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[SPARK-11497] [MLlib] [Python] PySpark RowMatrix Constructor Has Type Erasure Issue #9458
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Test build #44992 has finished for PR 9458 at commit
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@mengxr This PR is ready for review and discussion. |
Note: The following reproduces this issue on the latest Git head, 1.5.1, and 1.5.0: from pyspark.mllib.linalg.distributed import RowMatrix
rows = sc.parallelize([[3, -6], [4, -8], [0, 1]])
mat = RowMatrix(rows)
mat._java_matrix_wrapper.call("tallSkinnyQR", True) Should result in the following exception:
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Sorry for the long delay! I looked through the discussions, and this LGTM. I'll run tests once before merging it. |
Test build #2207 has finished for PR 9458 at commit
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Merged with master, branch-1.6 and branch-1.5 |
…rasure Issue As noted in PR #9441, implementing `tallSkinnyQR` uncovered a bug with our PySpark `RowMatrix` constructor. As discussed on the dev list [here](http://apache-spark-developers-list.1001551.n3.nabble.com/K-Means-And-Class-Tags-td10038.html), there appears to be an issue with type erasure with RDDs coming from Java, and by extension from PySpark. Although we are attempting to construct a `RowMatrix` from an `RDD[Vector]` in [PythonMLlibAPI](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala#L1115), the `Vector` type is erased, resulting in an `RDD[Object]`. Thus, when calling Scala's `tallSkinnyQR` from PySpark, we get a Java `ClassCastException` in which an `Object` cannot be cast to a Spark `Vector`. As noted in the aforementioned dev list thread, this issue was also encountered with `DecisionTrees`, and the fix involved an explicit `retag` of the RDD with a `Vector` type. `IndexedRowMatrix` and `CoordinateMatrix` do not appear to have this issue likely due to their related helper functions in `PythonMLlibAPI` creating the RDDs explicitly from DataFrames with pattern matching, thus preserving the types. This PR currently contains that retagging fix applied to the `createRowMatrix` helper function in `PythonMLlibAPI`. This PR blocks #9441, so once this is merged, the other can be rebased. cc holdenk Author: Mike Dusenberry <[email protected]> Closes #9458 from dusenberrymw/SPARK-11497_PySpark_RowMatrix_Constructor_Has_Type_Erasure_Issue. (cherry picked from commit 1b82203) Signed-off-by: Joseph K. Bradley <[email protected]>
…rasure Issue As noted in PR #9441, implementing `tallSkinnyQR` uncovered a bug with our PySpark `RowMatrix` constructor. As discussed on the dev list [here](http://apache-spark-developers-list.1001551.n3.nabble.com/K-Means-And-Class-Tags-td10038.html), there appears to be an issue with type erasure with RDDs coming from Java, and by extension from PySpark. Although we are attempting to construct a `RowMatrix` from an `RDD[Vector]` in [PythonMLlibAPI](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala#L1115), the `Vector` type is erased, resulting in an `RDD[Object]`. Thus, when calling Scala's `tallSkinnyQR` from PySpark, we get a Java `ClassCastException` in which an `Object` cannot be cast to a Spark `Vector`. As noted in the aforementioned dev list thread, this issue was also encountered with `DecisionTrees`, and the fix involved an explicit `retag` of the RDD with a `Vector` type. `IndexedRowMatrix` and `CoordinateMatrix` do not appear to have this issue likely due to their related helper functions in `PythonMLlibAPI` creating the RDDs explicitly from DataFrames with pattern matching, thus preserving the types. This PR currently contains that retagging fix applied to the `createRowMatrix` helper function in `PythonMLlibAPI`. This PR blocks #9441, so once this is merged, the other can be rebased. cc holdenk Author: Mike Dusenberry <[email protected]> Closes #9458 from dusenberrymw/SPARK-11497_PySpark_RowMatrix_Constructor_Has_Type_Erasure_Issue. (cherry picked from commit 1b82203) Signed-off-by: Joseph K. Bradley <[email protected]>
Great, thanks @jkbradley! |
As noted in PR #9441, implementing
tallSkinnyQR
uncovered a bug with our PySparkRowMatrix
constructor. As discussed on the dev list here, there appears to be an issue with type erasure with RDDs coming from Java, and by extension from PySpark. Although we are attempting to construct aRowMatrix
from anRDD[Vector]
in PythonMLlibAPI, theVector
type is erased, resulting in anRDD[Object]
. Thus, when calling Scala'stallSkinnyQR
from PySpark, we get a JavaClassCastException
in which anObject
cannot be cast to a SparkVector
. As noted in the aforementioned dev list thread, this issue was also encountered withDecisionTrees
, and the fix involved an explicitretag
of the RDD with aVector
type.IndexedRowMatrix
andCoordinateMatrix
do not appear to have this issue likely due to their related helper functions inPythonMLlibAPI
creating the RDDs explicitly from DataFrames with pattern matching, thus preserving the types.This PR currently contains that retagging fix applied to the
createRowMatrix
helper function inPythonMLlibAPI
. This PR blocks #9441, so once this is merged, the other can be rebased.cc @holdenk