diff --git a/core/src/main/scala/org/apache/spark/SparkConf.scala b/core/src/main/scala/org/apache/spark/SparkConf.scala index 0c1c68de89f81981bf2fb4a931d7857d97a8782b..d78b9f1b29685b5205b8a8b9d537bdca4bc23c73 100644 --- a/core/src/main/scala/org/apache/spark/SparkConf.scala +++ b/core/src/main/scala/org/apache/spark/SparkConf.scala @@ -378,7 +378,9 @@ class SparkConf(loadDefaults: Boolean) extends Cloneable with Logging with Seria settings.entrySet().asScala.map(x => (x.getKey, x.getValue)).toArray } - /** Get all parameters that start with `prefix` */ + /** + * Get all parameters that start with `prefix` + */ def getAllWithPrefix(prefix: String): Array[(String, String)] = { getAll.filter { case (k, v) => k.startsWith(prefix) } .map { case (k, v) => (k.substring(prefix.length), v) } diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala index a32a4b28c17318ed821356d15ae2371e87a4f81b..b71af0d42cdb078a86fb46c33388e3584f440fcb 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala @@ -45,7 +45,9 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) import JavaDoubleRDD.fromRDD - /** Persist this RDD with the default storage level (`MEMORY_ONLY`). */ + /** + * Persist this RDD with the default storage level (`MEMORY_ONLY`). + */ def cache(): JavaDoubleRDD = fromRDD(srdd.cache()) /** diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala index d7e3a1b1be48c2f3f2840cbc209c2bf048dc3d87..766aea213a972fa922f11087a1fd58a3e97a783f 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala @@ -54,7 +54,9 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)]) // Common RDD functions - /** Persist this RDD with the default storage level (`MEMORY_ONLY`). */ + /** + * Persist this RDD with the default storage level (`MEMORY_ONLY`). + */ def cache(): JavaPairRDD[K, V] = new JavaPairRDD[K, V](rdd.cache()) /** @@ -454,13 +456,17 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)]) fromRDD(rdd.subtractByKey(other)) } - /** Return an RDD with the pairs from `this` whose keys are not in `other`. */ + /** + * Return an RDD with the pairs from `this` whose keys are not in `other`. + */ def subtractByKey[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, V] = { implicit val ctag: ClassTag[W] = fakeClassTag fromRDD(rdd.subtractByKey(other, numPartitions)) } - /** Return an RDD with the pairs from `this` whose keys are not in `other`. */ + /** + * Return an RDD with the pairs from `this` whose keys are not in `other`. + */ def subtractByKey[W](other: JavaPairRDD[K, W], p: Partitioner): JavaPairRDD[K, V] = { implicit val ctag: ClassTag[W] = fakeClassTag fromRDD(rdd.subtractByKey(other, p)) diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala b/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala index 94e26e687c66b86add0195afb2a8a1fbd09b150e..41b5cab601c36dbe6856278c92e9d3e8374d64f9 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala @@ -34,7 +34,9 @@ class JavaRDD[T](val rdd: RDD[T])(implicit val classTag: ClassTag[T]) // Common RDD functions - /** Persist this RDD with the default storage level (`MEMORY_ONLY`). */ + /** + * Persist this RDD with the default storage level (`MEMORY_ONLY`). + */ def cache(): JavaRDD[T] = wrapRDD(rdd.cache()) /** diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index 969cd47038cfa6f6afda118a59a52c2ceee634a6..dc123e23b781c608c6d2d031c22cd358b17a3c06 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -916,14 +916,18 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) subtractByKey(other, self.partitioner.getOrElse(new HashPartitioner(self.partitions.length))) } - /** Return an RDD with the pairs from `this` whose keys are not in `other`. */ + /** + * Return an RDD with the pairs from `this` whose keys are not in `other`. + */ def subtractByKey[W: ClassTag]( other: RDD[(K, W)], numPartitions: Int): RDD[(K, V)] = self.withScope { subtractByKey(other, new HashPartitioner(numPartitions)) } - /** Return an RDD with the pairs from `this` whose keys are not in `other`. */ + /** + * Return an RDD with the pairs from `this` whose keys are not in `other`. + */ def subtractByKey[W: ClassTag](other: RDD[(K, W)], p: Partitioner): RDD[(K, V)] = self.withScope { new SubtractedRDD[K, V, W](self, other, p) } diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index f723fcb837f8819f72febe197613c5cb13be66d5..d285e917b8a672c3062d86b83f411eb0a7f745a0 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -195,10 +195,14 @@ abstract class RDD[T: ClassTag]( } } - /** Persist this RDD with the default storage level (`MEMORY_ONLY`). */ + /** + * Persist this RDD with the default storage level (`MEMORY_ONLY`). + */ def persist(): this.type = persist(StorageLevel.MEMORY_ONLY) - /** Persist this RDD with the default storage level (`MEMORY_ONLY`). */ + /** + * Persist this RDD with the default storage level (`MEMORY_ONLY`). + */ def cache(): this.type = persist() /** diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgeRDDImpl.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgeRDDImpl.scala index faa985594ec081bbe8d481b8e3ad035af72b2f9c..376c7b06f9d2b30a8ff84395816363d629a8db07 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgeRDDImpl.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgeRDDImpl.scala @@ -63,7 +63,9 @@ class EdgeRDDImpl[ED: ClassTag, VD: ClassTag] private[graphx] ( this } - /** Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY. */ + /** + * Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY. + */ override def cache(): this.type = { partitionsRDD.persist(targetStorageLevel) this diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala index 3810110099993306bb26b45526e7bd3a7e2fa26f..5d2a53782b55d0135d95310c7a40f35d02e37af9 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala @@ -277,7 +277,9 @@ class GraphImpl[VD: ClassTag, ED: ClassTag] protected ( object GraphImpl { - /** Create a graph from edges, setting referenced vertices to `defaultVertexAttr`. */ + /** + * Create a graph from edges, setting referenced vertices to `defaultVertexAttr`. + */ def apply[VD: ClassTag, ED: ClassTag]( edges: RDD[Edge[ED]], defaultVertexAttr: VD, @@ -286,7 +288,9 @@ object GraphImpl { fromEdgeRDD(EdgeRDD.fromEdges(edges), defaultVertexAttr, edgeStorageLevel, vertexStorageLevel) } - /** Create a graph from EdgePartitions, setting referenced vertices to `defaultVertexAttr`. */ + /** + * Create a graph from EdgePartitions, setting referenced vertices to `defaultVertexAttr`. + */ def fromEdgePartitions[VD: ClassTag, ED: ClassTag]( edgePartitions: RDD[(PartitionID, EdgePartition[ED, VD])], defaultVertexAttr: VD, @@ -296,7 +300,9 @@ object GraphImpl { vertexStorageLevel) } - /** Create a graph from vertices and edges, setting missing vertices to `defaultVertexAttr`. */ + /** + * Create a graph from vertices and edges, setting missing vertices to `defaultVertexAttr`. + */ def apply[VD: ClassTag, ED: ClassTag]( vertices: RDD[(VertexId, VD)], edges: RDD[Edge[ED]], diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexRDDImpl.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexRDDImpl.scala index d314522de991689a8fdf9edb8800309afa103d9f..3c6f22d97360d778c508ae9bf5b75a51b6ec4f9c 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexRDDImpl.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexRDDImpl.scala @@ -63,7 +63,9 @@ class VertexRDDImpl[VD] private[graphx] ( this } - /** Persists the vertex partitions at `targetStorageLevel`, which defaults to MEMORY_ONLY. */ + /** + * Persists the vertex partitions at `targetStorageLevel`, which defaults to MEMORY_ONLY. + */ override def cache(): this.type = { partitionsRDD.persist(targetStorageLevel) this diff --git a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala index 4d4b06b0952bd2e6b4334185b7cd9fa1545e3564..d9ffdeb797fb896f7000bfd964b5bd4e3e98ca5c 100644 --- a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala +++ b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Matrices.scala @@ -85,11 +85,15 @@ sealed trait Matrix extends Serializable { @Since("2.0.0") def copy: Matrix - /** Transpose the Matrix. Returns a new `Matrix` instance sharing the same underlying data. */ + /** + * Transpose the Matrix. Returns a new `Matrix` instance sharing the same underlying data. + */ @Since("2.0.0") def transpose: Matrix - /** Convenience method for `Matrix`-`DenseMatrix` multiplication. */ + /** + * Convenience method for `Matrix`-`DenseMatrix` multiplication. + */ @Since("2.0.0") def multiply(y: DenseMatrix): DenseMatrix = { val C: DenseMatrix = DenseMatrix.zeros(numRows, y.numCols) @@ -97,13 +101,17 @@ sealed trait Matrix extends Serializable { C } - /** Convenience method for `Matrix`-`DenseVector` multiplication. For binary compatibility. */ + /** + * Convenience method for `Matrix`-`DenseVector` multiplication. For binary compatibility. + */ @Since("2.0.0") def multiply(y: DenseVector): DenseVector = { multiply(y.asInstanceOf[Vector]) } - /** Convenience method for `Matrix`-`Vector` multiplication. */ + /** + * Convenience method for `Matrix`-`Vector` multiplication. + */ @Since("2.0.0") def multiply(y: Vector): DenseVector = { val output = new DenseVector(new Array[Double](numRows)) diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala index 38176b96ba2ed6f41e58e0decb260ddd3a1e7129..08e9cb9ba86688539958b841a822dca2eb6a07dc 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala @@ -216,7 +216,9 @@ object Pipeline extends MLReadable[Pipeline] { } } - /** Methods for `MLReader` and `MLWriter` shared between [[Pipeline]] and [[PipelineModel]] */ + /** + * Methods for `MLReader` and `MLWriter` shared between [[Pipeline]] and [[PipelineModel]] + */ private[ml] object SharedReadWrite { import org.json4s.JsonDSL._ diff --git a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala index 527cb2d547b63e6e59f4710494530f1ebdd53075..21a246e454c83ac3461b5b25cdf417014e5a0847 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala @@ -239,7 +239,9 @@ object AttributeGroup { } } - /** Creates an attribute group from a `StructField` instance. */ + /** + * Creates an attribute group from a `StructField` instance. + */ def fromStructField(field: StructField): AttributeGroup = { require(field.dataType == new VectorUDT) if (field.metadata.contains(ML_ATTR)) { diff --git a/mllib/src/main/scala/org/apache/spark/ml/attribute/attributes.scala b/mllib/src/main/scala/org/apache/spark/ml/attribute/attributes.scala index cc7e8bc301ad39f0554524e9a6922a26a67e32b5..7fbfee75e96a9866d5f8261b6820d0fac27c257d 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/attribute/attributes.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/attribute/attributes.scala @@ -109,7 +109,9 @@ sealed abstract class Attribute extends Serializable { StructField(name.get, DoubleType, nullable = false, newMetadata) } - /** Converts to a `StructField`. */ + /** + * Converts to a `StructField`. + */ def toStructField(): StructField = toStructField(Metadata.empty) override def toString: String = toMetadataImpl(withType = true).toString @@ -369,12 +371,16 @@ class NominalAttribute private[ml] ( override def withIndex(index: Int): NominalAttribute = copy(index = Some(index)) override def withoutIndex: NominalAttribute = copy(index = None) - /** Copy with new values and empty `numValues`. */ + /** + * Copy with new values and empty `numValues`. + */ def withValues(values: Array[String]): NominalAttribute = { copy(numValues = None, values = Some(values)) } - /** Copy with new values and empty `numValues`. */ + /** + * Copy with new values and empty `numValues`. + */ @varargs def withValues(first: String, others: String*): NominalAttribute = { copy(numValues = None, values = Some((first +: others).toArray)) @@ -385,12 +391,16 @@ class NominalAttribute private[ml] ( copy(values = None) } - /** Copy with a new `numValues` and empty `values`. */ + /** + * Copy with a new `numValues` and empty `values`. + */ def withNumValues(numValues: Int): NominalAttribute = { copy(numValues = Some(numValues), values = None) } - /** Copy without the `numValues`. */ + /** + * Copy without the `numValues`. + */ def withoutNumValues: NominalAttribute = copy(numValues = None) /** diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala index ec582266e6a47031bfae2000244a3eb3758a5229..d3ae62e243302df57eccc323e06e4bc122910219 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala @@ -1105,7 +1105,9 @@ sealed trait LogisticRegressionTrainingSummary extends LogisticRegressionSummary */ sealed trait LogisticRegressionSummary extends Serializable { - /** Dataframe output by the model's `transform` method. */ + /** + * Dataframe output by the model's `transform` method. + */ def predictions: DataFrame /** Field in "predictions" which gives the probability of each class as a vector. */ diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala index e718cda2623a0b598e10413e79c6c40d5fcd1348..770a2571bb9c2f662b61c0675decf89f725d9c53 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala @@ -886,7 +886,9 @@ class GeneralizedLinearRegressionSummary private[regression] ( protected val model: GeneralizedLinearRegressionModel = origModel.copy(ParamMap.empty).setPredictionCol(predictionCol) - /** Predictions output by the model's `transform` method. */ + /** + * Predictions output by the model's `transform` method. + */ @Since("2.0.0") @transient val predictions: DataFrame = model.transform(dataset) private[regression] lazy val family: Family = Family.fromName(model.getFamily) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala b/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala index f9156b642785f36fb3aa9e3909159a4131408755..05ad2492f8c43a7fa76b6b5a02be2b444648ee34 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala @@ -255,10 +255,14 @@ class ChiSqSelector @Since("2.1.0") () extends Serializable { private[spark] object ChiSqSelector { - /** String name for `numTopFeatures` selector type. */ + /** + * String name for `numTopFeatures` selector type. + */ val NumTopFeatures: String = "numTopFeatures" - /** String name for `percentile` selector type. */ + /** + * String name for `percentile` selector type. + */ val Percentile: String = "percentile" /** String name for `fpr` selector type. */ diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala index 542a69b3ef8cf1b93c4e84fe44814c19f25b5d90..6c39fe5d8486548b3c6aa2e884984077dbb170ae 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala @@ -91,11 +91,15 @@ sealed trait Matrix extends Serializable { @Since("1.2.0") def copy: Matrix - /** Transpose the Matrix. Returns a new `Matrix` instance sharing the same underlying data. */ + /** + * Transpose the Matrix. Returns a new `Matrix` instance sharing the same underlying data. + */ @Since("1.3.0") def transpose: Matrix - /** Convenience method for `Matrix`-`DenseMatrix` multiplication. */ + /** + * Convenience method for `Matrix`-`DenseMatrix` multiplication. + */ @Since("1.2.0") def multiply(y: DenseMatrix): DenseMatrix = { val C: DenseMatrix = DenseMatrix.zeros(numRows, y.numCols) @@ -103,13 +107,17 @@ sealed trait Matrix extends Serializable { C } - /** Convenience method for `Matrix`-`DenseVector` multiplication. For binary compatibility. */ + /** + * Convenience method for `Matrix`-`DenseVector` multiplication. For binary compatibility. + */ @Since("1.2.0") def multiply(y: DenseVector): DenseVector = { multiply(y.asInstanceOf[Vector]) } - /** Convenience method for `Matrix`-`Vector` multiplication. */ + /** + * Convenience method for `Matrix`-`Vector` multiplication. + */ @Since("1.4.0") def multiply(y: Vector): DenseVector = { val output = new DenseVector(new Array[Double](numRows)) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala index 9e75217410d36a7057eeafffe0234da4022f60aa..ff81a2f03e2a85b1c49dfa9a5150181480cd0982 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala @@ -295,7 +295,9 @@ class BlockMatrix @Since("1.3.0") ( new IndexedRowMatrix(rows) } - /** Collect the distributed matrix on the driver as a `DenseMatrix`. */ + /** + * Collect the distributed matrix on the driver as a `DenseMatrix`. + */ @Since("1.3.0") def toLocalMatrix(): Matrix = { require(numRows() < Int.MaxValue, "The number of rows of this matrix should be less than " + diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala index d2c5b14a5b128c00223bc006a0f16f3ecd20858d..26ca1ef9be8700c0c1c2a7b37e11bc2a432ed8e3 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala @@ -101,7 +101,9 @@ class CoordinateMatrix @Since("1.0.0") ( toIndexedRowMatrix().toRowMatrix() } - /** Converts to BlockMatrix. Creates blocks of `SparseMatrix` with size 1024 x 1024. */ + /** + * Converts to BlockMatrix. Creates blocks of `SparseMatrix` with size 1024 x 1024. + */ @Since("1.3.0") def toBlockMatrix(): BlockMatrix = { toBlockMatrix(1024, 1024) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala index 590e959daa1f4fb521062f9a3a8f48b9c12df507..d7255d527f036391c6222dcb26f0e30fc24ecda6 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala @@ -90,7 +90,9 @@ class IndexedRowMatrix @Since("1.0.0") ( new RowMatrix(rows.map(_.vector), 0L, nCols) } - /** Converts to BlockMatrix. Creates blocks of `SparseMatrix` with size 1024 x 1024. */ + /** + * Converts to BlockMatrix. Creates blocks of `SparseMatrix` with size 1024 x 1024. + */ @Since("1.3.0") def toBlockMatrix(): BlockMatrix = { toBlockMatrix(1024, 1024) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/Statistics.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/Statistics.scala index 7ba9b292969e7853fbb8e6d19f5608f148a578d1..5ebbfb2b6298d18c6dd1caec10a3ee96620bc7cc 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/stat/Statistics.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/Statistics.scala @@ -176,7 +176,9 @@ object Statistics { ChiSqTest.chiSquaredFeatures(data) } - /** Java-friendly version of `chiSqTest()` */ + /** + * Java-friendly version of `chiSqTest()` + */ @Since("1.5.0") def chiSqTest(data: JavaRDD[LabeledPoint]): Array[ChiSqTestResult] = chiSqTest(data.rdd) @@ -218,7 +220,9 @@ object Statistics { KolmogorovSmirnovTest.testOneSample(data, distName, params: _*) } - /** Java-friendly version of `kolmogorovSmirnovTest()` */ + /** + * Java-friendly version of `kolmogorovSmirnovTest()` + */ @Since("1.5.0") @varargs def kolmogorovSmirnovTest( diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala index b9f8c46443021f6f1fd10757b36d63878ac97cdc..68ea47cedac9a59cfb265381c47c5220d2d89ff9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala @@ -77,6 +77,8 @@ trait Encoder[T] extends Serializable { /** Returns the schema of encoding this type of object as a Row. */ def schema: StructType - /** A ClassTag that can be used to construct and Array to contain a collection of `T`. */ + /** + * A ClassTag that can be used to construct and Array to contain a collection of `T`. + */ def clsTag: ClassTag[T] } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/ArrayType.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/ArrayType.scala index 5d70ef01373f5cae42320221794e8e19bdb6936d..d409271fbc6b5f6177d80f188be254627698b096 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/ArrayType.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/ArrayType.scala @@ -31,7 +31,9 @@ import org.apache.spark.sql.catalyst.util.ArrayData */ @InterfaceStability.Stable object ArrayType extends AbstractDataType { - /** Construct a [[ArrayType]] object with the given element type. The `containsNull` is true. */ + /** + * Construct a [[ArrayType]] object with the given element type. The `containsNull` is true. + */ def apply(elementType: DataType): ArrayType = ArrayType(elementType, containsNull = true) override private[sql] def defaultConcreteType: DataType = ArrayType(NullType, containsNull = true) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala b/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala index c3b28bd516da591ac6f83038f3f91e07562e7bde..dcd698c860d8bdcf7f00c6e433ed47781f1eb300 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala @@ -70,10 +70,14 @@ import org.apache.spark.util.ClosureCleaner @Experimental sealed abstract class StateSpec[KeyType, ValueType, StateType, MappedType] extends Serializable { - /** Set the RDD containing the initial states that will be used by `mapWithState` */ + /** + * Set the RDD containing the initial states that will be used by `mapWithState` + */ def initialState(rdd: RDD[(KeyType, StateType)]): this.type - /** Set the RDD containing the initial states that will be used by `mapWithState` */ + /** + * Set the RDD containing the initial states that will be used by `mapWithState` + */ def initialState(javaPairRDD: JavaPairRDD[KeyType, StateType]): this.type /**