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14
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My Accepted Solutions
| Title | Views | Posted |
|---|---|---|
| 4132 | 11-22-2016 02:51 PM | |
| 30012 | 06-17-2016 09:05 AM |
04-07-2023
07:03 AM
Hi @francescodevere, I would suggest reaching out to sales via this contact page.
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01-25-2017
12:03 PM
You can search for 'heap size' in Service Monitor and Host Monitor's configuration page. Make sure they are restarted after you save your configuration changes.
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12-15-2016
01:53 PM
Thanks. That resolved the issue on our environment as well.
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11-22-2016
02:51 PM
Hello Everybody ! I found the answer to this problem not too long after my last post. Since mahout arff.vector command only likes integer input, transform your doubles and float data into integer values (whole numbers). This is done by mulplying each column of data by 10 raised to the necesaary power. Eg If you have data like 22.23 then multiply by 100, if you have data like 13.854 multiply by 1000. NB Always multiply the whole dataset by the same number. This multiplication by some factor just rescales the data without changing its characterstics. Here is my rescaled iris data @RELATION iris
@ATTRIBUTE sepallength numeric
@ATTRIBUTE sepalwidth numeric
@ATTRIBUTE petallength numeric
@ATTRIBUTE petalwidth numeric
@ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica}
@DATA
35,14,2,51,Iris-setosa
30,14,2,49,Iris-setosa
32,13,2,47,Iris-setosa
31,15,2,46,Iris-setosa
36,14,2,50,Iris-setosa
39,17,4,54,Iris-setosa
: : And here my rescaled seeds data @RELATION seeds
@ATTRIBUTE area numeric
@ATTRIBUTE perimeter numeric
@ATTRIBUTE compactness numeric
@ATTRIBUTE kernel_length numeric
@ATTRIBUTE kernel_width numeric
@ATTRIBUTE asymmetry_coefficient numeric
@ATTRIBUTE kernel_groove numeric
@ATTRIBUTE class {1,2,3}
@DATA
14840,15260,5763,3312,2221,5220,871,1
14570,14880,5554,3333,1018,4956,881,1
14090,14290,5291,3337,2699,4825,905,1
13940,13840,5324,3379,2259,4805,896,1
14990,16140,5658,3562,1355,5175,903,1
14210,14380,5386,3312,2462,4956,895,1
; : After this mahout arff.vector works fine producing the required mahout seqdumper output: For the iris data Input Path: hdfs://childnode1:8020/user/Masternode/iris_data/kmeansout/clusteredPoints/part-m-00000
Key class: class org.apache.hadoop.io.IntWritable Value Class: class org.apache.mahout.clustering.classify.WeightedPropertyVectorWritable
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Key: 4: Value: wt: 1.0 distance: 1.9796969465046923 vec: [36.000, 14.000, 2.000, 50.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 6.838069903123147 vec: [39.000, 17.000, 4.000, 54.000, 1.000]
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: : : : Count: 150 And for the seeds data Input Path: hdfs://childnode1:8020/user/Masternode/seeds/kmeans_out/clusteredPoints/part-m-00000
Key class: class org.apache.hadoop.io.IntWritable Value Class: class org.apache.mahout.clustering.classify.WeightedPropertyVectorWritable
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Key: 24: Value: wt: 1.0 distance: 802.2824508737174 vec: [14290.000, 14010.000, 5609.000, 3158.000, 2217.000, 5132.000, 862.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 1230.3844556714478 vec: [14390.000, 14370.000, 5569.000, 3153.000, 1464.000, 5300.000, 873.000, 1.000]
Key: 177: Value: wt: 1.0 distance: 1533.2295745642984 vec: [13750.000, 12730.000, 5412.000, 2882.000, 3533.000, 5067.000, 846.000, 1.000]
Key: 76: Value: wt: 1.0 distance: 1242.0782987132768 vec: [15980.000, 17630.000, 6191.000, 3561.000, 4076.000, 6060.000, 867.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 2284.8314552331644 vec: [15670.000, 16840.000, 5998.000, 3484.000, 4675.000, 5877.000, 862.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 1865.3220945799494 vec: [15730.000, 17260.000, 5978.000, 3594.000, 4539.000, 5791.000, 876.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 802.7846465017649 vec: [16260.000, 19110.000, 6154.000, 3930.000, 2936.000, 6079.000, 908.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 2130.8931341845782 vec: [15510.000, 16820.000, 6017.000, 3486.000, 4004.000, 5841.000, 879.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 2497.1535713990975 vec: [15620.000, 16770.000, 5927.000, 3438.000, 4920.000, 5795.000, 864.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 1519.304200689462 vec: [15910.000, 17320.000, 6064.000, 3403.000, 3824.000, 5922.000, 860.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 2415.437198684845 vec: [17230.000, 20710.000, 6579.000, 3814.000, 4451.000, 6451.000, 876.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 1538.7977024244756 vec: [16490.000, 18940.000, 6445.000, 3639.000, 5064.000, 6362.000, 875.000, 2.000]
Key: 76: Value: wt: 1.0 distance: 1983.9629595142953 vec: [15550.000, 17120.000, 5850.000, 3566.000, 2858.000, 5746.000, 889.000, 2.000]
: : : : Count: 210
And for the mahout clusterdump output, ie the clusters: For the iris data VL-128{n=62 c=[27.484, 43.935, 14.339, 59.016, 2.226] r=[2.939, 5.048, 2.951, 4.626, 0.418]}
Weight : [props - optional]: Point:
1.0 : [distance=12.27183013149531]: [32.000, 47.000, 14.000, 70.000, 2.000]
1.0 : [distance=6.845135447338132]: [32.000, 45.000, 15.000, 64.000, 2.000]
1.0 : [distance=7.318849411742204]: [23.000, 40.000, 13.000, 55.000, 2.000]
: :
: :
VL-4{n=50 c=[34.180, 14.640, 2.440, 50.060, 1.000] r=[0:3.772, 1:1.718, 2:1.061, 3:3.489]}
Weight : [props - optional]: Point:
1.0 : [distance=1.4694216549377501]: [35.000, 14.000, 2.000, 51.000, 1.000]
1.0 : [distance=4.381689171997383]: [30.000, 14.000, 2.000, 49.000, 1.000]
1.0 : [distance=4.123008610226189]: [32.000, 13.000, 2.000, 47.000, 1.000]
: :
: :
VL-100{n=38 c=[30.737, 57.421, 20.711, 68.500, 2.947] r=[2.862, 4.821, 2.762, 4.876, 0.223]}
Weight : [props - optional]: Point:
1.0 : [distance=10.234304921679705]: [31.000, 49.000, 15.000, 69.000, 2.000]
1.0 : [distance=8.516482308683988]: [30.000, 50.000, 17.000, 67.000, 2.000]
1.0 : [distance=7.773365278708711]: [33.000, 60.000, 25.000, 63.000, 3.000]
: :
: : And for the seeds data VL-76{n=61 c=[16297.377, 18721.803, 6208.934, 3722.672, 3603.590, 6066.098, 885.115, 1.984] r=[470.329, 1087.056, 218.340, 150.079, 1222.928, 222.042, 14.901, 0.127]}
Weight : [props - optional]: Point:
1.0 : [distance=2107.009330735528]: [15380.000, 17080.000, 5832.000, 3683.000, 2956.000, 5484.000, 908.000, 1.000]
1.0 : [distance=1242.0782987132768]: [15980.000, 17630.000, 6191.000, 3561.000, 4076.000, 6060.000, 867.000, 2.000]
1.0 : [distance=2284.8314552331644]: [15670.000, 16840.000, 5998.000, 3484.000, 4675.000, 5877.000, 862.000, 2.000]
: :
: :
VL-177{n=77 c=[13274.805, 11964.416, 5229.286, 2872.922, 4759.740, 5088.519, 852.208, 2.766] r=[370.481, 808.956, 141.698, 162.027, 1292.441, 182.253, 22.964, 0.643]}
Weight : [props - optional]: Point:
1.0 : [distance=2237.7216511574297]: [13830.000, 13990.000, 5119.000, 3383.000, 5234.000, 4781.000, 918.000, 1.000]
1.0 : [distance=1073.5112523108057]: [13570.000, 12720.000, 5226.000, 3049.000, 4102.000, 4914.000, 869.000, 1.000]
1.0 : [distance=1842.0639979312034]: [13760.000, 13020.000, 5395.000, 3026.000, 3373.000, 4825.000, 864.000, 1.000]
: :
: :
VL-24{n=72 c=[14460.417, 14648.472, 5563.778, 3277.903, 2648.931, 5192.319, 880.556, 1.194] r=[531.885, 1108.561, 218.877, 158.321, 1093.229, 318.248, 21.182, 0.461]}
Weight : [props - optional]: Point:
1.0 : [distance=861.9071668766143]: [14840.000, 15260.000, 5763.000, 3312.000, 2221.000, 5220.000, 871.000, 1.000]
1.0 : [distance=1668.6900610565315]: [14570.000, 14880.000, 5554.000, 3333.000, 1018.000, 4956.000, 881.000, 1.000]
1.0 : [distance=694.0022557455687]: [14090.000, 14290.000, 5291.000, 3337.000, 2699.000, 4825.000, 905.000, 1.000]
: :
: : So the mahout arff.vector command works fine. Always !!!! Sorry for the delay in replying !
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