Operations on a Distributed Block Matrix in scala spark
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I am forming a distributed block matrix from an indexed row matrix by controlling the size of the blocks formed.
var populationSize = 1000000
var chromosomeLength = 4
var mutationRate = 0.05
var mutationNumber = 1000000*(mutationRate)
var populationMatrix = new IndexedRowMatrix(
RandomRDDs.uniformVectorRDD(sc, populationSize, chromosomeLength).zipWithIndex.map {case (v, i) => IndexedRow(i, v)}
)
var mutationBlockMatrix = populationMatrix.toBlockMatrix(mutationNumber.toInt,chromosomeLength)
Now only one random row from these distributed blocks needs to be selected in a distributed manner and then collected into moved into another distributed matrix
var s = mutationBlockMatrix.colsPerBlock
var r = mutationBlockMatrix.rowsPerBlock
var t = mutationBlockMatrix.numRowBlocks
var w = mutationBlockMatrix.blocks.toDF
s: Int = 4
r: Int = 50000
t: Int = 20
w: org.apache.spark.sql.DataFrame = [_1: struct<_1: int, _2: int>, _2: matrix]
In this for example - 'w' is and RDD of block matrices of dimensions (4,20) in this example and there are 50000 such matrices. My goal is to randomly select a row of 4 out 20 for each 'w' and create a new distributed block matrix having 50000 block matrices of dimensions(4,1) . This has to be a distributed function hopefully .
scala apache-spark
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
add a comment |
I am forming a distributed block matrix from an indexed row matrix by controlling the size of the blocks formed.
var populationSize = 1000000
var chromosomeLength = 4
var mutationRate = 0.05
var mutationNumber = 1000000*(mutationRate)
var populationMatrix = new IndexedRowMatrix(
RandomRDDs.uniformVectorRDD(sc, populationSize, chromosomeLength).zipWithIndex.map {case (v, i) => IndexedRow(i, v)}
)
var mutationBlockMatrix = populationMatrix.toBlockMatrix(mutationNumber.toInt,chromosomeLength)
Now only one random row from these distributed blocks needs to be selected in a distributed manner and then collected into moved into another distributed matrix
var s = mutationBlockMatrix.colsPerBlock
var r = mutationBlockMatrix.rowsPerBlock
var t = mutationBlockMatrix.numRowBlocks
var w = mutationBlockMatrix.blocks.toDF
s: Int = 4
r: Int = 50000
t: Int = 20
w: org.apache.spark.sql.DataFrame = [_1: struct<_1: int, _2: int>, _2: matrix]
In this for example - 'w' is and RDD of block matrices of dimensions (4,20) in this example and there are 50000 such matrices. My goal is to randomly select a row of 4 out 20 for each 'w' and create a new distributed block matrix having 50000 block matrices of dimensions(4,1) . This has to be a distributed function hopefully .
scala apache-spark
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
add a comment |
I am forming a distributed block matrix from an indexed row matrix by controlling the size of the blocks formed.
var populationSize = 1000000
var chromosomeLength = 4
var mutationRate = 0.05
var mutationNumber = 1000000*(mutationRate)
var populationMatrix = new IndexedRowMatrix(
RandomRDDs.uniformVectorRDD(sc, populationSize, chromosomeLength).zipWithIndex.map {case (v, i) => IndexedRow(i, v)}
)
var mutationBlockMatrix = populationMatrix.toBlockMatrix(mutationNumber.toInt,chromosomeLength)
Now only one random row from these distributed blocks needs to be selected in a distributed manner and then collected into moved into another distributed matrix
var s = mutationBlockMatrix.colsPerBlock
var r = mutationBlockMatrix.rowsPerBlock
var t = mutationBlockMatrix.numRowBlocks
var w = mutationBlockMatrix.blocks.toDF
s: Int = 4
r: Int = 50000
t: Int = 20
w: org.apache.spark.sql.DataFrame = [_1: struct<_1: int, _2: int>, _2: matrix]
In this for example - 'w' is and RDD of block matrices of dimensions (4,20) in this example and there are 50000 such matrices. My goal is to randomly select a row of 4 out 20 for each 'w' and create a new distributed block matrix having 50000 block matrices of dimensions(4,1) . This has to be a distributed function hopefully .
scala apache-spark
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
I am forming a distributed block matrix from an indexed row matrix by controlling the size of the blocks formed.
var populationSize = 1000000
var chromosomeLength = 4
var mutationRate = 0.05
var mutationNumber = 1000000*(mutationRate)
var populationMatrix = new IndexedRowMatrix(
RandomRDDs.uniformVectorRDD(sc, populationSize, chromosomeLength).zipWithIndex.map {case (v, i) => IndexedRow(i, v)}
)
var mutationBlockMatrix = populationMatrix.toBlockMatrix(mutationNumber.toInt,chromosomeLength)
Now only one random row from these distributed blocks needs to be selected in a distributed manner and then collected into moved into another distributed matrix
var s = mutationBlockMatrix.colsPerBlock
var r = mutationBlockMatrix.rowsPerBlock
var t = mutationBlockMatrix.numRowBlocks
var w = mutationBlockMatrix.blocks.toDF
s: Int = 4
r: Int = 50000
t: Int = 20
w: org.apache.spark.sql.DataFrame = [_1: struct<_1: int, _2: int>, _2: matrix]
In this for example - 'w' is and RDD of block matrices of dimensions (4,20) in this example and there are 50000 such matrices. My goal is to randomly select a row of 4 out 20 for each 'w' and create a new distributed block matrix having 50000 block matrices of dimensions(4,1) . This has to be a distributed function hopefully .
scala apache-spark
scala apache-spark
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
asked Nov 16 '18 at 13:03
LeothornLeothorn
4221926
4221926
add a comment |
add a comment |
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