[GLUTEN-4594][SUB-3] Refactor Gluten Spark34 Unit Test (apache#4744)

gluten-ut/spark34/src/test/scala/io/glutenproject/utils/velox/VeloxTestSettings.scala

@@ -141,8 +141,8 @@ class VeloxTestSettings extends BackendTestSettings {
   enableSuite[GlutenSortOrderExpressionsSuite]
   enableSuite[GlutenStringExpressionsSuite]
   enableSuite[VeloxAdaptiveQueryExecSuite]
+    .includeAllGlutenTests()
     .includeByPrefix(
-      "gluten",
       "SPARK-29906",
       "SPARK-30291",
       "SPARK-30403",
@@ -299,9 +299,9 @@ class VeloxTestSettings extends BackendTestSettings {
     .exclude("appending insert")
     .exclude("overwrite insert")
     .exclude("SPARK-34897: Support reconcile schemas based on index after nested column pruning")
-    .exclude("Gluten - SPARK-31238: compatibility with Spark 2.4 in reading dates")
-    .exclude("Gluten - SPARK-31238, SPARK-31423: rebasing dates in write")
-    .exclude("Gluten - SPARK-34862: Support ORC vectorized reader for nested column")
+    .excludeGlutenTest("SPARK-31238: compatibility with Spark 2.4 in reading dates")
+    .excludeGlutenTest("SPARK-31238, SPARK-31423: rebasing dates in write")
+    .excludeGlutenTest("SPARK-34862: Support ORC vectorized reader for nested column")
     // exclude as struct not supported
     .exclude("SPARK-36663: OrcUtils.toCatalystSchema should correctly handle a column name which consists of only numbers")
     .exclude("SPARK-37812: Reuse result row when deserializing a struct")
@@ -812,8 +812,8 @@ class VeloxTestSettings extends BackendTestSettings {
     .exclude("change column type from short to int/long")
     .exclude("change column type from int to long")
     .exclude("change column type from float to double")
-    .exclude("Gluten - read byte, int, short, long together")
-    .exclude("Gluten - read float and double together")
+    .excludeGlutenTest("read byte, int, short, long together")
+    .excludeGlutenTest("read float and double together")
   enableSuite[GlutenMergedOrcReadSchemaSuite]
     .exclude("append column into middle")
     .exclude("add a nested column at the end of the leaf struct column")

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenBloomFilterAggregateQuerySuite.scala

@@ -29,7 +29,7 @@ class GlutenBloomFilterAggregateQuerySuite
   with AdaptiveSparkPlanHelper {
   import testImplicits._
 
-  test("Test bloom_filter_agg with big RUNTIME_BLOOM_FILTER_MAX_NUM_ITEMS") {
+  testGluten("Test bloom_filter_agg with big RUNTIME_BLOOM_FILTER_MAX_NUM_ITEMS") {
     val table = "bloom_filter_test"
     withSQLConf(
       SQLConf.RUNTIME_BLOOM_FILTER_MAX_NUM_ITEMS.key -> "5000000",
@@ -55,7 +55,7 @@ class GlutenBloomFilterAggregateQuerySuite
     }
   }
 
-  test("Test that might_contain on bloom_filter_agg with empty input") {
+  testGluten("Test that might_contain on bloom_filter_agg with empty input") {
     checkAnswer(
       spark.sql("""SELECT might_contain((select bloom_filter_agg(cast(id as long))
                   | from range(1, 1)), cast(123 as long))""".stripMargin),
@@ -68,7 +68,7 @@ class GlutenBloomFilterAggregateQuerySuite
       Row(null))
   }
 
-  test("Test bloom_filter_agg fallback") {
+  testGluten("Test bloom_filter_agg fallback") {
     val table = "bloom_filter_test"
     val numEstimatedItems = 5000000L
     val numBits = GlutenConfig.getConf.veloxBloomFilterMaxNumBits

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenCachedTableSuite.scala

@@ -33,7 +33,7 @@ class GlutenCachedTableSuite
     super.sparkConf.set(GlutenConfig.COLUMNAR_TABLE_CACHE_ENABLED.key, "true")
   }
 
-  test("GLUTEN - InMemoryRelation statistics") {
+  testGluten("InMemoryRelation statistics") {
     sql("CACHE TABLE testData")
     spark.table("testData").queryExecution.withCachedData.collect {
       case cached: InMemoryRelation =>

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenComplexTypesSuite.scala

@@ -47,9 +47,7 @@ class GlutenComplexTypesSuite extends ComplexTypesSuite with GlutenSQLTestsTrait
     }
   }
 
-  test(
-    GlutenTestConstants.GLUTEN_TEST +
-      "types bool/byte/short/float/double/decimal/binary/map/array/struct") {
+  testGluten("types bool/byte/short/float/double/decimal/binary/map/array/struct") {
     val df = spark
       .table("tab_types")
       .selectExpr(

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDataFrameAggregateSuite.scala

@@ -35,7 +35,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
 
   // blackTestNameList is defined in ClickHouseNotSupport
 
-  test(GLUTEN_TEST + "count") {
+  testGluten("count") {
     // agg with no input col
     assert(testData2.count() === testData2.rdd.map(_ => 1).count())
 
@@ -44,7 +44,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
       Row(6, 6.0))
   }
 
-  test(GLUTEN_TEST + "null count") {
+  testGluten("null count") {
     checkAnswer(testData3.groupBy($"a").agg(count($"b")), Seq(Row(1, 0), Row(2, 1)))
 
     checkAnswer(testData3.groupBy($"a").agg(count($"a" + $"b")), Seq(Row(1, 0), Row(2, 1)))
@@ -61,7 +61,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
 //    )
   }
 
-  test(GLUTEN_TEST + "groupBy") {
+  testGluten("groupBy") {
     checkAnswer(testData2.groupBy("a").agg(sum($"b")), Seq(Row(1, 3), Row(2, 3), Row(3, 3)))
     checkAnswer(testData2.groupBy("a").agg(sum($"b").as("totB")).agg(sum($"totB")), Row(9))
     checkAnswer(testData2.groupBy("a").agg(count("*")), Row(1, 2) :: Row(2, 2) :: Row(3, 2) :: Nil)
@@ -103,7 +103,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
 //    )
   }
 
-  test(GLUTEN_TEST + "average") {
+  testGluten("average") {
 
     checkAnswer(testData2.agg(avg($"a"), mean($"a")), Row(2.0, 2.0))
 
@@ -130,7 +130,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
 //      Row(new java.math.BigDecimal(2), new java.math.BigDecimal(6)) :: Nil)
   }
 
-  ignore("gluten SPARK-32038: NormalizeFloatingNumbers should work on distinct aggregate") {
+  ignore(GLUTEN_TEST + "SPARK-32038: NormalizeFloatingNumbers should work on distinct aggregate") {
     withTempView("view") {
       Seq(
         ("mithunr", Float.NaN),
@@ -144,14 +144,14 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
     }
   }
 
-  test(GLUTEN_TEST + "variance") {
+  testGluten("variance") {
     checkAnswer(
       testData2.agg(var_samp($"a"), var_pop($"a"), variance($"a")),
       Row(0.8, 2.0 / 3.0, 0.8))
     checkAnswer(testData2.agg(var_samp("a"), var_pop("a"), variance("a")), Row(0.8, 2.0 / 3.0, 0.8))
   }
 
-  test("aggregation with filter") {
+  testGluten("aggregation with filter") {
     Seq(
       ("mithunr", 12.3f, 5.0f, true, 9.4f),
       ("mithunr", 15.5f, 4.0f, false, 19.9f),
@@ -175,7 +175,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
     checkAnswer(df, Row(2) :: Nil)
   }
 
-  test(GLUTEN_TEST + "extend with cast expression") {
+  testGluten("extend with cast expression") {
     checkAnswer(
       decimalData.agg(
         sum($"a".cast("double")),
@@ -186,7 +186,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
   }
 
   // This test is applicable to velox backend. For CH backend, the replacement is disabled.
-  test(GLUTEN_TEST + "use gluten hash agg to replace vanilla spark sort agg") {
+  testGluten("use gluten hash agg to replace vanilla spark sort agg") {
 
     withSQLConf(("spark.gluten.sql.columnar.force.hashagg", "false")) {
       Seq("A", "B", "C", "D").toDF("col1").createOrReplaceTempView("t1")
@@ -207,7 +207,7 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
     }
   }
 
-  test("mixed supported and unsupported aggregate functions") {
+  testGluten("mixed supported and unsupported aggregate functions") {
     withUserDefinedFunction(("udaf_sum", true)) {
       spark.udf.register(
         "udaf_sum",
@@ -273,8 +273,8 @@ class GlutenDataFrameAggregateSuite extends DataFrameAggregateSuite with GlutenS
     }
   }
 
-  test(
-    GLUTEN_TEST + "SPARK-19471: AggregationIterator does not initialize the generated" +
+  testGluten(
+    "SPARK-19471: AggregationIterator does not initialize the generated" +
       " result projection before using it") {
     Seq(
       monotonically_increasing_id(),

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDataFramePivotSuite.scala

@@ -23,7 +23,7 @@ class GlutenDataFramePivotSuite extends DataFramePivotSuite with GlutenSQLTestsT
   // This test is ported from vanilla spark with pos value (1-based) changed from 0 to 1 for
   // substring. In vanilla spark, pos=0 has same effectiveness as pos=1. But in velox, pos=0
   // will return an empty string as substring result.
-  test("pivot with column definition in groupby - using pos=1") {
+  testGluten("pivot with column definition in groupby - using pos=1") {
     val df = courseSales
       .groupBy(substring(col("course"), 1, 1).as("foo"))
       .pivot("year", Seq(2012, 2013))

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDataFrameSuite.scala

@@ -19,7 +19,6 @@ package org.apache.spark.sql
 import io.glutenproject.execution.{ProjectExecTransformer, WholeStageTransformer}
 
 import org.apache.spark.SparkException
-import org.apache.spark.sql.GlutenTestConstants.GLUTEN_TEST
 import org.apache.spark.sql.catalyst.expressions.{EqualTo, Expression}
 import org.apache.spark.sql.execution.ColumnarShuffleExchangeExec
 import org.apache.spark.sql.execution.aggregate.HashAggregateExec
@@ -35,7 +34,7 @@ import scala.util.Random
 
 class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
 
-  test(GlutenTestConstants.GLUTEN_TEST + "repartitionByRange") {
+  testGluten("repartitionByRange") {
     val partitionNum = 10
     withSQLConf(
       SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "false",
@@ -94,7 +93,7 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
     }
   }
 
-  test(GlutenTestConstants.GLUTEN_TEST + "distributeBy and localSort") {
+  testGluten("distributeBy and localSort") {
     import testImplicits._
     val data = spark.sparkContext.parallelize((1 to 100).map(i => TestData2(i % 10, i))).toDF()
 
@@ -210,7 +209,7 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
     }
   }
 
-  test(GLUTEN_TEST + "reuse exchange") {
+  testGluten("reuse exchange") {
     withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "2") {
       val df = spark.range(100).toDF()
       val join = df.join(df, "id")
@@ -237,7 +236,7 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
   }
 
   /** Failed to check WholeStageCodegenExec, so we rewrite the UT. */
-  test(GLUTEN_TEST + "SPARK-22520: support code generation for large CaseWhen") {
+  testGluten("SPARK-22520: support code generation for large CaseWhen") {
     import org.apache.spark.sql.catalyst.dsl.expressions.StringToAttributeConversionHelper
     val N = 30
     var expr1 = when(equalizer($"id", lit(0)), 0)
@@ -261,7 +260,7 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
     ("David", 60, 192),
     ("Amy", 24, 180)).toDF("name", "age", "height")
 
-  test(GLUTEN_TEST + "describe") {
+  testGluten("describe") {
     val describeResult = Seq(
       Row("count", "4", "4", "4"),
       Row("mean", null, "33.0", "178.0"),
@@ -323,9 +322,7 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
     }
   }
 
-  test(
-    GLUTEN_TEST +
-      "Allow leading/trailing whitespace in string before casting") {
+  testGluten("Allow leading/trailing whitespace in string before casting") {
     def checkResult(df: DataFrame, expectedResult: Seq[Row]): Unit = {
       checkAnswer(df, expectedResult)
       assert(find(df.queryExecution.executedPlan)(_.isInstanceOf[ProjectExecTransformer]).isDefined)

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDataFrameTungstenSuite.scala

@@ -20,7 +20,7 @@ import org.apache.spark.sql.types._
 
 class GlutenDataFrameTungstenSuite extends DataFrameTungstenSuite with GlutenSQLTestsTrait {
 
-  test("Map type with struct type as key") {
+  testGluten("Map type with struct type as key") {
     val kv = Map(Row(1, 2L) -> Seq("v"))
     val data = sparkContext.parallelize(Seq(Row(1, kv)))
     val schema = new StructType()

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDataFrameWindowFunctionsSuite.scala

@@ -16,7 +16,6 @@
  */
 package org.apache.spark.sql
 
-import org.apache.spark.sql.GlutenTestConstants.GLUTEN_TEST
 import org.apache.spark.sql.expressions.Window
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.internal.SQLConf
@@ -27,9 +26,7 @@ class GlutenDataFrameWindowFunctionsSuite
 
   import testImplicits._
 
-  test(
-    GLUTEN_TEST +
-      "covar_samp, var_samp (variance), stddev_samp (stddev) functions in specific window") {
+  testGluten("covar_samp, var_samp (variance), stddev_samp (stddev) functions in specific window") {
     withSQLConf(SQLConf.LEGACY_STATISTICAL_AGGREGATE.key -> "true") {
       val df = Seq(
         ("a", "p1", 10.0, 20.0),
@@ -84,7 +81,7 @@ class GlutenDataFrameWindowFunctionsSuite
     }
   }
 
-  test(GLUTEN_TEST + "corr, covar_pop, stddev_pop functions in specific window") {
+  testGluten("corr, covar_pop, stddev_pop functions in specific window") {
     withSQLConf(SQLConf.LEGACY_STATISTICAL_AGGREGATE.key -> "true") {
       val df = Seq(
         ("a", "p1", 10.0, 20.0),

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDatasetSuite.scala

@@ -21,7 +21,7 @@ import org.apache.spark.sql.execution.ColumnarShuffleExchangeExec
 class GlutenDatasetSuite extends DatasetSuite with GlutenSQLTestsTrait {
   import testImplicits._
 
-  test("Gluten: dropDuplicates: columns with same column name") {
+  testGluten("dropDuplicates: columns with same column name") {
     val ds1 = Seq(("a", 1), ("a", 2), ("b", 1), ("a", 1)).toDS()
     val ds2 = Seq(("a", 1), ("a", 2), ("b", 1), ("a", 1)).toDS()
     // The dataset joined has two columns of the same name "_2".
@@ -30,7 +30,7 @@ class GlutenDatasetSuite extends DatasetSuite with GlutenSQLTestsTrait {
     checkDatasetUnorderly(joined.dropDuplicates(), (1, 2), (1, 1), (2, 1), (2, 2))
   }
 
-  test("Gluten: groupBy.as") {
+  testGluten("groupBy.as") {
     val df1 = Seq(DoubleData(1, "one"), DoubleData(2, "two"), DoubleData(3, "three"))
       .toDS()
       .repartition($"id")

gluten-ut/spark34/src/test/scala/org/apache/spark/sql/GlutenDateFunctionsSuite.scala

@@ -16,7 +16,6 @@
  */
 package org.apache.spark.sql
 
-import org.apache.spark.sql.GlutenTestConstants.GLUTEN_TEST
 import org.apache.spark.sql.catalyst.util.DateTimeUtils
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.internal.SQLConf
@@ -30,7 +29,7 @@ class GlutenDateFunctionsSuite extends DateFunctionsSuite with GlutenSQLTestsTra
 
   private def secs(millis: Long): Long = TimeUnit.MILLISECONDS.toSeconds(millis)
 
-  test(GLUTEN_TEST + "unix_timestamp") {
+  testGluten("unix_timestamp") {
     Seq("corrected", "legacy").foreach {
       legacyParserPolicy =>
         withSQLConf(
@@ -143,7 +142,7 @@ class GlutenDateFunctionsSuite extends DateFunctionsSuite with GlutenSQLTestsTra
     }
   }
 
-  test(GLUTEN_TEST + "to_unix_timestamp") {
+  testGluten("to_unix_timestamp") {
     Seq("corrected", "legacy").foreach {
       legacyParserPolicy =>
         withSQLConf(
@@ -207,7 +206,7 @@ class GlutenDateFunctionsSuite extends DateFunctionsSuite with GlutenSQLTestsTra
   }
 
   // Ported from spark with a test case for legacy mode removed.
-  test(GLUTEN_TEST + "to_timestamp") {
+  testGluten("to_timestamp") {
     Seq("legacy", "corrected").foreach {
       legacyParserPolicy =>
         withSQLConf(SQLConf.LEGACY_TIME_PARSER_POLICY.key -> legacyParserPolicy) {