数学库 colt （版本1.2）取决于库 EDU.oswego.cs.dl.util.concurrent （gee.cs.oswego.edu/dl /classes/EDU/oswego/cs/dl/util/concurrent/intro.html）。编译并发（版本1.3.4）适用于Java版本7或以前的版本。但是编译在java 8上失败（javac版本1.8）。编译器选项-source 1.4 -target 1.4无法解决问题。
原因是，java 8在java.util.Map接口中引入了一个新方法“remove”：default boolean remove(Object key, Object value)。
这个新方法与实现java.util.Map的库类ConcurrentHashMap.java中的方法“remove”冲突：protected Object remove(Object key, Object value)。
一旦确定了问题的原因，我就可以通过重命名库类ConcurrentHashMap.java中的方法来解决问题。这是可以接受的，因为库方法只受保护（而不是公共）。
还有其他可能性来确保兼容java 8吗？
答案 0 :(得分：2)
没有编译器选项和注释会忽略冲突的方法签名。
如果您（或者，在这种情况下， colt ）不使用新的remove方法，只需在Java 7下编译它。在Java 8下编译它赢了＆＃ 39;给你任何好处。
但在这种情况下，我实际上更喜欢你的解决方案。
答案 1 :(得分：1)
考虑到这个类是JRE类的基础，也称为ConcurrentHashMap，这里没有名称冲突，因为该方法具有完全预期的语义。发生冲突，因为该方法是protected，这个决定早就已经修改过了。即当你查看该类的Java 5版本时，你会发现它已经有the method remove(Object, Object)而且它是public。 ConcurrentMap interface也要求它，因此必须 public。
所以最简单的修复不是重命名，而是将修饰符更改为public并调整返回类型。
但你是对的in your comment，从长远来看，最好的解决方案是迁移到该类as recommend by the author himself的JRE版本：
注意：在发布J2SE 5.0后，此程序包进入维护模式：仅发布必要的更正。 J2SE5包java.util.concurrent包含此包中主要组件的改进的，更有效的标准化版本。请计划转换您的应用程序以使用它们。
这是十多年前的事了......
答案 2 :(得分：0)
将colt从 EDU.oswego.cs.dl.util.concurrent 迁移到 java.util.concurrent 类。正如Holger的回答所述，并发库作者建议这样做。
Gentoo为colt 1.2.0源代码提供patch：
--- src/cern/colt/matrix/linalg/SmpBlas.java.orig 2015-10-07 22:23:44.969486000 +0000
+++ src/cern/colt/matrix/linalg/SmpBlas.java 2015-10-07 22:29:15.475486000 +0000
@@ -10,7 +10,8 @@
import cern.colt.matrix.DoubleMatrix1D;
import cern.colt.matrix.DoubleMatrix2D;
-import EDU.oswego.cs.dl.util.concurrent.FJTask;
+
+import java.util.concurrent.ForkJoinTask;
/**
Parallel implementation of the Basic Linear Algebra System for symmetric multi processing boxes.
Currently only a few algorithms are parallelised; the others are fully functional, but run in sequential mode.
@@ -198,7 +199,7 @@
// set up concurrent tasks
int span = width/noOfTasks;
- final FJTask[] subTasks = new FJTask[noOfTasks];
+ final ForkJoinTask[] subTasks = new ForkJoinTask[noOfTasks];
for (int i=0; i<noOfTasks; i++) {
final int offset = i*span;
if (i==noOfTasks-1) span = width - span*i; // last span may be a bit larger
@@ -217,24 +218,30 @@
CC = C.viewPart(offset,0,span,p);
}
- subTasks[i] = new FJTask() {
+ subTasks[i] = new ForkJoinTask() {
public void run() {
seqBlas.dgemm(transposeA,transposeB,alpha,AA,BB,beta,CC);
//System.out.println("Hello "+offset);
}
+
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
};
}
// run tasks and wait for completion
- try {
- this.smp.taskGroup.invoke(
- new FJTask() {
- public void run() {
- coInvoke(subTasks);
- }
- }
- );
- } catch (InterruptedException exc) {}
+ this.smp.taskGroup.invoke(
+ new ForkJoinTask() {
+ public void run() {
+ invokeAll(subTasks);
+ }
+
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
+ }
+ );
}
public void dgemv(final boolean transposeA, final double alpha, DoubleMatrix2D A, final DoubleMatrix1D x, final double beta, DoubleMatrix1D y) {
/*
@@ -271,7 +278,7 @@
// set up concurrent tasks
int span = width/noOfTasks;
- final FJTask[] subTasks = new FJTask[noOfTasks];
+ final ForkJoinTask[] subTasks = new ForkJoinTask[noOfTasks];
for (int i=0; i<noOfTasks; i++) {
final int offset = i*span;
if (i==noOfTasks-1) span = width - span*i; // last span may be a bit larger
@@ -280,24 +287,30 @@
final DoubleMatrix2D AA = A.viewPart(offset,0,span,n);
final DoubleMatrix1D yy = y.viewPart(offset,span);
- subTasks[i] = new FJTask() {
+ subTasks[i] = new ForkJoinTask() {
public void run() {
seqBlas.dgemv(transposeA,alpha,AA,x,beta,yy);
//System.out.println("Hello "+offset);
}
+
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
};
}
// run tasks and wait for completion
- try {
- this.smp.taskGroup.invoke(
- new FJTask() {
- public void run() {
- coInvoke(subTasks);
- }
- }
- );
- } catch (InterruptedException exc) {}
+ this.smp.taskGroup.invoke(
+ new ForkJoinTask() {
+ public void run() {
+ invokeAll(subTasks);
+ }
+
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
+ }
+ );
}
public void dger(double alpha, DoubleMatrix1D x, DoubleMatrix1D y, DoubleMatrix2D A) {
seqBlas.dger(alpha,x,y,A);
@@ -369,9 +382,6 @@
/**
* Prints various snapshot statistics to System.out; Simply delegates to {@link EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup#stats}.
*/
-public void stats() {
- if (this.smp!=null) this.smp.stats();
-}
private double xsum(DoubleMatrix2D A) {
double[] sums = run(A,true,
new Matrix2DMatrix2DFunction() {
--- src/cern/colt/matrix/linalg/Smp.java.orig 2015-10-07 21:08:19.443486000 +0000
+++ src/cern/colt/matrix/linalg/Smp.java 2015-10-07 22:28:24.722486000 +0000
@@ -9,12 +9,13 @@
package cern.colt.matrix.linalg;
import cern.colt.matrix.DoubleMatrix2D;
-import EDU.oswego.cs.dl.util.concurrent.FJTask;
-import EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup;
+import java.util.concurrent.ForkJoinTask;
+import java.util.concurrent.ForkJoinPool;
+
/*
*/
class Smp {
- protected FJTaskRunnerGroup taskGroup; // a very efficient and light weight thread pool
+ protected ForkJoinPool taskGroup; // a very efficient and light weight thread pool
protected int maxThreads;
/**
@@ -24,41 +25,39 @@
maxThreads = Math.max(1,maxThreads);
this.maxThreads = maxThreads;
if (maxThreads>1) {
- this.taskGroup = new FJTaskRunnerGroup(maxThreads);
+ this.taskGroup = new ForkJoinPool(maxThreads);
}
else { // avoid parallel overhead
this.taskGroup = null;
}
}
-/**
- * Clean up deamon threads, if necessary.
- */
-public void finalize() {
- if (this.taskGroup!=null) this.taskGroup.interruptAll();
-}
protected void run(final DoubleMatrix2D[] blocksA, final DoubleMatrix2D[] blocksB, final double[] results, final Matrix2DMatrix2DFunction function) {
- final FJTask[] subTasks = new FJTask[blocksA.length];
+ final ForkJoinTask[] subTasks = new ForkJoinTask[blocksA.length];
for (int i=0; i<blocksA.length; i++) {
final int k = i;
- subTasks[i] = new FJTask() {
+ subTasks[i] = new ForkJoinTask() {
public void run() {
double result = function.apply(blocksA[k],blocksB != null ? blocksB[k] : null);
if (results!=null) results[k] = result;
//System.out.print(".");
}
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
};
}
// run tasks and wait for completion
- try {
- this.taskGroup.invoke(
- new FJTask() {
- public void run() {
- coInvoke(subTasks);
- }
- }
- );
- } catch (InterruptedException exc) {}
+ this.taskGroup.invoke(
+ new ForkJoinTask() {
+ public void run() {
+ invokeAll(subTasks);
+ }
+ public boolean exec() { return true; }
+ public void setRawResult(Object o) {}
+ public Object getRawResult() {return null;}
+ }
+ );
}
protected DoubleMatrix2D[] splitBlockedNN(DoubleMatrix2D A, int threshold, long flops) {
/*
@@ -186,10 +185,4 @@
}
return blocks;
}
-/**
- * Prints various snapshot statistics to System.out; Simply delegates to {@link EDU.oswego.cs.dl.util.concurrent.FJTaskRunnerGroup#stats}.
- */
-public void stats() {
- if (this.taskGroup!=null) this.taskGroup.stats();
-}
}