Commit a86a565c authored by IBRAHIM Shadi's avatar IBRAHIM Shadi
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fix Readme

parent e45fb888
......@@ -8,13 +8,7 @@ The data are meant to serve as an example dataset for users to play with the str
* Platform: Hadoop 2.7.3 was used for running our experiments. We configured Hadoop with one dedicated node as the Resource Manager, which is hosting the NameNode and the Application Manager processes. The rest 20 nodes were each running one DataNode process and one Node Manager process. Each node, hosting Node Manager process, was configured to run 8 Map tasks and 8 Reduce tasks maximum at a time.
* Application: We chose WordCount, a simple yet representative MapReduce application amongst 13 different applications provided by the Puma benchmark.
* Detection mechanisms: We selected three straggler detection mechanisms for examining in our experiments: Default, LATE and Hierarchical.
* Environment heterogeneity: Besides the provided homogeneous environment, we tuned the hardware setting in order to introduce a heterogeneous environment. For our cluster of 20 workers, we divide them into four groups, G<sub>1
, G<sub>2
, G<sub>3
, G<sub>4
. Each group consists of a specific number of nodes. All nodes belonging to group G<sub>i
will have i active cores. For instance, the nodes in group G<sub>3
will all have 3 active cores. We vary the ratio of the four groups to present different scenarios covering a broad range of possible heterogeneous cluster setting. The data we present in this dataset include four settings, which are: {35-35-5-25}, {25-25-25-25}, {10-10-5-75} and {5-5-0-90}.
* Environment heterogeneity: Besides the provided homogeneous environment, we tuned the hardware setting in order to introduce a heterogeneous environment. For our cluster of 20 workers, we divide them into four groups, G<sub>1</sub>, G<sub>2</sub>, G<sub>3</sub>, G<sub>4</sub>. Each group consists of a specific number of nodes. All nodes belonging to group G<sub>i </sub>will have i active cores. For instance, the nodes in group G<sub>3</sub> will all have 3 active cores. We vary the ratio of the four groups to present different scenarios covering a broad range of possible heterogeneous cluster setting. The data we present in this dataset include four settings, which are: {35-35-5-25}, {25-25-25-25}, {10-10-5-75} and {5-5-0-90}.
* The data of each scenario are collected by repeating 5-10 running times.
## DataSet format
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