[SPARK-25610][SQL][TEST] Improve execution time of DatasetCacheSuite: cache UDF result correctly

## What changes were proposed in this pull request?
In this test case, we are verifying that the result of an UDF  is cached when the underlying data frame is cached and that the udf is not evaluated again when the cached data frame is used.

To reduce the runtime we do :
1) Use a single partition dataframe, so the total execution time of UDF is more deterministic.
2) Cut down the size of the dataframe from 10 to 2.
3) Reduce the sleep time in the UDF from 5secs to 2secs.
4) Reduce the failafter condition from 3 to 2.

With the above change, it takes about 4 secs to cache the first dataframe. And subsequent check takes a few hundred milliseconds.
The new runtime for 5 consecutive runs of this test is as follows :
```
[info] - cache UDF result correctly (4 seconds, 906 milliseconds)
[info] - cache UDF result correctly (4 seconds, 281 milliseconds)
[info] - cache UDF result correctly (4 seconds, 288 milliseconds)
[info] - cache UDF result correctly (4 seconds, 355 milliseconds)
[info] - cache UDF result correctly (4 seconds, 280 milliseconds)
```
## How was this patch tested?
This is s test fix.

Closes #22638 from dilipbiswal/SPARK-25610.

Authored-by: Dilip Biswal <dbiswal@us.ibm.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>

Author: dilipbiswal

sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala

@@ -127,16 +127,16 @@ class DatasetCacheSuite extends QueryTest with SharedSQLContext with TimeLimits
   }
 
   test("cache UDF result correctly") {
-    val expensiveUDF = udf({x: Int => Thread.sleep(5000); x})
-    val df = spark.range(0, 10).toDF("a").withColumn("b", expensiveUDF($"a"))
+    val expensiveUDF = udf({x: Int => Thread.sleep(2000); x})
+    val df = spark.range(0, 2).toDF("a").repartition(1).withColumn("b", expensiveUDF($"a"))
     val df2 = df.agg(sum(df("b")))
 
     df.cache()
     df.count()
     assertCached(df2)
 
     // udf has been evaluated during caching, and thus should not be re-evaluated here
-    failAfter(3 seconds) {
+    failAfter(2 seconds) {
       df2.collect()
     }