This report is the anchor of the Workload Characterization application and provides a complete overview of the results of the clustering process. You can use this report to make a quick determination of how well the operation performed and to better understand how each cluster feature contributed to the overall performance of the process. Additionally, the execution options and operating parameters used in the process are included to provide a record of the complete operation.
Workload Characterization Analysis 1 Cluster Performance Summary For: Monday, July 1, 2003 Clustering Execution Options Cluster Input Data: SAMPLE Clustering Method: RADIUS Maximum Cluster Radius: 3.0 Training Sample Size: 2000 Sample Trim Limit: 97.5 Pct. Sampling Percentage : 2.0 Pct. Include Outliers in Clusters: YES Include Sparse Clusters: NO Sparse Cluster Limit: 0.5 Pct. Report Cluster Population: YES Report Using Account Codes: YES Report Sparse Clusters : NO Report Outliers Separately: NO Create Cluster Index Graph: NO Create Population Graph: NO Input CA MICS Files: BATJOB Input Dataset Name: 'COGDA01.AUDIT.BATJOB'
_____________________________________________________________________________________ Cluster Feature Contents Feature --------Outlier Limits------- Name ------------- Description -------------- Lower Upper Cases ________ ________________________________________ ____________ ____________ ______ JOBTCBTM Job TCB CPU Time 0:00:00.00 0:05:40.49 50 TAPEUSE Tape Device Usage Indicator 0.00 1.00 1 ====== 51 Note: A given case may be classified as an outlier more than once if multiple analysis elements contain abnormal values. Therefore, the totals in this report section will not necessarily agree with those of the Population section. _____________________________________________________________________________________
Workload Characterization Analysis 2 Cluster Performance Summary For: Monday, July 1, 2003 Cluster Population Summary Cluster Radius Normal Outlying Total % of Clustering Obs. Obs. Obs. Population Index ______ ______ ______ ________ _______ __________ __________ 1 0.00 1 13 14 0.70 0.00 2* 0.00 0 2 2 0.10 0.00 3* 0.17 0 2 2 0.10 0.17 4* 0.20 0 2 2 0.10 0.20 5* 0.36 5 0 5 0.25 0.21 6* 0.65 0 2 2 0.10 0.65 7* 0.69 0 2 2 0.10 0.69 8* 1.06 0 6 6 0.30 0.82 9 1.19 1,840 0 1,840 92.00 0.19 10* 1.20 6 0 6 0.30 0.82 11 1.44 31 0 31 1.55 0.79 12* 1.44 1 6 7 0.35 1.12 13 1.71 12 0 12 0.60 0.66 14 2.02 46 0 46 2.30 0.72 15* 2.44 0 3 3 0.15 1.74 16* 2.88 0 7 7 0.35 1.58 17* 2.91 0 6 6 0.30 1.81 18* 2.99 7 0 7 0.35 1.57 ====== ====== ======= ====== 1,949 51 2,000 100.00 '*' Indicates that the cluster is sparsely populated. Sparse clusters are defined as having a population that is less than 0.5% of the total population. In this study, the sparse cluster population limit is 10 cases. _____________________________________________________________________________________
Figure 15-26. Clustering Performance Summary report In the above report, cluster 9 accounts for nearly 92 percent of all jobs. The jobs represented by this cluster are the bulk of the work performed by this LPAR, and any new job class structure should ensure that these jobs receive priority in terms of the number of initiators. Additionally, clusters 11 & 14 contain significant numbers of jobs and will need to be considered in any new job class scheme as well.
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