diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 000000000000..2f69e81b8b64
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1,103 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+This is a fork of Apache Arrow DataFusion, an extensible query execution framework written in Rust that uses Apache Arrow as its in-memory format. This fork is maintained by Cube and includes custom extensions and optimizations.
+
+## Key Commands
+
+### Building
+```bash
+cargo build                          # Build the project
+cargo build --release                # Build with optimizations
+cargo build -p datafusion            # Build specific package
+```
+
+### Testing
+```bash
+# Setup test data (required before first test run)
+git submodule init
+git submodule update
+export PARQUET_TEST_DATA=$(pwd)/parquet-testing/data/
+export ARROW_TEST_DATA=$(pwd)/testing/data/
+
+# Run tests
+cargo test                           # Run all tests
+cargo test -p datafusion             # Test specific package
+cargo test test_name                 # Run specific test
+cargo test -- --nocapture           # Show println! output during tests
+```
+
+### Formatting and Linting
+```bash
+cargo fmt                            # Format code
+cargo fmt --check                    # Check formatting without changes
+cargo clippy                         # Run linter
+```
+
+### Benchmarks
+```bash
+cargo bench                          # Run benchmarks
+cargo bench -p datafusion            # Run datafusion benchmarks
+```
+
+## Architecture Overview
+
+### Core Components
+
+1. **Logical Planning** (`datafusion/src/logical_plan/`)
+   - `LogicalPlan`: Represents logical query plans (SELECT, JOIN, etc.)
+   - `Expr`: Expression trees for filters, projections, aggregations
+   - `DFSchema`: Schema representation with field metadata
+   - SQL parsing and planning in `datafusion/src/sql/`
+
+2. **Physical Planning** (`datafusion/src/physical_plan/`)
+   - `ExecutionPlan`: Physical execution operators
+   - Expression implementations for actual computation
+   - Aggregate functions with `Accumulator` trait
+   - Custom operators for hash joins, sorts, aggregations
+
+3. **Execution** (`datafusion/src/execution/`)
+   - `ExecutionContext`: Main entry point for query execution
+   - DataFrame API for programmatic query building
+   - Manages memory, concurrency, and resource limits
+
+4. **Optimizer** (`datafusion/src/optimizer/`)
+   - Rule-based optimizer with passes like:
+     - Predicate pushdown
+     - Projection pushdown
+     - Constant folding
+     - Join reordering
+
+5. **Cube Extensions** (`datafusion/src/cube_ext/`)
+   - Custom operators and functions specific to Cube's fork
+   - Performance optimizations including:
+     - `GroupsAccumulator` for efficient grouped aggregation
+     - `GroupsAccumulatorFlatAdapter` for flattened group values
+     - Specialized join and aggregation implementations
+
+### Key Design Patterns
+
+- **Visitor Pattern**: Used extensively for traversing and transforming plans
+- **Async/Await**: All execution is async using Tokio runtime
+- **Arrow Arrays**: All data processing uses Arrow columnar format
+- **Stream Processing**: Results are produced as async streams of RecordBatches
+
+### Adding New Functionality
+
+**Scalar Functions**: Implement in appropriate module under `physical_plan/`, register in `physical_plan/functions.rs`
+
+**Aggregate Functions**: Create `Accumulator` implementation, register in `physical_plan/aggregates.rs`
+
+**Optimizer Rules**: Implement `OptimizerRule` trait, add to optimizer pipeline
+
+**Physical Operators**: Implement `ExecutionPlan` trait with proper partitioning and execution
+
+## Important Notes
+
+- This is a Cube fork with custom modifications - Ballista components are disabled
+- The `cube_ext` module contains Cube-specific extensions and optimizations
+- Performance-critical paths often have specialized implementations for primitive types
+- Always run tests with proper test data environment variables set
\ No newline at end of file
diff --git a/datafusion/src/physical_plan/planner.rs b/datafusion/src/physical_plan/planner.rs
index 3ef9ac689e0f..fe163aa02643 100644
--- a/datafusion/src/physical_plan/planner.rs
+++ b/datafusion/src/physical_plan/planner.rs
@@ -249,12 +249,14 @@ pub trait ExtensionPlanner {
 /// Default single node physical query planner that converts a
 /// `LogicalPlan` to an `ExecutionPlan` suitable for execution.
 pub struct DefaultPhysicalPlanner {
+    should_evaluate_constants: bool,
     extension_planners: Vec<Arc<dyn ExtensionPlanner + Send + Sync>>,
 }
 
 impl Default for DefaultPhysicalPlanner {
     fn default() -> Self {
         Self {
+            should_evaluate_constants: true,
             extension_planners: vec![
                 Arc::new(LogicalAliasPlanner {}),
                 Arc::new(CrossJoinPlanner {}),
@@ -265,6 +267,15 @@ impl Default for DefaultPhysicalPlanner {
     }
 }
 
+impl DefaultPhysicalPlanner {
+    pub fn disable_constant_evaluation(self) -> Self {
+        let mut mv = self;
+        mv.should_evaluate_constants = false;
+
+        mv
+    }
+}
+
 impl PhysicalPlanner for DefaultPhysicalPlanner {
     /// Create a physical plan from a logical plan
     fn create_physical_plan(
@@ -334,7 +345,7 @@ impl DefaultPhysicalPlanner {
         extension_planners.insert(1, Arc::new(CrossJoinPlanner {}));
         extension_planners.insert(2, Arc::new(CrossJoinAggPlanner {}));
         extension_planners.insert(3, Arc::new(crate::cube_ext::rolling::Planner {}));
-        Self { extension_planners }
+        Self { should_evaluate_constants: true, extension_planners }
     }
 
     /// Create a physical plan from a logical plan
@@ -1360,9 +1371,10 @@ impl DefaultPhysicalPlanner {
         res_expr: Arc<dyn PhysicalExpr>,
         inputs: Vec<Arc<dyn PhysicalExpr>>,
     ) -> Result<Arc<dyn PhysicalExpr>> {
-        if inputs
-            .iter()
-            .all(|i| i.as_any().downcast_ref::<Literal>().is_some())
+        if self.should_evaluate_constants
+            && inputs
+                .iter()
+                .all(|i| i.as_any().downcast_ref::<Literal>().is_some())
         {
             Ok(evaluate_const(res_expr)?)
         } else {