diff --git a/datafusion/physical-plan/src/aggregates/group_values/mod.rs b/datafusion/physical-plan/src/aggregates/group_values/mod.rs
index eca53c889b06..866349ab3f79 100644
--- a/datafusion/physical-plan/src/aggregates/group_values/mod.rs
+++ b/datafusion/physical-plan/src/aggregates/group_values/mod.rs
@@ -162,9 +162,16 @@ pub trait GroupValues: Send {
     fn clear_shrink(&mut self, batch: &RecordBatch);
 }
 
-pub fn new_group_values(schema: SchemaRef, partitioning_group_values: bool, num_partitions: usize) -> Result<GroupValuesLike> {
+pub fn new_group_values(
+    schema: SchemaRef,
+    partitioning_group_values: bool,
+    num_partitions: usize,
+) -> Result<GroupValuesLike> {
     let group_values = if partitioning_group_values && schema.fields.len() > 1 {
-        GroupValuesLike::Partitioned(Box::new(PartitionedGroupValuesRows::try_new(schema, num_partitions)?))
+        GroupValuesLike::Partitioned(Box::new(PartitionedGroupValuesRows::try_new(
+            schema,
+            num_partitions,
+        )?))
     } else {
         GroupValuesLike::Single(new_single_group_values(schema)?)
     };
diff --git a/datafusion/physical-plan/src/aggregates/row_hash.rs b/datafusion/physical-plan/src/aggregates/row_hash.rs
index cdd6ac8e59e3..e9362fdd05e4 100644
--- a/datafusion/physical-plan/src/aggregates/row_hash.rs
+++ b/datafusion/physical-plan/src/aggregates/row_hash.rs
@@ -64,6 +64,8 @@ pub(crate) enum ExecutionState {
     /// When producing output, the remaining rows to output are stored
     /// here and are sliced off as needed in batch_size chunks
     ProducingOutput(RecordBatch),
+
+    ProducingPartitionedOutput(Vec<Option<RecordBatch>>),
     /// Produce intermediate aggregate state for each input row without
     /// aggregation.
     ///
@@ -76,6 +78,29 @@ pub(crate) enum ExecutionState {
 use super::order::GroupOrdering;
 use super::AggregateExec;
 
+struct PartitionedOutput {
+    batches: Vec<Option<RecordBatch>>,
+    current_idx: usize,
+    exhausted: bool
+}
+
+impl PartitionedOutput {
+    pub fn new(batches: Vec<RecordBatch>) -> Self {
+        let batches = batches.into_iter().map(|batch| Some(batch)).collect();
+
+        Self {
+            batches,
+            current_idx: 0,
+            exhausted: false,
+        }
+    }
+
+    pub fn next_batch(&mut self) -> Option<RecordBatch> {
+
+    }
+}
+
+
 /// This encapsulates the spilling state
 struct SpillState {
     // ========================================================================
@@ -677,7 +702,9 @@ impl Stream for GroupedHashAggregateStream {
                             }
 
                             if let Some(to_emit) = self.group_ordering.emit_to() {
-                                let batch = extract_ok!(self.emit(to_emit, false));
+                                let mut batch = extract_ok!(self.emit(to_emit, false));
+                                assert_eq!(batch.len(), 1);
+                                let batch = batch.pop().unwrap();
                                 self.exec_state = ExecutionState::ProducingOutput(batch);
                                 timer.done();
                                 // make sure the exec_state just set is not overwritten below
@@ -759,6 +786,8 @@ impl Stream for GroupedHashAggregateStream {
                     let _ = self.update_memory_reservation();
                     return Poll::Ready(None);
                 }
+
+                ExecutionState::ProducingPartitionedOutput(_) => todo!(),
             }
         }
     }
@@ -1101,7 +1130,9 @@ impl GroupedHashAggregateStream {
 
     /// Emit all rows, sort them, and store them on disk.
     fn spill(&mut self) -> Result<()> {
-        let emit = self.emit(EmitTo::All, true)?;
+        let mut emit = self.emit(EmitTo::All, true)?;
+        assert_eq!(emit.len(), 1);
+        let emit = emit.pop().unwrap();
         let sorted = sort_batch(&emit, &self.spill_state.spill_expr, None)?;
         let spillfile = self.runtime.disk_manager.create_tmp_file("HashAggSpill")?;
         // TODO: slice large `sorted` and write to multiple files in parallel
@@ -1138,9 +1169,16 @@ impl GroupedHashAggregateStream {
             && matches!(self.mode, AggregateMode::Partial)
             && self.update_memory_reservation().is_err()
         {
-            let n = self.group_values.len() / self.batch_size * self.batch_size;
-            let batch = self.emit(EmitTo::First(n), false)?;
-            self.exec_state = ExecutionState::ProducingOutput(batch);
+            if !self.group_values.is_partitioned() {
+                let n = self.group_values.len() / self.batch_size * self.batch_size;
+                let mut batch = self.emit(EmitTo::First(n), false)?;
+                let batch = batch.pop().unwrap();
+                self.exec_state = ExecutionState::ProducingOutput(batch);
+            } else {
+                let batches = self.emit(EmitTo::All, false)?;
+                let batches = batches.into_iter().map(|batch| Some(batch)).collect();
+                self.exec_state = ExecutionState::ProducingPartitionedOutput(batches);
+            }
         }
         Ok(())
     }
@@ -1150,7 +1188,9 @@ impl GroupedHashAggregateStream {
     /// Conduct a streaming merge sort between the batch and spilled data. Since the stream is fully
     /// sorted, set `self.group_ordering` to Full, then later we can read with [`EmitTo::First`].
     fn update_merged_stream(&mut self) -> Result<()> {
-        let batch = self.emit(EmitTo::All, true)?;
+        let mut batch = self.emit(EmitTo::All, true)?;
+        assert_eq!(batch.len(), 1);
+        let batch = batch.pop().unwrap();
         // clear up memory for streaming_merge
         self.clear_all();
         self.update_memory_reservation()?;
@@ -1198,8 +1238,15 @@ impl GroupedHashAggregateStream {
         let elapsed_compute = self.baseline_metrics.elapsed_compute().clone();
         let timer = elapsed_compute.timer();
         self.exec_state = if self.spill_state.spills.is_empty() {
-            let batch = self.emit(EmitTo::All, false)?;
-            ExecutionState::ProducingOutput(batch)
+            if !self.group_values.is_partitioned() {
+                let mut batch = self.emit(EmitTo::All, false)?;
+                let batch = batch.pop().unwrap();
+                ExecutionState::ProducingOutput(batch)
+            } else {
+                let batches = self.emit(EmitTo::All, false)?;
+                let batches = batches.into_iter().map(|batch| Some(batch)).collect();
+                ExecutionState::ProducingPartitionedOutput(batches)
+            }
         } else {
             // If spill files exist, stream-merge them.
             self.update_merged_stream()?;
@@ -1231,8 +1278,15 @@ impl GroupedHashAggregateStream {
     fn switch_to_skip_aggregation(&mut self) -> Result<()> {
         if let Some(probe) = self.skip_aggregation_probe.as_mut() {
             if probe.should_skip() {
-                let batch = self.emit(EmitTo::All, false)?;
-                self.exec_state = ExecutionState::ProducingOutput(batch);
+                if !self.group_values.is_partitioned() {
+                    let mut batch = self.emit(EmitTo::All, false)?;
+                    let batch = batch.pop().unwrap();
+                    self.exec_state = ExecutionState::ProducingOutput(batch);
+                } else {
+                    let batches = self.emit(EmitTo::All, false)?;
+                    let batches = batches.into_iter().map(|batch| Some(batch)).collect();
+                    self.exec_state = ExecutionState::ProducingPartitionedOutput(batches);
+                }
             }
         }