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author | Xiangrui Meng <meng@databricks.com> | 2014-08-19 22:05:29 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2014-08-19 22:05:29 -0700 |
commit | fce5c0fb6384f3a142a4155525a5d62640725150 (patch) | |
tree | 588a1cccbc995bcba1508442ce40b3f7e094dc82 /mllib | |
parent | 068b6fe6a10eb1c6b2102d88832203267f030e85 (diff) | |
download | spark-fce5c0fb6384f3a142a4155525a5d62640725150.tar.gz spark-fce5c0fb6384f3a142a4155525a5d62640725150.tar.bz2 spark-fce5c0fb6384f3a142a4155525a5d62640725150.zip |
[HOTFIX][Streaming][MLlib] use temp folder for checkpoint
or Jenkins will complain about no Apache header in checkpoint files. tdas rxin
Author: Xiangrui Meng <meng@databricks.com>
Closes #2046 from mengxr/tmp-checkpoint and squashes the following commits:
0d3ec73 [Xiangrui Meng] remove ssc.stop
9797843 [Xiangrui Meng] change checkpointDir to lazy val
89964ab [Xiangrui Meng] use temp folder for checkpoint
Diffstat (limited to 'mllib')
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala | 6 |
1 files changed, 0 insertions, 6 deletions
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala index 28489410f8..03b71301e9 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala @@ -49,7 +49,6 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // Test if we can accurately learn Y = 10*X1 + 10*X2 on streaming data test("parameter accuracy") { - // create model val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(0.0, 0.0)) @@ -82,7 +81,6 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // Test that parameter estimates improve when learning Y = 10*X1 on streaming data test("parameter convergence") { - // create model val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(0.0)) @@ -113,12 +111,10 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { assert(deltas.forall(x => (x._1 - x._2) <= 0.1)) // check that error shrunk on at least 2 batches assert(deltas.map(x => if ((x._1 - x._2) < 0) 1 else 0).sum > 1) - } // Test predictions on a stream test("predictions") { - // create model initialized with true weights val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(10.0, 10.0)) @@ -142,7 +138,5 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // compute the mean absolute error and check that it's always less than 0.1 val errors = output.map(batch => batch.map(p => math.abs(p._1 - p._2)).sum / nPoints) assert(errors.forall(x => x <= 0.1)) - } - } |