update doc

Author: uncleGen

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala

@@ -46,7 +46,7 @@ object LocalRelation {
 /**
  * @param dataFromStreaming indicate if this relation comes from a streaming source.
  *                          In a streaming query, stream relation will be cut into a
- *                          couple of batch relations.
+ *                          series of batch relations.
  */
 case class LocalRelation(
     output: Seq[Attribute],

sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala

@@ -131,7 +131,7 @@ case class ExternalRDDScanExec[T](
  *
  * @param dataFromStreaming indicate if this relation comes from a streaming source.
  *                          In a streaming query, stream relation will be cut into a
- *                          couple of batch relations.
+ *                          series of batch relations.
  */
 case class LogicalRDD(
     output: Seq[Attribute],

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala

@@ -33,7 +33,7 @@ import org.apache.spark.util.Utils
  *
  * @param dataFromStreaming indicate if this relation comes from a streaming source.
  *                          In a streaming query, stream relation will be cut into a
- *                          couple of batch relations.
+ *                          series of batch relations.
  */
 case class LogicalRelation(
     relation: BaseRelation,

sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/Source.scala

@@ -60,7 +60,7 @@ trait Source  {
   def getBatch(start: Option[Offset], end: Offset): DataFrame
 
   /**
-   * In a streaming query, stream relation will be cut into a couple of batch relations.
+   * In a streaming query, stream relation will be cut into a series of batch relations.
    * We need to mark the batch relation as streaming, i.e. data coming from a stream source,
    * so we can apply those streaming strategies to it.
    */