Repository: spark Updated Branches: refs/heads/branch-2.1 06a56df22 -> 84b2af229
http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala index 83857c3..e328b86 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala @@ -40,8 +40,8 @@ case class JdbcType(databaseTypeDefinition : String, jdbcNullType : Int) * SQL dialect of a certain database or jdbc driver. * Lots of databases define types that aren't explicitly supported * by the JDBC spec. Some JDBC drivers also report inaccurate - * information---for instance, BIT(n>1) being reported as a BIT type is quite - * common, even though BIT in JDBC is meant for single-bit values. Also, there + * information---for instance, BIT(n{@literal >}1) being reported as a BIT type is quite + * common, even though BIT in JDBC is meant for single-bit values. Also, there * does not appear to be a standard name for an unbounded string or binary * type; we use BLOB and CLOB by default but override with database-specific * alternatives when these are absent or do not behave correctly. http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index ff6dd8c..f288ad6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -112,7 +112,7 @@ trait SchemaRelationProvider { /** * ::Experimental:: - * Implemented by objects that can produce a streaming [[Source]] for a specific format or system. + * Implemented by objects that can produce a streaming `Source` for a specific format or system. * * @since 2.0.0 */ @@ -143,7 +143,7 @@ trait StreamSourceProvider { /** * ::Experimental:: - * Implemented by objects that can produce a streaming [[Sink]] for a specific format or system. + * Implemented by objects that can produce a streaming `Sink` for a specific format or system. * * @since 2.0.0 */ @@ -185,7 +185,7 @@ trait CreatableRelationProvider { /** * Represents a collection of tuples with a known schema. Classes that extend BaseRelation must - * be able to produce the schema of their data in the form of a [[StructType]]. Concrete + * be able to produce the schema of their data in the form of a `StructType`. Concrete * implementation should inherit from one of the descendant `Scan` classes, which define various * abstract methods for execution. * @@ -216,10 +216,10 @@ abstract class BaseRelation { /** * Whether does it need to convert the objects in Row to internal representation, for example: - * java.lang.String -> UTF8String - * java.lang.Decimal -> Decimal + * java.lang.String to UTF8String + * java.lang.Decimal to Decimal * - * If `needConversion` is `false`, buildScan() should return an [[RDD]] of [[InternalRow]] + * If `needConversion` is `false`, buildScan() should return an `RDD` of `InternalRow` * * @note The internal representation is not stable across releases and thus data sources outside * of Spark SQL should leave this as true. http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala ---------------------------------------------------------------------- diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala index a2d64da..5f5c8e2 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala @@ -57,9 +57,17 @@ import org.apache.spark.util.SerializableJobConf * @param partition a map from the partition key to the partition value (optional). If the partition * value is optional, dynamic partition insert will be performed. * As an example, `INSERT INTO tbl PARTITION (a=1, b=2) AS ...` would have - * Map('a' -> Some('1'), 'b' -> Some('2')), + * + * {{{ + * Map('a' -> Some('1'), 'b' -> Some('2')) + * }}} + * * and `INSERT INTO tbl PARTITION (a=1, b) AS ...` - * would have Map('a' -> Some('1'), 'b' -> None). + * would have + * + * {{{ + * Map('a' -> Some('1'), 'b' -> None) + * }}}. * @param child the logical plan representing data to write to. * @param overwrite overwrite existing table or partitions. * @param ifNotExists If true, only write if the table or partition does not exist. http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala ---------------------------------------------------------------------- diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala index 4203308..e30e0f9 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala @@ -175,7 +175,7 @@ private[hive] case class HiveGenericUDF( /** * Converts a Hive Generic User Defined Table Generating Function (UDTF) to a - * [[Generator]]. Note that the semantics of Generators do not allow + * `Generator`. Note that the semantics of Generators do not allow * Generators to maintain state in between input rows. Thus UDTFs that rely on partitioning * dependent operations like calls to `close()` before producing output will not operate the same as * in Hive. However, in practice this should not affect compatibility for most sane UDTFs http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala ---------------------------------------------------------------------- diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala index e53c3e4..16cfa9d 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveWriterContainers.scala @@ -48,7 +48,7 @@ import org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter /** * Internal helper class that saves an RDD using a Hive OutputFormat. - * It is based on [[SparkHadoopWriter]]. + * It is based on `SparkHadoopWriter`. */ private[hive] class SparkHiveWriterContainer( @transient private val jobConf: JobConf, http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala ---------------------------------------------------------------------- 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 7c1ea2f..c3b28bd 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala @@ -30,7 +30,7 @@ import org.apache.spark.util.ClosureCleaner * `mapWithState` operation of a * [[org.apache.spark.streaming.dstream.PairDStreamFunctions pair DStream]] (Scala) or a * [[org.apache.spark.streaming.api.java.JavaPairDStream JavaPairDStream]] (Java). - * Use [[org.apache.spark.streaming.StateSpec.function() StateSpec.function]] factory methods + * Use `org.apache.spark.streaming.StateSpec.function()` factory methods * to create instances of this class. * * Example in Scala: @@ -100,7 +100,7 @@ sealed abstract class StateSpec[KeyType, ValueType, StateType, MappedType] exten /** * :: Experimental :: - * Builder object for creating instances of [[org.apache.spark.streaming.StateSpec StateSpec]] + * Builder object for creating instances of `org.apache.spark.streaming.StateSpec` * that is used for specifying the parameters of the DStream transformation `mapWithState` * that is used for specifying the parameters of the DStream transformation * `mapWithState` operation of a http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala ---------------------------------------------------------------------- diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala index aa4003c..2ec907c 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala @@ -434,8 +434,8 @@ class JavaPairDStream[K, V](val dstream: DStream[(K, V)])( * Return a [[JavaMapWithStateDStream]] by applying a function to every key-value element of * `this` stream, while maintaining some state data for each unique key. The mapping function * and other specification (e.g. partitioners, timeouts, initial state data, etc.) of this - * transformation can be specified using [[StateSpec]] class. The state data is accessible in - * as a parameter of type [[State]] in the mapping function. + * transformation can be specified using `StateSpec` class. The state data is accessible in + * as a parameter of type `State` in the mapping function. * * Example of using `mapWithState`: * {{{ http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala ---------------------------------------------------------------------- diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala index b43b940..982e72c 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala @@ -44,7 +44,7 @@ import org.apache.spark.streaming.scheduler.StreamingListener * A Java-friendly version of [[org.apache.spark.streaming.StreamingContext]] which is the main * entry point for Spark Streaming functionality. It provides methods to create * [[org.apache.spark.streaming.api.java.JavaDStream]] and - * [[org.apache.spark.streaming.api.java.JavaPairDStream.]] from input sources. The internal + * [[org.apache.spark.streaming.api.java.JavaPairDStream]] from input sources. The internal * org.apache.spark.api.java.JavaSparkContext (see core Spark documentation) can be accessed * using `context.sparkContext`. After creating and transforming DStreams, the streaming * computation can be started and stopped using `context.start()` and `context.stop()`, http://git-wip-us.apache.org/repos/asf/spark/blob/84b2af22/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala ---------------------------------------------------------------------- diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala index ac73941..f38c1e7 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala @@ -356,8 +356,8 @@ class PairDStreamFunctions[K, V](self: DStream[(K, V)]) * Return a [[MapWithStateDStream]] by applying a function to every key-value element of * `this` stream, while maintaining some state data for each unique key. The mapping function * and other specification (e.g. partitioners, timeouts, initial state data, etc.) of this - * transformation can be specified using [[StateSpec]] class. The state data is accessible in - * as a parameter of type [[State]] in the mapping function. + * transformation can be specified using `StateSpec` class. The state data is accessible in + * as a parameter of type `State` in the mapping function. * * Example of using `mapWithState`: * {{{ --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
