krishna - 1 year ago 151

Scala Question

I need addition of two matrices that are stored in two files.

The content of

`latest1.txt`

`latest2.txt`

1 2 3

4 5 6

7 8 9

I am reading those files as follows:

`scala> val rows = sc.textFile(“latest1.txt”).map { line => val values = line.split(‘ ‘).map(_.toDouble)`

Vectors.sparse(values.length,values.zipWithIndex.map(e => (e._2, e._1)).filter(_._2 != 0.0))

}

scala> val r1 = rows

r1: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector] = MappedRDD[2] at map at :14

scala> val rows = sc.textFile(“latest2.txt”).map { line => val values = line.split(‘ ‘).map(_.toDouble)

Vectors.sparse(values.length,values.zipWithIndex.map(e => (e._2, e._1)).filter(_._2 != 0.0))

}

scala> val r2 = rows

r2: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector] = MappedRDD[2] at map at :14

I want to add r1, r2. So, Is there any way to add this two

`RDD[mllib.linalg.Vector]`

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Answer Source

This is actually a good question. I work with mllib regularly and did not realize these basic linear algebra operations are not easily accessible.

The point is that the underlying **breeze** vectors have all of the linear algebra manipulations you would expect - including of course basic element wise addition that you specifically mentioned.

However the breeze implementation is hidden from the outside world via:

```
[private mllib]
```

So then, from the outside world/public API perspective, how do we access those primitives?

Some of them are already exposed: e.g. sum of squares:

```
/**
* Returns the squared distance between two Vectors.
* @param v1 first Vector.
* @param v2 second Vector.
* @return squared distance between two Vectors.
*/
def sqdist(v1: Vector, v2: Vector): Double = {
...
}
```

However the selection of such available methods is limited - and in fact does *not* include the basic operations including element wise addition, subtraction, multiplication, etc.

So here is the best I could see:

- Convert the vectors to breeze:
- Perform the vector operations in breeze
- Convert back from breeze to mllib Vector

Here is some sample code:

```
val v1 = Vectors.dense(1.0, 2.0, 3.0)
val v2 = Vectors.dense(4.0, 5.0, 6.0)
val bv1 = new DenseVector(v1.toArray)
val bv2 = new DenseVector(v2.toArray)
val vectout = Vectors.dense((bv1 + bv2).toArray)
vectout: org.apache.spark.mllib.linalg.Vector = [5.0,7.0,9.0]
```

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