by default enable skip agg

docs/additional-functionality/advanced_configs.md

@@ -50,7 +50,6 @@ Name | Description | Default Value | Applicable at
 <a name="shuffle.ucx.activeMessages.forceRndv"></a>spark.rapids.shuffle.ucx.activeMessages.forceRndv|Set to true to force 'rndv' mode for all UCX Active Messages. This should only be required with UCX 1.10.x. UCX 1.11.x deployments should set to false.|false|Startup
 <a name="shuffle.ucx.managementServerHost"></a>spark.rapids.shuffle.ucx.managementServerHost|The host to be used to start the management server|null|Startup
 <a name="shuffle.ucx.useWakeup"></a>spark.rapids.shuffle.ucx.useWakeup|When set to true, use UCX's event-based progress (epoll) in order to wake up the progress thread when needed, instead of a hot loop.|true|Startup
-<a name="sql.agg.skipAggPassReductionRatio"></a>spark.rapids.sql.agg.skipAggPassReductionRatio|In non-final aggregation stages, if the previous pass has a row reduction ratio greater than this value, the next aggregation pass will be skipped.Setting this to 1 essentially disables this feature.|1.0|Runtime
 <a name="sql.allowMultipleJars"></a>spark.rapids.sql.allowMultipleJars|Allow multiple rapids-4-spark, spark-rapids-jni, and cudf jars on the classpath. Spark will take the first one it finds, so the version may not be expected. Possisble values are ALWAYS: allow all jars, SAME_REVISION: only allow jars with the same revision, NEVER: do not allow multiple jars at all.|SAME_REVISION|Startup
 <a name="sql.castDecimalToFloat.enabled"></a>spark.rapids.sql.castDecimalToFloat.enabled|Casting from decimal to floating point types on the GPU returns results that have tiny difference compared to results returned from CPU.|true|Runtime
 <a name="sql.castFloatToDecimal.enabled"></a>spark.rapids.sql.castFloatToDecimal.enabled|Casting from floating point types to decimal on the GPU returns results that have tiny difference compared to results returned from CPU.|true|Runtime

sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuAggregateExec.scala

@@ -983,7 +983,7 @@ class GpuMergeAggregateIterator(
         // It's only based on first batch of first pass agg, so it's an estimate
         val firstPassReductionRatioEstimate = 1.0 * peek.numRows() / localInputRowsCount.value
         if (firstPassReductionRatioEstimate > skipAggPassReductionRatio) {
-          logDebug("Skipping second and third pass aggregation due to " +
+          logInfo("Skipping second and third pass aggregation due to " +
             "too high reduction ratio in first pass: " +
             s"$firstPassReductionRatioEstimate")
           // if so, skip any aggregation, return the origin batch directly

sql-plugin/src/main/scala/com/nvidia/spark/rapids/RapidsConf.scala

@@ -1601,12 +1601,15 @@ val GPU_COREDUMP_PIPE_PATTERN = conf("spark.rapids.gpu.coreDump.pipePattern")
     .createWithDefault(true)
 
   val SKIP_AGG_PASS_REDUCTION_RATIO = conf("spark.rapids.sql.agg.skipAggPassReductionRatio")
-    .doc("In non-final aggregation stages, if the previous pass has a row reduction ratio " +
+    .doc("In non-final aggregation stages, if the previous pass has a row retention ratio " +
         "greater than this value, the next aggregation pass will be skipped." +
-        "Setting this to 1 essentially disables this feature.")
+        "Setting this to 1 essentially disables this feature. For Historical reasons it is " +
+        "called skipAggPassReductionRatio, actually skipAggPassRetentionRatio would have " +
+        "been better")
+    .internal()
     .doubleConf
     .checkValue(v => v >= 0 && v <= 1, "The ratio value must be in [0, 1].")
-    .createWithDefault(1.0)
+    .createWithDefault(0.85)
 
   val FORCE_SINGLE_PASS_PARTIAL_SORT_AGG: ConfEntryWithDefault[Boolean] =
     conf("spark.rapids.sql.agg.forceSinglePassPartialSort")