Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/9190#discussion_r42960493
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -0,0 +1,392 @@
+/*
+ * 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
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.encoders._
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.types.StructType
+
+/**
+ * A [[Dataset]] is a strongly typed collection of objects that can be
transformed in parallel
+ * using functional or relational operations.
+ *
+ * A [[Dataset]] differs from an [[RDD]] in the following ways:
+ * - Internally, a [[Dataset]] is represented by a Catalyst logical plan
and the data is stored
+ * in the encoded form. This representation allows for additional
logical operations and
+ * enables many operations (sorting, shuffling, etc.) to be performed
without deserializing to
+ * an object.
+ * - The creation of a [[Dataset]] requires the presence of an explicit
[[Encoder]] that can be
+ * used to serialize the object into a binary format. Encoders are
also capable of mapping the
+ * schema of a given object to the Spark SQL type system. In contrast,
RDDs rely on runtime
+ * reflection based serialization. Operations that change the type of
object stored in the
+ * dataset also need an encoder for the new type.
+ *
+ * A [[Dataset]] can be thought of as a specialized DataFrame, where the
elements map to a specific
+ * JVM object type, instead of to a generic [[Row]] container. A DataFrame
can be transformed into
+ * specific Dataset by calling `df.as[ElementType]`. Similarly you can
transform a strongly-typed
+ * [[Dataset]] to a generic DataFrame by calling `ds.toDF()`.
+ *
+ * COMPATIBILITY NOTE: Long term we plan to make [[DataFrame]] extend
`Dataset[Row]`. However,
+ * making this change to the class hierarchy would break the function
signatures for the existing
+ * functional operations (map, flatMap, etc). As such, this class should
be considered a preview
+ * of the final API. Changes will be made to the interface after Spark
1.6.
+ *
+ * @since 1.6.0
+ */
+@Experimental
+class Dataset[T] private[sql](
+ @transient val sqlContext: SQLContext,
+ @transient val queryExecution: QueryExecution)(
--- End diff --
Will `sqlContext` and `queryExecution.sqlContext` different?
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