MapReduce

问题 I am trying to read a Excel file containing some data for aggregation in hadoop.The map reduce program seems to be working fine but the output produce is in a non readable format.Do I need to use any special InputFormat reader for Excel file in Hadoop Map Reduce ?.My configuration is as below Configuration conf=getConf(); Job job=new Job(conf,"LatestWordCount"); job.setJarByClass(FlightDetailsCount.class); Path input=new Path(args[0]); Path output=new Path(args[1]); FileInputFormat

问题 This question already has answers here : How can I include a python package with Hadoop streaming job? (5 answers) Closed 6 years ago . I am writing MapReduce job in Python, and want to use some third libraries like chardet . I konw that we can use option -libjars=... to include them for java MapReduce. But how to include third party libraries in Python MapReduce Job ? Thank you! 回答1: Problem has been solved by zipimport . Then I zip chardet to file module.mod , and used like this: importer =

问题 I recently set up a test environment cluster for hadoop -One master and two slaves. Master is NOT a dataNode (although some use master node as both master and slave). So basically I have 2 datanodes. The default configuration for replication is 3. Initially, I did not change any configuration on conf/hdfs-site.xml . I was getting error could only be replicated to 0 nodes instead of 1 . I then changed the configuration in conf/hdfs-site.xml in both my master and slave as follows: <property>

问题 Recently I came across this issue. I had a file at a Hadoop Distributed File System path and related hive table. The table had 30 partitions on both sides. I deleted 5 partitions from HDFS and then executed "msck repair table <db.tablename>;" on the hive table. It completed fine but outputted "Partitions missing from filesystem:" I tried running select count(*) <db.tablename>; (on tez) it failed with the following error: Caused by: java.util.concurrent.ExecutionException: java.io

问题 I have unbalanced tree data stored in tabular format like: parent,child a,b b,c c,d c,f f,g The depth of tree is unknow. how to flatten this hierarchy where each row contains entire path from leaf node to root node in a row as: leaf node, root node, intermediate nodes d,a,d:c:b f,a,e:b Any suggestions to solve above problem using hive, pig or mapreduce? Thanks in advance. 回答1: I tried to solve it using pig, here are the sample code: Join function: -- Join parent and child Define join

问题 I’m new to both Java and Hadoop. I’m trying a very simple program to get Frequent pairs. e.g. Input: My name is Foo. Foo is student. Intermediate Output: Map: (my, name): 1 (name ,is): 1 (is, Foo): 2 // (is, Foo) = (Foo, is) (is, student) So finally it should give frequent pair is (is ,Foo) . Pseudo code looks like this: Map(Key: line_num, value: line) words = split_words(line) for each w in words: for each neighbor x: emit((w, x)), 1) Here my key is not one, it’s pair. While going through

问题 Before starting Pig in map reduce mode you always have to start the history server else while trying to execute Pig Latin statements the below mentioned logs are generated: 2018-10-18 15:59:13,709 [main] INFO org.apache.hadoop.mapred.ClientServiceDelegate - Application state is completed. FinalApplicationStatus=SUCCEEDED. **Redirecting to job history server** 2018-10-18 15:59:14,713 [main] INFO org.apache.hadoop.ipc.Client - Retrying connect to server: 0.0.0.0/0.0.0.0:10020. Already tried 0

问题 I wrote a custom partitioner but am unable to set it to the JobConf object in the main class. import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Partitioner; public class FirstCharTextPartitioner extends Partitioner<Text, Text> { @Override public int getPartition(Text key, Text value, int numReduceTasks) { return (key.toString().charAt(0)) % numReduceTasks; } } But when I try to set this to the JobConf object, I get the following error. The method setPartitionerClass(Class)

问题 Exception in thread "main" java.lang.ClassNotFoundException:WordCount-> so many answers relate to this issue and it seems like I am definitely missing a small point again which took me hours to figure. I will try to be as clear as possible about the paths, code itself and other possible solutions I tried and did not work. I am kinda sure about my correctly configuring Hadoop as everything was working up until the last stage. But still posting the details: Environment variables and paths >

问题 all I want to ask, now I'm running hadoop 2.6.0. So how can I separate this secondary namenode from the primary one? What's the configuration? Have I use one additional computer to become a secondary namenode, or it can be in a datanode? I need your suggest, thanks... 回答1: NameNode, Secondary NameNode, DataNodes are just names given to "machines" based on the job they perform. In a "ideal" distributed enviornment, they all can and should reside in separate machines. The only requirement for a