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[SPARK-8925] [MLlib] Add @since tags to mllib.util #7436

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[SPARK-8925] [MLlib] Add @since tags to mllib.util #7436

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b7a8ae8
Adding the annotation since
Jul 15, 2015
201e0fd
resubmitting
sthota2014 Jul 17, 2015
902d49b
pulled @deprecated outside of comment block
sthota2014 Jul 23, 2015
865149c
removed space and deprecated kept the annotation
sthota2014 Aug 5, 2015
5eece6e
remove one more space found
sthota2014 Aug 5, 2015
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22 changes: 21 additions & 1 deletion mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@ object MLUtils {
* feature dimensions.
* @param minPartitions min number of partitions
* @return labeled data stored as an RDD[LabeledPoint]
* @since 1.0.0
*/
def loadLibSVMFile(
sc: SparkContext,
Expand Down Expand Up @@ -113,7 +114,10 @@ object MLUtils {
}

// Convenient methods for `loadLibSVMFile`.


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@mengxr mengxr Jul 23, 2015

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I think we need to leave the @deprecated outside the JavaDoc as a Scala annotation to make it work in Scala.

/**
* @since 1.0.0
*/
@deprecated("use method without multiclass argument, which no longer has effect", "1.1.0")
def loadLibSVMFile(
sc: SparkContext,
Expand All @@ -126,13 +130,17 @@ object MLUtils {
/**
* Loads labeled data in the LIBSVM format into an RDD[LabeledPoint], with the default number of
* partitions.
* @since 1.0.0
*/
def loadLibSVMFile(
sc: SparkContext,
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@mengxr mengxr Aug 5, 2015

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We still need to keep this as an annotation. @deprecated in comments is a JavaDoc tag, while @deprecated outside comments is a Scala annotation, which helps generate compiler warnings.

We should keep each PR minimal, so please keep all @deprecated annotation unchanged.

path: String,
numFeatures: Int): RDD[LabeledPoint] =
loadLibSVMFile(sc, path, numFeatures, sc.defaultMinPartitions)

/**
* @since 1.0.0
*/
@deprecated("use method without multiclass argument, which no longer has effect", "1.1.0")
def loadLibSVMFile(
sc: SparkContext,
Expand All @@ -141,6 +149,9 @@ object MLUtils {
numFeatures: Int): RDD[LabeledPoint] =
loadLibSVMFile(sc, path, numFeatures)

/**
* @since 1.0.0
*/
@deprecated("use method without multiclass argument, which no longer has effect", "1.1.0")
def loadLibSVMFile(
sc: SparkContext,
Expand All @@ -151,6 +162,7 @@ object MLUtils {
/**
* Loads binary labeled data in the LIBSVM format into an RDD[LabeledPoint], with number of
* features determined automatically and the default number of partitions.
* @since 1.0.0
*/
def loadLibSVMFile(sc: SparkContext, path: String): RDD[LabeledPoint] =
loadLibSVMFile(sc, path, -1)
Expand Down Expand Up @@ -181,12 +193,14 @@ object MLUtils {
* @param path file or directory path in any Hadoop-supported file system URI
* @param minPartitions min number of partitions
* @return vectors stored as an RDD[Vector]
* @since 1.1.0
*/
def loadVectors(sc: SparkContext, path: String, minPartitions: Int): RDD[Vector] =
sc.textFile(path, minPartitions).map(Vectors.parse)

/**
* Loads vectors saved using `RDD[Vector].saveAsTextFile` with the default number of partitions.
* @since 1.1.0
*/
def loadVectors(sc: SparkContext, path: String): RDD[Vector] =
sc.textFile(path, sc.defaultMinPartitions).map(Vectors.parse)
Expand All @@ -197,13 +211,15 @@ object MLUtils {
* @param path file or directory path in any Hadoop-supported file system URI
* @param minPartitions min number of partitions
* @return labeled points stored as an RDD[LabeledPoint]
* @since 1.1.0
*/
def loadLabeledPoints(sc: SparkContext, path: String, minPartitions: Int): RDD[LabeledPoint] =
sc.textFile(path, minPartitions).map(LabeledPoint.parse)

/**
* Loads labeled points saved using `RDD[LabeledPoint].saveAsTextFile` with the default number of
* partitions.
* @since 1.1.0
*/
def loadLabeledPoints(sc: SparkContext, dir: String): RDD[LabeledPoint] =
loadLabeledPoints(sc, dir, sc.defaultMinPartitions)
Expand All @@ -220,6 +236,7 @@ object MLUtils {
*
* @deprecated Should use [[org.apache.spark.rdd.RDD#saveAsTextFile]] for saving and
* [[org.apache.spark.mllib.util.MLUtils#loadLabeledPoints]] for loading.
* @since 1.0.0
*/
@deprecated("Should use MLUtils.loadLabeledPoints instead.", "1.0.1")
def loadLabeledData(sc: SparkContext, dir: String): RDD[LabeledPoint] = {
Expand All @@ -241,6 +258,7 @@ object MLUtils {
*
* @deprecated Should use [[org.apache.spark.rdd.RDD#saveAsTextFile]] for saving and
* [[org.apache.spark.mllib.util.MLUtils#loadLabeledPoints]] for loading.
* @since 1.0.0
*/
@deprecated("Should use RDD[LabeledPoint].saveAsTextFile instead.", "1.0.1")
def saveLabeledData(data: RDD[LabeledPoint], dir: String) {
Expand All @@ -253,6 +271,7 @@ object MLUtils {
* Return a k element array of pairs of RDDs with the first element of each pair
* containing the training data, a complement of the validation data and the second
* element, the validation data, containing a unique 1/kth of the data. Where k=numFolds.
* @since 1.0.0
*/
@Experimental
def kFold[T: ClassTag](rdd: RDD[T], numFolds: Int, seed: Int): Array[(RDD[T], RDD[T])] = {
Expand All @@ -268,6 +287,7 @@ object MLUtils {

/**
* Returns a new vector with `1.0` (bias) appended to the input vector.
* @since 1.0.0
*/
def appendBias(vector: Vector): Vector = {
vector match {
Expand Down