window aggregation -> window function; change formatter

CMakeLists.txt

@@ -328,9 +328,9 @@ set(P3_FILES
         "src/include/execution/executors/sort_executor.h"
         "src/include/execution/executors/topn_executor.h"
         "src/include/execution/executors/update_executor.h"
-        "src/include/execution/executors/window_aggregate_executor.h"
+        "src/include/execution/executors/window_function_executor.h"
         "src/execution/aggregation_executor.cpp"
-        "src/execution/window_aggregate_executor.cpp"
+        "src/execution/window_function_executor.cpp"
         "src/execution/delete_executor.cpp"
         "src/execution/filter_executor.cpp"
         "src/execution/hash_join_executor.cpp"

src/binder/bind_select.cpp

@@ -564,7 +564,7 @@ auto Binder::BindFuncCall(duckdb_libpgquery::PGFuncCall *root) -> std::unique_pt
   }
 
   if (function_name == "min" || function_name == "max" || function_name == "first" || function_name == "last" ||
-      function_name == "sum" || function_name == "count") {
+      function_name == "sum" || function_name == "count" || function_name == "rank") {
     // Rewrite count(*) to count_star().
     if (function_name == "count" && children.empty()) {
       function_name = "count_star";

src/execution/CMakeLists.txt

@@ -22,7 +22,7 @@ add_library(
         topn_check_executor.cpp
         update_executor.cpp
         values_executor.cpp
-        window_aggregate_executor.cpp
+        window_function_executor.cpp
 )
 
 set(ALL_OBJECT_FILES

src/execution/executor_factory.cpp

@@ -34,7 +34,7 @@
 #include "execution/executors/topn_executor.h"
 #include "execution/executors/update_executor.h"
 #include "execution/executors/values_executor.h"
-#include "execution/executors/window_aggregate_executor.h"
+#include "execution/executors/window_function_executor.h"
 #include "execution/plans/filter_plan.h"
 #include "execution/plans/mock_scan_plan.h"
 #include "execution/plans/projection_plan.h"
@@ -96,9 +96,9 @@ auto ExecutorFactory::CreateExecutor(ExecutorContext *exec_ctx, const AbstractPl
     }
 
     case PlanType::Window: {
-      auto window_plan = dynamic_cast<const WindowAggregationPlanNode *>(plan.get());
+      auto window_plan = dynamic_cast<const WindowFunctionPlanNode *>(plan.get());
       auto child_executor = ExecutorFactory::CreateExecutor(exec_ctx, window_plan->GetChildPlan());
-      return std::make_unique<WindowAggregationExecutor>(exec_ctx, window_plan, std::move(child_executor));
+      return std::make_unique<WindowFunctionExecutor>(exec_ctx, window_plan, std::move(child_executor));
     }
 
     // Create a new nested-loop join executor

src/execution/fmt_impl.cpp

@@ -1,4 +1,5 @@
 #include <type_traits>
+#include "execution/expressions/column_value_expression.h"
 #include "execution/plans/update_plan.h"
 #include "execution/plans/window_plan.h"
 #include "fmt/format.h"
@@ -37,13 +38,23 @@ auto AggregationPlanNode::PlanNodeToString() const -> std::string {
   return fmt::format("Agg {{ types={}, aggregates={}, group_by={} }}", agg_types_, aggregates_, group_bys_);
 }
 
-auto WindowAggregationPlanNode::PlanNodeToString() const -> std::string {
+auto WindowFunctionPlanNode::PlanNodeToString() const -> std::string {
+  std::string columns_str;
+  for (const auto &col : columns_) {
+    const auto &col_val = dynamic_cast<const ColumnValueExpression &>(*col);
+    if (col_val.GetColIdx() == static_cast<uint32_t>(-1)) {
+      columns_str += "placeholder, ";
+      continue;
+    }
+    columns_str += col->ToString() + ", ";
+  }
+
   std::vector<std::string> map_content;
   map_content.reserve(window_functions_.size());
   for (const auto &[k, v] : window_functions_) {
     map_content.emplace_back(fmt::format("    {}=>{}", k, v));
   }
-  return fmt::format("WindowAgg {{\n  columns={},\n  window_functions={{\n{}\n  }}\n}}", columns_,
+  return fmt::format("WindowFunc {{\n  columns={},\n  window_functions={{\n{}\n  }}\n}}", columns_str,
                      fmt::join(map_content, ",\n"));
 }
 

src/execution/plan_node.cpp

@@ -80,7 +80,7 @@ auto AggregationPlanNode::InferAggSchema(const std::vector<AbstractExpressionRef
   return Schema(output);
 }
 
-auto WindowAggregationPlanNode::InferWindowSchema(const std::vector<AbstractExpressionRef> &columns) -> Schema {
+auto WindowFunctionPlanNode::InferWindowSchema(const std::vector<AbstractExpressionRef> &columns) -> Schema {
   std::vector<Column> output;
   // TODO(avery): correctly infer window call return type
   for (const auto &column : columns) {

src/execution/window_function_executor.cpp

@@ -0,0 +1,14 @@
+#include "execution/executors/window_function_executor.h"
+#include "execution/plans/window_plan.h"
+#include "storage/table/tuple.h"
+
+namespace bustub {
+
+WindowFunctionExecutor::WindowFunctionExecutor(ExecutorContext *exec_ctx, const WindowFunctionPlanNode *plan,
+                                               std::unique_ptr<AbstractExecutor> &&child_executor)
+    : AbstractExecutor(exec_ctx), plan_(plan), child_executor_(std::move(child_executor)) {}
+
+void WindowFunctionExecutor::Init() { throw NotImplementedException("WindowFunctionExecutor is not implemented"); }
+
+auto WindowFunctionExecutor::Next(Tuple *tuple, RID *rid) -> bool { return false; }
+}  // namespace bustub

src/include/execution/executors/window_aggregate_executor.h → src/include/execution/executors/window_function_executor.h

@@ -2,9 +2,9 @@
 //
 //                         BusTub
 //
-// window_aggregate_executor.h
+// window_function_executor.h
 //
-// Identification: src/include/execution/executors/projection_executor.h
+// Identification: src/include/execution/executors/window_function_executor.h
 //
 // Copyright (c) 2015-2022, Carnegie Mellon University Database Group
 //
@@ -23,52 +23,52 @@
 namespace bustub {
 
 /**
- * The WindowAggregationExecutor executor executes a window aggregation for columns using window function.
+ * The WindowFunctionExecutor executor executes a window function for columns using window function.
  *
- * Window Aggregation is different from normal aggregation as it outputs one row for each inputing rows,
- * and can be combined with normal selected columns. The columns in WindowAggregationPlanNode contains both
- * normal selected columns and placeholder columns for window aggregations.
+ * Window function is different from normal aggregation as it outputs one row for each inputing rows,
+ * and can be combined with normal selected columns. The columns in WindowFunctionPlanNode contains both
+ * normal selected columns and placeholder columns for window functions.
  *
  * For example, if we have a query like:
  *    SELECT 0.1, 0.2, SUM(0.3) OVER (PARTITION BY 0.2 ORDER BY 0.3), SUM(0.4) OVER (PARTITION BY 0.1 ORDER BY 0.2,0.3)
  *      FROM table;
  *
- * The WindowAggregationPlanNode contains following structure:
+ * The WindowFunctionPlanNode contains following structure:
  *    columns: std::vector<AbstractExpressionRef>{0.1, 0.2, 0.-1(placeholder), 0.-1(placeholder)}
  *    window_functions_: {
  *      3: {
  *        partition_by: std::vector<AbstractExpressionRef>{0.2}
  *        order_by: std::vector<AbstractExpressionRef>{0.3}
- *        aggregate: std::vector<AbstractExpressionRef>{0.3}
- *        window_agg_type: WindowAggregationType::SumAggregate
+ *        functions: std::vector<AbstractExpressionRef>{0.3}
+ *        window_func_type: WindowFunctionType::SumAggregate
  *      }
  *      4: {
  *        partition_by: std::vector<AbstractExpressionRef>{0.1}
  *        order_by: std::vector<AbstractExpressionRef>{0.2,0.3}
- *        aggregate: std::vector<AbstractExpressionRef>{0.4}
- *        window_agg_type: WindowAggregationType::SumAggregate
+ *        functions: std::vector<AbstractExpressionRef>{0.4}
+ *        window_func_type: WindowFunctionType::SumAggregate
  *      }
  *    }
  *
  * Your executor should use child executor and exprs in columns to produce selected columns except for window
- * aggregation columns, and use window_agg_indexes, partition_bys, order_bys, aggregates and window_agg_types to
- * generate window aggregation columns results. Directly use placeholders for window aggregation columns in columns is
+ * function columns, and use window_agg_indexes, partition_bys, order_bys, functionss and window_agg_types to
+ * generate window function columns results. Directly use placeholders for window function columns in columns is
  * not allowed, as it contains invalid column id.
  *
- * Your windowAggregationExecutor does not need to support specified window frames (eg: 1 preceding and 1 following).
+ * Your WindowFunctionExecutor does not need to support specified window frames (eg: 1 preceding and 1 following).
  * You can assume that all window frames are UNBOUNDED FOLLOWING AND CURRENT ROW when there is ORDER BY clause, and
  * UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING when there is no ORDER BY clause.
  *
  */
-class WindowAggregationExecutor : public AbstractExecutor {
+class WindowFunctionExecutor : public AbstractExecutor {
  public:
   /**
-   * Construct a new WindowAggregationExecutor instance.
+   * Construct a new WindowFunctionExecutor instance.
    * @param exec_ctx The executor context
    * @param plan The window aggregation plan to be executed
    */
-  WindowAggregationExecutor(ExecutorContext *exec_ctx, const WindowAggregationPlanNode *plan,
-                            std::unique_ptr<AbstractExecutor> &&child_executor);
+  WindowFunctionExecutor(ExecutorContext *exec_ctx, const WindowFunctionPlanNode *plan,
+                         std::unique_ptr<AbstractExecutor> &&child_executor);
 
   /** Initialize the window aggregation */
   void Init() override;
@@ -86,7 +86,7 @@ class WindowAggregationExecutor : public AbstractExecutor {
 
  private:
   /** The window aggregation plan node to be executed */
-  const WindowAggregationPlanNode *plan_;
+  const WindowFunctionPlanNode *plan_;
 
   /** The child executor from which tuples are obtained */
   std::unique_ptr<AbstractExecutor> child_executor_;

src/include/execution/plans/window_plan.h

@@ -27,47 +27,47 @@
 
 namespace bustub {
 
-/** WindowAggregationType enumerates all the possible window aggregation functions in our system */
-enum class WindowAggregationType { CountStarAggregate, CountAggregate, SumAggregate, MinAggregate, MaxAggregate };
+/** WindowFunctionType enumerates all the possible window functions in our system */
+enum class WindowFunctionType { CountStarAggregate, CountAggregate, SumAggregate, MinAggregate, MaxAggregate, Rank };
 
-class WindowAggregationPlanNode : public AbstractPlanNode {
+class WindowFunctionPlanNode : public AbstractPlanNode {
  public:
   /**
-   * Construct a new WindowAggregationPlanNode.
+   * Construct a new WindowFunctionPlanNode.
    * @param output_schema The output format of this plan node
    * @param child The child plan to aggregate data over
-   * @param window_agg_indexes The indexes of the window aggregation functions
-   * @param columns All columns include the placeholder for window aggregation functions
-   * @param partition_bys The partition by clause of the window aggregations
-   * @param order_bys The order by clause of the window aggregations
-   * @param aggregates The expressions that we are aggregating
-   * @param window_agg_types The types that we are aggregating
+   * @param window_func_indexes The indexes of the window functions
+   * @param columns All columns include the placeholder for window functions
+   * @param partition_bys The partition by clause of the window functions
+   * @param order_bys The order by clause of the window functions
+   * @param funcions The expressions that we are aggregating
+   * @param window_func_types The types that we are aggregating
    *
    * Window Aggregation is different from normal aggregation as it outputs one row for each inputing rows,
-   * and can be combined with normal selected columns. The columns in WindowAggregationPlanNode contains both
+   * and can be combined with normal selected columns. The columns in WindowFunctionPlanNode contains both
    * normal selected columns and placeholder columns for window aggregations.
    *
    * For example, if we have a query like:
    *    SELECT 0.1, 0.2, SUM(0.3) OVER (PARTITION BY 0.2 ORDER BY 0.3), SUM(0.4) OVER (PARTITION BY 0.1 ORDER BY
    * 0.2,0.3) FROM table;
    *
-   * The WindowAggregationPlanNode should contains following structure:
+   * The WindowFunctionPlanNode should contains following structure:
    *    columns: std::vector<AbstractExpressionRef>{0.1, 0.2, 0.-1(placeholder), 0.-1(placeholder)}
    *    partition_bys: std::vector<std::vector<AbstractExpressionRef>>{{0.2}, {0.1}}
    *    order_bys: std::vector<std::vector<AbstractExpressionRef>>{{0.3}, {0.2,0.3}}
-   *    aggregates: std::vector<AbstractExpressionRef>{0.3, 0.4}
-   *    window_agg_types: std::vector<WindowAggregationType>{SumAggregate, SumAggregate}
+   *    functions: std::vector<AbstractExpressionRef>{0.3, 0.4}
+   *    window_func_types: std::vector<WindowFunctionType>{SumAggregate, SumAggregate}
    */
-  WindowAggregationPlanNode(SchemaRef output_schema, AbstractPlanNodeRef child,
-                            std::vector<uint32_t> window_agg_indexes, std::vector<AbstractExpressionRef> columns,
-                            std::vector<std::vector<AbstractExpressionRef>> partition_bys,
-                            std::vector<std::vector<std::pair<OrderByType, AbstractExpressionRef>>> order_bys,
-                            std::vector<AbstractExpressionRef> aggregates,
-                            std::vector<WindowAggregationType> window_agg_types)
+  WindowFunctionPlanNode(SchemaRef output_schema, AbstractPlanNodeRef child, std::vector<uint32_t> window_func_indexes,
+                         std::vector<AbstractExpressionRef> columns,
+                         std::vector<std::vector<AbstractExpressionRef>> partition_bys,
+                         std::vector<std::vector<std::pair<OrderByType, AbstractExpressionRef>>> order_bys,
+                         std::vector<AbstractExpressionRef> functions,
+                         std::vector<WindowFunctionType> window_func_types)
       : AbstractPlanNode(std::move(output_schema), {std::move(child)}), columns_(std::move(columns)) {
-    for (uint32_t i = 0; i < window_agg_indexes.size(); i++) {
-      window_functions_[window_agg_indexes[i]] =
-          WindowFunction{aggregates[i], window_agg_types[i], partition_bys[i], order_bys[i]};
+    for (uint32_t i = 0; i < window_func_indexes.size(); i++) {
+      window_functions_[window_func_indexes[i]] =
+          WindowFunction{functions[i], window_func_types[i], partition_bys[i], order_bys[i]};
     }
   }
 
@@ -82,11 +82,11 @@ class WindowAggregationPlanNode : public AbstractPlanNode {
 
   static auto InferWindowSchema(const std::vector<AbstractExpressionRef> &columns) -> Schema;
 
-  BUSTUB_PLAN_NODE_CLONE_WITH_CHILDREN(WindowAggregationPlanNode);
+  BUSTUB_PLAN_NODE_CLONE_WITH_CHILDREN(WindowFunctionPlanNode);
 
   struct WindowFunction {
-    AbstractExpressionRef aggregate_;
-    WindowAggregationType type_;
+    AbstractExpressionRef function_;
+    WindowFunctionType type_;
     std::vector<AbstractExpressionRef> partition_by_;
     std::vector<std::pair<OrderByType, AbstractExpressionRef>> order_by_;
   };
@@ -103,37 +103,40 @@ class WindowAggregationPlanNode : public AbstractPlanNode {
 }  // namespace bustub
 
 template <>
-struct fmt::formatter<bustub::WindowAggregationPlanNode::WindowFunction> : formatter<std::string> {
+struct fmt::formatter<bustub::WindowFunctionPlanNode::WindowFunction> : formatter<std::string> {
   template <typename FormatContext>
-  auto format(const bustub::WindowAggregationPlanNode::WindowFunction &x, FormatContext &ctx) const {
-    return formatter<std::string>::format(fmt::format("{{ aggregate={}, type={}, partition_by={}, order_by={} }}",
-                                                      x.aggregate_, x.type_, x.partition_by_, x.order_by_),
+  auto format(const bustub::WindowFunctionPlanNode::WindowFunction &x, FormatContext &ctx) const {
+    return formatter<std::string>::format(fmt::format("{{ function_arg={}, type={}, partition_by={}, order_by={} }}",
+                                                      x.function_, x.type_, x.partition_by_, x.order_by_),
                                           ctx);
   }
 };
 
 template <>
-struct fmt::formatter<bustub::WindowAggregationType> : formatter<std::string> {
+struct fmt::formatter<bustub::WindowFunctionType> : formatter<std::string> {
   template <typename FormatContext>
-  auto format(bustub::WindowAggregationType c, FormatContext &ctx) const {
-    using bustub::WindowAggregationType;
+  auto format(bustub::WindowFunctionType c, FormatContext &ctx) const {
+    using bustub::WindowFunctionType;
     std::string name = "unknown";
     switch (c) {
-      case WindowAggregationType::CountStarAggregate:
+      case WindowFunctionType::CountStarAggregate:
         name = "count_star";
         break;
-      case WindowAggregationType::CountAggregate:
+      case WindowFunctionType::CountAggregate:
         name = "count";
         break;
-      case WindowAggregationType::SumAggregate:
+      case WindowFunctionType::SumAggregate:
         name = "sum";
         break;
-      case WindowAggregationType::MinAggregate:
+      case WindowFunctionType::MinAggregate:
         name = "min";
         break;
-      case WindowAggregationType::MaxAggregate:
+      case WindowFunctionType::MaxAggregate:
         name = "max";
         break;
+      case WindowFunctionType::Rank:
+        name = "rank";
+        break;
     }
     return formatter<std::string>::format(name, ctx);
   }

src/include/planner/planner.h

@@ -140,7 +140,7 @@ class Planner {
       -> std::tuple<AggregationType, std::vector<AbstractExpressionRef>>;
 
   auto GetWindowAggCallFromFactory(const std::string &func_name, std::vector<AbstractExpressionRef> args)
-      -> std::tuple<WindowAggregationType, std::vector<AbstractExpressionRef>>;
+      -> std::tuple<WindowFunctionType, std::vector<AbstractExpressionRef>>;
 
   auto GetBinaryExpressionFromFactory(const std::string &op_name, AbstractExpressionRef left,
                                       AbstractExpressionRef right) -> AbstractExpressionRef;

src/planner/CMakeLists.txt

@@ -8,7 +8,7 @@ add_library(
   plan_insert.cpp
   plan_table_ref.cpp
   plan_select.cpp
-  plan_window_aggregation.cpp
+  plan_window_function.cpp
   planner.cpp)
 
 set(ALL_OBJECT_FILES