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| Title | Views | Posted |
|---|---|---|
| 4133 | 11-22-2016 02:51 PM | |
| 30032 | 06-17-2016 09:05 AM |
04-07-2023
03:00 AM
Hello Team I have a small development POC HDP Cluster installed on 4 machines I was using the Public Repositories of Hortonworks/Cloudera that are no longer valid http://public-repo-1.hortonworks.com/HDP-GPL/centos7/3.x/updates/3.1.4.0/repodata/repomd.xml http://public-repo-1.hortonworks.com/HDP/centos7/3.x/updates/3.1.4.0/repodata/repomd.xml http://public-repo-1.hortonworks.com/HDP-UTILS-1.1.0.22/repos/centos7/repodata/repomd.xml http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.7.3.0/repodata/repomd.xml Quote "Starting with the HDP 3.1.5 release and Ambari 2.7.5 access to HDP, Ambari repositories requires authentication. Authentication credentials for new customers are sent sent from Cloudera to registered support contacts" To be a registered support contact I suppose one needs a subscription. How do I obtain the subscription for access to the repositories and how much does it cost annually and monthly approximately. Are they still available for legacy HDP and Ambari Platforms
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Hortonworks Data Platform (HDP)
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: 4.123008610226189 vec: [32.000, 13.000, 2.000, 47.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 5.188371613521854 vec: [31.000, 15.000, 2.000, 46.000, 1.000]
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]
Key: 4: Value: wt: 1.0 distance: 4.152011560677545 vec: [34.000, 14.000, 3.000, 46.000, 1.000]
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Key: 4: Value: wt: 1.0 distance: 4.919268238264621 vec: [30.000, 14.000, 1.000, 48.000, 1.000]
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Key: 4: Value: wt: 1.0 distance: 10.201921387660274 vec: [40.000, 12.000, 2.000, 58.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 12.130919173747719 vec: [44.000, 15.000, 4.000, 57.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 6.624137679728539 vec: [39.000, 13.000, 4.000, 54.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 1.5097019573412485 vec: [35.000, 14.000, 3.000, 51.000, 1.000]
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Key: 4: Value: wt: 1.0 distance: 4.019850743497717 vec: [32.000, 16.000, 2.000, 47.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.049592572099055 vec: [31.000, 16.000, 2.000, 48.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.25666536152411 vec: [34.000, 15.000, 4.000, 54.000, 1.000]
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Key: 4: Value: wt: 1.0 distance: 5.287645979072288 vec: [35.000, 13.000, 2.000, 55.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 3.6659514453958333 vec: [31.000, 15.000, 1.000, 49.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 7.555077762670502 vec: [30.000, 13.000, 2.000, 44.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 1.1131936040060575 vec: [34.000, 15.000, 2.000, 51.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 1.9181240835774944 vec: [35.000, 13.000, 3.000, 50.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 12.39351443296044 vec: [23.000, 13.000, 3.000, 45.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 6.6602702647864795 vec: [32.000, 13.000, 2.000, 44.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 3.898615138738256 vec: [35.000, 16.000, 6.000, 50.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 6.076117181226863 vec: [38.000, 19.000, 4.000, 51.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.737003272111904 vec: [30.000, 14.000, 3.000, 48.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.185594342503789 vec: [38.000, 16.000, 2.000, 51.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.673242985336684 vec: [32.000, 14.000, 2.000, 46.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 4.113295515763298 vec: [37.000, 15.000, 2.000, 53.000, 1.000]
Key: 4: Value: wt: 1.0 distance: 1.413930691370691 vec: [33.000, 14.000, 2.000, 50.000, 1.000]
Key: 128: Value: wt: 1.0 distance: 12.27183013149531 vec: [32.000, 47.000, 14.000, 70.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 6.845135447338132 vec: [32.000, 45.000, 15.000, 64.000, 2.000]
Key: 100: Value: wt: 1.0 distance: 10.234304921679705 vec: [31.000, 49.000, 15.000, 69.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 7.318849411742204 vec: [23.000, 40.000, 13.000, 55.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 6.3893365248584155 vec: [28.000, 46.000, 15.000, 65.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 2.7032373546600645 vec: [28.000, 45.000, 13.000, 57.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 7.648597295107581 vec: [33.000, 47.000, 16.000, 63.000, 2.000]
Key: 128: Value: wt: 1.0 distance: 15.840467020307052 vec: [24.000, 33.000, 10.000, 49.000, 2.000]
: : : : 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
Key: 24: Value: wt: 1.0 distance: 861.9071668766143 vec: [14840.000, 15260.000, 5763.000, 3312.000, 2221.000, 5220.000, 871.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 1668.6900610565315 vec: [14570.000, 14880.000, 5554.000, 3333.000, 1018.000, 4956.000, 881.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 694.0022557455687 vec: [14090.000, 14290.000, 5291.000, 3337.000, 2699.000, 4825.000, 905.000, 1.000]
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Key: 177: Value: wt: 1.0 distance: 1525.05309032792 vec: [13840.000, 13220.000, 5395.000, 3070.000, 4157.000, 5088.000, 868.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 2603.1739906169455 vec: [13570.000, 12780.000, 5262.000, 3026.000, 1176.000, 4782.000, 872.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 2164.8100360288104 vec: [13500.000, 12880.000, 5139.000, 3119.000, 2352.000, 4607.000, 888.000, 1.000]
Key: 24: Value: wt: 1.0 distance: 1379.1305505369796 vec: [14370.000, 14340.000, 5630.000, 3190.000, 1313.000, 5150.000, 873.000, 1.000]
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 !
... View more
08-25-2016
09:51 PM
Hello Cloudera I have an update on my NAN problem I have discovered I can use mahout seqdumper to view the vectors written by the mahout arff.vector command to see whether or not it is actualy writing the vectors properly. I checked all three files: iris.arff.mvc, seeds.arff.mvc and balance.arff.mvc using mahout seqdumper. It turns out that in fact it was the mahout.arff.vector creating the NaN output which was transferred to my kmeans/canopy and clusterdump output; Here we can see my seqdumper output for my seeds and iris datasets and my balance scale dataset (which works okay) Masternode@Masterdatanode ~]$ mahout seqdumper -i /user/Masternode/seeds/seeds_data.arff.mvc > /tmp/seeds/dump.txt
16/08/26 01:52:49 WARN driver.MahoutDriver: No seqdumper.props found on classpath, will use command-line arguments only
16/08/26 01:52:50 INFO common.AbstractJob: Command line arguments: {--endPhase=[2147483647], --input=[/user/Masternode/seeds/seeds_data.arff.mvc], --startPhase=[0], --tempDir=[temp]}
16/08/26 01:52:53 INFO zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
16/08/26 01:52:53 INFO compress.CodecPool: Got brand-new decompressor [.deflate]
16/08/26 01:52:53 INFO driver.MahoutDriver: Program took 3827 ms (Minutes: 0.06378333333333333)
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MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
Running on hadoop, using /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/hadoop/bin/hadoop and HADOOP_CONF_DIR=/etc/hadoop/conf
MAHOUT-JOB: /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/mahout/mahout-examples-0.9-cdh5.6.0-job.jar
Input Path: /user/Masternode/seeds/seeds_data.arff.mvc
Key class: class org.apache.hadoop.io.LongWritable Value Class: class org.apache.mahout.math.VectorWritable
Key: 0: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:1.0}
Key: 1: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:1.0}
Key: 2: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:1.0}
Key: 3: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:1.0}
Key: 4: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:1.0}
: :
: :
Key: 205: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:3.0}
Key: 206: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:3.0}
Key: 207: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:3.0}
Key: 208: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:3.0}
Key: 209: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:3.0}
Count: 210
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[Masternode@Masterdatanode ~]$ mahout seqdumper -i /user/Masternode/iris_data/kmeans3/iris.arff.mvc > /tmp/iris_data/dump.txt
16/08/26 03:52:28 WARN driver.MahoutDriver: No seqdumper.props found on classpath, will use command-line arguments only
16/08/26 03:52:29 INFO common.AbstractJob: Command line arguments: {--endPhase=[2147483647], --input=[/user/Masternode/iris_data/kmeans3/iris.arff.mvc], --startPhase=[0], --tempDir=[temp]}
16/08/26 03:52:32 INFO zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
16/08/26 03:52:32 INFO compress.CodecPool: Got brand-new decompressor [.deflate]
16/08/26 03:52:32 INFO driver.MahoutDriver: Program took 3746 ms (Minutes: 0.062433333333333334)
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MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
Running on hadoop, using /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/hadoop/bin/hadoop and HADOOP_CONF_DIR=/etc/hadoop/conf
MAHOUT-JOB: /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/mahout/mahout-examples-0.9-cdh5.6.0-job.jar
Input Path: /user/Masternode/iris_data/kmeans3/iris.arff.mvc
Key class: class org.apache.hadoop.io.LongWritable Value Class: class org.apache.mahout.math.VectorWritable
Key: 0: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:1.0}
Key: 1: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:1.0}
Key: 2: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:1.0}
Key: 3: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:1.0}
Key: 4: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:1.0}
: :
: :
Key: 145: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:3.0}
Key: 146: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:3.0}
Key: 147: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:3.0}
Key: 148: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:3.0}
Key: 149: Value: {0:NaN,1:NaN,2:NaN,3:NaN,4:3.0}
Count: 150
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[Masternode@Masterdatanode ~]$ mahout seqdumper -i /user/Masternode/balance/balance.arff.mvc > /tmp/balance/dump.txt
16/08/26 01:58:33 WARN driver.MahoutDriver: No seqdumper.props found on classpath, will use command-line arguments only
16/08/26 01:58:34 INFO common.AbstractJob: Command line arguments: {--endPhase=[2147483647], --input=[/user/Masternode/balance/balance.arff.mvc], --startPhase=[0], --tempDir=[temp]}
16/08/26 01:58:37 INFO zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
16/08/26 01:58:37 INFO compress.CodecPool: Got brand-new decompressor [.deflate]
16/08/26 01:58:37 INFO driver.MahoutDriver: Program took 3889 ms (Minutes: 0.06481666666666666)
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxMAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
Running on hadoop, using /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/hadoop/bin/hadoop and HADOOP_CONF_DIR=/etc/hadoop/conf
MAHOUT-JOB: /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/mahout/mahout-examples-0.9-cdh5.6.0-job.jar
Input Path: /user/Masternode/balance/balance.arff.mvc
Key class: class org.apache.hadoop.io.LongWritable Value Class: class org.apache.mahout.math.VectorWritable
Key: 0: Value: {0:1.0,1:1.0,2:1.0,3:1.0,4:2.0}
Key: 1: Value: {0:1.0,1:1.0,2:1.0,3:2.0,4:3.0}
Key: 2: Value: {0:1.0,1:1.0,2:1.0,3:3.0,4:3.0}
Key: 3: Value: {0:1.0,1:1.0,2:1.0,3:4.0,4:3.0}
Key: 4: Value: {0:1.0,1:1.0,2:1.0,3:5.0,4:3.0}
: :
: :
Key: 620: Value: {0:5.0,1:5.0,2:5.0,3:1.0,4:1.0}
Key: 621: Value: {0:5.0,1:5.0,2:5.0,3:2.0,4:1.0}
Key: 622: Value: {0:5.0,1:5.0,2:5.0,3:3.0,4:1.0}
Key: 623: Value: {0:5.0,1:5.0,2:5.0,3:4.0,4:1.0}
Key: 624: Value: {0:5.0,1:5.0,2:5.0,3:5.0,4:2.0}
Count: 625
Here are the clusters for the balance scale dataset [Masternode@Masterdatanode ~]$ mahout clusterdump -i /user/Masternode/balance/kmeans-out/clusters-1-final -o /tmp/balance/balance_clusters.txt -p /user/Masternode/balance/kmeans-out/clusteredPoints -dm org.apache.mahout.common.distance.TanimotoDistanceMeasure
MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
Running on hadoop, using /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/hadoop/bin/hadoop and HADOOP_CONF_DIR=/etc/hadoop/conf
MAHOUT-JOB: /opt/cloudera/parcels/CDH-5.6.0-1.cdh5.6.0.p0.45/lib/mahout/mahout-examples-0.9-cdh5.6.0-job.jar
16/08/22 23:05:40 WARN driver.MahoutDriver: No clusterdump.props found on classpath, will use command-line arguments only
16/08/22 23:05:40 INFO common.AbstractJob: Command line arguments: {--dictionaryType=[text], --distanceMeasure=[org.apache.mahout.common.distance.TanimotoDistanceMeasure], --endPhase=[2147483647], --input=[/user/Masternode/balance/kmeans-out/clusters-1-final], --output=[/tmp/balance/balance_clusters.txt], --outputFormat=[TEXT], --pointsDir=[/user/Masternode/balance/kmeans-out/clusteredPoints], --startPhase=[0], --tempDir=[temp]}
16/08/22 23:05:44 INFO clustering.ClusterDumper: Wrote 3 clusters
16/08/22 23:05:44 INFO driver.MahoutDriver: Program took 4136 ms (Minutes: 0.06893333333333333)
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VL-410{n=213 c=[4.038, 2.131, 2.746, 2.446, 1.737] r=[0.968, 1.058, 1.361, 1.287, 0.917]}
Weight : [props - optional]: Point:
1.0 : [distance=0.39346254907223044]: [2.000, 1.000, 1.000, 1.000, 1.000]
1.0 : [distance=0.29099665375325723]: [2.000, 1.000, 1.000, 2.000, 2.000]
1.0 : [distance=0.2737469670505256]: [2.000, 1.000, 2.000, 1.000, 2.000]
1.0 : [distance=0.2602217061100983]: [2.000, 1.000, 3.000, 1.000, 3.000]
1.0 : [distance=0.2703429967956935]: [2.000, 1.000, 4.000, 1.000, 3.000]
: :
VL-82{n=275 c=[1.975, 3.033, 2.669, 3.676, 2.415] r=[1.011, 1.379, 1.344, 1.242, 0.875]}
Weight : [props - optional]: Point:
1.0 : [distance=0.4843955662442676]: [1.000, 1.000, 1.000, 1.000, 2.000]
1.0 : [distance=0.3310139832226746]: [1.000, 1.000, 1.000, 2.000, 3.000]
1.0 : [distance=0.25039239421781456]: [1.000, 1.000, 1.000, 3.000, 3.000]
1.0 : [distance=0.21916087567042697]: [1.000, 1.000, 1.000, 4.000, 3.000]
1.0 : [distance=0.23026798575608354]: [1.000, 1.000, 1.000, 5.000, 3.000]
: :
VL-370{n=140 c=[3.429, 4.271, 4.043, 2.486, 1.579] r=[1.283, 0.877, 1.095, 1.344, 0.854]}
Weight : [props - optional]: Point:
1.0 : [distance=0.291345734798266]: [1.000, 2.000, 5.000, 1.000, 3.000]
1.0 : [distance=0.22857469129979302]: [1.000, 3.000, 4.000, 1.000, 3.000]
1.0 : [distance=0.22469106732898325]: [1.000, 3.000, 5.000, 1.000, 3.000]
1.0 : [distance=0.18798153075739144]: [1.000, 3.000, 5.000, 2.000, 3.000]
1.0 : [distance=0.27974934890340164]: [1.000, 4.000, 2.000, 1.000, 1.000]
: : Further on inspecting my balance.arff dataset. I noticed that the file data were only integers seperated by commas ie @relation balance-scale
@attribute left-weight numeric
@attribute left-distance numeric
@attribute right-weight numeric
@attribute right-distance numeric
@attribute class { L, B, R}
@data
1,1,1,1,B
1,1,1,2,R
1,1,1,3,R
1,1,1,4,R
1,1,1,5,R
1,1,2,1,R
1,1,2,2,R
1,1,2,3,R
1,1,2,4,R
1,1,2,5,R
: : Whereas my other datasets had doubles and float values as the data ie for seeds.arff dataset and iris.arff datasets @relation seeds
@attribute area numeric
@attribute perimeter numeric
@attribute compactness numeric
@attribute kernel-length numeric
@attribute kernel-width numeric
@attribute asymmetry numeric
@attribute kernel-groove numeric
@attribute class { 1, 2, 3}
@data
15.26,14.84,0.871,5.763,3.312,2.221,5.22,1
14.88,14.57,0.8811,5.554,3.333,1.018,4.956,1
14.29,14.09,0.905,5.291,3.337,2.699,4.825,1
13.84,13.94,0.8955,5.324,3.379,2.259,4.805,1
16.14,14.99,0.9034,5.658,3.562,1.355,5.175,1
14.38,14.21,0.8951,5.386,3.312,2.462,4.956,1
14.69,14.49,0.8799,5.563,3.259,3.586,5.219,1
14.11,14.1,0.8911,5.42,3.302,2.7,5,1
16.63,15.46,0.8747,6.053,3.465,2.04,5.877,1
16.44,15.25,0.888,5.884,3.505,1.969,5.533,1
: :
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@RELATION iris
@ATTRIBUTE sepallength numeric
@ATTRIBUTE sepalwidth numeric
@ATTRIBUTE petallength numeric
@ATTRIBUTE petalwidth numeric
@ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica}
@DATA
5.1,3.5,1.4,0.2,Iris-setosa
4.9,3.0,1.4,0.2,Iris-setosa
4.7,3.2,1.3,0.2,Iris-setosa
4.6,3.1,1.5,0.2,Iris-setosa
5.0,3.6,1.4,0.2,Iris-setosa
5.4,3.9,1.7,0.4,Iris-setosa
4.6,3.4,1.4,0.3,Iris-setosa
5.0,3.4,1.5,0.2,Iris-setosa
4.4,2.9,1.4,0.2,Iris-setosa
4.9,3.1,1.5,0.1,Iris-setosa
: : So THIS is what is causing the problem for the mahout arff.vector command. It does not seem to like these double and float input data. Is there any solution to this ??????????????????? I am using Cloudera CDH5 Version 5.6.0-1.cdh5.6.0.p0.45 and Mahout Version 0.9+cdh5.6.0+26 ANY HELP MOST WELCOME !!!!!!!!!!!!!!!!!!!!!!!!!!
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Labels:
06-17-2016
09:05 AM
Thanks a lot you guys the problem is solved !!! I carried out a number of configuration changes including increasing the heap size as recommended, briefly 1 I realigned the "decalage horloge" which was about 2mins on my cluster 2 I increased the java heap pile from 256 to 512mb on the Host and Service monitor 3 I stopped a few unnecessary services on the cluster, ie HBase Hive Hue and Oozie I will explain the last step quickly One of the Cluster configuration problems is the surcharge on the memory of host CHILDNODE1. This host has 11 roles allocated to it which leads to health problems. Therefore I am to reallocate the roles among the hosts. Which was why I mentioned in my last post I am going to add a new host. To do just this The new 2 screenshots now show all health status reports working okay (the concerning health status comes primarily from the overloaded host CHILNODE1) Some final thoughts/questions on good housekeeping 1 Should I stop all services on a nightly basis when I retire and before I log off from Cloudera Manager. And restart them after I have logged onto Cloudera Manager ? This would have avoided the problems I encountered after my holiday. 2 One can run hadoop jobs with Cloudera Manager showing good or concerning health status but not bad health status. Is this so ? Thanks again
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06-08-2016
06:53 PM
Hi Everyone ! After leaving CM not used for a week during a holiday I returned to an unknown health status issue Everything was up and running fine before ! I have successfully got up and running a 3 node CDH Cluster with 4 go RAM in each and also 1 TB hard disc space for each (I am to add a fourth node soon) . Hostnames are Childnode1, Childnode2 and Masterdatanode. Masterdatanode has Cloudera Manager installed I have attached the screen shots of the CM UI's and the host and welcome pages (note they are in French) I often see in the health check explanations:Not enough data to test: Test to verify if a host has established contact with Cloudera Manager ie In French :Pas assez de données à tester : Test vérifiant si un hôte a établi un contact avec Cloudera Manager. As you can see from the screenshots all services are up and running I sometimes get the message on start up (When there are no charts and tables) " Internal error while querying the host monitor " But this goes away when I restart Cloudera Management services Cloudera Manager server and agents are okay the agents are heartbeating normally as you can see from the hosts page screenshot There must be something straight forward wrong as all icons show unknown health status (little question mark) Can someone offer some help ?
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11-21-2014
05:48 PM
Hello Cloudera, I have an installation problem with the latest version of cloudera manager 5.2.0 My CDH5 installation fails on trying to install the cloudera manager agent I have installed the latest rpm version of the cloudera manager agent on my red hat linux 6.6 yet during install it does not recognise it and keeps asking for it. To help I have found the same error in "CDH Users Japan". Here is the link https://groups.google.com/a/cloudera.org/forum/#!topic/cdh-user-jp/pGdGKHnYT0I Apparently it is an environnement problem. My red hat linux is installed with the french language and I live in France. Also my cloudera manager displays in french. However the cloudera website is all in English and the cloudera install and yum commands seem to be effected in English. This is why (according to my Japanese colleagues) cloudera manager does not recognise my installed cloudera manager agent (it is recorded and installed in french) Do you have any ideas on how to align my cloudera installation environment with my french red hat linux distribution ? If this is the problem. best wishes francesco Here is my cloudera log details /tmp/scm_prepare_node.0TCbcjrM using SSH_CLIENT to get the SCM hostname: 192.168.1.14 55021 22 opening logging file descriptor Démarrage du script d'installation… Acquisition du verrou d'installation… BEGIN flock 4 END (0) Détection des privilèges racine… effective UID is 0 Détection de la distribution… BEGIN grep Tikanga /etc/redhat-release END (1) BEGIN grep 'CentOS release 5' /etc/redhat-release END (1) BEGIN grep 'Scientific Linux release 5' /etc/redhat-release END (1) BEGIN grep Santiago /etc/redhat-release END (0) /etc/redhat-release ==> RHEL 6 Détection de Cloudera Manager Server… BEGIN host -t PTR 192.168.1.14 Red Hat Enterprise Linux Workstation release 6.6 (Santiago) END (1) Host 14.1.168.192.in-addr.arpa. not found: 3(NXDOMAIN) BEGIN which python END (0) BEGIN python -c 'import socket; import sys; s = socket.socket(socket.AF_INET); s.settimeout(5.0); s.connect((sys.argv[1], int(sys.argv[2]))); s.close();' 192.168.1.14 7182 /usr/bin/python END (0) BEGIN which wget END (0) /usr/bin/wget BEGIN wget -qO- -T 1 -t 1 http://169.254.169.254/latest/meta-data/public-hostname && /bin/echo END (4) Installation des référentiels de packages… validating format of repository file /tmp/scm_prepare_node.0TCbcjrM/repos/rhel6/cloudera-manager.repo installing repository file /tmp/scm_prepare_node.0TCbcjrM/repos/rhel6/cloudera-manager.repo repository file /tmp/scm_prepare_node.0TCbcjrM/repos/rhel6/cloudera-manager.repo installed Actualisation des métadonnées du package... BEGIN yum clean all Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager Nettoyage des dépôts : adobe-linux-x86_64 cloudera-manager : rhel-x86_64-workstation-6 Nettoyage complet END (0) BEGIN rm -Rf /var/cache/yum/x86_64 END (0) BEGIN yum makecache Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Cache des méta données créé END (0) Installation du package jdk… BEGIN yum list installed jdk Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés jdk.x86_64 2000:1.6.0_31-fcs @Cloudera-manager END (0) BEGIN echo jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons | grep jdk jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons END (0) BEGIN yum info jdk Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés Nom : jdk Architecture : x86_64 Date : 2000 Version : 1.6.0_31 Révision : fcs Taille : 143 M Dépôt : installed Depuis le dépôt : cloudera-manager Résumé : Java(TM) Platform Standard Edition Development Kit URL : http://java.sun.com/ Licence : Copyright (c) 2011, Oracle and/or its affiliates. All rights : reserved. Also under other license(s) as shown at the : Description field. Description : The Java Platform Standard Edition Development Kit (JDK) includes : both the runtime environment (Java virtual machine, the Java : platform classes and supporting files) and development tools : (compilers, debuggers, tool libraries and other tools). : : The JDK is a development environment for building applications, : applets and components that can be deployed with the Java Platform : Standard Edition Runtime Environment. END (0) BEGIN yum -y install jdk.x86_64 Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Configuration du processus d'installation Le paquet 2000:jdk-1.6.0_31-fcs.x86_64 est déjà installé dans sa dernière version Rien à faire END (0) remote package jdk installed Installation du package oracle-j2sdk1.7… BEGIN yum list installed oracle-j2sdk1.7 Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés oracle-j2sdk1.7.x86_64 1.7.0+update67-1 @Cloudera-manager END (0) BEGIN echo jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons | grep oracle-j2sdk1.7 jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons END (0) BEGIN yum info oracle-j2sdk1.7 Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés Nom : oracle-j2sdk1.7 Architecture : x86_64 Version : 1.7.0+update67 Révision : 1 Taille : 279 M Dépôt : installed Depuis le dépôt : cloudera-manager Résumé : no description given URL : http://example.com/no-uri-given Licence : unknown Description : no description given END (0) BEGIN yum -y install oracle-j2sdk1.7.x86_64 Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Configuration du processus d'installation Le paquet oracle-j2sdk1.7-1.7.0+update67-1.x86_64 est déjà installé dans sa dernière version Rien à faire END (0) remote package oracle-j2sdk1.7 installed Installation du package cloudera-manager-agent… BEGIN yum list installed cloudera-manager-agent Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés cloudera-manager-agent.x86_64 5.2.0-1.cm520.p0.60.el6 installed END (0) BEGIN echo jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons | grep cloudera-manager-agent END (0) jdk oracle-j2sdk1.7 cloudera-manager-agent cloudera-manager-daemons BEGIN yum info cloudera-manager-agent Modules complémentaires chargés : product-id, refresh-packagekit, rhnplugin, : security, subscription-manager This system is receiving updates from RHN Classic or RHN Satellite. Paquets installés Nom : cloudera-manager-agent Architecture : x86_64 Version : 5.2.0 Révision : 1.cm520.p0.60.el6 Taille : 27 M Dépôt : installed Résumé : The Cloudera Manager Agent URL : http://www.cloudera.com Licence : Proprietary Description : The Cloudera Manager Agent. : : The Agent is deployed to machines running services managed by : Cloudera Manager. END (0) Version : 5.2.0 cloudera-manager-agent must have Version=5.2.0 and Build=60, exiting closing logging file descriptor 1 2 3 4 5 6 apologies for the cross posting in getting started
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