[SPARK-34310][CORE][SQL] Replaces map and flatten with flatMap

### What changes were proposed in this pull request?
Replaces `collection.map(f1).flatten(f2)` with `collection.flatMap` if possible. it's semantically consistent, but looks simpler.

### Why are the changes needed?
Code Simpilefications.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Pass the Jenkins or GitHub Action

Closes #31416 from LuciferYang/SPARK-34310.

Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>

core/src/main/scala/org/apache/spark/rdd/SubtractedRDD.scala

@@ -124,7 +124,7 @@ private[spark] class SubtractedRDD[K: ClassTag, V: ClassTag, W: ClassTag](
     integrate(0, t => getSeq(t._1) += t._2)
     // the second dep is rdd2; remove all of its keys
     integrate(1, t => map.remove(t._1))
-    map.asScala.iterator.map(t => t._2.iterator.map((t._1, _))).flatten
+    map.asScala.iterator.flatMap(t => t._2.iterator.map((t._1, _)))
   }
 
   override def clearDependencies(): Unit = {

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteDistinctAggregates.scala

@@ -292,7 +292,7 @@ object RewriteDistinctAggregates extends Rule[LogicalPlan] {
           // Final aggregate
           val operators = expressions.map { e =>
             val af = e.aggregateFunction
-            val condition = e.filter.map(distinctAggFilterAttrLookup.get(_)).flatten
+            val condition = e.filter.flatMap(distinctAggFilterAttrLookup.get)
             val naf = if (af.children.forall(_.foldable)) {
               // If aggregateFunction's children are all foldable, we only put the first child in
               // distinctAggGroups. So here we only need to rewrite the first child to

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/HadoopFileLinesReaderSuite.scala

@@ -36,13 +36,13 @@ class HadoopFileLinesReaderSuite extends SharedSparkSession {
     val delimOpt = delimiter.map(_.getBytes(StandardCharsets.UTF_8))
     Files.write(path.toPath, text.getBytes(StandardCharsets.UTF_8))
 
-    val lines = ranges.map { case (start, length) =>
+    val lines = ranges.flatMap { case (start, length) =>
       val file = PartitionedFile(InternalRow.empty, path.getCanonicalPath, start, length)
       val hadoopConf = conf.getOrElse(spark.sessionState.newHadoopConf())
       val reader = new HadoopFileLinesReader(file, delimOpt, hadoopConf)
 
       reader.map(_.toString)
-    }.flatten
+    }
 
     lines
   }