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Commit 38605206 authored by Mike Dusenberry's avatar Mike Dusenberry Committed by Xiangrui Meng
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[SPARK-7744] [DOCS] [MLLIB] Distributed matrix" section in MLlib "Data Types"... 

[SPARK-7744] [DOCS] [MLLIB] Distributed matrix" section in MLlib "Data Types" documentation should be reordered.

The documentation for BlockMatrix should come after RowMatrix, IndexedRowMatrix, and CoordinateMatrix, as BlockMatrix references the later three types, and RowMatrix is considered the "basic" distributed matrix.  This will improve comprehensibility of the "Distributed matrix" section, especially for the new reader.

Author: Mike Dusenberry <dusenberrymw@gmail.com>

Closes #6270 from dusenberrymw/Reorder_MLlib_Data_Types_Distributed_matrix_docs and squashes the following commits:

6313bab [Mike Dusenberry] The documentation for BlockMatrix should come after RowMatrix, IndexedRowMatrix, and CoordinateMatrix, as BlockMatrix references the later three types, and RowMatrix is considered the "basic" distributed matrix.  This will improve comprehensibility of the "Distributed matrix" section, especially for the new reader.
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......@@ -296,70 +296,6 @@ backed by an RDD of its entries.
The underlying RDDs of a distributed matrix must be deterministic, because we cache the matrix size.
In general the use of non-deterministic RDDs can lead to errors.
### BlockMatrix
A `BlockMatrix` is a distributed matrix backed by an RDD of `MatrixBlock`s, where a `MatrixBlock` is
a tuple of `((Int, Int), Matrix)`, where the `(Int, Int)` is the index of the block, and `Matrix` is
the sub-matrix at the given index with size `rowsPerBlock` x `colsPerBlock`.
`BlockMatrix` supports methods such as `add` and `multiply` with another `BlockMatrix`.
`BlockMatrix` also has a helper function `validate` which can be used to check whether the
`BlockMatrix` is set up properly.
<div class="codetabs">
<div data-lang="scala" markdown="1">
A [`BlockMatrix`](api/scala/index.html#org.apache.spark.mllib.linalg.distributed.BlockMatrix) can be
most easily created from an `IndexedRowMatrix` or `CoordinateMatrix` by calling `toBlockMatrix`.
`toBlockMatrix` creates blocks of size 1024 x 1024 by default.
Users may change the block size by supplying the values through `toBlockMatrix(rowsPerBlock, colsPerBlock)`.
{% highlight scala %}
import org.apache.spark.mllib.linalg.distributed.{BlockMatrix, CoordinateMatrix, MatrixEntry}
val entries: RDD[MatrixEntry] = ... // an RDD of (i, j, v) matrix entries
// Create a CoordinateMatrix from an RDD[MatrixEntry].
val coordMat: CoordinateMatrix = new CoordinateMatrix(entries)
// Transform the CoordinateMatrix to a BlockMatrix
val matA: BlockMatrix = coordMat.toBlockMatrix().cache()
// Validate whether the BlockMatrix is set up properly. Throws an Exception when it is not valid.
// Nothing happens if it is valid.
matA.validate()
// Calculate A^T A.
val ata = matA.transpose.multiply(matA)
{% endhighlight %}
</div>
<div data-lang="java" markdown="1">
A [`BlockMatrix`](api/java/org/apache/spark/mllib/linalg/distributed/BlockMatrix.html) can be
most easily created from an `IndexedRowMatrix` or `CoordinateMatrix` by calling `toBlockMatrix`.
`toBlockMatrix` creates blocks of size 1024 x 1024 by default.
Users may change the block size by supplying the values through `toBlockMatrix(rowsPerBlock, colsPerBlock)`.
{% highlight java %}
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.mllib.linalg.distributed.BlockMatrix;
import org.apache.spark.mllib.linalg.distributed.CoordinateMatrix;
import org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix;
JavaRDD<MatrixEntry> entries = ... // a JavaRDD of (i, j, v) Matrix Entries
// Create a CoordinateMatrix from a JavaRDD<MatrixEntry>.
CoordinateMatrix coordMat = new CoordinateMatrix(entries.rdd());
// Transform the CoordinateMatrix to a BlockMatrix
BlockMatrix matA = coordMat.toBlockMatrix().cache();
// Validate whether the BlockMatrix is set up properly. Throws an Exception when it is not valid.
// Nothing happens if it is valid.
matA.validate();
// Calculate A^T A.
BlockMatrix ata = matA.transpose().multiply(matA);
{% endhighlight %}
</div>
</div>
### RowMatrix
A `RowMatrix` is a row-oriented distributed matrix without meaningful row indices, backed by an RDD
......@@ -530,3 +466,67 @@ IndexedRowMatrix indexedRowMatrix = mat.toIndexedRowMatrix();
{% endhighlight %}
</div>
</div>
### BlockMatrix
A `BlockMatrix` is a distributed matrix backed by an RDD of `MatrixBlock`s, where a `MatrixBlock` is
a tuple of `((Int, Int), Matrix)`, where the `(Int, Int)` is the index of the block, and `Matrix` is
the sub-matrix at the given index with size `rowsPerBlock` x `colsPerBlock`.
`BlockMatrix` supports methods such as `add` and `multiply` with another `BlockMatrix`.
`BlockMatrix` also has a helper function `validate` which can be used to check whether the
`BlockMatrix` is set up properly.
<div class="codetabs">
<div data-lang="scala" markdown="1">
A [`BlockMatrix`](api/scala/index.html#org.apache.spark.mllib.linalg.distributed.BlockMatrix) can be
most easily created from an `IndexedRowMatrix` or `CoordinateMatrix` by calling `toBlockMatrix`.
`toBlockMatrix` creates blocks of size 1024 x 1024 by default.
Users may change the block size by supplying the values through `toBlockMatrix(rowsPerBlock, colsPerBlock)`.
{% highlight scala %}
import org.apache.spark.mllib.linalg.distributed.{BlockMatrix, CoordinateMatrix, MatrixEntry}
val entries: RDD[MatrixEntry] = ... // an RDD of (i, j, v) matrix entries
// Create a CoordinateMatrix from an RDD[MatrixEntry].
val coordMat: CoordinateMatrix = new CoordinateMatrix(entries)
// Transform the CoordinateMatrix to a BlockMatrix
val matA: BlockMatrix = coordMat.toBlockMatrix().cache()
// Validate whether the BlockMatrix is set up properly. Throws an Exception when it is not valid.
// Nothing happens if it is valid.
matA.validate()
// Calculate A^T A.
val ata = matA.transpose.multiply(matA)
{% endhighlight %}
</div>
<div data-lang="java" markdown="1">
A [`BlockMatrix`](api/java/org/apache/spark/mllib/linalg/distributed/BlockMatrix.html) can be
most easily created from an `IndexedRowMatrix` or `CoordinateMatrix` by calling `toBlockMatrix`.
`toBlockMatrix` creates blocks of size 1024 x 1024 by default.
Users may change the block size by supplying the values through `toBlockMatrix(rowsPerBlock, colsPerBlock)`.
{% highlight java %}
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.mllib.linalg.distributed.BlockMatrix;
import org.apache.spark.mllib.linalg.distributed.CoordinateMatrix;
import org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix;
JavaRDD<MatrixEntry> entries = ... // a JavaRDD of (i, j, v) Matrix Entries
// Create a CoordinateMatrix from a JavaRDD<MatrixEntry>.
CoordinateMatrix coordMat = new CoordinateMatrix(entries.rdd());
// Transform the CoordinateMatrix to a BlockMatrix
BlockMatrix matA = coordMat.toBlockMatrix().cache();
// Validate whether the BlockMatrix is set up properly. Throws an Exception when it is not valid.
// Nothing happens if it is valid.
matA.validate();
// Calculate A^T A.
BlockMatrix ata = matA.transpose().multiply(matA);
{% endhighlight %}
</div>
</div>
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