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Both sides previous revision Previous revision 2012/02/06 14:52 dusek 2012/02/06 13:26 straka 2012/02/06 13:25 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:23 straka 2012/02/06 13:11 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 09:22 straka 2012/02/06 09:01 straka 2012/02/06 08:55 straka 2012/02/06 08:50 straka 2012/02/06 08:41 straka 2012/02/06 08:40 straka 2012/02/06 08:28 straka 2012/02/06 08:26 straka 2012/02/06 08:21 straka 2012/02/06 08:21 straka 2012/02/06 08:20 straka 2012/02/06 08:20 straka 2012/02/06 08:18 straka 2012/02/06 08:13 straka 2012/02/06 08:10 straka 2012/02/06 08:09 straka 2012/02/06 08:03 straka 2012/02/06 08:03 straka 2012/02/06 08:02 straka 2012/02/06 07:59 straka vytvořeno Go		2012/02/06 14:52 dusek 2012/02/06 13:26 straka 2012/02/06 13:25 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:23 straka 2012/02/06 13:11 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 09:22 straka 2012/02/06 09:01 straka 2012/02/06 08:55 straka 2012/02/06 08:50 straka 2012/02/06 08:41 straka 2012/02/06 08:40 straka 2012/02/06 08:28 straka 2012/02/06 08:26 straka 2012/02/06 08:21 straka 2012/02/06 08:21 straka 2012/02/06 08:20 straka 2012/02/06 08:20 straka 2012/02/06 08:18 straka 2012/02/06 08:13 straka 2012/02/06 08:10 straka 2012/02/06 08:09 straka 2012/02/06 08:03 straka 2012/02/06 08:03 straka 2012/02/06 08:02 straka 2012/02/06 07:59 straka vytvořeno Go Next revision Both sides next revision
courses:mapreduce-tutorial:step-31 [2012/02/06 08:28] straka		courses:mapreduce-tutorial:step-31 [2012/02/06 08:40] straka
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	===== Exercise 2 =====		===== Exercise 2 =====
-	Implement an AllReduce job on ''/net/projects/hadoop/examples/inputs/numbers-small'', which computes	+	Implement an AllReduce job on ''/net/projects/hadoop/examples/inputs/numbers-small'', which computes median of the input data. You can use the following iterative algorithm:
		+	* At the beginning, set //min<sub>1</sub>// = ''Integer.MIN_VALUE'', //max<sub>1</sub>// = ''Integer.MAX_VALUE'', //index_to_find// = number_of_input_data / 2.
		+	* In step //i//, do the following:
		+	- Consider only input keys in range <//min<sub>i</sub>//, //max<sub>i</sub>//>.
		+	- Compute //split// = ceiling of mean of the keys.
		+	- If the //index_to_find// is in range <1+number of keys less than //split//, number of keys less or equal to //split//>, then ''split'' is median.
		+	- Else, if //index_to_find// is at most the number of keys less than //split//, set //max<sub>i+1</sub>// = //split//-1.
		+	- Else, set //min<sub>i+1</sub>// = //split//+1 and subtract from //index_to_find// the number of keys less or equal to //split//.
	You can download the template {{:courses:mapreduce-tutorial:step-31-exercise2.txt|Median.java}} and execute it using:		You can download the template {{:courses:mapreduce-tutorial:step-31-exercise2.txt|Median.java}} and execute it using:

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