[SPARK-18338][SQL][TEST-MAVEN] Fix test case initialization order under Maven builds

## What changes were proposed in this pull request?

Test case initialization order under Maven and SBT are different. Maven always creates instances of all test cases and then run them all together.

This fails `ObjectHashAggregateSuite` because the randomized test cases there register a temporary Hive function right before creating a test case, and can be cleared while initializing other successive test cases. In SBT, this is fine since the created test case is executed immediately after creating the temporary function.

To fix this issue, we should put initialization/destruction code into `beforeAll()` and `afterAll()`.

## How was this patch tested?

Existing tests.

Author: Cheng Lian <lian@databricks.com>

Closes #15802 from liancheng/fix-flaky-object-hash-agg-suite.

1 files changed, 10 insertions, 13 deletions

diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
index 527626beeb..93fc5e8a5e 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
@@ -25,11 +25,10 @@ import org.scalatest.Matchers._
 import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.FunctionIdentifier
 import org.apache.spark.sql.catalyst.analysis.UnresolvedFunction
-import org.apache.spark.sql.catalyst.expressions.{ExpressionEvalHelper, ExpressionInfo, Literal}
+import org.apache.spark.sql.catalyst.expressions.{ExpressionEvalHelper, Literal}
 import org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile
 import org.apache.spark.sql.execution.aggregate.{HashAggregateExec, ObjectHashAggregateExec, SortAggregateExec}
 import org.apache.spark.sql.functions._
-import org.apache.spark.sql.hive.HiveSessionCatalog
 import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SQLTestUtils
@@ -43,6 +42,14 @@ class ObjectHashAggregateSuite
 
   import testImplicits._
 
+  protected override def beforeAll(): Unit = {
+    sql(s"CREATE TEMPORARY FUNCTION hive_max AS '${classOf[GenericUDAFMax].getName}'")
+  }
+
+  protected override def afterAll(): Unit = {
+    sql(s"DROP TEMPORARY FUNCTION IF EXISTS hive_max")
+  }
+
   test("typed_count without grouping keys") {
     val df = Seq((1: Integer, 2), (null, 2), (3: Integer, 4)).toDF("a", "b")
 
@@ -199,10 +206,7 @@ class ObjectHashAggregateSuite
     val typed = percentile_approx($"c0", 0.5)
 
     // A Hive UDAF without partial aggregation support
-    val withoutPartial = {
-      registerHiveFunction("hive_max", classOf[GenericUDAFMax])
-      function("hive_max", $"c1")
-    }
+    val withoutPartial = function("hive_max", $"c1")
 
     // A Spark SQL native aggregate function with partial aggregation support that can be executed
     // by the Tungsten `HashAggregateExec`
@@ -420,13 +424,6 @@ class ObjectHashAggregateSuite
     }
   }
 
-  private def registerHiveFunction(functionName: String, clazz: Class[_]): Unit = {
-    val sessionCatalog = spark.sessionState.catalog.asInstanceOf[HiveSessionCatalog]
-    val builder = sessionCatalog.makeFunctionBuilder(functionName, clazz.getName)
-    val info = new ExpressionInfo(clazz.getName, functionName)
-    sessionCatalog.createTempFunction(functionName, info, builder, ignoreIfExists = false)
-  }
-
   private def function(name: String, args: Column*): Column = {
     Column(UnresolvedFunction(FunctionIdentifier(name), args.map(_.expr), isDistinct = false))
   }