Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/7175#discussion_r33748103
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/AbstractDataType.scala
---
@@ -0,0 +1,116 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.types
+
+import scala.reflect.ClassTag
+import scala.reflect.runtime.universe.{TypeTag, runtimeMirror}
+
+import org.apache.spark.sql.catalyst.ScalaReflectionLock
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.util.Utils
+
+/**
+ * A non-concrete data type, reserved for internal uses.
+ */
+private[sql] abstract class AbstractDataType {
+ def defaultConcreteType: DataType
+}
+
+
+/**
+ * An internal type used to represent everything that is not null, UDTs,
arrays, structs, and maps.
+ */
+protected[sql] abstract class AtomicType extends DataType {
+ private[sql] type InternalType
+ @transient private[sql] val tag: TypeTag[InternalType]
+ private[sql] val ordering: Ordering[InternalType]
+
+ @transient private[sql] val classTag = ScalaReflectionLock.synchronized {
+ val mirror = runtimeMirror(Utils.getSparkClassLoader)
+ ClassTag[InternalType](mirror.runtimeClass(tag.tpe))
+ }
+}
+
+
+/**
+ * :: DeveloperApi ::
+ * Numeric data types.
+ *
+ * @group dataType
+ */
+abstract class NumericType extends AtomicType {
+ // Unfortunately we can't get this implicitly as that breaks Spark
Serialization. In order for
+ // implicitly[Numeric[JvmType]] to be valid, we have to change JvmType
from a type variable to a
+ // type parameter and add a numeric annotation (i.e., [JvmType :
Numeric]). This gets
+ // desugared by the compiler into an argument to the objects
constructor. This means there is no
+ // longer an no argument constructor and thus the JVM cannot serialize
the object anymore.
+ private[sql] val numeric: Numeric[InternalType]
+}
+
+
+private[sql] object NumericType extends AbstractDataType {
+ /**
+ * Enables matching against NumericType for expressions:
+ * {{{
+ * case Cast(child @ NumericType(), StringType) =>
+ * ...
+ * }}}
+ */
+ def unapply(e: Expression): Boolean =
e.dataType.isInstanceOf[NumericType]
+
+ override def defaultConcreteType: DataType = IntegerType
--- End diff --
Most of the rule seems like to be:
DecimalType => DecimalType
FractionalType => DoubleType
LongType => LongType
IntegralType => IntegerType
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
