I run my application using ruby client: ruby elastic-mapreduce -j j-20PEKMT9BRSUC --jar s3n://sakae55/lib/edu.cit.som.jar --main-class edu.cit.som.hadoop.SOMDriver --arg s3n://sakae55/repository/input
I\'m having a problem with Hadoop producing too many log files in $HADOOP_LOG_DIR/userlogs (the Ext3 filesystem allows only 32000 subdirectories) which looks like开发者_如何转开发 the same problem in
Currently am implementing PageRank on Disco.As an iterative algorithm, t开发者_如何学运维he results of one iteration are used as input to the next iteration.
My reducer class produces outputs with TextOutpu开发者_如何学编程tFormat (the default OutputFormat given by Job). I like to consume this outputs after the MapReduce job complete to aggregate the outpu
In many real-life situations wh开发者_开发百科ere you apply MapReduce, the final algorithms end up being several MapReduce steps.
I need some ideas for a weekend project about Hadoop and OpenStreetMap. I have access to AWS EC2 instance with OpenStreetMap snapshot in my EBS volume.
I want to write a map/reduce job to select a number of random samples from a large dataset based on a row level condition. I want to minimize the number of intermediate keys.
I am testing jobs in EMR and each and every test takes a lot of time to start up. Is there a way to keep the server/master node alive in Amazon EMR?I know this can be done with the API.But, I wanted t
My Couchdb database as a main document type that looks something like: { \"_id\" : \"doc1\", \"type\" : \"main_doc\",
Map Reduce is a pattern that seems to get a lot of traction lately and I start to see it manifest in one of my projects that is focused on an event processing pipeline (iPhone Accelerometer and GPS da
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