diff --git a/src/Microsoft.ML.FastTree/FastTreeArguments.cs b/src/Microsoft.ML.FastTree/FastTreeArguments.cs
index 743b9afb76..a21dcc8448 100644
--- a/src/Microsoft.ML.FastTree/FastTreeArguments.cs
+++ b/src/Microsoft.ML.FastTree/FastTreeArguments.cs
@@ -4,6 +4,7 @@
 
 using System;
 using Microsoft.ML.CommandLine;
+using Microsoft.ML.Data;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Internallearn;
 using Microsoft.ML.Runtime;
@@ -301,6 +302,7 @@ public EarlyStoppingRankingMetric EarlyStoppingMetric
             public Options()
             {
                 EarlyStoppingMetric = EarlyStoppingRankingMetric.NdcgAt1; // Use L1 by default.
+                RowGroupColumnName = DefaultColumnNames.GroupId; // Use GroupId as default for ranking options.
             }
 
             ITrainer IComponentFactory<ITrainer>.CreateComponent(IHostEnvironment env) => new FastTreeRankingTrainer(env, this);
diff --git a/src/Microsoft.ML.LightGbm/LightGbmRankingTrainer.cs b/src/Microsoft.ML.LightGbm/LightGbmRankingTrainer.cs
index 1b22995b23..8e395ba734 100644
--- a/src/Microsoft.ML.LightGbm/LightGbmRankingTrainer.cs
+++ b/src/Microsoft.ML.LightGbm/LightGbmRankingTrainer.cs
@@ -156,6 +156,11 @@ static Options()
                 NameMapping.Add(nameof(EvaluateMetricType.NormalizedDiscountedCumulativeGain), "ndcg");
             }
 
+            public Options()
+            {
+                RowGroupColumnName = DefaultColumnNames.GroupId; // Use GroupId as default for ranking options.
+            }
+
             internal override Dictionary<string, object> ToDictionary(IHost host)
             {
                 var res = base.ToDictionary(host);
diff --git a/src/Microsoft.ML.SamplesUtils/SamplesDatasetUtils.cs b/src/Microsoft.ML.SamplesUtils/SamplesDatasetUtils.cs
index 6bdb83f6ea..51ce75b3af 100644
--- a/src/Microsoft.ML.SamplesUtils/SamplesDatasetUtils.cs
+++ b/src/Microsoft.ML.SamplesUtils/SamplesDatasetUtils.cs
@@ -5,6 +5,7 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
+using System.Linq;
 using System.Net;
 using Microsoft.ML.Data;
 
@@ -262,6 +263,17 @@ public static IEnumerable<BinaryLabelFloatFeatureVectorFloatWeightSample> Genera
             return data;
         }
 
+        public class FloatLabelFloatFeatureVectorUlongGroupIdSample
+        {
+            public float Label;
+
+            [VectorType(_simpleBinaryClassSampleFeatureLength)]
+            public float[] Features;
+
+            [KeyType(ulong.MaxValue - 1)]
+            public ulong GroupId;
+        }
+
         public class FloatLabelFloatFeatureVectorSample
         {
             public float Label;
@@ -270,6 +282,21 @@ public class FloatLabelFloatFeatureVectorSample
             public float[] Features;
         }
 
+        public static IEnumerable<FloatLabelFloatFeatureVectorUlongGroupIdSample> GenerateFloatLabelFloatFeatureVectorUlongGroupIdSamples(int exampleCount, double naRate = 0, ulong minGroupId = 1, ulong maxGroupId = 5)
+        {
+            var data = new List<FloatLabelFloatFeatureVectorUlongGroupIdSample>();
+            var rnd = new Random(0);
+            var intermediate = GenerateFloatLabelFloatFeatureVectorSamples(exampleCount, naRate).ToList();
+
+            for (int i = 0; i < exampleCount; ++i)
+            {
+                var sample = new FloatLabelFloatFeatureVectorUlongGroupIdSample() { Label = intermediate[i].Label, Features = intermediate[i].Features, GroupId = (ulong)rnd.Next((int)minGroupId, (int)maxGroupId) };
+                data.Add(sample);
+            }
+
+            return data;
+        }
+
         public static IEnumerable<FloatLabelFloatFeatureVectorSample> GenerateFloatLabelFloatFeatureVectorSamples(int exampleCount, double naRate = 0)
         {
             var rnd = new Random(0);
diff --git a/test/BaselineOutput/Common/EntryPoints/core_manifest.json b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
index 3f38b41727..aceaad8c99 100644
--- a/test/BaselineOutput/Common/EntryPoints/core_manifest.json
+++ b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
@@ -7675,7 +7675,7 @@
           "Required": false,
           "SortOrder": 5.0,
           "IsNullable": false,
-          "Default": null
+          "Default": "GroupId"
         },
         {
           "Name": "NormalizeFeatures",
@@ -12532,7 +12532,7 @@
           "Required": false,
           "SortOrder": 5.0,
           "IsNullable": false,
-          "Default": null
+          "Default": "GroupId"
         },
         {
           "Name": "NormalizeFeatures",
@@ -27371,7 +27371,7 @@
               "Required": false,
               "SortOrder": 5.0,
               "IsNullable": false,
-              "Default": null
+              "Default": "GroupId"
             },
             {
               "Name": "NormalizeFeatures",
diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs
index 71253a32b3..68dee8a5b9 100644
--- a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs
+++ b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs
@@ -538,7 +538,7 @@ public void TestFastTreeTweedieFeaturizationInPipeline()
         public void TestFastTreeRankingFeaturizationInPipeline()
         {
             int dataPointCount = 200;
-            var data = SamplesUtils.DatasetUtils.GenerateFloatLabelFloatFeatureVectorSamples(dataPointCount).ToList();
+            var data = SamplesUtils.DatasetUtils.GenerateFloatLabelFloatFeatureVectorUlongGroupIdSamples(dataPointCount).ToList();
             var dataView = ML.Data.LoadFromEnumerable(data);
             dataView = ML.Data.Cache(dataView);