may not be predictable and may produce data-races, deadlocks or invalidation of state if care is not taken. It is up to the programmer to either avoid using side-effects or to use some form of synchronization when accessing mutable data.
- K
the key type of the map
- V
the value type of the map
-
trait
ParSeq[T] extends GenSeq[T] with ParIterable[T] with parallel.ParSeq[T] with GenericParTemplate[T, ParSeq] with ParSeqLike[T, ParSeq[T], mutable.Seq[T]]
A mutable variant of
ParSeq
. -
trait
ParSet[T] extends GenSet[T] with ParIterable[T] with parallel.ParSet[T] with GenericParTemplate[T, ParSet] with ParSetLike[T, ParSet[T], mutable.Set[T]]
A mutable variant of
ParSet
. -
trait
ParSetLike[T, +Repr <: ParSetLike[T, Repr, Sequential] with ParSet[T], +Sequential <: mutable.Set[T] with mutable.SetLike[T, Sequential]] extends GenSetLike[T, Repr] with ParIterableLike[T, Repr, Sequential] with parallel.ParSetLike[T, Repr, Sequential] with Growable[T] with Shrinkable[T] with mutable.Cloneable[Repr]
A template trait for mutable parallel sets.
A template trait for mutable parallel sets. This trait is mixed in with concrete parallel sets to override the representation type.
The higher-order functions passed to certain operations may contain side-effects. Since implementations of bulk operations may not be sequential, this means that side-effects may not be predictable and may produce data-races, deadlocks or invalidation of state if care is not taken. It is up to the programmer to either avoid using side-effects or to use some form of synchronization when accessing mutable data.
- T
the element type of the set
-
final
class
ParTrieMap[K, V] extends ParMap[K, V] with GenericParMapTemplate[K, V, ParTrieMap] with ParMapLike[K, V, ParTrieMap[K, V], TrieMap[K, V]] with ParTrieMapCombiner[K, V] with Serializable
Parallel TrieMap collection.
Parallel TrieMap collection.
It has its bulk operations parallelized, but uses the snapshot operation to create the splitter. This means that parallel bulk operations can be called concurrently with the modifications.
- Since
2.10
- See also
Scala's Parallel Collections Library overview section on
ParTrieMap
for more information.
-
trait
ResizableParArrayCombiner[T] extends LazyCombiner[T, ParArray[T], ExposedArrayBuffer[T]]
An array combiner that uses a chain of arraybuffers to store elements.
-
trait
UnrolledParArrayCombiner[T] extends Combiner[T, ParArray[T]]
An array combiner that uses doubling unrolled buffers to store elements.
Value Members
- val ParArrayCombiner: ResizableParArrayCombiner.type
-
object
ParArray extends ParFactory[ParArray] with Serializable
This object provides a set of operations to create
values.mutable.ParArray
-
object
ParHashMap extends ParMapFactory[ParHashMap] with Serializable
This object provides a set of operations needed to create
values.mutable.ParHashMap
-
object
ParHashSet extends ParSetFactory[ParHashSet] with Serializable
This object provides a set of operations needed to create
values.mutable.ParHashSet
-
object
ParIterable extends ParFactory[ParIterable]
This object provides a set of operations to create
values.ParIterable
- object ParMap extends ParMapFactory[ParMap]
-
object
ParSeq extends ParFactory[ParSeq]
This object provides a set of operations to create
values.mutable.ParSeq
-
object
ParSet extends ParSetFactory[ParSet]
This object provides a set of operations needed to create
values.mutable.ParSet
- object ParTrieMap extends ParMapFactory[ParTrieMap] with Serializable
- object ResizableParArrayCombiner
- object UnrolledParArrayCombiner
This is the documentation for the Scala standard library.
Package structure
The scala package contains core types like
Int
,Float
,Array
orOption
which are accessible in all Scala compilation units without explicit qualification or imports.Notable packages include:
scala.collection
and its sub-packages contain Scala's collections frameworkscala.collection.immutable
- Immutable, sequential data-structures such asVector
,List
,Range
,HashMap
orHashSet
scala.collection.mutable
- Mutable, sequential data-structures such asArrayBuffer
,StringBuilder
,HashMap
orHashSet
scala.collection.concurrent
- Mutable, concurrent data-structures such asTrieMap
scala.collection.parallel.immutable
- Immutable, parallel data-structures such asParVector
,ParRange
,ParHashMap
orParHashSet
scala.collection.parallel.mutable
- Mutable, parallel data-structures such asParArray
,ParHashMap
,ParTrieMap
orParHashSet
scala.concurrent
- Primitives for concurrent programming such asFutures
andPromises
scala.io
- Input and output operationsscala.math
- Basic math functions and additional numeric types likeBigInt
andBigDecimal
scala.sys
- Interaction with other processes and the operating systemscala.util.matching
- Regular expressionsOther packages exist. See the complete list on the right.
Additional parts of the standard library are shipped as separate libraries. These include:
scala.reflect
- Scala's reflection API (scala-reflect.jar)scala.xml
- XML parsing, manipulation, and serialization (scala-xml.jar)scala.swing
- A convenient wrapper around Java's GUI framework called Swing (scala-swing.jar)scala.util.parsing
- Parser combinators (scala-parser-combinators.jar)Automatic imports
Identifiers in the scala package and the
scala.Predef
object are always in scope by default.Some of these identifiers are type aliases provided as shortcuts to commonly used classes. For example,
List
is an alias forscala.collection.immutable.List
.Other aliases refer to classes provided by the underlying platform. For example, on the JVM,
String
is an alias forjava.lang.String
.