Merge pull request #192 from myoshi2891/dev-from-macmini

Dev from macmini

Author: myoshi2891

.gitignore

@@ -102,4 +102,4 @@ credentials.json
 # Node.js関連
 node_modules/
 package-lock.json
-bun.lock
+bun.lock

.python-version

@@ -1 +1 @@
-3.12.11
+3.12.11

SQL/Leetcode/Advanced select/601. Human Traffic of Stadium/gpt/Human_Traffic_of_Stadium_mysql.ipynb

@@ -0,0 +1,319 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# MySQL 8.0.40\n",
+    "\n",
+    "## 0) 前提\n",
+    "\n",
+    "* エンジン: **MySQL 8**\n",
+    "* 並び順: 任意（`ORDER BY` を付けない）\n",
+    "  ※本問題は仕様で **`visit_date` 昇順** を要求 → 最終行に `ORDER BY visit_date`\n",
+    "* `NOT IN` は NULL 罠のため回避\n",
+    "* 判定は **ID 基準**（連続 ID かつ各行 `people >= 100`）、表示は仕様どおりの列名と順序\n",
+    "\n",
+    "## 1) 問題\n",
+    "\n",
+    "* `3 つ以上の連続した id を持ち、各行の people >= 100 のレコードを表示する。結果は visit_date 昇順。`\n",
+    "* 入力テーブル例: `Stadium(id INT, visit_date DATE, people INT)`\n",
+    "* 出力仕様: `id, visit_date, people` を **連続 ID の島（gaps-and-islands）** のうち長さ ≥ 3 の行のみ。最終並びは `visit_date ASC`。\n",
+    "\n",
+    "## 2) 最適解（単一クエリ）\n",
+    "\n",
+    "> people ≥ 100 を先に絞り込み、`id - ROW_NUMBER()` で **連続 ID の島キー** を作り、長さ ≥ 3 の島だけ残す。\n",
+    "\n",
+    "```sql\n",
+    "WITH pre AS (\n",
+    "  SELECT id, visit_date, people\n",
+    "  FROM Stadium\n",
+    "  WHERE people >= 100\n",
+    "),\n",
+    "grp AS (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    id - ROW_NUMBER() OVER (ORDER BY id) AS grp_key\n",
+    "  FROM pre\n",
+    "),\n",
+    "big_islands AS (\n",
+    "  SELECT grp_key\n",
+    "  FROM grp\n",
+    "  GROUP BY grp_key\n",
+    "  HAVING COUNT(*) >= 3\n",
+    ")\n",
+    "SELECT\n",
+    "  g.id,\n",
+    "  g.visit_date,\n",
+    "  g.people\n",
+    "FROM grp AS g\n",
+    "JOIN big_islands AS b\n",
+    "  USING (grp_key)\n",
+    "ORDER BY g.visit_date;\n",
+    "\n",
+    "Runtime 352 ms\n",
+    "Beats 56.94%\n",
+    "\n",
+    "```\n",
+    "\n",
+    "## 3) 代替解\n",
+    "\n",
+    "> `LAG` を使って「連続しているか」をフラグ化し、累積和で島を採番する方法。\n",
+    "\n",
+    "```sql\n",
+    "WITH pre AS (\n",
+    "  SELECT id, visit_date, people\n",
+    "  FROM Stadium\n",
+    "  WHERE people >= 100\n",
+    "),\n",
+    "marked AS (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    CASE WHEN id = LAG(id) OVER (ORDER BY id) + 1 THEN 0 ELSE 1 END AS is_break\n",
+    "  FROM pre\n",
+    "),\n",
+    "islands AS (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    SUM(is_break) OVER (ORDER BY id) AS grp_key\n",
+    "  FROM marked\n",
+    "),\n",
+    "big_islands AS (\n",
+    "  SELECT grp_key\n",
+    "  FROM islands\n",
+    "  GROUP BY grp_key\n",
+    "  HAVING COUNT(*) >= 3\n",
+    ")\n",
+    "SELECT i.id, i.visit_date, i.people\n",
+    "FROM islands AS i\n",
+    "JOIN big_islands AS b USING (grp_key)\n",
+    "ORDER BY i.visit_date;\n",
+    "\n",
+    "Runtime 335 ms\n",
+    "Beats 76.87%\n",
+    "\n",
+    "```\n",
+    "\n",
+    "## 4) 要点解説\n",
+    "\n",
+    "* **判定基準は ID の連続**：日付は連続でなくてよい（問題文のとおり）。\n",
+    "* **Gaps-and-Islands パターン**：`id - ROW_NUMBER()` が同じ値の集合は ID が連番の「島」になる。\n",
+    "* 先に `people >= 100` を絞ることでウィンドウ行数を縮小し、高速化。\n",
+    "* `NOT IN` 不使用。結合は `JOIN ... USING (grp_key)` を採用。\n",
+    "* 並び順は仕様に従い **`visit_date ASC`**。\n",
+    "\n",
+    "## 5) 計算量（概算）\n",
+    "\n",
+    "* フィルタ後レコード数を `n` とすると：\n",
+    "\n",
+    "  * ウィンドウ関数（`ROW_NUMBER` / `LAG`）: **O(n log n)**（`ORDER BY id`）\n",
+    "  * `GROUP BY grp_key`: **O(n)**〜**O(n log n)**\n",
+    "  * 結合: **O(n)** 近似\n",
+    "* インデックス推奨: `PRIMARY KEY(id)` / `INDEX(people)`（`people >= 100` の選択度が高いほど効く）\n",
+    "\n",
+    "## 6) 図解（Mermaid 超保守版）\n",
+    "\n",
+    "```mermaid\n",
+    "flowchart TD\n",
+    "  A[入力 Stadium] --> B[前処理 people >= 100]\n",
+    "  B --> C[ウィンドウ id - ROW_NUMBER で島キー]\n",
+    "  C --> D[島ごとに COUNT>=3 を抽出]\n",
+    "  D --> E[該当島と結合して投影]\n",
+    "  E --> F[visit_date 昇順で出力]\n",
+    "```\n",
+    "\n",
+    "まだ少しだけ速く・シンプルにできます。主な改善点は **`big_islands` との結合をやめて、ウィンドウ `COUNT()` で島の長さを直接フィルタ**することと、**適切なインデックス**です。\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## 改善版（JOIN 排除・1 回のスキャンで判定）\n",
+    "\n",
+    "```sql\n",
+    "WITH pre AS (\n",
+    "  SELECT id, visit_date, people\n",
+    "  FROM Stadium\n",
+    "  WHERE people >= 100\n",
+    "),\n",
+    "grp AS (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    id - ROW_NUMBER() OVER (ORDER BY id) AS grp_key\n",
+    "  FROM pre\n",
+    ")\n",
+    "SELECT id, visit_date, people\n",
+    "FROM (\n",
+    "  SELECT\n",
+    "    g.*,\n",
+    "    COUNT(*) OVER (PARTITION BY grp_key) AS island_len\n",
+    "  FROM grp AS g\n",
+    ") x\n",
+    "WHERE island_len >= 3\n",
+    "ORDER BY visit_date;\n",
+    "\n",
+    "Runtime 353 ms\n",
+    "Beats 55.35%\n",
+    "\n",
+    "```\n",
+    "\n",
+    "**ポイント**\n",
+    "\n",
+    "* `big_islands` と `JOIN` を削除 → マテリアライズや結合コストを削減\n",
+    "* 同一 `grp_key`（連番の島）内の行数を `COUNT(*) OVER (PARTITION BY grp_key)` で算出し、外側で `WHERE island_len >= 3`\n",
+    "* 可読性も向上\n",
+    "\n",
+    "実行計画上は「`ORDER BY id` のウィンドウ → `PARTITION BY grp_key` のウィンドウ → 最終フィルタ」の二段で済みます。\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## 代替の等価書き換え（`ROW_NUMBER` を 1 回に）\n",
+    "\n",
+    "MySQL は同一 SELECT 句でエイリアスを別のウィンドウ関数の `PARTITION BY` に直接使えないため、上のように 2 段に分けます。もし 1 段に詰めたい場合は、CTE を 1 個にして派生表で包むのが最小です。\n",
+    "\n",
+    "```sql\n",
+    "SELECT id, visit_date, people\n",
+    "FROM (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    COUNT(*) OVER (PARTITION BY (id - ROW_NUMBER() OVER (ORDER BY id))) AS island_len\n",
+    "  FROM Stadium\n",
+    "  WHERE people >= 100\n",
+    ") t\n",
+    "WHERE island_len >= 3\n",
+    "ORDER BY visit_date;\n",
+    "\n",
+    "Error\n",
+    "0 / 15 testcases passed\n",
+    "You cannot nest a window function in the specification of window '<unnamed window>'.\n",
+    "```\n",
+    "\n",
+    "> ただし上記は一部バージョンでオプティマイザが式の再計算を増やす可能性があるため、安定運用なら **CTE 2 段**（前掲の改善版）を推奨します。\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## インデックス最適化\n",
+    "\n",
+    "フィルタが `people >= 100`、ウィンドウが `ORDER BY id`、出力で `visit_date` を返すため、次を推奨します。\n",
+    "\n",
+    "```sql\n",
+    "-- people で範囲抽出しつつ id の順序性を活かす\n",
+    "CREATE INDEX ix_stadium_people_id ON Stadium (people, id);\n",
+    "\n",
+    "-- さらにカバリングさせたいなら（ストレージと更新コストと相談）\n",
+    "CREATE INDEX ix_stadium_people_id_date ON Stadium (people, id, visit_date);\n",
+    "```\n",
+    "\n",
+    "効果：\n",
+    "\n",
+    "* `pre` で `people` 条件の範囲スキャン\n",
+    "* そのまま `id` 昇順の並びを得やすく、`ROW_NUMBER() OVER (ORDER BY id)` のソートコストを低減\n",
+    "* 最終 `ORDER BY visit_date` は別ソートになりますが、対象行は **島長 ≥ 3** に絞られているためコストは小さくなります\n",
+    "  （要件的には `visit_date ASC` 必須ですが、仕様上「id ↑ ⇒ date ↑」なので、許容される環境なら `ORDER BY id` で等価にできます）\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## 追加の微調整\n",
+    "\n",
+    "* データ量が少ない/中程度なら現状でも十分。大規模（数百万行〜）なら統計更新と `ANALYZE TABLE Stadium;` を適宜実施。\n",
+    "* CTE は MySQL 8 では多くの場合インライン化されますが、環境によっては派生表のマテリアライズが起きます。実行計画を見て重い場合は **派生表に `/*+ NO_MERGE() */` / `/*+ MERGE() */` ヒント**の検討（バージョン依存）も。\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## まとめ\n",
+    "\n",
+    "* **JOIN を外し、ウィンドウ `COUNT()` で直接フィルタ**：短く速く\n",
+    "* **`(people, id[, visit_date])` の複合インデックス**：ソート・走査コスト削減\n",
+    "* これで一般に **数〜十数 % 程度の短縮**が見込めます（データ分布とバージョン次第）\n",
+    "\n",
+    "MySQL 8 は **ウィンドウ関数の“入れ子”を禁止**しており、`PARTITION BY (id - ROW_NUMBER() OVER (...))` のような書き方はできません。そのため、**`ROW_NUMBER()` を先に別レイヤーで計算してから**、外側で `COUNT() OVER (PARTITION BY ...)` を使う形に分解してください。\n",
+    "\n",
+    "## 動く修正版（派生表2段でネスト回避）\n",
+    "\n",
+    "```sql\n",
+    "SELECT id, visit_date, people\n",
+    "FROM (\n",
+    "  SELECT\n",
+    "    t.*,\n",
+    "    COUNT(*) OVER (PARTITION BY (id - rn)) AS island_len\n",
+    "  FROM (\n",
+    "    SELECT\n",
+    "      id,\n",
+    "      visit_date,\n",
+    "      people,\n",
+    "      ROW_NUMBER() OVER (ORDER BY id) AS rn\n",
+    "    FROM Stadium\n",
+    "    WHERE people >= 100\n",
+    "  ) AS t\n",
+    ") AS x\n",
+    "WHERE island_len >= 3\n",
+    "ORDER BY visit_date;\n",
+    "\n",
+    "Runtime 332 ms\n",
+    "Beats 80.65%\n",
+    "\n",
+    "```\n",
+    "\n",
+    "* 内側：`ROW_NUMBER()` を `rn` として計算\n",
+    "* 中間：`grp_key = id - rn` を式で作る（ここでは単なる通常列演算）\n",
+    "* 外側：`COUNT(*) OVER (PARTITION BY (id - rn))` で島の長さを算出して `>= 3` を抽出\n",
+    "\n",
+    "> ポイント：**ウィンドウ関数の引数や `PARTITION BY` 式の中に別のウィンドウ関数を置かない**こと。必ず一段外に出してから使う。\n",
+    "\n",
+    "## CTE 版（読みやすさ重視・推奨）\n",
+    "\n",
+    "```sql\n",
+    "WITH pre AS (\n",
+    "  SELECT id, visit_date, people\n",
+    "  FROM Stadium\n",
+    "  WHERE people >= 100\n",
+    "),\n",
+    "grp AS (\n",
+    "  SELECT\n",
+    "    id,\n",
+    "    visit_date,\n",
+    "    people,\n",
+    "    id - ROW_NUMBER() OVER (ORDER BY id) AS grp_key\n",
+    "  FROM pre\n",
+    ")\n",
+    "SELECT id, visit_date, people\n",
+    "FROM (\n",
+    "  SELECT\n",
+    "    g.*,\n",
+    "    COUNT(*) OVER (PARTITION BY grp_key) AS island_len\n",
+    "  FROM grp AS g\n",
+    ") x\n",
+    "WHERE island_len >= 3\n",
+    "ORDER BY visit_date;\n",
+    "```\n",
+    "\n",
+    "こちらは既にご提案済みの「JOIN 省略版」で、**ネストなし**・可読性良好です。\n",
+    "\n",
+    "---\n",
+    "\n",
+    "### 参考メモ\n",
+    "\n",
+    "* MySQL 8 の制約：`You cannot nest a window function in the specification of window ...`\n",
+    "  → **サブクエリ（派生表 or CTE）で段階計算**が定石です。\n",
+    "* パフォーマンス面では、どちらの書き方も**結合を無くし、スキャン回数を減らせる**ため、先の `big_islands` 版より有利になりやすいです。\n",
+    "* 追加最適化：`CREATE INDEX ix_stadium_people_id ON Stadium(people, id);` は引き続き有効です。\n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}