Practical exercise unit 7 Topic : MapReduce program in Java Work purpose : Display function, convolution function and the assignment perform the code study

Tested to work drop off
MapReduce task completed code with depends each how sure problems immediately determination for him small data in the collection try to see worth it First , Hadoop install it offline . In this Hadoop mode local file system _ and local work perform system with works _ Book on the website to the instructions according to examples install it and make up
Let's do our job above five row in the collection try let's ( result page to the width suitable respectively formatted ):



Control questions :
1. Structural cable system purpose what _
2. Cable systems how to classes divided ?
3. What is 10BaseT ?
4. In 10 Base 2 technology how cable used ?
5. In 10 Base 5 technology how cable used ?
6. In the network information transmission for how kind of from cables used ?
PRACTICAL EXERCISE UNIT - 8


Topic : Distributed MapReduce work perform


Work purpose : learning API support for MapReduce mapping and shorten functions From Java another in languages to write possibility gives _

Same that's it program of information complete in the collection never how unchanged works ¬. MapReduce exactly that's it for intended : it data and hardware _ with measures . High on a 10 -node EC 2 cluster with CPU Additional big An example program perform for six minute time went

Hadoop Streaming
Hadoop API provided will do for MapReduce mapping and shorten functions From Java another in languages to write possibility gives _ Hadoop technology The stream ¬_ is from the standard Unix stream uses Hadoop interaction organize to do for programs with , therefore MapReduce programs for in writing standard from the entrance study ( standard input ) and standard to exit ( default exit ) to write supports each how from the language your use can _ ¬ Collection function standard from input ( frame warranty the key according to sorted ) strings reads and the results standard to exit writes _
What is Hadoop ? work show for Streaming , we our MapReduce program again we write maximum the temperature to find for .
Ruby
In Ruby mapping of the function exemplary The implementation is in Listing 2.8 given .

har from STDIN one line for program block done , standard access lines across passes . (IO global constant of type ). Block every one access from the line necessary fields emits and if the temperature right if ¬ year and temperature with \ t separated without standard to exit writes (puts from the function used without ).
Between streaming important architectural the difference to emphasize need and the Java MapReduce _ API . Java API mapping function through records consecutively again to work directed . ¬ The map ( ) of your Frame Mapper application method calls _ Enter in the collection each one writing for , from Stream when using access how again to work display of the program himself solution does - for example , it is one of time in itself one how many lines easily read takes and again because it works reading process his control under . Adapted in Java mapping done increase records consecutively take comes , but it is an example of ¬Mapper in the variable previous lines collect through one of time in itself one how many records again performance can _ Such without , you last writing that it was read you know and ¬ last rows the group again to work your finish for close () method your application need _
Without using Hadoop easily try to see can :

The program is also standard from input lines across is repeated , but this trip we each one buttons the group again work in the process condition information our storage need _ Ours in our example keys years , we are the last found the key and this the key for found maximum the temperature we keep A MapReduce framework to keys order to give guarantees ; therefore for , if the key from before difference If it does , it's new to us keys to the group our past means _ Unlike Java like From streaming when using each one the key group provide an iterator for API group _ borders in the program determination need _
Each _ line for the key and value is taken . If the group just finished _ if ( last_key && last_ key ! = key ), we new the key for maximum the temperature from recovery before , we key and ¬ in the group maximum the temperature labels with we separate . If the group yet unfinished if , the program only current the key for maximum the temperature updates .
In a cluster big in volume data collection with from the -combiner option when running use need combine function to determine
After 1.x in versions combine function each What Streaming command to be can _ The former in publications combine The function is written in Java need was _ therefore for in practice often used temporary solution without using Java mapping in the function in hand combine was _ Ours in case , display function pipe line with replacement can _