groovyx.gpars
[Java] Class GParsPoolUtil

java.lang.Object
  groovyx.gpars.GParsPoolUtil

public class GParsPoolUtil

This class forms the core of the DSL initialized by GParsPool. The static methods of GParsPoolUtil get attached to their first arguments (the Groovy Category mechanism) and can be then invoked as if they were part of the argument classes.

Authors:

Vaclav Pech

Robert Fischer Date: Mar 10, 2010

See Also:

GParsPool

timer

private static final GeneralTimer timer

Allows timeouts for async operations

GParsPoolUtil

GParsPoolUtil()

anyParallel

public static boolean anyParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. The anyParallel() method is lazy and once a positive answer has been given by at least one element, it avoids running the supplied closure on subsequent elements. After all the elements have been processed, the method returns a boolean value indicating, whether at least one element of the collection meets the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new anyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     assert [1, 2, 3, 4, 5].anyParallel {Number number -> number > 3}*     assert ![1, 2, 3].anyParallel {Number number -> number > 3}*}* 

anyParallel

public static boolean anyParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. The anyParallel() method is lazy and once a positive answer has been given by at least one element, it avoids running the supplied closure on subsequent elements. After all the elements have been processed, the method returns a boolean value indicating, whether at least one element of the collection meets the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new anyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     assert [1, 2, 3, 4, 5].anyParallel {Number number -> number > 3}*     assert ![1, 2, 3].anyParallel {Number number -> number > 3}*}* 

anyParallel

public static boolean anyParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. The anyParallel() method is lazy and once a positive answer has been given by at least one element, it avoids running the supplied closure on subsequent elements. After all the elements have been processed, the method returns a boolean value indicating, whether at least one element of the collection meets the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new anyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     assert [1, 2, 3, 4, 5].anyParallel {Number number -> number > 3}*     assert ![1, 2, 3].anyParallel {Number number -> number > 3}*}* 

asConcurrent

public static void asConcurrent(java.lang.Object collection, groovy.lang.Closure code)

Makes the collection concurrent for the passed-in block of code. The iterative methods like each or collect are given concurrent semantics inside the passed-in closure. Once the closure finishes, the original sequential semantics of the methods is restored. Must be invoked inside a withPool block.

Parameters:

collection - The collection to enhance

code - The closure to run with the collection enhanced.

async

public static groovy.lang.Closure async(groovy.lang.Closure cl)

Creates an asynchronous variant of the supplied closure, which, when invoked returns a future for the potential return value

asyncFun

public static groovy.lang.Closure asyncFun(groovy.lang.Closure original)

Creates an asynchronous and composable variant of the supplied closure, which, when invoked returns a DataflowVariable for the potential return value

asyncFun

public static groovy.lang.Closure asyncFun(groovy.lang.Closure original, boolean blocking)

Creates an asynchronous and composable variant of the supplied closure, which, when invoked returns a DataflowVariable for the potential return value

asyncFun

public static groovy.lang.Closure asyncFun(groovy.lang.Closure original, FJPool pool)

Creates an asynchronous and composable variant of the supplied closure, which, when invoked returns a DataflowVariable for the potential return value

asyncFun

public static groovy.lang.Closure asyncFun(groovy.lang.Closure original, FJPool pool, boolean blocking)

Creates an asynchronous and composable variant of the supplied closure, which, when invoked returns a DataflowVariable for the potential return value

callAsync

public static java.util.concurrent.Future callAsync(groovy.lang.Closure cl, java.lang.Object... args)

Calls a closure in a separate thread supplying the given arguments, returning a future for the potential return value.

callParallel

public static java.util.concurrent.Future callParallel(groovy.lang.Closure task)

schedules the supplied closure for processing in the underlying thread pool.

callTimeoutAsync

public static java.util.concurrent.Future callTimeoutAsync(groovy.lang.Closure cl, long timeout, java.lang.Object... args)

Calls a closure in a separate thread supplying the given arguments, returning a future for the potential return value. Also allows the asynchronous calculation to be cancelled after a given timeout. In order to allow cancellation, the asynchronously running code must keep checking the _interrupted_ flag of its own thread and cease the calculation once the flag is set to true.

Parameters:

timeout - The timeout in milliseconds to wait before the calculation gets cancelled.

callTimeoutAsync

public static java.util.concurrent.Future callTimeoutAsync(groovy.lang.Closure cl, groovy.time.Duration timeout, java.lang.Object... args)

Calls a closure in a separate thread supplying the given arguments, returning a future for the potential return value. Also allows the asynchronous calculation to be cancelled after a given timeout. In order to allow cancellation, the asynchronously running code must keep checking the _interrupted_ flag of its own thread and cease the calculation once the flag is set to true.

Parameters:

timeout - The timeout to wait before the calculation gets cancelled.

collectManyParallel

public static java.util.List collectManyParallel(java.util.Collection collection, groovy.lang.Closure projection)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied projection closure as the transformation operation. The projection closure should return a (possibly empty) collection of items which are subsequently flattened to produce a new collection. The projection closure will be effectively invoked concurrently on the elements of the original collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectManyParallel(Closure projection) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def squaresAndCubesOfOdds = [1, 2, 3, 4, 5].collectManyParallel { Number number ->
         number % 2 ? [number ** 2, number ** 3] : []
 }*     assert squaresAndCubesOfOdds == [1, 1, 9, 27, 25, 125]
 }* 

collectManyParallel

public static java.util.List collectManyParallel(java.lang.Object collection, groovy.lang.Closure projection)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied projection closure as the transformation operation. The projection closure should return a (possibly empty) collection of items which are subsequently flattened to produce a new collection. The projection closure will be effectively invoked concurrently on the elements of the original collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectManyParallel(Closure projection) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def squaresAndCubesOfOdds = [1, 2, 3, 4, 5].collectManyParallel { Number number ->
         number % 2 ? [number ** 2, number ** 3] : []
 }*     assert squaresAndCubesOfOdds == [1, 1, 9, 27, 25, 125]
 }* 

collectManyParallel

public static java.util.List collectManyParallel(java.util.Map collection, groovy.lang.Closure projection)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied projection closure as the transformation operation. The projection closure should return a (possibly empty) collection of items which are subsequently flattened to produce a new collection. The projection closure will be effectively invoked concurrently on the elements of the original collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectManyParallel(Closure projection) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def squaresAndCubesOfOdds = [1, 2, 3, 4, 5].collectManyParallel { Number number ->
         number % 2 ? [number ** 2, number ** 3] : []
 }*     assert squaresAndCubesOfOdds == [1, 1, 9, 27, 25, 125]
 }* 

collectParallel

public static java.util.Collection collectParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].collectParallel {Number number -> number * 10}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

collectParallel

public static java.util.Collection collectParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].collectParallel {Number number -> number * 10}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

collectParallel

public static java.util.Collection collectParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new collectParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].collectParallel {Number number -> number * 10}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

countParallel

public static int countParallel(java.util.Collection collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].countParallel(4)
     assertEquals(1, result)
 }* 

countParallel

public static int countParallel(java.lang.Object collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].countParallel(4)
     assertEquals(1, result)
 }* 

countParallel

public static int countParallel(java.util.Collection collection, groovy.lang.Closure filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def isOdd = { it % 2 }*     def result = [1, 2, 3, 4, 5].countParallel(isOdd)
     assert result == 3
 }* 

countParallel

public static int countParallel(java.lang.Object collection, groovy.lang.Closure filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def isEven = { it % 2 == 0 }*     def result = [1, 2, 3, 4, 5].countParallel(isEven)
     assert result == 2
 }* 

createPA

private static ParallelArray createPA(java.util.Map collection, ForkJoinPool pool)

eachParallel

public static java.util.Collection eachParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new eachParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = new ConcurrentSkipListSet()
     [1, 2, 3, 4, 5].eachParallel {Number number -> result.add(number * 10)}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

Note that the result variable is synchronized to prevent race conditions between multiple threads.

eachParallel

public static java.lang.Object eachParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new eachParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = new ConcurrentSkipListSet()
     [1, 2, 3, 4, 5].eachParallel {Number number -> result.add(number * 10)}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

Note that the result variable is synchronized to prevent race conditions between multiple threads.

eachParallel

public static java.util.Map eachParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new eachParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = new ConcurrentSkipListSet()
     [1, 2, 3, 4, 5].eachParallel {Number number -> result.add(number * 10)}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

Note that the result variable is synchronized to prevent race conditions between multiple threads.

eachWithIndexParallel

public static java.util.Collection eachWithIndexParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new eachWithIndexParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = new ConcurrentSkipListSet()
     [1, 2, 3, 4, 5].eachWithIndexParallel {Number number, int index -> result.add(number * 10)}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

Note that the result variable is synchronized to prevent race conditions between multiple threads.

eachWithIndexParallel

public static java.lang.Object eachWithIndexParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the transformation operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new eachWithIndexParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = new ConcurrentSkipListSet()
     [1, 2, 3, 4, 5].eachWithIndexParallel {Number number, int index -> result.add(number * 10)}*     assertEquals(new HashSet([10, 20, 30, 40, 50]), result)
 }* 

Note that the result variable is synchronized to prevent race conditions between multiple threads.

eachWithIndexParallel

public static java.util.Map eachWithIndexParallel(java.util.Map collection, groovy.lang.Closure cl)

Does parallel eachWithIndex on maps

everyParallel

public static boolean everyParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a boolean value indicating, whether all the elements of the collection meet the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new everyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool(5) {*     assert ![1, 2, 3, 4, 5].everyParallel {Number number -> number > 3}*     assert [1, 2, 3].everyParallel() {Number number -> number <= 3}*}* 

everyParallel

public static boolean everyParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a boolean value indicating, whether all the elements of the collection meet the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new everyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool(5) {*     assert ![1, 2, 3, 4, 5].everyParallel {Number number -> number > 3}*     assert [1, 2, 3].everyParallel() {Number number -> number <= 3}*}* 

everyParallel

public static boolean everyParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a boolean value indicating, whether all the elements of the collection meet the predicate. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new everyParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool(5) {*     assert ![1, 2, 3, 4, 5].everyParallel {Number number -> number > 3}*     assert [1, 2, 3].everyParallel() {Number number -> number <= 3}*}* 

findAllParallel

public static java.util.Collection findAllParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findAllParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findAllParallel {Number number -> number > 3}*     assertEquals(new HashSet([4, 5]), result)
 }* 

findAllParallel

public static java.util.Collection findAllParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findAllParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findAllParallel {Number number -> number > 3}*     assertEquals(new HashSet([4, 5]), result)
 }* 

findAllParallel

public static java.util.Map findAllParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findAllParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example: GParsPool.withPool {* def result = [1, 2, 3, 4, 5].findAllParallel {Number number -> number > 3}* assertEquals(new HashSet([4, 5]), result) }*

findAnyParallel

public static java.lang.Object findAnyParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. Unlike with the find method, findAnyParallel() does not guarantee that the a matching element with the lowest index is returned. The findAnyParallel() method evaluates elements lazily and stops processing further elements of the collection once a match has been found. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a random value from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findParallel {Number number -> number > 3}*     assert (result in [4, 5])
 }* 

findAnyParallel

public static java.lang.Object findAnyParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. Unlike with the find method, findAnyParallel() does not guarantee that the a matching element with the lowest index is returned. The findAnyParallel() method evaluates elements lazily and stops processing further elements of the collection once a match has been found. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a random value from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example: GParsPool.withPool {* def result = [1, 2, 3, 4, 5].findAnyParallel {Number number -> number > 3}* assert (result in [4, 5]) }*

findAnyParallel

public static java.util.Map$Entry findAnyParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied closure as the filter predicate. Unlike with the find method, findAnyParallel() does not guarantee that the matching element with the lowest index is returned. The findAnyParallel() method evaluates elements lazily and stops processing further elements of the collection once a match has been found. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a random value from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findAnyParallel {Number number -> number > 3}*     assert (result in [4, 5])
 }* 

findParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object findParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a value from the resulting Parallel Array with the minimum index. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findParallel {Number number -> number > 3}*     assert (result in [4, 5])
 }* 

findParallel

public static java.lang.Object findParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a value from the resulting Parallel Array with the minimum index. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findParallel {Number number -> number > 3}*     assert (result in [4, 5])
 }* 

findParallel

public static java.util.Map$Entry findParallel(java.util.Map collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied closure as the filter predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a value from the resulting Parallel Array with the minimum index. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new findParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].findParallel {Number number -> number > 3}*     assert (result in [4, 5])
 }* 

foldParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object foldParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its reduce() method using the supplied closure as the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the reduction result of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new reduce(Closure cl) method, which delegates to the GParsPoolUtil class.

foldParallel

public static java.lang.Object foldParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its reduce() method using the supplied closure as the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the reduction result of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new reduce(Closure cl) method, which delegates to the GParsPoolUtil class.

foldParallel

public static java.lang.Object foldParallel(java.util.Collection collection, java.lang.Object seed, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its reduce() method using the supplied closure as the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the reduction result of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new reduce(Closure cl) method, which delegates to the GParsPoolUtil class.

Parameters:

seed - A seed value to initialize the operation

foldParallel

public static java.lang.Object foldParallel(java.lang.Object collection, java.lang.Object seed, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its reduce() method using the supplied closure as the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the reduction result of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new reduce(Closure cl) method, which delegates to the GParsPoolUtil class.

Parameters:

seed - A seed value to initialize the operation

getParallel

public static PAWrapper getParallel(java.util.Collection collection)

Creates a PAWrapper around a ParallelArray wrapping the elements of the original collection. This allows further parallel processing operations on the collection to chain and so effectively leverage the underlying ParallelArray implementation.

getParallel

public static PAWrapper getParallel(java.lang.Object collection)

Creates a PAWrapper around a ParallelArray wrapping the elements of the original collection. This allows further parallel processing operations on the collection to chain and so effectively leverage the underlying ParallelArray implementation.

getParallelArray

@SuppressWarnings("GroovyAssignabilityCheck")
public static ParallelArray getParallelArray(java.util.Collection collection)

Creates a ParallelArray wrapping the elements of the original collection.

getParallelArray

public static ParallelArray getParallelArray(java.lang.Object collection)

Creates a ParallelArray wrapping the elements of the original collection.

gmemoize

public static groovy.lang.Closure gmemoize(groovy.lang.Closure cl)

Creates a caching variant of the supplied closure. Whenever the closure is called, the mapping between the parameters and the return value is preserved in cache making subsequent calls with the same arguments fast. This variant will keep all values forever, i.e. till the closure gets garbage-collected. The returned function can be safely used concurrently from multiple threads, however, the implementation values high average-scenario performance and so concurrent calls on the memoized function with identical argument values may not necessarily be able to benefit from each other's cached return value. With this having been mentioned, the performance trade-off still makes concurrent use of memoized functions safe and highly recommended.

The cache gets garbage-collected together with the memoized closure.

Returns:

A new function forwarding to the original one while caching the results

gmemoizeAtLeast

public static groovy.lang.Closure gmemoizeAtLeast(groovy.lang.Closure cl, int protectedCacheSize)

Creates a caching variant of the supplied closure with automatic cache size adjustment and lower limit on the cache size. Whenever the closure is called, the mapping between the parameters and the return value is preserved in cache making subsequent calls with the same arguments fast. This variant allows the garbage collector to release entries from the cache and at the same time allows the user to specify how many entries should be protected from the eventual gc-initiated eviction. Cached entries exceeding the specified preservation threshold are made available for eviction based on the LRU (Last Recently Used) strategy. Given the non-deterministic nature of garbage collector, the actual cache size may grow well beyond the limits set by the user if memory is plentiful. The returned function can be safely used concurrently from multiple threads, however, the implementation values high average-scenario performance and so concurrent calls on the memoized function with identical argument values may not necessarily be able to benefit from each other's cached return value. Also the protectedCacheSize parameter might not be respected accurately in such scenarios for some periods of time. With this having been mentioned, the performance trade-off still makes concurrent use of memoized functions safe and highly recommended.

The cache gets garbage-collected together with the memoized closure.

gmemoizeAtMost

public static groovy.lang.Closure gmemoizeAtMost(groovy.lang.Closure cl, int maxCacheSize)

Creates a caching variant of the supplied closure with upper limit on the cache size. Whenever the closure is called, the mapping between the parameters and the return value is preserved in cache making subsequent calls with the same arguments fast. This variant will keep all values until the upper size limit is reached. Then the values in the cache start rotating using the LRU (Last Recently Used) strategy. The returned function can be safely used concurrently from multiple threads, however, the implementation values high average-scenario performance and so concurrent calls on the memoized function with identical argument values may not necessarily be able to benefit from each other's cached return value. With this having been mentioned, the performance trade-off still makes concurrent use of memoized functions safe and highly recommended.

The cache gets garbage-collected together with the memoized closure.

Parameters:

maxCacheSize - The maximum size the cache can grow to

Returns:

A new function forwarding to the original one while caching the results

gmemoizeBetween

public static groovy.lang.Closure gmemoizeBetween(groovy.lang.Closure cl, int protectedCacheSize, int maxCacheSize)

Creates a caching variant of the supplied closure with automatic cache size adjustment and lower and upper limits on the cache size. Whenever the closure is called, the mapping between the parameters and the return value is preserved in cache making subsequent calls with the same arguments fast. This variant allows the garbage collector to release entries from the cache and at the same time allows the user to specify how many entries should be protected from the eventual gc-initiated eviction. Cached entries exceeding the specified preservation threshold are made available for eviction based on the LRU (Last Recently Used) strategy. Given the non-deterministic nature of garbage collector, the actual cache size may grow well beyond the protected size limits set by the user, if memory is plentiful. Also, this variant will never exceed in size the upper size limit. Once the upper size limit has been reached, the values in the cache start rotating using the LRU (Last Recently Used) strategy. The returned function can be safely used concurrently from multiple threads, however, the implementation values high average-scenario performance and so concurrent calls on the memoized function with identical argument values may not necessarily be able to benefit from each other's cached return value. Also the protectedCacheSize parameter might not be respected accurately in such scenarios for some periods of time. With this having been mentioned, the performance trade-off still makes concurrent use of memoized functions safe and highly recommended.

The cache gets garbage-collected together with the memoized closure.

grepParallel

public static java.util.Collection grepParallel(java.util.Collection collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].grepParallel(4..6)
     assertEquals(new HashSet([4, 5]), result)
 }* 

grepParallel

public static java.lang.Object grepParallel(java.lang.Object collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].grepParallel(4..6)
     assertEquals(new HashSet([4, 5]), result)
 }* 

grepParallel

public static java.util.Map grepParallel(java.util.Map collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied map and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].grepParallel(4..6)
     assertEquals(new HashSet([4, 5]), result)
 }* 

groupByParallel

public static java.util.Map groupByParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the mapping predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a map of groups of the original elements. Elements in the same group gave identical results when the supplied closure was invoked on them. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new groupByParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     assert ([1, 2, 3, 4, 5].groupByParallel {Number number -> number % 2}).size() == 2
 }* 

groupByParallel

public static java.util.Map groupByParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes the withMapping() method using the supplied closure as the mapping predicate. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns a map of groups of the original elements. Elements in the same group gave identical results when the supplied closure was invoked on them. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new groupByParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     assert ([1, 2, 3, 4, 5].groupByParallel {Number number -> number % 2}).size() == 2
 }* 

groupByParallelPA

private static java.util.Map groupByParallelPA(ParallelArray pa, groovy.lang.Closure cl)

isConcurrent

public static boolean isConcurrent(java.lang.Object collection)

Indicates whether the iterative methods like each() or collect() work have been altered to work concurrently.

leftShift

public static java.util.concurrent.Future leftShift(ForkJoinPool pool, groovy.lang.Closure task)

Submits the task for asynchronous processing returning the Future received from the executor service. Allows for the following syntax:

 executorService << {println 'Inside parallel task'}* 

makeConcurrent

public static java.lang.Object makeConcurrent(java.lang.Object collection)

Overrides the iterative methods like each(), collect() and such, so that they call their parallel variants from the GParsPoolUtil class like eachParallel(), collectParallel() and such. The first time it is invoked on a collection the method creates a TransparentParallel class instance and mixes it in the object it is invoked on. After mixing-in, the isConcurrent() method will return true. Delegates to GParsPoolUtil.makeConcurrent().

Parameters:

collection - The object to make transparent

Returns:

The instance of the TransparentParallel class wrapping the original object and overriding the iterative methods with new parallel behavior

makeSequential

public static java.lang.Object makeSequential(java.lang.Object collection)

Gives the iterative methods like each() or find() the original sequential semantics.

Parameters:

collection - The collection to apply the change to

Returns:

The collection itself

maxParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object maxParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its max() method using the supplied closure as the comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the maximum of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new max(Closure cl) method, which delegates to the GParsPoolUtil class. If the supplied closure takes two arguments it is used directly as a comparator. If the supplied closure takes one argument, the values returned by the supplied closure for individual elements are used for comparison by the implicit comparator.

Parameters:

cl - A one or two-argument closure

maxParallel

public static java.lang.Object maxParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its max() method using the supplied closure as the comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the maximum of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new max(Closure cl) method, which delegates to the GParsPoolUtil class. If the supplied closure takes two arguments it is used directly as a comparator. If the supplied closure takes one argument, the values returned by the supplied closure for individual elements are used for comparison by the implicit comparator.

Parameters:

cl - A one or two-argument closure

maxParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object maxParallel(java.util.Collection collection)

Creates a Parallel Array out of the supplied collection/object and invokes its max() method using the default comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the maximum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new max(Closure cl) method, which delegates to the GParsPoolUtil class.

maxParallel

public static java.lang.Object maxParallel(java.lang.Object collection)

Creates a Parallel Array out of the supplied collection/object and invokes its max() method using the default comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the maximum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new max(Closure cl) method, which delegates to the GParsPoolUtil class.

minParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object minParallel(java.util.Collection collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its min() method using the supplied closure as the comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the minimum of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new min(Closure cl) method, which delegates to the GParsPoolUtil class. If the supplied closure takes two arguments it is used directly as a comparator. If the supplied closure takes one argument, the values returned by the supplied closure for individual elements are used for comparison by the implicit comparator.

Parameters:

cl - A one or two-argument closure

minParallel

public static java.lang.Object minParallel(java.lang.Object collection, groovy.lang.Closure cl)

Creates a Parallel Array out of the supplied collection/object and invokes its min() method using the supplied closure as the comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the minimum of the elements in the collection. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new min(Closure cl) method, which delegates to the GParsPoolUtil class. If the supplied closure takes two arguments it is used directly as a comparator. If the supplied closure takes one argument, the values returned by the supplied closure for individual elements are used for comparison by the implicit comparator.

Parameters:

cl - A one or two-argument closure

minParallel

@SuppressWarnings("GroovyAssignabilityCheck")
public static java.lang.Object minParallel(java.util.Collection collection)

Creates a Parallel Array out of the supplied collection/object and invokes its min() method using the default comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the minimum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new min(Closure cl) method, which delegates to the GParsPoolUtil class.

minParallel

public static java.lang.Object minParallel(java.lang.Object collection)

Creates a Parallel Array out of the supplied collection/object and invokes its min() method using the default comparator. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the minimum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new min(Closure cl) method, which delegates to the GParsPoolUtil class.

retrievePool

private static ForkJoinPool retrievePool()

splitParallel

public static java.util.Collection splitParallel(java.util.Collection collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class.

splitParallel

public static java.lang.Object splitParallel(java.lang.Object collection, java.lang.Object filter)

Creates a Parallel Array out of the supplied collection/object and invokes the withFilter() method using the supplied rule as the filter predicate. The filter will be effectively used concurrently on the elements of the collection. After all the elements have been processed, the method returns a collection of values from the resulting Parallel Array. It's important to protect any shared resources used by the supplied closure from race conditions caused by multi-threaded access. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new grepParallel(Closure cl) method, which delegates to the GParsPoolUtil class. Example:

 GParsPool.withPool {*     def result = [1, 2, 3, 4, 5].splitParallel(4..6)
     assert [3, 4, 5] as Set == result[0] as Set
     assert [1, 2] as Set == result[1] as Set
 }* 

sumParallel

public static java.lang.Object sumParallel(java.util.Collection collection)

Creates a Parallel Array out of the supplied collection/object and summarizes its elements using the foldParallel() method with the + operator and the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the sum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new sun(Closure cl) method, which delegates to the GParsPoolUtil class.

sumParallel

public static java.lang.Object sumParallel(java.lang.Object collection)

Creates a Parallel Array out of the supplied collection/object and summarizes its elements using the foldParallel() method with the + operator and the reduction operation. The closure will be effectively invoked concurrently on the elements of the collection. After all the elements have been processed, the method returns the sum of the elements in the collection. Alternatively a DSL can be used to simplify the code. All collections/objects within the withPool block have a new sum(Closure cl) method, which delegates to the GParsPoolUtil class.

Copyright © 2008–2012 Václav Pech. All Rights Reserved.