Hi There,
Using spark-mllib_2.11-2.1.0. Facing issue that
BucketedRandomProjectionLSHModel.approxNearestNeighbors returns one result,
always.
Dataset looks like:
+----+--------------------+-------------+------------------------+----------------------+
| id|
features|kmeansCluster|predictionVectorFeatures|featuresInNewDimension|
+----+--------------------+-------------+------------------------+----------------------+
|1045|(16384,[196,11016...| 0| (16384,[196],[0.2...| [[0.0],
[0.0], [0...|
|1041|(16384,[4110,1065...| 0| (16384,[196],[0.2...| [[0.0],
[0.0], [-...|
+----+--------------------+-------------+------------------------+----------------------+
Execution code:
Dataset<Row> approximatedDS = (Dataset<Row>)
((BucketedRandomProjectionLSHModel)model)
.approxNearestNeighbors(dataset,
vectorToCalculateAgainst, numberOfResults,
false, MLFlowConstants.THEMES_PREDICTION_COLUMNS.distance.name());
Where:
numberOfResults = 2
vectorToCalculateAgainst = first vector in predictionVectorFeatures column
approximatedDS looks like follows:
+----+--------------------+-------------+------------------------+----------------------+------------------+
| id|
features|kmeansCluster|predictionVectorFeatures|featuresInNewDimension|
distance|
+----+--------------------+-------------+------------------------+----------------------+------------------+
|1061|(16384,[196,11016...| 1| (16384,[196],[0.2...| [[0.0],
[0.0], [0...|0.8536603178950374|
+----+--------------------+-------------+------------------------+----------------------+------------------+
I have suspicion, that in LSH.scala
// Compute threshold to get exact k elements.
// TODO: SPARK-18409: Use approxQuantile to get the threshold
val modelDatasetSortedByHash =
modelDataset.sort(hashDistCol).limit(numNearestNeighbors)
val thresholdDataset = modelDatasetSortedByHash.select(max(hashDistCol))
val hashThreshold = thresholdDataset.take(1).head.getDouble(0)
// Filter the dataset where the hash value is less than the threshold.
modelDataset.filter(hashDistCol <= hashThreshold)
}
last filter does wrong filtering, but may be wrong (do not know scala).
Can anyone help me understand how to make
BucketedRandomProjectionLSHModel.approxNearestNeighbors to return multiple
"nearest" vectors?
Thanks,
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/BucketedRandomProjectionLSHModel-algorithm-details-tp28578.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.
---------------------------------------------------------------------
To unsubscribe e-mail: user-unsubscr...@spark.apache.org
