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author | wm624@hotmail.com <wm624@hotmail.com> | 2016-04-29 16:18:25 +0200 |
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committer | Nick Pentreath <nickp@za.ibm.com> | 2016-04-29 16:18:25 +0200 |
commit | b6fa7e5934ca5d1c3c757629833396b810894067 (patch) | |
tree | 9dd550f4367f3453fc06a2215913bb12251d8700 | |
parent | 6d5aeaae264579673bb75d32a8e4cd96aad9cf83 (diff) | |
download | spark-b6fa7e5934ca5d1c3c757629833396b810894067.tar.gz spark-b6fa7e5934ca5d1c3c757629833396b810894067.tar.bz2 spark-b6fa7e5934ca5d1c3c757629833396b810894067.zip |
[SPARK-14571][ML] Log instrumentation in ALS
## What changes were proposed in this pull request?
Add log instrumentation for parameters:
rank, numUserBlocks, numItemBlocks, implicitPrefs, alpha,
userCol, itemCol, ratingCol, predictionCol, maxIter,
regParam, nonnegative, checkpointInterval, seed
Add log instrumentation for numUserFeatures and numItemFeatures
## How was this patch tested?
Manual test: Set breakpoint in intellij and run def testALS(). Single step debugging and check the log method is called.
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes #12560 from wangmiao1981/log.
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala | 5 | ||||
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/util/Instrumentation.scala | 7 |
2 files changed, 12 insertions, 0 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala index 6e4e6a6d85..cbcbfe8249 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala @@ -395,6 +395,10 @@ class ALS(@Since("1.4.0") override val uid: String) extends Estimator[ALSModel] .map { row => Rating(row.getInt(0), row.getInt(1), row.getFloat(2)) } + val instrLog = Instrumentation.create(this, ratings) + instrLog.logParams(rank, numUserBlocks, numItemBlocks, implicitPrefs, alpha, + userCol, itemCol, ratingCol, predictionCol, maxIter, + regParam, nonnegative, checkpointInterval, seed) val (userFactors, itemFactors) = ALS.train(ratings, rank = $(rank), numUserBlocks = $(numUserBlocks), numItemBlocks = $(numItemBlocks), maxIter = $(maxIter), regParam = $(regParam), implicitPrefs = $(implicitPrefs), @@ -403,6 +407,7 @@ class ALS(@Since("1.4.0") override val uid: String) extends Estimator[ALSModel] val userDF = userFactors.toDF("id", "features") val itemDF = itemFactors.toDF("id", "features") val model = new ALSModel(uid, $(rank), userDF, itemDF).setParent(this) + instrLog.logSuccess(model) copyValues(model) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/Instrumentation.scala b/mllib/src/main/scala/org/apache/spark/ml/util/Instrumentation.scala index 869104e090..71a626647a 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/util/Instrumentation.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/util/Instrumentation.scala @@ -85,6 +85,13 @@ private[spark] class Instrumentation[E <: Estimator[_]] private ( } /** + * Logs the value with customized name field. + */ + def logNamedValue(name: String, num: Long): Unit = { + log(compact(render(name -> num))) + } + + /** * Logs the successful completion of the training session and the value of the learned model. */ def logSuccess(model: Model[_]): Unit = { |