MapReduce

问题 I am trying to run a very simple job to test my hadoop setup so I tried with Word Count Example , which get stuck in 0% , so i tried some other simple jobs and each one of them stuck 52191_0003/ 14/07/14 23:55:51 INFO mapreduce.Job: Running job: job_1405376352191_0003 14/07/14 23:55:57 INFO mapreduce.Job: Job job_1405376352191_0003 running in uber mode : false 14/07/14 23:55:57 INFO mapreduce.Job: map 0% reduce 0% I am using hadoop version- Hadoop 2.3.0-cdh5.0.2 I did quick research on Google

问题 I am working on a project that requires a big knowledgebase to be constructed based on word co-occurrences in text. As I have researched, a similar approach has not been tried in appengine. I would like to use appengine's flexibility and scalability, to be able to serve the knowledgebase and do reasoning on it to a wide scale of users. So far I have come up with a mapreduce implementation based on the demo app for the pipeline. The source texts are stored in in the blobstore as zipped files

问题 I am trying to use JobControl to connect multiple Mappers and Reducers together but encounter the following error when invoking JobConf.setMapperClass : setMapperClass(java.lang.Class<? extends org.apache.hadoop.mapred.Mapper>) in org.apache.hadoop.mapred.JobConf cannot be applied to (java.lang.Class<capture#530 of ? extends org.apache.hadoop.mapreduce.Mapper>) It seems that java complains my implementation of Mapper, which is based on mapreduce.Mapper , while JobControl takes mapred.Mapper .

问题 I am using a 0 reduce approach to my problem. I wish to preprocess data from one file and then to write it out as another file, but with no new lines and tab delimeters? How can I output my map job that has processed my data with the same file format it came in minus the preprocess. That is, I have something like this: Preprocess: <TITLE> Herp derp </Title> I am a major general Post Process: Herp Derp I am a major general What I want it to do is this: Herp Derp I am a major general I believe

问题 If multiple mappers are executed on the same node, will combiner combine the results from multiple mappers? I can't find the answer for this in documents or books. And combiner examples I can find all seem to make a difference even if it can aggregate results from one mapper only. 回答1: From Yahoo's Hadoop Tutorial: The Combiner will receive as input all data emitted by the Mapper instances on a given node. The output from the Combiner is then sent to the Reducers, instead of the output from

问题 would be possible with an aggregate. I change the key of the object to the _id of it. I'm trying to do with map-reduce in aggregation with project. Any idea? what I have: {"serie" : { "_id" : ObjectId("5a55f988b6c9dd15b47faa2a"), "updatedAt" : ISODate("2018-02-09T13:22:54.521Z"), "createdAt" : ISODate("2018-01-10T11:31:20.978Z"), "deletar" : false, "infantil" : false, "status" : true, "turma" : [], }} How I'm trying to leave: {"5a55f988b6c9dd15b47faa2a" : { "updatedAt" : ISODate("2018-02

问题 So I have an RDD as follows RDD[(String, Int, String)] And as an example ('b', 1, 'a') ('a', 1, 'b') ('a', 0, 'b') ('a', 0, 'a') The final result should look something like ('a', 0, 'a') ('a', 0, 'b') ('a', 1, 'b') ('b', 1, 'a') How would I do something like this? 回答1: Try this: rdd.sortBy(r => r) If you wanted to switch the sort order around, you could do this: rdd.sortBy(r => (r._3, r._1, r._2)) For reverse order: rdd.sortBy(r => r, false) 来源： https://stackoverflow.com/questions/36393224

问题 In my mapReduce program, i have to use a Partitionner : public class TweetPartitionner extends HashPartitioner<Text, IntWritable>{ public int getPartition(Text a_key, IntWritable a_value, int a_nbPartitions) { if(a_key.toString().startsWith("#")) return 0; else return 1; } } And I have set the number of reduce tasks : job.setNumReduceTasks(2); But I get the following error : java.io.IOException: Illegal partition for #rescinfo (1) The parameter a_nbPartitions returns 1 . I've read in another

问题 sample document : {"name":"John", "age":35, "address":".....",.....} Employees whose join_month=3 is priority 1 Employees whose address contains the string "Avenue" is priority 2 Employees whose address contains the string "Street" is priority 3 Employees whose address contains the string "Road" is priority 4 As of now, I'm at this stage: db.collection.aggregate([ { "$match": { "$or": [ { "join_month": 3 }, { "address": /.*Avenue.*/i }, { "address": /.*Street.*/i }, { "address": /.*Road.*/i }

问题 I am getting some error while running my MapReduce WordCount job. Error: java.io.IOException: Initialization of all the collectors failed. Error in last collector was :class wordcount.wordmapper at org.apache.hadoop.mapred.MapTask.createSortingCollector(MapTask.java:414) at org.apache.hadoop.mapred.MapTask.access$100(MapTask.java:81) at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs