###EXAMPLES

1. hello world - set up a basic working algorithm
2. input output - learn how to read and write datasets
3. dimensions - organize datasets into categories
4. externalLib - include classes from an extra library (gdal)
5. read json - an example using Skysat metadata
6. image algo - Use all the previous material to read a Skysat Dataset and run a basic scene content algorithm by calculating the average color.
7. yarn - an example illustrating how to use YARN runtime resource allocation on a basic map/reduce algorithm.
8. mbtiles - an example using the MR4C Geospatial library to export a mbtiles file from a Skysat scene.
9. random access - when you need to deal with large datasets, you will need to read in smaller chunks. This example shows you the various ways that MR4C can help you do this.

###Run in Hadoop

• HDFS commands - use the format:

    hdfs dfs -<COMMAND> <URI>
  

  • COMMAND: ls, mkdir, rm, get, put etc. Similar to Linux

  • URI : see item 2.

  • for example the command below would list the files at /user/tbowdoin/test:

    hdfs dfs -ls /user/tbowdoin/test/
    

• URIs - in our cluster we can use hdfs URIs which use the format:

    hdfs:///user/<USER>/<PATH>
  

  • USER: is your hadoop user
  • PATH: is the hdfs path relative to your hdfs user directory

• packaging external libraries

  • If you are porting an algorithm from one local machine or cluster to another you should include any linked shared objects along with your algorithm so.
  • This will make your algorithm truely portable to any cluster.