我有一个有很多方法的课程。数据未就绪时，所有方法都会抛出一个异常。在这种情况下，我想在一定间隔后重试该方法。所以在catch中，我需要添加重试逻辑。我需要为所有方法添加相同的逻辑。
是否有一些方法/模式可以为所有catch子句执行相同的逻辑而无需复制粘贴
我能想到的一种方法是编写自己的Exception类并抛出该异常。并从My Exception类中执行此重试逻辑。
还有其他更好的方法吗？
class MyClass {
public void method1() {
try {
//do some logic
} catch (Exception e) {
//retry logic
//existing exception handling logic
}
}
public void method2() {
try {
//do some logic
} catch (Exception e) {
//retry logic
//existing exception handling logic
}
}
public void method3() {
try {
//do some logic
} catch (Exception e) {
//retry logic
//existing exception handling logic
}
}
}
修改：
class MyClass {
public void method1(int a, int b) {
try {
//do some logic
} catch (Exception e) {
Object args[] = {a,b};
executeLater("method1",args);
//retry logic
//existing exception handling logic
}
}
public void method2() {
try {
//do some logic
} catch (Exception e) {
Object args[] = null;
executeLater("method1",args);
//retry logic
//existing exception handling logic
}
}
public void method3(String abcd, int a) {
try {
//do some logic
} catch (Exception e) {
Object args[] = {abcd,a};
executeLater("method1",args);
//retry logic
//existing exception handling logic
}
}
public boolean executeLater(String methodName, Object args[]){
//Execute given method with the supplied args
return true;
}
}
添加了显示我将在每个catch子句中执行的操作的代码
答案 0 :(得分：0)
* Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
172.17.0.55 - - [05/Jan/2018 10:41:26] "GET /parameters HTTP/1.1" 200 -
172.17.0.55 - - [05/Jan/2018 10:41:26] "POST /update HTTP/1.1" 500 -
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1997, in __call__
return self.wsgi_app(environ, start_response)
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1985, in wsgi_app
response = self.handle_exception(e)
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1540, in handle_exception
reraise(exc_type, exc_value, tb)
File "/opt/conda/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
raise value
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1982, in wsgi_app
response = self.full_dispatch_request()
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1614, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1517, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/opt/conda/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
raise value
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1612, in full_dispatch_request
rv = self.dispatch_request()
File "/opt/conda/lib/python3.6/site-packages/flask/app.py", line 1598, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py", line 160, in update_parameters
constraints = self.master_network.model.constraints
AttributeError: 'Model' object has no attribute 'constraints'
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-10-44a540be31e8> in <module>()
----> 1 spark_model.train(rdd, nb_epoch=20, batch_size=32, verbose=0, validation_split=0.1)
/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py in train(self, rdd, nb_epoch, batch_size, verbose, validation_split)
195
196 if self.mode in ['asynchronous', 'synchronous', 'hogwild']:
--> 197 self._train(rdd, nb_epoch, batch_size, verbose, validation_split, master_url)
198 else:
199 print("""Choose from one of the modes: asynchronous, synchronous or hogwild""")
/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py in _train(self, rdd, nb_epoch, batch_size, verbose, validation_split, master_url)
215 self.master_optimizer, self.master_loss, self.master_metrics, self.custom_objects
216 )
--> 217 rdd.mapPartitions(worker.train).collect()
218 new_parameters = get_server_weights(master_url)
219 elif self.mode == 'synchronous':
/usr/local/spark/python/pyspark/rdd.py in collect(self)
807 """
808 with SCCallSiteSync(self.context) as css:
--> 809 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
810 return list(_load_from_socket(port, self._jrdd_deserializer))
811
/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 9, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
process()
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py", line 311, in train
put_deltas_to_server(deltas, self.master_url)
File "/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py", line 44, in put_deltas_to_server
return urllib2.urlopen(request).read()
File "/opt/conda/lib/python3.6/urllib/request.py", line 223, in urlopen
return opener.open(url, data, timeout)
File "/opt/conda/lib/python3.6/urllib/request.py", line 532, in open
response = meth(req, response)
File "/opt/conda/lib/python3.6/urllib/request.py", line 642, in http_response
'http', request, response, code, msg, hdrs)
File "/opt/conda/lib/python3.6/urllib/request.py", line 570, in error
return self._call_chain(*args)
File "/opt/conda/lib/python3.6/urllib/request.py", line 504, in _call_chain
result = func(*args)
File "/opt/conda/lib/python3.6/urllib/request.py", line 650, in http_error_default
raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 500: INTERNAL SERVER ERROR
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:458)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
process()
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py", line 311, in train
put_deltas_to_server(deltas, self.master_url)
File "/opt/conda/lib/python3.6/site-packages/elephas/spark_model.py", line 44, in put_deltas_to_server
return urllib2.urlopen(request).read()
File "/opt/conda/lib/python3.6/urllib/request.py", line 223, in urlopen
return opener.open(url, data, timeout)
File "/opt/conda/lib/python3.6/urllib/request.py", line 532, in open
response = meth(req, response)
File "/opt/conda/lib/python3.6/urllib/request.py", line 642, in http_response
'http', request, response, code, msg, hdrs)
File "/opt/conda/lib/python3.6/urllib/request.py", line 570, in error
return self._call_chain(*args)
File "/opt/conda/lib/python3.6/urllib/request.py", line 504, in _call_chain
result = func(*args)
File "/opt/conda/lib/python3.6/urllib/request.py", line 650, in http_error_default
raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 500: INTERNAL SERVER ERROR
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
这可能会给你一个想法。它一直尝试调用doProcess，直到它不抛出异常。如果发生任何异常，则等待10秒。
答案 1 :(得分：0)
好吧，您可以将整个catch块内容提取到方法并调用该方法，但这仅在您的重试逻辑不依赖于特定方法时才有效。并且每种方法都需要try-catch。
相反，使用函数式编程来缩短它：
public class Playground
{
public static void main(String[] args)
{
new Playground().method2(1, 2);
new Playground().method1();
}
public void method1()
{
tryAndTryAgain(() -> {
// logic 1
System.out.println("no params");
throw new RuntimeException();
});
}
public void method2(int a, int b)
{
tryAndTryAgain(() -> {
// logic 2
System.out.println(a + " " + b);
throw new RuntimeException();
});
}
public static void tryAndTryAgain(Runnable tryThis)
{
try
{
tryThis.run();
}
catch (Exception e)
{
new Timer().schedule(new TimerTask()
{
@Override
public void run()
{
tryAndTryAgain(tryThis);
}
}, 1000);
// existing exception handling logic
}
}
}
确切的结构取决于您的具体实现，但它应该让您了解如何构建它。好处是所有这些方法都可以专注于业务逻辑，重试逻辑和异常处理是在util方法中完成的。而且这种util方法甚至不需要知道任何关于参数，方法或任何东西的知识，因为所有的业务逻辑都包含在Runnable中。