Repository: spark Updated Branches: refs/heads/master c68344400 -> df7974b8e
SPARK-3359 [DOCS] sbt/sbt unidoc doesn't work with Java 8 This follows https://github.com/apache/spark/pull/2893 , but does not completely fix SPARK-3359 either. This fixes minor scaladoc/javadoc issues that Javadoc 8 will treat as errors. Author: Sean Owen <[email protected]> Closes #2909 from srowen/SPARK-3359 and squashes the following commits: f62c347 [Sean Owen] Fix some javadoc issues that javadoc 8 considers errors. This is not all of the errors turned up when javadoc 8 runs on output of genjavadoc. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/df7974b8 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/df7974b8 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/df7974b8 Branch: refs/heads/master Commit: df7974b8e59d00e8efbb61629418fa6265c1ddab Parents: c683444 Author: Sean Owen <[email protected]> Authored: Sat Oct 25 23:18:02 2014 -0700 Committer: Xiangrui Meng <[email protected]> Committed: Sat Oct 25 23:18:02 2014 -0700 ---------------------------------------------------------------------- core/src/main/java/org/apache/spark/TaskContext.java | 2 -- .../org/apache/spark/api/java/function/PairFunction.java | 3 ++- .../main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala | 6 +++--- .../main/scala/org/apache/spark/api/java/JavaPairRDD.scala | 4 ++-- .../scala/org/apache/spark/api/java/JavaSparkContext.scala | 5 ++++- .../scala/org/apache/spark/mllib/feature/Normalizer.scala | 2 +- .../apache/spark/mllib/linalg/distributed/RowMatrix.scala | 7 ++++--- .../src/main/scala/org/apache/spark/mllib/util/MLUtils.scala | 8 ++++---- .../scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala | 2 +- 9 files changed, 21 insertions(+), 18 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/core/src/main/java/org/apache/spark/TaskContext.java ---------------------------------------------------------------------- diff --git a/core/src/main/java/org/apache/spark/TaskContext.java b/core/src/main/java/org/apache/spark/TaskContext.java index 2d998d4..0d69732 100644 --- a/core/src/main/java/org/apache/spark/TaskContext.java +++ b/core/src/main/java/org/apache/spark/TaskContext.java @@ -71,7 +71,6 @@ public abstract class TaskContext implements Serializable { /** * Add a (Java friendly) listener to be executed on task completion. * This will be called in all situation - success, failure, or cancellation. - * <p/> * An example use is for HadoopRDD to register a callback to close the input stream. */ public abstract TaskContext addTaskCompletionListener(TaskCompletionListener listener); @@ -79,7 +78,6 @@ public abstract class TaskContext implements Serializable { /** * Add a listener in the form of a Scala closure to be executed on task completion. * This will be called in all situations - success, failure, or cancellation. - * <p/> * An example use is for HadoopRDD to register a callback to close the input stream. */ public abstract TaskContext addTaskCompletionListener(final Function1<TaskContext, Unit> f); http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/core/src/main/java/org/apache/spark/api/java/function/PairFunction.java ---------------------------------------------------------------------- diff --git a/core/src/main/java/org/apache/spark/api/java/function/PairFunction.java b/core/src/main/java/org/apache/spark/api/java/function/PairFunction.java index abd9bcc..99bf240 100644 --- a/core/src/main/java/org/apache/spark/api/java/function/PairFunction.java +++ b/core/src/main/java/org/apache/spark/api/java/function/PairFunction.java @@ -22,7 +22,8 @@ import java.io.Serializable; import scala.Tuple2; /** - * A function that returns key-value pairs (Tuple2<K, V>), and can be used to construct PairRDDs. + * A function that returns key-value pairs (Tuple2<K, V>), and can be used to + * construct PairRDDs. */ public interface PairFunction<T, K, V> extends Serializable { public Tuple2<K, V> call(T t) throws Exception; http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala ---------------------------------------------------------------------- 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 a6123bd..8e8f7f6 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 @@ -114,7 +114,7 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[JDouble, Ja * Return an RDD with the elements from `this` that are not in `other`. * * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting - * RDD will be <= us. + * RDD will be <= us. */ def subtract(other: JavaDoubleRDD): JavaDoubleRDD = fromRDD(srdd.subtract(other)) @@ -233,11 +233,11 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[JDouble, Ja * to the left except for the last which is closed * e.g. for the array * [1,10,20,50] the buckets are [1,10) [10,20) [20,50] - * e.g 1<=x<10 , 10<=x<20, 20<=x<50 + * e.g 1<=x<10 , 10<=x<20, 20<=x<50 * And on the input of 1 and 50 we would have a histogram of 1,0,0 * * Note: if your histogram is evenly spaced (e.g. [0, 10, 20, 30]) this can be switched - * from an O(log n) inseration to O(1) per element. (where n = # buckets) if you set evenBuckets + * from an O(log n) insertion to O(1) per element. (where n = # buckets) if you set evenBuckets * to true. * buckets must be sorted and not contain any duplicates. * buckets array must be at least two elements http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala ---------------------------------------------------------------------- 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 c38b965..e37f3ac 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 @@ -392,7 +392,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)]) * Return an RDD with the elements from `this` that are not in `other`. * * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting - * RDD will be <= us. + * RDD will be <= us. */ def subtract(other: JavaPairRDD[K, V]): JavaPairRDD[K, V] = fromRDD(rdd.subtract(other)) @@ -413,7 +413,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)]) * Return an RDD with the pairs from `this` whose keys are not in `other`. * * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting - * RDD will be <= us. + * RDD will be <= us. */ def subtractByKey[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, V] = { implicit val ctag: ClassTag[W] = fakeClassTag http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala ---------------------------------------------------------------------- diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala index 45168ba..0565adf 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala @@ -215,7 +215,10 @@ class JavaSparkContext(val sc: SparkContext) * hdfs://a-hdfs-path/part-nnnnn * }}} * - * Do `JavaPairRDD<String, String> rdd = sparkContext.wholeTextFiles("hdfs://a-hdfs-path")`, + * Do + * {{{ + * JavaPairRDD<String, String> rdd = sparkContext.wholeTextFiles("hdfs://a-hdfs-path") + * }}} * * <p> then `rdd` contains * {{{ http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/mllib/src/main/scala/org/apache/spark/mllib/feature/Normalizer.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/mllib/feature/Normalizer.scala b/mllib/src/main/scala/org/apache/spark/mllib/feature/Normalizer.scala index 4734251..dfad25d 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/feature/Normalizer.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/Normalizer.scala @@ -26,7 +26,7 @@ import org.apache.spark.mllib.linalg.{Vector, Vectors} * :: Experimental :: * Normalizes samples individually to unit L^p^ norm * - * For any 1 <= p < Double.PositiveInfinity, normalizes samples using + * For any 1 <= p < Double.PositiveInfinity, normalizes samples using * sum(abs(vector).^p^)^(1/p)^ as norm. * * For p = Double.PositiveInfinity, max(abs(vector)) will be used as norm for normalization. http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala index ec2d481..10a515a 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala @@ -152,7 +152,7 @@ class RowMatrix( * storing the right singular vectors, is computed via matrix multiplication as * U = A * (V * S^-1^), if requested by user. The actual method to use is determined * automatically based on the cost: - * - If n is small (n < 100) or k is large compared with n (k > n / 2), we compute the Gramian + * - If n is small (n < 100) or k is large compared with n (k > n / 2), we compute the Gramian * matrix first and then compute its top eigenvalues and eigenvectors locally on the driver. * This requires a single pass with O(n^2^) storage on each executor and on the driver, and * O(n^2^ k) time on the driver. @@ -169,7 +169,8 @@ class RowMatrix( * @note The conditions that decide which method to use internally and the default parameters are * subject to change. * - * @param k number of leading singular values to keep (0 < k <= n). It might return less than k if + * @param k number of leading singular values to keep (0 < k <= n). + * It might return less than k if * there are numerically zero singular values or there are not enough Ritz values * converged before the maximum number of Arnoldi update iterations is reached (in case * that matrix A is ill-conditioned). @@ -192,7 +193,7 @@ class RowMatrix( /** * The actual SVD implementation, visible for testing. * - * @param k number of leading singular values to keep (0 < k <= n) + * @param k number of leading singular values to keep (0 < k <= n) * @param computeU whether to compute U * @param rCond the reciprocal condition number * @param maxIter max number of iterations (if ARPACK is used) http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala index ca35100..dce0adf 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala @@ -196,8 +196,8 @@ object MLUtils { /** * Load labeled data from a file. The data format used here is - * <L>, <f1> <f2> ... - * where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double. + * L, f1 f2 ... + * where f1, f2 are feature values in Double and L is the corresponding label as Double. * * @param sc SparkContext * @param dir Directory to the input data files. @@ -219,8 +219,8 @@ object MLUtils { /** * Save labeled data to a file. The data format used here is - * <L>, <f1> <f2> ... - * where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double. + * L, f1 f2 ... + * where f1, f2 are feature values in Double and L is the corresponding label as Double. * * @param data An RDD of LabeledPoints containing data to be saved. * @param dir Directory to save the data. http://git-wip-us.apache.org/repos/asf/spark/blob/df7974b8/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala index e7faba0..1e0ccb3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala @@ -193,7 +193,7 @@ class JavaSchemaRDD( * Return an RDD with the elements from `this` that are not in `other`. * * Uses `this` partitioner/partition size, because even if `other` is huge, the resulting - * RDD will be <= us. + * RDD will be <= us. */ def subtract(other: JavaSchemaRDD): JavaSchemaRDD = this.baseSchemaRDD.subtract(other.baseSchemaRDD).toJavaSchemaRDD --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
