Interface CacheStream<R>

Type Parameters:
R - The type of the stream
All Superinterfaces:
AutoCloseable, BaseCacheStream<R, Stream<R>>, BaseStream<R, Stream<R>>, Stream<R>
All Known Implementing Classes:
AbstractDelegatingCacheStream, DistributedCacheStream, IntermediateCacheStream
public interface CacheStream<R> extends Stream<R>, BaseCacheStream<R, Stream<R>>
A Stream that has additional operations to monitor or control behavior when used from a Cache.

Whenever the iterator or spliterator methods are used the user must close the Stream that the method was invoked on after completion of its operation. Failure to do so may cause a thread leakage if the iterator or spliterator are not fully consumed.

When using stream that is backed by a distributed cache these operations will be performed using remote distribution controlled by the segments that each key maps to. All intermediate operations are lazy, even the special cases described in later paragraphs and are not evaluated until a final terminal operation is invoked on the stream. Essentially each set of intermediate operations is shipped to each remote node where they are applied to a local stream there and finally the terminal operation is completed. If this stream is parallel the processing on remote nodes is also done using a parallel stream.

Parallel distribution is enabled by default for all operations except for iterator() and spliterator(). Please see sequentialDistribution() and parallelDistribution(). With this disabled only a single node will process the operation at a time (includes locally).

Rehash aware is enabled by default for all operations. Any intermediate or terminal operation may be invoked multiple times during a rehash and thus you should ensure the are idempotent. This can be problematic for forEach(Consumer) as it may be difficult to implement with such requirements, please see it for more information. If you wish to disable rehash aware operations you can disable them by calling disableRehashAware() which should provide better performance for some operations. The performance is most affected for the key aware operations iterator(), spliterator(), forEach(Consumer). Disabling rehash can cause incorrect results if the terminal operation is invoked and a rehash occurs before the operation completes. If incorrect results do occur it is guaranteed that it will only be that entries were missed and no entries are duplicated.

Any stateful intermediate operation requires pulling all information up to that point local to operate properly. Each of these methods may have slightly different behavior, so make sure you check the method you are utilizing.

An example of such an operation is using distinct intermediate operation. What will happen is upon calling the terminal operation a remote retrieval operation will be run using all the intermediate operations up to the distinct operation remotely. This retrieval is then used to fuel a local stream where all the remaining intermediate operations are performed and then finally the terminal operation is applied as normal. Note in this case the intermediate iterator still obeys the distributedBatchSize(int) setting irrespective of the terminal operator.

Since:
8.0

  • Method Details

    • sequentialDistribution

      CacheStream<R> sequentialDistribution()
      This would disable sending requests to all other remote nodes compared to one at a time. This can reduce memory pressure on the originator node at the cost of performance.

      Parallel distribution is enabled by default except for iterator() and spliterator()

      Specified by:
      sequentialDistribution in interface BaseCacheStream<R, Stream<R>>
      Returns:
      a stream with parallel distribution disabled.

    • parallelDistribution

      CacheStream<R> parallelDistribution()
      This would enable sending requests to all other remote nodes when a terminal operator is performed. This requires additional overhead as it must process results concurrently from various nodes, but should perform faster in the majority of cases.

      Parallel distribution is enabled by default except for iterator() and spliterator()

      Specified by:
      parallelDistribution in interface BaseCacheStream<R, Stream<R>>
      Returns:
      a stream with parallel distribution enabled.

    • filterKeySegments

      CacheStream<R> filterKeySegments(IntSet segments)
      Filters which entries are returned by what segment they are present in. This method can be substantially more efficient than using a regular filter(Predicate) method as this can control what nodes are asked for data and what entries are read from the underlying CacheStore if present.
      Specified by:
      filterKeySegments in interface BaseCacheStream<R, Stream<R>>
      Parameters:
      segments - The segments to use for this stream operation. Any segments not in this set will be ignored.
      Returns:
      a stream with the segments filtered.

    • filterKeys

      CacheStream<R> filterKeys(Set<?> keys)
      Filters which entries are returned by only returning ones that map to the given key. This method will be faster than a regular filter(Predicate) if the filter is holding references to the same keys.
      Specified by:
      filterKeys in interface BaseCacheStream<R, Stream<R>>
      Parameters:
      keys - The keys that this stream will only operate on.
      Returns:
      a stream with the keys filtered.

    • distributedBatchSize

      CacheStream<R> distributedBatchSize(int batchSize)
      Controls how many keys are returned from a remote node when using a stream terminal operation with a distributed cache to back this stream. This value is ignored when terminal operators that don't track keys are used. Key tracking terminal operators are iterator(), spliterator(), forEach(Consumer). Please see those methods for additional information on how this value may affect them.

      This value may be used in the case of a a terminal operator that doesn't track keys if an intermediate operation is performed that requires bringing keys locally to do computations. Examples of such intermediate operations are sorted(), sorted(Comparator), distinct(), limit(long), skip(long)

      This value is always ignored when this stream is backed by a cache that is not distributed as all values are already local.

      Specified by:
      distributedBatchSize in interface BaseCacheStream<R, Stream<R>>
      Parameters:
      batchSize - The size of each batch. This defaults to the state transfer chunk size.
      Returns:
      a stream with the batch size updated

    • segmentCompletionListener

      CacheStream<R> segmentCompletionListener(BaseCacheStream.SegmentCompletionListener listener)
      Allows registration of a segment completion listener that is notified when a segment has completed processing. If the terminal operator has a short circuit this listener may never be called.

      This method is designed for the sole purpose of use with the iterator() to allow for a user to track completion of segments as they are returned from the iterator. Behavior of other methods is not specified. Please see iterator() for more information.

      Multiple listeners may be registered upon multiple invocations of this method. The ordering of notified listeners is not specified.

      This is only used if this stream did not invoke BaseCacheStream.disableRehashAware() and has no flat map based operations. If this is done no segments will be notified.

      Specified by:
      segmentCompletionListener in interface BaseCacheStream<R, Stream<R>>
      Parameters:
      listener - The listener that will be called back as segments are completed.
      Returns:
      a stream with the listener registered.

    • disableRehashAware

      CacheStream<R> disableRehashAware()
      Disables tracking of rehash events that could occur to the underlying cache. If a rehash event occurs while a terminal operation is being performed it is possible for some values that are in the cache to not be found. Note that you will never have an entry duplicated when rehash awareness is disabled, only lost values.

      Most terminal operations will run faster with rehash awareness disabled even without a rehash occuring. However if a rehash occurs with this disabled be prepared to possibly receive only a subset of values.

      Specified by:
      disableRehashAware in interface BaseCacheStream<R, Stream<R>>
      Returns:
      a stream with rehash awareness disabled.

    • timeout

      CacheStream<R> timeout(long timeout, TimeUnit unit)
      Sets a given time to wait for a remote operation to respond by. This timeout does nothing if the terminal operation does not go remote.

      If a timeout does occur then a TimeoutException is thrown from the terminal operation invoking thread or on the next call to the Iterator or Spliterator.

      Note that if a rehash occurs this timeout value is reset for the subsequent retry if rehash aware is enabled.

      Specified by:
      timeout in interface BaseCacheStream<R, Stream<R>>
      Parameters:
      timeout - the maximum time to wait
      unit - the time unit of the timeout argument
      Returns:
      a stream with the timeout set

    • forEach

      void forEach(Consumer<? super R> action)

      This operation is performed remotely on the node that is the primary owner for the key tied to the entry(s) in this stream.

      NOTE: This method while being rehash-aware has the lowest consistency of all the operators. This operation will be performed on every entry at least once in the cluster, as long as the originator doesn't go down while it is being performed. This is due to how the distributed action is performed. Essentially the distributedBatchSize(int) value controls how many elements are processed per node at a time when rehash is enabled. After those are complete the keys are sent to the originator to confirm that those were processed. If that node goes down during/before the response those keys will be processed a second time.

      It is possible to have the cache local to each node injected into this instance if the provided Consumer also implements the CacheAware interface. This method will be invoked before the consumer accept() method is invoked.

      This method is run distributed by default with a distributed backing cache. However, if you wish for this operation to run locally you can use the stream().iterator().forEachRemaining(action) for a single threaded variant. If you wish to have a parallel variant you can use StreamSupport.stream(Spliterator, boolean) passing in the spliterator from the stream. In either case remember you must close the stream after you are done processing the iterator or spliterator..

      Specified by:
      forEach in interface Stream<R>
      Parameters:
      action - consumer to be ran for each element in the stream

    • forEach

      default void forEach(SerializableConsumer<? super R> action)
      Same as forEach(Consumer) except that the Consumer must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      action - consumer to be ran for each element in the stream

    • forEach

      <K,V> void forEach(BiConsumer<Cache<K,V>, ? super R> action)
      Same as forEach(Consumer) except that it takes a BiConsumer that provides access to the underlying Cache that is backing this stream.

      Note that the CacheAware interface is not supported for injection using this method as the cache is provided in the consumer directly.

      Type Parameters:
      K - key type of the cache
      V - value type of the cache
      Parameters:
      action - consumer to be ran for each element in the stream

    • forEach

      default <K,V> void forEach(SerializableBiConsumer<Cache<K,V>, ? super R> action)
      Same as forEach(BiConsumer) except that the BiConsumer must also implement Serializable
      Type Parameters:
      K - key type of the cache
      V - value type of the cache
      Parameters:
      action - consumer to be ran for each element in the stream

    • iterator

      Iterator<R> iterator()

      Usage of this operator requires closing this stream after you are done with the iterator. The preferred usage is to use a try with resource block on the stream.

      This method has special usage with the BaseCacheStream.SegmentCompletionListener in that as entries are retrieved from the next method it will complete segments.

      This method obeys the distributedBatchSize(int). Note that when using methods such as flatMap(Function) that you will have possibly more than 1 element mapped to a given key so this doesn't guarantee that many number of entries are returned per batch.

      Note that the Iterator.remove() method is only supported if no intermediate operations have been applied to the stream and this is not a stream created from a Cache.values() collection.

      Specified by:
      iterator in interface BaseStream<R, Stream<R>>
      Returns:
      the element iterator for this stream

    • spliterator

      Spliterator<R> spliterator()

      Usage of this operator requires closing this stream after you are done with the spliterator. The preferred usage is to use a try with resource block on the stream.

      Specified by:
      spliterator in interface BaseStream<R, Stream<R>>
      Returns:
      the element spliterator for this stream

    • sorted

      CacheStream<R> sorted()

      This operation is performed entirely on the local node irrespective of the backing cache. This operation will act as an intermediate iterator operation requiring data be brought locally for proper behavior. Beware this means it will require having all entries of this cache into memory at one time. This is described in more detail at CacheStream

      Any subsequent intermediate operations and the terminal operation are also performed locally.

      Specified by:
      sorted in interface Stream<R>
      Returns:
      the new stream

    • sorted

      CacheStream<R> sorted(Comparator<? super R> comparator)

      This operation is performed entirely on the local node irrespective of the backing cache. This operation will act as an intermediate iterator operation requiring data be brought locally for proper behavior. Beware this means it will require having all entries of this cache into memory at one time. This is described in more detail at CacheStream

      Any subsequent intermediate operations and the terminal operation are then performed locally.

      Specified by:
      sorted in interface Stream<R>
      Parameters:
      comparator - the comparator to be used for sorting the elements
      Returns:
      the new stream

    • sorted

      default CacheStream<R> sorted(SerializableComparator<? super R> comparator)
      Same as sorted(Comparator) except that the Comparator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      comparator - a non-interfering, stateless Comparator to be used to compare stream elements
      Returns:
      the new stream

    • limit

      CacheStream<R> limit(long maxSize)

      This intermediate operation will be performed both remotely and locally to reduce how many elements are sent back from each node. More specifically this operation is applied remotely on each node to only return up to the maxSize value and then the aggregated results are limited once again on the local node.

      This operation will act as an intermediate iterator operation requiring data be brought locally for proper behavior. This is described in more detail in the CacheStream documentation

      Any subsequent intermediate operations and the terminal operation are then performed locally.

      Specified by:
      limit in interface Stream<R>
      Parameters:
      maxSize - how many elements to limit this stream to.
      Returns:
      the new stream

    • skip

      CacheStream<R> skip(long n)

      This operation is performed entirely on the local node irrespective of the backing cache. This operation will act as an intermediate iterator operation requiring data be brought locally for proper behavior. This is described in more detail in the CacheStream documentation

      Depending on the terminal operator this may or may not require all entries or a subset after skip is applied to be in memory all at once.

      Any subsequent intermediate operations and the terminal operation are then performed locally.

      Specified by:
      skip in interface Stream<R>
      Parameters:
      n - how many elements to skip from this stream
      Returns:
      the new stream

    • peek

      CacheStream<R> peek(Consumer<? super R> action)
      Specified by:
      peek in interface Stream<R>
      Parameters:
      action - the action to perform on the stream
      Returns:
      the new stream

    • peek

      default CacheStream<R> peek(SerializableConsumer<? super R> action)
      Same as peek(Consumer) except that the Consumer must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      action - a non-interfering action to perform on the elements as they are consumed from the stream
      Returns:
      the new stream

    • distinct

      CacheStream<R> distinct()

      This operation will be invoked both remotely and locally when used with a distributed cache backing this stream. This operation will act as an intermediate iterator operation requiring data be brought locally for proper behavior. This is described in more detail in the CacheStream documentation

      This intermediate iterator operation will be performed locally and remotely requiring possibly a subset of all elements to be in memory

      Any subsequent intermediate operations and the terminal operation are then performed locally.

      Specified by:
      distinct in interface Stream<R>
      Returns:
      the new stream

    • collect

      <R1,A> R1 collect(Collector<? super R, A, R1> collector)

      Note when using a distributed backing cache for this stream the collector must be marshallable. This prevents the usage of Collectors class. However you can use the CacheCollectors static factory methods to create a serializable wrapper, which then creates the actual collector lazily after being deserialized. This is useful to use any method from the Collectors class as you would normally. Alternatively, you can call collect(SerializableSupplier) too.

      Note: The collector is applied on each node until all the local stream's values are reduced into a single object. Because of marshalling limitations, the final result of the collector on remote nodes is limited to a size of 2GB. If you need to process more than 2GB of data, you must force the collector to run on the originator with spliterator(): 

       StreamSupport.stream(stream.filter(entry -> ...)
                            .map(entry -> ...)
                            .spliterator(),
                      false)
              .collect(Collectors.toList());
      Specified by:
      collect in interface Stream<R>
      Type Parameters:
      R1 - collected type
      A - intermediate collected type if applicable
      Parameters:
      collector -
      Returns:
      the collected value
      See Also:

    • collect

      default <R1> R1 collect(SerializableSupplier<Collector<? super R, ?, R1>> supplier)
      Performs a mutable reduction operation on the elements of this stream using a Collector that is lazily created from the SerializableSupplier provided. This method behaves exactly the same as collect(Collector) with the enhanced capability of working even when the mutable reduction operation has to run in a remote node and the operation is not Serializable or otherwise marshallable. So, this method is specially designed for situations when the user wants to use a Collector instance that has been created by Collectors static factory methods. In this particular case, the function that instantiates the Collector will be marshalled according to the Serializable rules.

      Note: The collector is applied on each node until all the local stream's values are reduced into a single object. Because of marshalling limitations, the final result of the collector on remote nodes is limited to a size of 2GB. If you need to process more than 2GB of data, you must force the collector to run on the originator with spliterator(): 

       StreamSupport.stream(stream.filter(entry -> ...)
                            .map(entry -> ...)
                            .spliterator(),
                      false)
              .collect(Collectors.toList());
      Type Parameters:
      R1 - The resulting type of the collector
      Parameters:
      supplier - The supplier to create the collector that is specifically serializable
      Returns:
      the collected value
      Since:
      9.2

    • collect

      default <R1> R1 collect(Supplier<Collector<? super R, ?, R1>> supplier)
      Performs a mutable reduction operation on the elements of this stream using a Collector that is lazily created from the Supplier provided. This method behaves exactly the same as collect(Collector) with the enhanced capability of working even when the mutable reduction operation has to run in a remote node and the operation is not Serializable or otherwise marshallable. So, this method is specially designed for situations when the user wants to use a Collector instance that has been created by Collectors static factory methods. In this particular case, the function that instantiates the Collector will be marshalled using Infinispan Externalizer class or one of its subtypes.

      Note: The collector is applied on each node until all the local stream's values are reduced into a single object. Because of marshalling limitations, the final result of the collector on remote nodes is limited to a size of 2GB. If you need to process more than 2GB of data, you must force the collector to run on the originator with spliterator(): 

       StreamSupport.stream(stream.filter(entry -> ...)
                            .map(entry -> ...)
                            .spliterator(),
                      false)
              .collect(Collectors.toList());
      Type Parameters:
      R1 - The resulting type of the collector
      Parameters:
      supplier - The supplier to create the collector
      Returns:
      the collected value
      Since:
      9.2

    • collect

      default <R1> R1 collect(SerializableSupplier<R1> supplier, SerializableBiConsumer<R1, ? super R> accumulator, SerializableBiConsumer<R1,R1> combiner)
      Same as collect(Supplier, BiConsumer, BiConsumer) except that the various arguments must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Type Parameters:
      R1 - type of the result
      Parameters:
      supplier - a function that creates a new result container. For a parallel execution, this function may be called multiple times and must return a fresh value each time. Must be serializable
      accumulator - an associative, non-interfering, stateless function for incorporating an additional element into a result and must be serializable
      combiner - an associative, non-interfering, stateless function for combining two values, which must be compatible with the accumulator function and serializable
      Returns:
      the result of the reduction

    • collect

      <R1> R1 collect(Supplier<R1> supplier, BiConsumer<R1, ? super R> accumulator, BiConsumer<R1,R1> combiner)

      Note: The accumulator and combiner are applied on each node until all the local stream's values are reduced into a single object. Because of marshalling limitations, the final result of the collector on remote nodes is limited to a size of 2GB. If you need to process more than 2GB of data, you must force the collector to run on the originator with spliterator(): 

       StreamSupport.stream(stream.filter(entry -> ...)
                            .map(entry -> ...)
                            .spliterator(),
                      false)
              .collect(Collectors.toList());
      Specified by:
      collect in interface Stream<R>

    • allMatch

      default boolean allMatch(SerializablePredicate<? super R> predicate)
      Same as Stream.allMatch(Predicate) except that the Predicate must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      predicate - a non-interfering, stateless predicate to apply to elements of this stream that is serializable
      Returns:
      true if either all elements of the stream match the provided predicate or the stream is empty, otherwise false

    • noneMatch

      default boolean noneMatch(SerializablePredicate<? super R> predicate)
      Same as Stream.noneMatch(Predicate) except that the Predicate must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      predicate - a non-interfering, stateless predicate to apply to elements of this stream that is serializable
      Returns:
      true if either no elements of the stream match the provided predicate or the stream is empty, otherwise false

    • anyMatch

      default boolean anyMatch(SerializablePredicate<? super R> predicate)
      Same as Stream.anyMatch(Predicate) except that the Predicate must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      predicate - a non-interfering, stateless predicate to apply to elements of this stream that is serializable
      Returns:
      true if any elements of the stream match the provided predicate, otherwise false

    • max

      default Optional<R> max(SerializableComparator<? super R> comparator)
      Same as Stream.max(Comparator) except that the Comparator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      comparator - a non-interfering, stateless Comparator to compare elements of this stream that is also serializable
      Returns:
      an Optional describing the maximum element of this stream, or an empty Optional if the stream is empty

    • min

      default Optional<R> min(SerializableComparator<? super R> comparator)
      Same as Stream.min(Comparator) except that the Comparator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      comparator - a non-interfering, stateless Comparator to compare elements of this stream that is also serializable
      Returns:
      an Optional describing the minimum element of this stream, or an empty Optional if the stream is empty

    • reduce

      default Optional<R> reduce(SerializableBinaryOperator<R> accumulator)
      Same as Stream.reduce(BinaryOperator) except that the BinaryOperator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      accumulator - an associative, non-interfering, stateless function for combining two values that is also serializable
      Returns:
      an Optional describing the result of the reduction

    • reduce

      default R reduce(R identity, SerializableBinaryOperator<R> accumulator)
      Same as Stream.reduce(Object, BinaryOperator) except that the BinaryOperator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      identity - the identity value for the accumulating function
      accumulator - an associative, non-interfering, stateless function for combining two values that is also serializable
      Returns:
      the result of the reduction

    • reduce

      default <U> U reduce(U identity, SerializableBiFunction<U, ? super R, U> accumulator, SerializableBinaryOperator<U> combiner)
      Same as Stream.reduce(Object, BiFunction, BinaryOperator) except that the BinaryOperator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Just like in the cache, null values are not supported.

      Type Parameters:
      U - The type of the result
      Parameters:
      identity - the identity value for the combiner function
      accumulator - an associative, non-interfering, stateless function for incorporating an additional element into a result that is also serializable
      combiner - an associative, non-interfering, stateless function for combining two values, which must be compatible with the accumulator function that is also serializable
      Returns:
      the result of the reduction

    • toArray

      default <A> A[] toArray(SerializableIntFunction<A[]> generator)
      Same as Stream.toArray(IntFunction) except that the BinaryOperator must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Type Parameters:
      A - the element type of the resulting array
      Parameters:
      generator - a function which produces a new array of the desired type and the provided length that is also serializable
      Returns:
      an array containing the elements in this stream

    • filter

      CacheStream<R> filter(Predicate<? super R> predicate)
      Specified by:
      filter in interface Stream<R>
      Returns:
      the new cache stream

    • filter

      default CacheStream<R> filter(SerializablePredicate<? super R> predicate)
      Same as filter(Predicate) except that the Predicate must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      predicate - a non-interfering, stateless predicate to apply to each element to determine if it should be included
      Returns:
      the new cache stream

    • map

      <R1> CacheStream<R1> map(Function<? super R, ? extends R1> mapper)

      Just like in the cache, null values are not supported.

      Specified by:
      map in interface Stream<R>
      Returns:
      the new cache stream

    • map

      default <R1> CacheStream<R1> map(SerializableFunction<? super R, ? extends R1> mapper)
      Same as map(Function) except that the Function must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Type Parameters:
      R1 - The element type of the new stream
      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new cache stream

    • mapToDouble

      DoubleCacheStream mapToDouble(ToDoubleFunction<? super R> mapper)
      Specified by:
      mapToDouble in interface Stream<R>
      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new double cache stream

    • mapToDouble

      default DoubleCacheStream mapToDouble(SerializableToDoubleFunction<? super R> mapper)
      Same as mapToDouble(ToDoubleFunction) except that the ToDoubleFunction must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new stream

    • mapToInt

      IntCacheStream mapToInt(ToIntFunction<? super R> mapper)
      Specified by:
      mapToInt in interface Stream<R>
      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new int cache stream

    • mapToInt

      default IntCacheStream mapToInt(SerializableToIntFunction<? super R> mapper)
      Same as mapToInt(ToIntFunction) except that the ToIntFunction must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new stream

    • mapToLong

      LongCacheStream mapToLong(ToLongFunction<? super R> mapper)
      Specified by:
      mapToLong in interface Stream<R>
      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new long cache stream

    • mapToLong

      default LongCacheStream mapToLong(SerializableToLongFunction<? super R> mapper)
      Same as mapToLong(ToLongFunction) except that the ToLongFunction must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element
      Returns:
      the new stream

    • flatMap

      <R1> CacheStream<R1> flatMap(Function<? super R, ? extends Stream<? extends R1>> mapper)
      Specified by:
      flatMap in interface Stream<R>
      Returns:
      the new cache stream

    • flatMap

      default <R1> CacheStream<R1> flatMap(SerializableFunction<? super R, ? extends Stream<? extends R1>> mapper)
      Same as flatMap(Function) except that the Function must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Type Parameters:
      R1 - The element type of the new stream
      Parameters:
      mapper - a non-interfering, stateless function to apply to each element which produces a stream of new values
      Returns:
      the new cache stream

    • flatMapToDouble

      DoubleCacheStream flatMapToDouble(Function<? super R, ? extends DoubleStream> mapper)
      Specified by:
      flatMapToDouble in interface Stream<R>
      Returns:
      the new cache stream

    • flatMapToDouble

      default DoubleCacheStream flatMapToDouble(SerializableFunction<? super R, ? extends DoubleStream> mapper)
      Same as flatMapToDouble(Function) except that the Function must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element which produces a stream of new values
      Returns:
      the new stream

    • flatMapToInt

      IntCacheStream flatMapToInt(Function<? super R, ? extends IntStream> mapper)
      Specified by:
      flatMapToInt in interface Stream<R>
      Returns:
      the new cache stream

    • flatMapToInt

      default IntCacheStream flatMapToInt(SerializableFunction<? super R, ? extends IntStream> mapper)
      Same as flatMapToInt(Function) except that the Function must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element which produces a stream of new values
      Returns:
      the new stream

    • flatMapToLong

      LongCacheStream flatMapToLong(Function<? super R, ? extends LongStream> mapper)
      Specified by:
      flatMapToLong in interface Stream<R>
      Returns:
      the new cache stream

    • flatMapToLong

      default LongCacheStream flatMapToLong(SerializableFunction<? super R, ? extends LongStream> mapper)
      Same as flatMapToLong(Function) except that the Function must also implement Serializable

      The compiler will pick this overload for lambda parameters, making them Serializable

      Parameters:
      mapper - a non-interfering, stateless function to apply to each element which produces a stream of new values
      Returns:
      the new stream

    • parallel

      CacheStream<R> parallel()
      Specified by:
      parallel in interface BaseStream<R, Stream<R>>
      Returns:
      a parallel cache stream

    • sequential

      CacheStream<R> sequential()
      Specified by:
      sequential in interface BaseStream<R, Stream<R>>
      Returns:
      a sequential cache stream

    • unordered

      CacheStream<R> unordered()
      Specified by:
      unordered in interface BaseStream<R, Stream<R>>
      Returns:
      an unordered cache stream

    • onClose

      CacheStream<R> onClose(Runnable closeHandler)
      Specified by:
      onClose in interface BaseStream<R, Stream<R>>
      Parameters:
      closeHandler -
      Returns:
      a cache stream with the handler applied