I can imagine that
> pointcut printWrite(): call(* Context.write(..));
might not do what you expect, I mean your type ‘Context’ - is it in a package?
You haven’t specified or wildcarded the package.
I don’t understand why
> pointcut printWrite(): call(* write(..));
doesn’t work though, are you *sure* that doesn’t work?
Andy
> On Sep 25, 2015, at 7:36 AM, xeonmailinglist <xeonmailingl...@gmail.com>
> wrote:
>
> I have found the solution. Strangely, this aspect works [1], but these
> pointcuts [2] don't. If anyone could try to explain I would be appreciated.
>
> [1] Aspect that works
> pointcut printWrite(): call(* *.write(..));
> before(): printWrite() {
> System.out.println("Busted2");
> }
>
> [2] Aspects that doesn't work
> pointcut printWrite(): call(* write(..));
> pointcut printWrite(): call(* Context.write(..));
>
>
>
>
> On 09/25/2015 03:12 PM, xeonmailinglist wrote:
>> In my example, I have the following snippet [1]. I want to execute my aspect
>> before calling context.write(this.word, one) from the example. Therefore, I
>> have created this aspect [2] based on your solution.
>>
>> The context variable is from this type public abstract class
>> TaskInputOutputContext<KEYIN, VALUEIN, KEYOUT, VALUEOUT> extends
>> TaskAttemptContext implements Progressable, and the superclass is from the
>> type public class TaskAttemptContext extends JobContext implements
>> Progressable.
>>
>> After I compile my code, I can see that the call invocation was not placed
>> in the class file [3].
>>
>> Why the call designator is not working?
>>
>> [1] Snippet of the wordcount example.
>>
>> while(itr.hasMoreTokens()) {
>> this.word.set(itr.nextToken());
>> context.write(this.word, one);
>> }
>>
>> [2] My aspect
>>
>>
>> before(): call(* *Context.write(..)) {
>> System.out.println("Aspects Write");
>> System.out.println(thisJoinPoint.getSourceLocation().getFileName());
>> }
>> [3] Compiled version of the job. This is the class file.
>>
>> public void map(LongWritable key, Text value, Context context) throws
>> IOException, InterruptedException {
>>
>> MapReduceCalls.aspectOf().ajc$before$org_apache_hadoop_mapred_aspects_MapReduceCalls$1$9e048e72();
>> StringTokenizer itr = new StringTokenizer(value.toString());
>>
>> while(itr.hasMoreTokens()) {
>> this.word.set(itr.nextToken());
>> context.write(this.word, one);
>> }
>> }
>> Cheers,
>>
>> On 09/23/2015 04:33 PM, Andy Clement wrote:
>>
>>> With pure AspectJ, if you want to intercept when map/reduce/cleanup are
>>> running, you can use something like this:
>>>
>>> === Foo.aj ===
>>> aspect Foo {
>>> before(): execution(* map(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> before(): execution(* reduce(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> before(): execution(* cleanup(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> }
>>> ===
>>>
>>> ajc -1.8 Foo.aj MyWordCount.java -showWeaveInfo
>>>
>>> This will compile and weave MyWordCount - when you run it you will see the
>>> advice output.
>>>
>>> Alternatively if you want to advise the call side of these things, you will
>>> need to weave the hadoop jar (whatever that is):
>>>
>>> === Foo.aj ===
>>> aspect Foo {
>>> before(): call(* map(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> before(): call(* reduce(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> before(): call(* cleanup(..)) {
>>> System.out.println(thisJoinPoint);
>>> }
>>> }
>>> ===
>>>
>>> ajc -1.8 Foo.aj -inpath hadoop.jar -outjar woven_hadoop.jar -showWeaveInfo
>>>
>>> Now when you run your MyWordCount program you need to be using the
>>> woven_hadoop jar instead of the regular hadoop jar.
>>>
>>> cheers,
>>> Andy
>>>
>>>> On Sep 23, 2015, at 7:34 AM, xeonmailinglist <xeonmailingl...@gmail.com
>>>> <mailto:xeonmailingl...@gmail.com>> wrote:
>>>>
>>>> Hi,
>>>>
>>>> I am trying to pointcut calls of map and reduce from Hadoop MapReduce.
>>>>
>>>> When you create a program to work with the application MapReduce, you need
>>>> to define map and reduce functions. The functions are called by the
>>>> framework MapReduce. Here is an example of a MapReduce program programmed
>>>> by the user [1].
>>>>
>>>> I am using Spring AOP to intercept the call to the map , reduce, and
>>>> cleanup functions, but it is not working. Maybe I must use AspectJ. The
>>>> problem is that I don’t know how to do it with AspectJ. Any help to try
>>>> make this work?
>>>>
>>>> [1] Wordcount program
>>>>
>>>>
>>>> package org.apache.hadoop.mapred.examples;
>>>>
>>>> import org.apache.hadoop.conf.Configuration;
>>>> import org.apache.hadoop.fs.Path;
>>>> import org.apache.hadoop.io.IntWritable;
>>>> import org.apache.hadoop.io.LongWritable;
>>>> import org.apache.hadoop.io.Text;
>>>> import org.apache.hadoop.mapred.*;
>>>> import org.apache.hadoop.mapred.lib.HashPartitioner;
>>>> import org.apache.hadoop.mapreduce.Mapper;
>>>> import org.apache.hadoop.mapreduce.ReduceContext;
>>>> import org.apache.hadoop.mapreduce.Reducer;
>>>> import org.apache.hadoop.util.GenericOptionsParser;
>>>>
>>>> import java.io.IOException;
>>>> import java.util.Iterator;
>>>> import java.util.StringTokenizer;
>>>>
>>>> /**
>>>> * My example of a common wordcount. Compare with the official
>>>> WordCount.class to understand the differences between both classes.
>>>> */
>>>> public class MyWordCount {
>>>> public static class MyMap extends Mapper {
>>>> private final static IntWritable one = new IntWritable(1);
>>>> private Text word = new Text();
>>>> private MedusaDigests parser = new MedusaDigests();
>>>>
>>>> public void map(LongWritable key, Text value,
>>>> OutputCollector<Text, IntWritable> output, Reporter reporter) throws
>>>> IOException {
>>>> StringTokenizer itr = new StringTokenizer(value.toString());
>>>> while (itr.hasMoreTokens()) {
>>>> word.set(itr.nextToken());
>>>> output.collect(word, one);
>>>> }
>>>> }
>>>>
>>>> public void run(Context context) throws IOException,
>>>> InterruptedException {
>>>> setup(context);
>>>> try {
>>>> while (context.nextKeyValue()) {
>>>> System.out.println("Key: " + context.getCurrentKey() +
>>>> " Value: " + context.getCurrentValue());
>>>> map(context.getCurrentKey(),
>>>> context.getCurrentValue(), context);
>>>> }
>>>> } finally {
>>>> cleanup(context);
>>>> }
>>>> }
>>>>
>>>> public void cleanup(Mapper.Context context) {}
>>>> }
>>>>
>>>> public static class MyReducer extends Reducer {
>>>> private IntWritable result = new IntWritable();
>>>> MedusaDigests parser = new MedusaDigests();
>>>>
>>>> public void reduce(Text key, Iterable<IntWritable> values, Context
>>>> context
>>>> ) throws IOException, InterruptedException {
>>>> int sum = 0;
>>>> for (IntWritable val : values) {
>>>> System.out.println(" - key ( " + key.getClass().toString()
>>>> + "): " + key.toString()
>>>> + " value ( " + val.getClass().toString() + " ): "
>>>> + val.toString());
>>>> sum += val.get();
>>>> }
>>>> result.set(sum);
>>>> context.write(key, result);
>>>> }
>>>>
>>>> public void run(Context context) throws IOException,
>>>> InterruptedException {
>>>> setup(context);
>>>> try {
>>>> while (context.nextKey()) {
>>>> System.out.println("Key: " + context.getCurrentKey());
>>>> reduce(context.getCurrentKey(), context.getValues(),
>>>> context);
>>>> // If a back up store is used, reset it
>>>> Iterator<IntWritable> iter =
>>>> context.getValues().iterator();
>>>> if(iter instanceof ReduceContext.ValueIterator) {
>>>>
>>>> ((ReduceContext.ValueIterator<IntWritable>)iter).resetBackupStore();
>>>> }
>>>> }
>>>> } finally {
>>>> cleanup(context);
>>>> }
>>>> }
>>>>
>>>> public void cleanup(Reducer.Context context) {}
>>>> }
>>>>
>>>> public static void main(String[] args) throws Exception {
>>>> GenericOptionsParser parser = new GenericOptionsParser(new
>>>> Configuration(), args);
>>>>
>>>> String[] otherArgs = parser.getRemainingArgs();
>>>> if (otherArgs.length < 2) {
>>>> System.err.println("Usage: wordcount [<in>...] <out>");
>>>> System.exit(2);
>>>> }
>>>>
>>>> // first map tasks
>>>> JobConf conf = new JobConf(MyWordCount.class);
>>>> conf.setJobName("wordcount");
>>>> conf.setClass("mapreduce.job.map.identity.class",
>>>> MyFullyIndentityMapper.class, Mapper.class);
>>>>
>>>> conf.setJarByClass(MyWordCount.class);
>>>> conf.setPartitionerClass(HashPartitioner.class);
>>>> conf.setOutputKeyClass(Text.class);
>>>> conf.setOutputValueClass(IntWritable.class);
>>>> conf.setNumReduceTasks(1);
>>>>
>>>> Path[] inputPaths = new Path[otherArgs.length-1];
>>>> for (int i = 0; i < otherArgs.length - 1; ++i) { inputPaths[i] =
>>>> new Path(otherArgs[i]); }
>>>> Path outputPath = new Path(otherArgs[otherArgs.length - 1]);
>>>> FileInputFormat.setInputPaths(conf, inputPaths);
>>>> FileOutputFormat.setOutputPath(conf, outputPath);
>>>>
>>>> // launch the job directly
>>>> Medusa.runJob(conf);
>>>> System.exit(0);
>>>> }
>>>> }
>>>> Thanks,
>>>>
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>>>
>>>
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