[MINOR][DOCS][SQL] Fix some comments about types(TypeCoercion,Partition) and exceptions.

## What changes were proposed in this pull request?

This PR contains a few changes on code comments.
- `HiveTypeCoercion` is renamed into `TypeCoercion`.
- `NoSuchDatabaseException` is only used for the absence of database.
- For partition type inference, only `DoubleType` is considered.

## How was this patch tested?

N/A

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #13674 from dongjoon-hyun/minor_doc_types.

4 files changed, 5 insertions, 5 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
index 16df628a57..baec6d14a2 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
@@ -73,7 +73,7 @@ object TypeCoercion {
       DoubleType)
 
   /**
-   * Case 1 type widening (see the classdoc comment above for HiveTypeCoercion).
+   * Case 1 type widening (see the classdoc comment above for TypeCoercion).
    *
    * Find the tightest common type of two types that might be used in a binary expression.
    * This handles all numeric types except fixed-precision decimals interacting with each other or
@@ -132,7 +132,7 @@ object TypeCoercion {
   }
 
   /**
-   * Case 2 type widening (see the classdoc comment above for HiveTypeCoercion).
+   * Case 2 type widening (see the classdoc comment above for TypeCoercion).
    *
    * i.e. the main difference with [[findTightestCommonTypeOfTwo]] is that here we allow some
    * loss of precision when widening decimal and double.
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalog.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalog.scala
index 81974b282b..6714846e8c 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalog.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalog.scala
@@ -27,7 +27,7 @@ import org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException
  * can be accessed in multiple threads. This is an external catalog because it is expected to
  * interact with external systems.
  *
- * Implementations should throw [[NoSuchDatabaseException]] when table or database don't exist.
+ * Implementations should throw [[NoSuchDatabaseException]] when databases don't exist.
  */
 abstract class ExternalCatalog {
   import CatalogTypes.TablePartitionSpec
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala
index 52e021070e..cc8175c0a3 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala
@@ -322,7 +322,7 @@ final class Decimal extends Ordered[Decimal] with Serializable {
     }
   }
 
-  // HiveTypeCoercion will take care of the precision, scale of result
+  // TypeCoercion will take care of the precision, scale of result
   def * (that: Decimal): Decimal =
     Decimal(toJavaBigDecimal.multiply(that.toJavaBigDecimal, MATH_CONTEXT))
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
index 2340ff0afe..388df7002d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
@@ -159,7 +159,7 @@ private[sql] object PartitioningUtils {
    *     Seq(
    *       Literal.create(42, IntegerType),
    *       Literal.create("hello", StringType),
-   *       Literal.create(3.14, FloatType)))
+   *       Literal.create(3.14, DoubleType)))
    * }}}
    * and the path when we stop the discovery is:
    * {{{