[SPARK-22159][SQL][FOLLOW-UP] Make config names consistently end with "enabled".

python/pyspark/sql/dataframe.py

@@ -1878,7 +1878,7 @@ def toPandas(self):
         1    5    Bob
         """
         import pandas as pd
-        if self.sql_ctx.getConf("spark.sql.execution.arrow.enable", "false").lower() == "true":
+        if self.sql_ctx.getConf("spark.sql.execution.arrow.enabled", "false").lower() == "true":
             try:
                 import pyarrow
                 tables = self._collectAsArrow()
@@ -1889,7 +1889,7 @@ def toPandas(self):
                     return pd.DataFrame.from_records([], columns=self.columns)
             except ImportError as e:
                 msg = "note: pyarrow must be installed and available on calling Python process " \
-                      "if using spark.sql.execution.arrow.enable=true"
+                      "if using spark.sql.execution.arrow.enabled=true"
                 raise ImportError("%s\n%s" % (e.message, msg))
         else:
             pdf = pd.DataFrame.from_records(self.collect(), columns=self.columns)

python/pyspark/sql/tests.py

@@ -3088,7 +3088,7 @@ class ArrowTests(ReusedPySparkTestCase):
     def setUpClass(cls):
         ReusedPySparkTestCase.setUpClass()
         cls.spark = SparkSession(cls.sc)
-        cls.spark.conf.set("spark.sql.execution.arrow.enable", "true")
+        cls.spark.conf.set("spark.sql.execution.arrow.enabled", "true")
         cls.schema = StructType([
             StructField("1_str_t", StringType(), True),
             StructField("2_int_t", IntegerType(), True),
@@ -3120,9 +3120,9 @@ def test_null_conversion(self):
 
     def test_toPandas_arrow_toggle(self):
         df = self.spark.createDataFrame(self.data, schema=self.schema)
-        self.spark.conf.set("spark.sql.execution.arrow.enable", "false")
+        self.spark.conf.set("spark.sql.execution.arrow.enabled", "false")
         pdf = df.toPandas()
-        self.spark.conf.set("spark.sql.execution.arrow.enable", "true")
+        self.spark.conf.set("spark.sql.execution.arrow.enabled", "true")
         pdf_arrow = df.toPandas()
         self.assertFramesEqual(pdf_arrow, pdf)
 

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala

@@ -539,7 +539,7 @@ case class HashAggregateExec(
   private def enableTwoLevelHashMap(ctx: CodegenContext) = {
     if (!checkIfFastHashMapSupported(ctx)) {
       if (modes.forall(mode => mode == Partial || mode == PartialMerge) && !Utils.isTesting) {
-        logInfo("spark.sql.codegen.aggregate.map.twolevel.enable is set to true, but"
+        logInfo("spark.sql.codegen.aggregate.map.twolevel.enabled is set to true, but"
           + " current version of codegened fast hashmap does not support this aggregate.")
       }
     } else {

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

@@ -24,29 +24,29 @@ import org.apache.spark.SparkConf
 class SingleLevelAggregateHashMapSuite extends DataFrameAggregateSuite with BeforeAndAfter {
   override protected def sparkConf: SparkConf = super.sparkConf
     .set("spark.sql.codegen.fallback", "false")
-    .set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+    .set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
 
   // adding some checking after each test is run, assuring that the configs are not changed
   // in test code
   after {
     assert(sparkConf.get("spark.sql.codegen.fallback") == "false",
       "configuration parameter changed in test body")
-    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enable") == "false",
+    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enabled") == "false",
       "configuration parameter changed in test body")
   }
 }
 
 class TwoLevelAggregateHashMapSuite extends DataFrameAggregateSuite with BeforeAndAfter {
   override protected def sparkConf: SparkConf = super.sparkConf
     .set("spark.sql.codegen.fallback", "false")
-    .set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+    .set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
 
   // adding some checking after each test is run, assuring that the configs are not changed
   // in test code
   after {
     assert(sparkConf.get("spark.sql.codegen.fallback") == "false",
       "configuration parameter changed in test body")
-    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enable") == "true",
+    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enabled") == "true",
       "configuration parameter changed in test body")
   }
 }
@@ -57,15 +57,15 @@ class TwoLevelAggregateHashMapWithVectorizedMapSuite
 
   override protected def sparkConf: SparkConf = super.sparkConf
     .set("spark.sql.codegen.fallback", "false")
-    .set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+    .set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
     .set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
 
   // adding some checking after each test is run, assuring that the configs are not changed
   // in test code
   after {
     assert(sparkConf.get("spark.sql.codegen.fallback") == "false",
       "configuration parameter changed in test body")
-    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enable") == "true",
+    assert(sparkConf.get("spark.sql.codegen.aggregate.map.twolevel.enabled") == "true",
       "configuration parameter changed in test body")
     assert(sparkConf.get("spark.sql.codegen.aggregate.map.vectorized.enable") == "true",
       "configuration parameter changed in test body")

sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/AggregateBenchmark.scala

@@ -107,14 +107,14 @@ class AggregateBenchmark extends BenchmarkBase {
 
     benchmark.addCase(s"codegen = T hashmap = F", numIters = 3) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "false")
       f()
     }
 
     benchmark.addCase(s"codegen = T hashmap = T", numIters = 5) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
       f()
     }
@@ -149,14 +149,14 @@ class AggregateBenchmark extends BenchmarkBase {
 
     benchmark.addCase(s"codegen = T hashmap = F", numIters = 3) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", value = true)
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "false")
       f()
     }
 
     benchmark.addCase(s"codegen = T hashmap = T", numIters = 5) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", value = true)
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
       f()
     }
@@ -189,14 +189,14 @@ class AggregateBenchmark extends BenchmarkBase {
 
     benchmark.addCase(s"codegen = T hashmap = F", numIters = 3) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "false")
       f()
     }
 
     benchmark.addCase(s"codegen = T hashmap = T", numIters = 5) { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
       f()
     }
@@ -228,14 +228,14 @@ class AggregateBenchmark extends BenchmarkBase {
 
     benchmark.addCase(s"codegen = T hashmap = F") { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "false")
       f()
     }
 
     benchmark.addCase(s"codegen = T hashmap = T") { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
       f()
     }
@@ -277,14 +277,14 @@ class AggregateBenchmark extends BenchmarkBase {
 
     benchmark.addCase(s"codegen = T hashmap = F") { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "false")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "false")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "false")
       f()
     }
 
     benchmark.addCase(s"codegen = T hashmap = T") { iter =>
       sparkSession.conf.set("spark.sql.codegen.wholeStage", "true")
-      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enable", "true")
+      sparkSession.conf.set("spark.sql.codegen.aggregate.map.twolevel.enabled", "true")
       sparkSession.conf.set("spark.sql.codegen.aggregate.map.vectorized.enable", "true")
       f()
     }

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala

@@ -1015,7 +1015,7 @@ class HashAggregationQueryWithControlledFallbackSuite extends AggregationQuerySu
 
   override protected def checkAnswer(actual: => DataFrame, expectedAnswer: Seq[Row]): Unit = {
     Seq("true", "false").foreach { enableTwoLevelMaps =>
-      withSQLConf("spark.sql.codegen.aggregate.map.twolevel.enable" ->
+      withSQLConf("spark.sql.codegen.aggregate.map.twolevel.enabled" ->
         enableTwoLevelMaps) {
         (1 to 3).foreach { fallbackStartsAt =>
           withSQLConf("spark.sql.TungstenAggregate.testFallbackStartsAt" ->