Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/15874#discussion_r87922281
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala ---
@@ -179,16 +211,13 @@ private[ml] abstract class LSHModel[T <: LSHModel[T]]
inputName: String,
explodeCols: Seq[String]): Dataset[_] = {
require(explodeCols.size == 2, "explodeCols must be two strings.")
- val vectorToMap = udf((x: Vector) => x.asBreeze.iterator.toMap,
- MapType(DataTypes.IntegerType, DataTypes.DoubleType))
val modelDataset: DataFrame = if
(!dataset.columns.contains($(outputCol))) {
transform(dataset)
} else {
dataset.toDF()
}
modelDataset.select(
- struct(col("*")).as(inputName),
- explode(vectorToMap(col($(outputCol)))).as(explodeCols))
+ struct(col("*")).as(inputName),
posexplode(col($(outputCol))).as(explodeCols))
--- End diff --
Well here's a fun one. When I run this test:
````scala
test("memory leak test") {
val numDim = 50
val data = {
for (i <- 0 until numDim; j <- Seq(-2, -1, 1, 2))
yield Vectors.sparse(numDim, Seq((i, j.toDouble)))
}
val df = spark.createDataFrame(data.map(Tuple1.apply)).toDF("keys")
// Project from 100 dimensional Euclidean Space to 10 dimensions
val brp = new BucketedRandomProjectionLSH()
.setNumHashTables(10)
.setInputCol("keys")
.setOutputCol("values")
.setBucketLength(2.5)
.setSeed(12345)
val model = brp.fit(df)
val joined = model.approxSimilarityJoin(df, df, Double.MaxValue,
"distCol")
joined.show()
}
````
I get the following error:
````
[info] - BucketedRandomProjectionLSH with high dimension data: test of LSH
property *** FAILED *** (7 seconds, 568 milliseconds)
[info] org.apache.spark.SparkException: Job aborted due to stage failure:
Task 0 in stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage
4.0 (TID 205, localhost, executor driver): org.apache.spark.SparkException:
Managed memory leak detected; size = 33816576 bytes, TID = 205
[info] at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:295)
[info] at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
[info] at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
[info] at java.lang.Thread.run(Thread.java:745)
````
Could you run the same test and see if you get an error?
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