See <https://builds.apache.org/job/Mahout-Quality/2902/>
------------------------------------------
[...truncated 6224 lines...]
{
0 => {0:0.3947476722883563,1:-0.08695028358267716,2:-1.0574297632219802}
1 => {0:0.4076559804271818,1:0.013563509240543453,2:-0.6050700722864573}
2 => {0:0.15935325307337903,1:0.07468219465060774,2:-0.37963073350622206}
}
ALS factorized approximation block:
{
0 => {0:0.3947518179224231,1:-0.08695389395155544,2:-1.0574494478839265}
1 => {0:0.4076399435035176,1:0.013566854170126305,2:-0.6050777716454986}
2 => {0:0.15934618500050707,1:0.0746779194686282,2:-0.3796636071626735}
}
norm of residuals 0.009174
train iteration rmses: List(1.7992630164822844E-7, 1.308589600373296E-7,
1.1214324598457284E-7, 1.6832499777966416E-7)
[32m- dals[0m
[32mDrmLikeOpsSuite:[0m
{
0 => {0:2.0,1:3.0,2:4.0}
1 => {0:3.0,1:4.0,2:5.0}
2 => {0:4.0,1:5.0,2:6.0}
3 => {0:5.0,1:6.0,2:7.0}
}
[32m- mapBlock[0m
{
0 => {0:2.0,1:3.0}
1 => {0:3.0,1:4.0}
2 => {0:4.0,1:5.0}
3 => {0:5.0,1:6.0}
}
[32m- col range[0m
{
0 => {0:2.0,1:3.0,2:4.0}
1 => {0:3.0,1:4.0,2:5.0}
}
[32m- row range[0m
{
0 => {0:3.0,1:4.0}
1 => {0:4.0,1:5.0}
}
[32m- col, row range[0m
[32m- exact, min and auto ||[0m
[32mNBSparkTestSuite:[0m
[32m- Simple Standard NB Model[0m
[32m- NB Aggregator[0m
[32m- Model DFS Serialization[0m
[32m- Spark NB Aggregator[0m
[32mItemSimilarityDriverSuite:[0m
[32m- ItemSimilarityDriver, non-full-spec CSV[0m
[32m- ItemSimilarityDriver TSV [0m
[32m- ItemSimilarityDriver log-ish files[0m
[32m- ItemSimilarityDriver legacy supported file format[0m
[32m- ItemSimilarityDriver write search engine output[0m
[32m- ItemSimilarityDriver recursive file discovery using filename patterns[0m
[32m- ItemSimilarityDriver, two input paths[0m
[32m- ItemSimilarityDriver, two inputs of different dimensions[0m
[32m- ItemSimilarityDriver cross similarity two separate items spaces[0m
[32m- A.t %*% B after changing row cardinality of A[0m
[32m- Changing row cardinality of an IndexedDataset[0m
[32m- ItemSimilarityDriver cross similarity two separate items spaces, missing
rows in B[0m
[32mBlasSuite:[0m
AB' num partitions = 2.
{
2 => {0:50.0,1:74.0}
1 => {0:38.0,1:56.0}
0 => {0:26.0,1:38.0}
}
[32m- ABt[0m
[32m- A * B Hadamard[0m
[32m- A + B Elementwise[0m
[32m- A - B Elementwise[0m
[32m- A / B Elementwise[0m
{
0 => {0:5.0,1:8.0}
1 => {0:8.0,1:13.0}
}
{
0 => {0:5.0,1:8.0}
1 => {0:8.0,1:13.0}
}
[32m- AtA slim[0m
{
0 => {0:1.0,1:2.0,2:3.0}
1 => {0:2.0,1:3.0,2:4.0}
2 => {0:3.0,1:4.0,2:5.0}
}
[32m- At[0m
[32mSimilarityAnalysisSuite:[0m
[32m- cooccurrence [A'A], [B'A] boolbean data using LLR[0m
[32m- cooccurrence [A'A], [B'A] double data using LLR[0m
[32m- cooccurrence [A'A], [B'A] integer data using LLR[0m
[32m- cooccurrence two matrices with different number of columns[0m
[32m- LLR calc[0m
[32m- downsampling by number per row[0m
[32mClassifierStatsSparkTestSuite:[0m
[32m- testFullRunningAverageAndStdDev[0m
[32m- testBigFullRunningAverageAndStdDev[0m
[32m- testStddevFullRunningAverageAndStdDev[0m
[32m- testFullRunningAverage[0m
[32m- testFullRunningAveragCopyConstructor[0m
[32m- testInvertedRunningAverage[0m
[32m- testInvertedRunningAverageAndStdDev[0m
[32m- testBuild[0m
[32m- GetMatrix[0m
[32m- testPrecisionRecallAndF1ScoreAsScikitLearn[0m
[32mRLikeDrmOpsSuite:[0m
[32m- A.t[0m
{
1 => {0:25.0,1:39.0}
0 => {0:11.0,1:17.0}
}
{
1 => {0:25.0,1:39.0}
0 => {0:11.0,1:17.0}
}
[32m- C = A %*% B[0m
{
0 => {0:11.0,1:17.0}
1 => {0:25.0,1:39.0}
}
{
0 => {0:11.0,1:17.0}
1 => {0:25.0,1:39.0}
}
Q=
{
0 => {0:0.40273861426601687,1:-0.9153150324187648}
1 => {0:0.9153150324227656,1:0.40273861426427493}
}
[32m- C = A %*% B mapBlock {}[0m
[32m- C = A %*% B incompatible B keys[0m
[32m- Spark-specific C = At %*% B , join[0m
[32m- C = At %*% B , join, String-keyed[0m
[32m- C = At %*% B , zippable, String-keyed[0m
{
0 => {0:26.0,1:35.0,2:46.0,3:51.0}
1 => {0:50.0,1:69.0,2:92.0,3:105.0}
2 => {0:62.0,1:86.0,2:115.0,3:132.0}
3 => {0:74.0,1:103.0,2:138.0,3:159.0}
}
[32m- C = A %*% inCoreB[0m
{
0 => {0:26.0,1:35.0,2:46.0,3:51.0}
1 => {0:50.0,1:69.0,2:92.0,3:105.0}
2 => {0:62.0,1:86.0,2:115.0,3:132.0}
3 => {0:74.0,1:103.0,2:138.0,3:159.0}
}
[32m- C = inCoreA %*%: B[0m
[32m- C = A.t %*% A[0m
[32m- C = A.t %*% A fat non-graph[0m
[32m- C = A.t %*% A non-int key[0m
[32m- C = A + B[0m
A=
{
0 => {0:1.0,1:2.0,2:3.0}
1 => {0:3.0,1:4.0,2:5.0}
2 => {0:5.0,1:6.0,2:7.0}
}
B=
{
0 => {0:0.5799239258498389,1:0.8936674056690244,2:0.3700584922234772}
1 => {0:0.3827924027537619,1:0.09801722679791958,2:0.42511574075317704}
2 => {0:0.13981744558389098,1:0.4927503268540476,2:0.5192245301882639}
}
C=
{
0 => {0:1.579923925849839,1:2.8936674056690244,2:3.3700584922234773}
1 => {0:3.382792402753762,1:4.09801722679792,2:5.425115740753177}
2 => {0:5.1398174455838905,1:6.492750326854048,2:7.519224530188264}
}
[32m- C = A + B, identically partitioned[0m
[32m- C = A + B side test 1[0m
[32m- C = A + B side test 2[0m
[32m- C = A + B side test 3[0m
[32m- Ax[0m
[32m- A'x[0m
[32m- colSums, colMeans[0m
[32m- rowSums, rowMeans[0m
[32m- A.diagv[0m
[32m- numNonZeroElementsPerColumn[0m
[32m- C = A cbind B, cogroup[0m
[32m- C = A cbind B, zip[0m
[32m- B = A + 1.0[0m
[32m- C = A rbind B[0m
[32m- C = A rbind B, with empty[0m
[32m- scalarOps[0m
[32m- C = A + B missing rows[0m
[32m- C = cbind(A, B) with missing rows[0m
collected A =
{
0 => {0:1.0,1:2.0,2:3.0}
1 => {}
2 => {}
3 => {0:3.0,1:4.0,2:5.0}
}
collected B =
{
2 => {0:1.0,1:1.0,2:1.0}
1 => {0:1.0,1:1.0,2:1.0}
3 => {0:4.0,1:5.0,2:6.0}
0 => {0:2.0,1:3.0,2:4.0}
}
[32m- B = A + 1.0 missing rows[0m
[36mRun completed in 1 minute, 43 seconds.[0m
[36mTotal number of tests run: 89[0m
[36mSuites: completed 12, aborted 0[0m
[36mTests: succeeded 88, failed 1, canceled 0, ignored 1, pending 0[0m
[31m*** 1 TEST FAILED ***[0m
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary:
[INFO]
[INFO] Mahout Build Tools ................................ SUCCESS [4.340s]
[INFO] Apache Mahout ..................................... SUCCESS [1.863s]
[INFO] Mahout Math ....................................... SUCCESS [2:13.562s]
[INFO] Mahout MapReduce Legacy ........................... SUCCESS [11:03.363s]
[INFO] Mahout Integration ................................ SUCCESS [1:23.162s]
[INFO] Mahout Examples ................................... SUCCESS [51.386s]
[INFO] Mahout Release Package ............................ SUCCESS [0.132s]
[INFO] Mahout Math Scala bindings ........................ SUCCESS [2:08.375s]
[INFO] Mahout Spark bindings ............................. FAILURE [2:26.561s]
[INFO] Mahout Spark bindings shell ....................... SKIPPED
[INFO] Mahout H2O backend ................................ SKIPPED
[INFO] ------------------------------------------------------------------------
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 20:14.795s
[INFO] Finished at: Sat Dec 20 17:34:22 UTC 2014
[INFO] Final Memory: 81M/455M
[INFO] ------------------------------------------------------------------------
[ERROR] Failed to execute goal org.scalatest:scalatest-maven-plugin:1.0-M2:test
(test) on project mahout-spark_2.10: There are test failures -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e
switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please
read the following articles:
[ERROR] [Help 1]
http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException
[ERROR]
[ERROR] After correcting the problems, you can resume the build with the command
[ERROR] mvn <goals> -rf :mahout-spark_2.10
Build step 'Invoke top-level Maven targets' marked build as failure
[PMD] Skipping publisher since build result is FAILURE
[TASKS] Skipping publisher since build result is FAILURE
Archiving artifacts
Sending artifact delta relative to Mahout-Quality #2901
Archived 72 artifacts
Archive block size is 32768
Received 3435 blocks and 27071335 bytes
Compression is 80.6%
Took 18 sec
Recording test results
Publishing Javadoc
