[SPARK-16355][SPARK-16354][SQL] Fix Bugs When LIMIT/TABLESAMPLE is Non-foldable, Zero or Negative

#### What changes were proposed in this pull request?
**Issue 1:** When a query containing LIMIT/TABLESAMPLE 0, the statistics could be zero. Results are correct but it could cause a huge performance regression. For example,
```Scala
Seq(("one", 1), ("two", 2), ("three", 3), ("four", 4)).toDF("k", "v")
  .createOrReplaceTempView("test")
val df1 = spark.table("test")
val df2 = spark.table("test").limit(0)
val df = df1.join(df2, Seq("k"), "left")
```
The statistics of both `df` and `df2` are zero. The statistics values should never be zero; otherwise `sizeInBytes` of `BinaryNode` will also be zero (product of children). This PR is to increase it to `1` when the num of rows is equal to 0.

**Issue 2:** When a query containing negative LIMIT/TABLESAMPLE, we should issue exceptions. Negative values could break the implementation assumption of multiple parts. For example, statistics calculation.  Below is the example query.
```SQL
SELECT * FROM testData TABLESAMPLE (-1 rows)
SELECT * FROM testData LIMIT -1
```
This PR is to issue an appropriate exception in this case.

**Issue 3:** Spark SQL follows the restriction of LIMIT clause in Hive. The argument to the LIMIT clause must evaluate to a constant value. It can be a numeric literal, or another kind of numeric expression involving operators, casts, and function return values. You cannot refer to a column or use a subquery. Currently, we do not detect whether the expression in LIMIT clause is foldable or not. If non-foldable, we might issue a strange error message. For example,
```SQL
SELECT * FROM testData LIMIT rand() > 0.2
```
Then, a misleading error message is issued, like
```
assertion failed: No plan for GlobalLimit (_nondeterministic#203 > 0.2)
+- Project [key#11, value#12, rand(-1441968339187861415) AS _nondeterministic#203]
   +- LocalLimit (_nondeterministic#202 > 0.2)
      +- Project [key#11, value#12, rand(-1308350387169017676) AS _nondeterministic#202]
         +- LogicalRDD [key#11, value#12]

java.lang.AssertionError: assertion failed: No plan for GlobalLimit (_nondeterministic#203 > 0.2)
+- Project [key#11, value#12, rand(-1441968339187861415) AS _nondeterministic#203]
   +- LocalLimit (_nondeterministic#202 > 0.2)
      +- Project [key#11, value#12, rand(-1308350387169017676) AS _nondeterministic#202]
         +- LogicalRDD [key#11, value#12]
```
This PR detects it and then issues a meaningful error message.

#### How was this patch tested?
Added test cases.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #14034 from gatorsmile/limit.

2 files changed, 79 insertions, 2 deletions

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index dca9e5e503..ede7d9a0c9 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -660,11 +660,11 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
 
   test("limit") {
     checkAnswer(
-      sql("SELECT * FROM testData LIMIT 10"),
+      sql("SELECT * FROM testData LIMIT 9 + 1"),
       testData.take(10).toSeq)
 
     checkAnswer(
-      sql("SELECT * FROM arrayData LIMIT 1"),
+      sql("SELECT * FROM arrayData LIMIT CAST(1 AS Integer)"),
       arrayData.collect().take(1).map(Row.fromTuple).toSeq)
 
     checkAnswer(
@@ -672,6 +672,39 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
       mapData.collect().take(1).map(Row.fromTuple).toSeq)
   }
 
+  test("non-foldable expressions in LIMIT") {
+    val e = intercept[AnalysisException] {
+      sql("SELECT * FROM testData LIMIT key > 3")
+    }.getMessage
+    assert(e.contains("The limit expression must evaluate to a constant value, " +
+      "but got (testdata.`key` > 3)"))
+  }
+
+  test("Expressions in limit clause are not integer") {
+    var e = intercept[AnalysisException] {
+      sql("SELECT * FROM testData LIMIT true")
+    }.getMessage
+    assert(e.contains("The limit expression must be integer type, but got boolean"))
+
+    e = intercept[AnalysisException] {
+      sql("SELECT * FROM testData LIMIT 'a'")
+    }.getMessage
+    assert(e.contains("The limit expression must be integer type, but got string"))
+  }
+
+  test("negative in LIMIT or TABLESAMPLE") {
+    val expected = "The limit expression must be equal to or greater than 0, but got -1"
+    var e = intercept[AnalysisException] {
+      sql("SELECT * FROM testData TABLESAMPLE (-1 rows)")
+    }.getMessage
+    assert(e.contains(expected))
+
+    e = intercept[AnalysisException] {
+      sql("SELECT * FROM testData LIMIT -1")
+    }.getMessage
+    assert(e.contains(expected))
+  }
+
   test("CTE feature") {
     checkAnswer(
       sql("with q1 as (select * from testData limit 10) select * from q1"),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala
index 4de3cf605c..ab55242ec0 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/StatisticsSuite.scala
@@ -17,10 +17,12 @@
 
 package org.apache.spark.sql
 
+import org.apache.spark.sql.catalyst.plans.logical.{GlobalLimit, Join, LocalLimit}
 import org.apache.spark.sql.test.SharedSQLContext
 import org.apache.spark.sql.types._
 
 class StatisticsSuite extends QueryTest with SharedSQLContext {
+  import testImplicits._
 
   test("SPARK-15392: DataFrame created from RDD should not be broadcasted") {
     val rdd = sparkContext.range(1, 100).map(i => Row(i, i))
@@ -31,4 +33,46 @@ class StatisticsSuite extends QueryTest with SharedSQLContext {
       spark.sessionState.conf.autoBroadcastJoinThreshold)
   }
 
+  test("estimates the size of limit") {
+    withTempTable("test") {
+      Seq(("one", 1), ("two", 2), ("three", 3), ("four", 4)).toDF("k", "v")
+        .createOrReplaceTempView("test")
+      Seq((0, 1), (1, 24), (2, 48)).foreach { case (limit, expected) =>
+        val df = sql(s"""SELECT * FROM test limit $limit""")
+
+        val sizesGlobalLimit = df.queryExecution.analyzed.collect { case g: GlobalLimit =>
+          g.statistics.sizeInBytes
+        }
+        assert(sizesGlobalLimit.size === 1, s"Size wrong for:\n ${df.queryExecution}")
+        assert(sizesGlobalLimit.head === BigInt(expected),
+          s"expected exact size $expected for table 'test', got: ${sizesGlobalLimit.head}")
+
+        val sizesLocalLimit = df.queryExecution.analyzed.collect { case l: LocalLimit =>
+          l.statistics.sizeInBytes
+        }
+        assert(sizesLocalLimit.size === 1, s"Size wrong for:\n ${df.queryExecution}")
+        assert(sizesLocalLimit.head === BigInt(expected),
+          s"expected exact size $expected for table 'test', got: ${sizesLocalLimit.head}")
+      }
+    }
+  }
+
+  test("estimates the size of a limit 0 on outer join") {
+    withTempTable("test") {
+      Seq(("one", 1), ("two", 2), ("three", 3), ("four", 4)).toDF("k", "v")
+        .createOrReplaceTempView("test")
+      val df1 = spark.table("test")
+      val df2 = spark.table("test").limit(0)
+      val df = df1.join(df2, Seq("k"), "left")
+
+      val sizes = df.queryExecution.analyzed.collect { case g: Join =>
+        g.statistics.sizeInBytes
+      }
+
+      assert(sizes.size === 1, s"number of Join nodes is wrong:\n ${df.queryExecution}")
+      assert(sizes.head === BigInt(96),
+        s"expected exact size 96 for table 'test', got: ${sizes.head}")
+    }
+  }
+
 }