MapReduce

问题 I was trying to analyse the default map reduce job, that doesn't define a mapper or a reducer. i.e. one that uses IdentityMapper & IdentityReducer To make myself clear I just wrote my identity reducer public static class MyIdentityReducer extends MapReduceBase implements Reducer<Text,Text,Text,Text> { @Override public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { while(values.hasNext()) { Text value = values.next();

问题 In a question on CouchDB I asked previously (Can you implement document joins using CouchDB 2.0 'Mango'?), the answer mentioned creating domain objects instead of storing relational data in Couch. My use case, however, is not necessarily to store relational data in Couch but to flatten relational data. For example, I have the entity of Invoice that I collect from several suppliers. So I have two different schemas for that entity. So I might end up with 2 docs in Couch that look like this: {

问题 In a question on CouchDB I asked previously (Can you implement document joins using CouchDB 2.0 'Mango'?), the answer mentioned creating domain objects instead of storing relational data in Couch. My use case, however, is not necessarily to store relational data in Couch but to flatten relational data. For example, I have the entity of Invoice that I collect from several suppliers. So I have two different schemas for that entity. So I might end up with 2 docs in Couch that look like this: {

问题 This is follow up from this question How to merge objects attributes from reduce to rereduce function in CouchDB I've been following the accepted answer from the previous question. For quick review, this is my JSON schema: {"emp_no": .., "salary": .., "from_date": .., "to_date": .., "type" : "salaries"} {"emp_no": .., "title": .., "from_date": .., "to_date" : .., "type" : "titles"} I want to find out the average salaries for each active titles (denoted by "from_date" = "9999-01-01"). Since

问题 I have three collections, _project - It contains all the projects _build - It contains all the builds and every build must belong to a project _build.details - It contains ads which must belong to an adset and each adset must belongs to a campaign and each campaign must belongs to a build. _project document structure: { "_id" : ObjectId("58d8c501be2bee2bc0b3b081"), "CreatedBy" : ObjectId("58c801c606f72508d87421c6"), .... .... },... _build document structure: { "_id" : ObjectId(

问题 The input file to my hadoop M/R job is a text file in which the records are separated by tab character '\t' instead of newline '\n'. How can I instruct hadoop to split using the tab character as by default it splits around newlines and each line in the text file is taken as a record. One way to do it is to use a custom input format class that uses a filter stream to convert all tabs in the original stream to newlines. But this does not look elegant. Another way would be to use java.util

问题 I have a MapReduce program as below import java.io.IOException; import java.util.Iterator; import java.util.StringTokenizer; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.FileInputFormat; import org.apache.hadoop.mapred.FileOutputFormat; import org.apache.hadoop.mapred.JobClient; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.KeyValueTextInputFormat; import org.apache.hadoop.mapred.MapReduceBase; import org.apache

问题 I using Hadoop Map/Reduce using Java Suppose, I have completed a whole map/reduce job. Is there any way I could repeat the whole map/reduce part only, without ending the job. I mean, I DON'T want to use any chaining of the different jobs but only only want the map/reduce part to repeat. Thank you! 回答1: So I am more familiar with hadoop streaming APIs but approach should translate to the native APIs. In my understanding what you are trying to do is run the several iterations of same map() and

问题 I Have managed to run the Hadoop wordcount example in a non-distributed mode; I get the output in a file named "part-00000"; I can see that it lists all words of all input files combined. After tracing the wordcount code I can see that it takes lines and splits the words based on spaces. I am trying to think of a way to just list the words that have occurred in multiple files and their occurrences? can this be achieved in Map/Reduce? -Added- Are these changes appropriate? //changes in the

问题 I am trying to build the KD tree(independent) for image features. I have extracted the image features,the feature contains suppose 1000 float values. Using map-reduce to distribute the images among the nodes of the cluster according to classification(eg, cat,dog,guns)ie. each node will contain the bunch of the similar images & then build KD tree of the images on each node. I am confused about how the tree can be built. So how can I build the KD tree using map-reduce? Each node will contain