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diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLWindowFunctionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLWindowFunctionSuite.scala
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+/*
+ * 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.hive.execution
+
+import org.apache.spark.sql.{AnalysisException, QueryTest, Row}
+import org.apache.spark.sql.hive.test.TestHiveSingleton
+import org.apache.spark.sql.test.SQLTestUtils
+
+
+case class WindowData(month: Int, area: String, product: Int)
+
+
+/**
+ * Test suite for SQL window functions.
+ */
+class SQLWindowFunctionSuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
+  import hiveContext.implicits._
+
+  test("window function: udaf with aggregate expression") {
+    val data = Seq(
+      WindowData(1, "a", 5),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 10)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product), sum(sum(product)) over (partition by area)
+          |from windowData group by month, area
+        """.stripMargin),
+      Seq(
+        ("a", 5, 11),
+        ("a", 6, 11),
+        ("b", 7, 15),
+        ("b", 8, 15),
+        ("c", 9, 19),
+        ("c", 10, 19)
+      ).map(i => Row(i._1, i._2, i._3)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product) - 1, sum(sum(product)) over (partition by area)
+          |from windowData group by month, area
+        """.stripMargin),
+      Seq(
+        ("a", 4, 11),
+        ("a", 5, 11),
+        ("b", 6, 15),
+        ("b", 7, 15),
+        ("c", 8, 19),
+        ("c", 9, 19)
+      ).map(i => Row(i._1, i._2, i._3)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product), sum(product) / sum(sum(product)) over (partition by area)
+          |from windowData group by month, area
+        """.stripMargin),
+      Seq(
+        ("a", 5, 5d/11),
+        ("a", 6, 6d/11),
+        ("b", 7, 7d/15),
+        ("b", 8, 8d/15),
+        ("c", 10, 10d/19),
+        ("c", 9, 9d/19)
+      ).map(i => Row(i._1, i._2, i._3)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product), sum(product) / sum(sum(product) - 1) over (partition by area)
+          |from windowData group by month, area
+        """.stripMargin),
+      Seq(
+        ("a", 5, 5d/9),
+        ("a", 6, 6d/9),
+        ("b", 7, 7d/13),
+        ("b", 8, 8d/13),
+        ("c", 10, 10d/17),
+        ("c", 9, 9d/17)
+      ).map(i => Row(i._1, i._2, i._3)))
+  }
+
+  test("window function: refer column in inner select block") {
+    val data = Seq(
+      WindowData(1, "a", 5),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 10)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select area, rank() over (partition by area order by tmp.month) + tmp.tmp1 as c1
+          |from (select month, area, product, 1 as tmp1 from windowData) tmp
+        """.stripMargin),
+      Seq(
+        ("a", 2),
+        ("a", 3),
+        ("b", 2),
+        ("b", 3),
+        ("c", 2),
+        ("c", 3)
+      ).map(i => Row(i._1, i._2)))
+  }
+
+  test("window function: partition and order expressions") {
+    val data = Seq(
+      WindowData(1, "a", 5),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 10)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select month, area, product, sum(product + 1) over (partition by 1 order by 2)
+          |from windowData
+        """.stripMargin),
+      Seq(
+        (1, "a", 5, 51),
+        (2, "a", 6, 51),
+        (3, "b", 7, 51),
+        (4, "b", 8, 51),
+        (5, "c", 9, 51),
+        (6, "c", 10, 51)
+      ).map(i => Row(i._1, i._2, i._3, i._4)))
+
+    checkAnswer(
+      sql(
+        """
+          |select month, area, product, sum(product)
+          |over (partition by month % 2 order by 10 - product)
+          |from windowData
+        """.stripMargin),
+      Seq(
+        (1, "a", 5, 21),
+        (2, "a", 6, 24),
+        (3, "b", 7, 16),
+        (4, "b", 8, 18),
+        (5, "c", 9, 9),
+        (6, "c", 10, 10)
+      ).map(i => Row(i._1, i._2, i._3, i._4)))
+  }
+
+  test("window function: distinct should not be silently ignored") {
+    val data = Seq(
+      WindowData(1, "a", 5),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 10)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    val e = intercept[AnalysisException] {
+      sql(
+        """
+          |select month, area, product, sum(distinct product + 1) over (partition by 1 order by 2)
+          |from windowData
+        """.stripMargin)
+    }
+    assert(e.getMessage.contains("Distinct window functions are not supported"))
+  }
+
+  test("window function: expressions in arguments of a window functions") {
+    val data = Seq(
+      WindowData(1, "a", 5),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 10)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select month, area, month % 2,
+          |lag(product, 1 + 1, product) over (partition by month % 2 order by area)
+          |from windowData
+        """.stripMargin),
+      Seq(
+        (1, "a", 1, 5),
+        (2, "a", 0, 6),
+        (3, "b", 1, 7),
+        (4, "b", 0, 8),
+        (5, "c", 1, 5),
+        (6, "c", 0, 6)
+      ).map(i => Row(i._1, i._2, i._3, i._4)))
+  }
+
+
+  test("window function: Sorting columns are not in Project") {
+    val data = Seq(
+      WindowData(1, "d", 10),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 11)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql("select month, product, sum(product + 1) over() from windowData order by area"),
+      Seq(
+        (2, 6, 57),
+        (3, 7, 57),
+        (4, 8, 57),
+        (5, 9, 57),
+        (6, 11, 57),
+        (1, 10, 57)
+      ).map(i => Row(i._1, i._2, i._3)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, rank() over (partition by area order by tmp.month) + tmp.tmp1 as c1
+          |from (select month, area, product as p, 1 as tmp1 from windowData) tmp order by p
+        """.stripMargin),
+      Seq(
+        ("a", 2),
+        ("b", 2),
+        ("b", 3),
+        ("c", 2),
+        ("d", 2),
+        ("c", 3)
+      ).map(i => Row(i._1, i._2)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, rank() over (partition by area order by month) as c1
+          |from windowData group by product, area, month order by product, area
+        """.stripMargin),
+      Seq(
+        ("a", 1),
+        ("b", 1),
+        ("b", 2),
+        ("c", 1),
+        ("d", 1),
+        ("c", 2)
+      ).map(i => Row(i._1, i._2)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product) / sum(sum(product)) over (partition by area) as c1
+          |from windowData group by area, month order by month, c1
+        """.stripMargin),
+      Seq(
+        ("d", 1.0),
+        ("a", 1.0),
+        ("b", 0.4666666666666667),
+        ("b", 0.5333333333333333),
+        ("c", 0.45),
+        ("c", 0.55)
+      ).map(i => Row(i._1, i._2)))
+  }
+
+  // todo: fix this test case by reimplementing the function ResolveAggregateFunctions
+  ignore("window function: Pushing aggregate Expressions in Sort to Aggregate") {
+    val data = Seq(
+      WindowData(1, "d", 10),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 11)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product) over () as c from windowData
+          |where product > 3 group by area, product
+          |having avg(month) > 0 order by avg(month), product
+        """.stripMargin),
+      Seq(
+        ("a", 51),
+        ("b", 51),
+        ("b", 51),
+        ("c", 51),
+        ("c", 51),
+        ("d", 51)
+      ).map(i => Row(i._1, i._2)))
+  }
+
+  test("window function: multiple window expressions in a single expression") {
+    val nums = sparkContext.parallelize(1 to 10).map(x => (x, x % 2)).toDF("x", "y")
+    nums.registerTempTable("nums")
+
+    val expected =
+      Row(1, 1, 1, 55, 1, 57) ::
+        Row(0, 2, 3, 55, 2, 60) ::
+        Row(1, 3, 6, 55, 4, 65) ::
+        Row(0, 4, 10, 55, 6, 71) ::
+        Row(1, 5, 15, 55, 9, 79) ::
+        Row(0, 6, 21, 55, 12, 88) ::
+        Row(1, 7, 28, 55, 16, 99) ::
+        Row(0, 8, 36, 55, 20, 111) ::
+        Row(1, 9, 45, 55, 25, 125) ::
+        Row(0, 10, 55, 55, 30, 140) :: Nil
+
+    val actual = sql(
+      """
+        |SELECT
+        |  y,
+        |  x,
+        |  sum(x) OVER w1 AS running_sum,
+        |  sum(x) OVER w2 AS total_sum,
+        |  sum(x) OVER w3 AS running_sum_per_y,
+        |  ((sum(x) OVER w1) + (sum(x) OVER w2) + (sum(x) OVER w3)) as combined2
+        |FROM nums
+        |WINDOW w1 AS (ORDER BY x ROWS BETWEEN UnBOUNDED PRECEDiNG AND CuRRENT RoW),
+        |       w2 AS (ORDER BY x ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOuNDED FoLLOWING),
+        |       w3 AS (PARTITION BY y ORDER BY x ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
+      """.stripMargin)
+
+    checkAnswer(actual, expected)
+
+    sqlContext.dropTempTable("nums")
+  }
+
+  test("SPARK-7595: Window will cause resolve failed with self join") {
+    sql("SELECT * FROM src") // Force loading of src table.
+
+    checkAnswer(sql(
+      """
+        |with
+        | v1 as (select key, count(value) over (partition by key) cnt_val from src),
+        | v2 as (select v1.key, v1_lag.cnt_val from v1, v1 v1_lag where v1.key = v1_lag.key)
+        | select * from v2 order by key limit 1
+      """.stripMargin), Row(0, 3))
+  }
+}