(doris-website) branch master updated: docs(i18n): translate 20 Japanese pages for T09-4X-060 (#4252)

morningman Tue, 13 Oct 2026 23:37:52 -0700

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The following commit(s) were added to refs/heads/master by this push:
     new 36d33a01d37 docs(i18n): translate 20 Japanese pages for T09-4X-060 
(#4252)
36d33a01d37 is described below

commit 36d33a01d375d8fa7445c4656c7e7a2278fdb9c1
Author: Mingyu Chen (Rayner) <[email protected]>
AuthorDate: Wed Oct 14 14:37:14 2026 +0800

    docs(i18n): translate 20 Japanese pages for T09-4X-060 (#4252)
    
    ## Summary
    
    Translate 20 Japanese pages for `T09-4X-060` from merged master
    `f9184fac0bbfb81ef27a7f834ad53f1764cc8929`. 11 pages reused a valid
    same-source Dev translation; 9 required new Japanese work. All pages
    have machine-reviewed state records.
    
    ## Pages
    
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-map.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/median.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-by.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-map.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-array.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-array.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-weighted.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile_reservoir.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/quantile-union.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgx.md`
    -
    
`i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md`
    
    ## Validation
    
    - Bundled protected-structure and state validator: 20/20 passed.
    - `git diff --check`: 12 source-inherited whitespace notices; no new
    whitespace issues.
    - Only the listed Japanese targets and their independent page-state
    files changed.
    - No local site build was run for this translation-only batch; PR CI
    checks the build.
    
    Passing pages use `reviewStatus=machine`; failed pages use
    `reviewStatus=unverified`. All pages use `ownership=machine`; no human
    Japanese proofreading is claimed.
    
    Co-authored-by: morningman <[email protected]>
---
 .../aggregate-functions/intersect-count.md         |  78 +++++++++++++
 .../sql-functions/aggregate-functions/kurt.md      |  82 ++++++++++++++
 .../aggregate-functions/linear-histogram.md        |  84 ++++++++++++++
 .../sql-functions/aggregate-functions/map-agg.md   | 105 +++++++++++++++++
 .../sql-functions/aggregate-functions/max-by.md    |  96 ++++++++++++++++
 .../sql-functions/aggregate-functions/max-map.md   | 115 +++++++++++++++++++
 .../sql-functions/aggregate-functions/max.md       | 124 +++++++++++++++++++++
 .../sql-functions/aggregate-functions/median.md    |  73 ++++++++++++
 .../sql-functions/aggregate-functions/min-by.md    |  96 ++++++++++++++++
 .../sql-functions/aggregate-functions/min-map.md   | 115 +++++++++++++++++++
 .../sql-functions/aggregate-functions/min.md       | 123 ++++++++++++++++++++
 .../aggregate-functions/percentile-approx-array.md | 108 ++++++++++++++++++
 .../percentile-approx-weighted.md                  | 111 ++++++++++++++++++
 .../aggregate-functions/percentile-approx.md       | 107 ++++++++++++++++++
 .../aggregate-functions/percentile-array.md        | 104 +++++++++++++++++
 .../aggregate-functions/percentile.md              | 103 +++++++++++++++++
 .../aggregate-functions/percentile_reservoir.md    |  90 +++++++++++++++
 .../aggregate-functions/quantile-union.md          |  93 ++++++++++++++++
 .../sql-functions/aggregate-functions/regr-avgx.md |  64 +++++++++++
 .../sql-functions/aggregate-functions/regr-avgy.md |  64 +++++++++++
 .../aggregate-functions/intersect-count.json       |  20 ++++
 .../sql-functions/aggregate-functions/kurt.json    |  20 ++++
 .../aggregate-functions/linear-histogram.json      |  20 ++++
 .../sql-functions/aggregate-functions/map-agg.json |  20 ++++
 .../sql-functions/aggregate-functions/max-by.json  |  20 ++++
 .../sql-functions/aggregate-functions/max-map.json |  20 ++++
 .../sql-functions/aggregate-functions/max.json     |  20 ++++
 .../sql-functions/aggregate-functions/median.json  |  20 ++++
 .../sql-functions/aggregate-functions/min-by.json  |  20 ++++
 .../sql-functions/aggregate-functions/min-map.json |  20 ++++
 .../sql-functions/aggregate-functions/min.json     |  20 ++++
 .../percentile-approx-array.json                   |  20 ++++
 .../percentile-approx-weighted.json                |  20 ++++
 .../aggregate-functions/percentile-approx.json     |  20 ++++
 .../aggregate-functions/percentile-array.json      |  20 ++++
 .../aggregate-functions/percentile.json            |  20 ++++
 .../aggregate-functions/percentile_reservoir.json  |  20 ++++
 .../aggregate-functions/quantile-union.json        |  20 ++++
 .../aggregate-functions/regr-avgx.json             |  20 ++++
 .../aggregate-functions/regr-avgy.json             |  20 ++++
 40 files changed, 2335 insertions(+)

diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md
new file mode 100644
index 00000000000..234c978d527
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md
@@ -0,0 +1,78 @@
+---
+{
+    "title": "INTERSECT_COUNT",
+    "language": "ja",
+    "description": "二つ以上のビットマップの共通部分を計算します。使用法: 
intersectcount(bitmapcolumntocount, filtercolumn, filtervalues ..."
+}
+---
+
+## 説明
+
+二つ以上のビットマップの共通部分を計算します。
+使用法: intersect_count(bitmap_column_to_count, filter_column, filter_values ...)
+例: intersect_count(user_id, event, 'A', 'B', 'C') は、A/B/C の 3 つのビットマップすべてに含まれる 
user_id の数を求めます。
+bitmap_column の要素のうち、column_to_filter が filter_values 
に一致するものの共通部分に含まれる要素数を計算します。
+
+## 構文
+
+```sql
+INTERSECT_COUNT(<bitmap_column>, <column_to_filter>, <filter_values> [, ...])
+```
+
+## パラメータ  
+
+| パラメータ         | 説明                                      |
+|------------------|--------------------------------------------------|
+| `<bitmap_column>`  | 入力するビットマップの列。対応する型: Bitmap。 |
+| `<column_to_filter>` | フィルタリングに使用するディメンション列。対応する型: 
TinyInt、SmallInt、Integer、BigInt、LargeInt。 |
+| `<filter_values>`  | ディメンション列のフィルタリングに使用する値。対応する型: 
TinyInt、SmallInt、Integer、BigInt、LargeInt。 |
+
+
+## 戻り値  
+
+指定したビットマップの共通部分に含まれる要素数を返します。
+
+## 例
+
+```sql
+-- setup
+CREATE TABLE pv_bitmap (
+       dt INT,
+       user_id BITMAP,
+       city STRING
+) DISTRIBUTED BY HASH(dt) BUCKETS 1
+PROPERTIES ("replication_num" = "1");
+INSERT INTO pv_bitmap VALUES
+       (20250801, to_bitmap(1), 'beijing'),
+       (20250801, to_bitmap(2), 'beijing'),
+       (20250801, to_bitmap(3), 'shanghai'),
+       (20250802, to_bitmap(3), 'beijing'),
+       (20250802, to_bitmap(4), 'shanghai'),
+       (20250802, to_bitmap(5), 'shenzhen');
+```
+
+```sql
+select intersect_count(user_id,dt,20250801) from pv_bitmap;
+```
+
+```text
++--------------------------------------+
+| intersect_count(user_id,dt,20250801) |
++--------------------------------------+
+|                                    3 |
++--------------------------------------+
+```
+
+二日間の共通部分を求めます。`20250801` と `20250802` の両日に存在するユーザーを数えます（両日に存在する `user_id` は 3 
のみです）。
+
+```sql
+select intersect_count(user_id,dt,20250801,20250802) from pv_bitmap;
+```
+
+```text
++-----------------------------------------------+
+| intersect_count(user_id,dt,20250801,20250802) |
++-----------------------------------------------+
+|                                             1 |
++-----------------------------------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md
new file mode 100644
index 00000000000..e5c5e2bb6ca
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md
@@ -0,0 +1,82 @@
+---
+{
+    "title": "KURT,KURT_POP,KURTOSIS",
+    "language": "ja",
+    "description": "KURTOSIS 関数はデータの尖度を計算します。使用する式は、第四次中心モーメント / (分散の二乗) - 3 
です。"
+}
+---
+
+## 説明
+
+KURTOSIS 
関数はデータの[尖度](https://en.wikipedia.org/wiki/Kurtosis)を計算します。使用する式は、第四次中心モーメント / 
(分散の二乗) - 3 です。
+
+## 別名
+
+KURT_POP, KURTOSIS
+
+## 構文
+
+```sql
+KURTOSIS(<expr>)
+KURT_POP(<expr>)
+KURT(<expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr>` | 計算対象の式。Double 型に対応します。 |
+
+## 戻り値
+
+尖度を表す DOUBLE 型の値を返します。
+分散がゼロの場合、NULL を返します。
+グループ内に有効なデータがない場合、NULL を返します。
+
+## 例
+
+```sql
+-- setup
+create table statistic_test(
+    tag int,
+    val1 double,
+    val2 double
+) distributed by hash(tag) buckets 1
+properties ("replication_num"="1");
+insert into statistic_test values
+    (1, -10, -10),
+    (2, -20, null),
+    (3, 100, null),
+    (4, 100, null),
+    (5, 1000, 1000);
+```
+
+```sql
+select kurt(val1), kurt(val2) from statistic_test;
+```
+
+```text
++---------------------+------------+
+| kurt(val1)          | kurt(val2) |
++---------------------+------------+
+| 0.16212458373485106 |         -2 |
++---------------------+------------+
+```
+
+```sql
+select kurt(val1), kurt(val2) from statistic_test group by tag;
+```
+
+```text
++------------+------------+
+| kurt(val1) | kurt(val2) |
++------------+------------+
+|       NULL |       NULL |
+|       NULL |       NULL |
+|       NULL |       NULL |
+|       NULL |       NULL |
+|       NULL |       NULL |
++------------+------------+
+```
+
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md
new file mode 100644
index 00000000000..a172e2db55d
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md
@@ -0,0 +1,84 @@
+---
+{
+    "title": "LINEAR_HISTOGRAM",
+    "language": "ja",
+    "description": "LINEARHISTOGRAM 関数はデータの分布を表します。"
+}
+---
+
+## 説明
+
+LINEAR_HISTOGRAM 関数はデータの分布を表します。「等幅」のバケット分割方式を使用し、データの値の大きさに応じてバケットに分割します。
+
+## 構文
+
+```sql
+LINEAR_HISTOGRAM(<expr>, DOUBLE <interval>[, DOUBLE <offset>])
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `interval` | バケットの幅。サポートされる型は 
TinyInt、SmallInt、Int、BigInt、LargeInt、Float、Double、Decimal です。 |
+| `offset`   | 省略可能。デフォルト値は 0 で、範囲は `[0, interval)` です。Double 型をサポートします。 |
+
+## 戻り値
+
+計算結果を JSON 型の値として返します。
+
+## 例
+
+```sql
+-- setup
+create table histogram_test(
+  a int
+) distributed by hash(a) buckets 1
+properties ("replication_num"="1");
+insert into histogram_test values
+  (0), (1), (2), (3), (4), (5), (6), (7), (8), (9), (10), (11), (null);
+```
+
+```sql
+select linear_histogram(a, 2) from histogram_test;
+```
+
+```text
++------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| linear_histogram(a, 2)                                                       
                                                                                
                                                                                
                                                                                
                  |
++------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 
{"num_buckets":6,"buckets":[{"lower":0.0,"upper":2.0,"count":2,"acc_count":2},{"lower":2.0,"upper":4.0,"count":2,"acc_count":4},{"lower":4.0,"upper":6.0,"count":2,"acc_count":6},{"lower":6.0,"upper":8.0,"count":2,"acc_count":8},{"lower":8.0,"upper":10.0,"count":2,"acc_count":10},{"lower":10.0,"upper":12.0,"count":2,"acc_count":12}]}
 |
++------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+```sql
+select linear_histogram(a, 2, 1) from histogram_test;
+```
+
+```text
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| linear_histogram(a, 2, 1)                                                    
                                                                                
                                                                                
                                                                                
                                                                     |
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| 
{"num_buckets":7,"buckets":[{"lower":-1.0,"upper":1.0,"count":1,"acc_count":1},{"lower":1.0,"upper":3.0,"count":2,"acc_count":3},{"lower":3.0,"upper":5.0,"count":2,"acc_count":5},{"lower":5.0,"upper":7.0,"count":2,"acc_count":7},{"lower":7.0,"upper":9.0,"count":2,"acc_count":9},{"lower":9.0,"upper":11.0,"count":2,"acc_count":11},{"lower":11.0,"upper":13.0,"count":1,"acc_count":12}]}
 |
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+```sql
+select linear_histogram(a, 2, 1) from histogram_test where a is null;
+```
+
+```text
++--------------------------------+
+| linear_histogram(a, 2, 1)      |
++--------------------------------+
+| {"num_buckets":0,"buckets":[]} |
+```
+
+フィールドの説明：
+
+- `num_buckets`: バケットの数。
+- `buckets`: ヒストグラム内のバケット。
+  - `lower`: 下限（この値を含みます）。
+  - `upper`: 上限（この値を含みません）。
+  - `count`: バケット内の要素数。
+  - `acc_count`: このバケットまでの累積要素数。
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md
new file mode 100644
index 00000000000..c413dbb7532
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md
@@ -0,0 +1,105 @@
+---
+{
+    "title": "MAP_AGG",
+    "language": "ja",
+    "description": "MAP_AGG 関数は、複数行のキーと値の組から MAP を作成します。"
+}
+---
+
+## 説明
+
+MAP_AGG 関数は、複数行のキーと値の組から MAP を作成します。
+
+キーが重複する場合、`MAP_AGG` 
は集約中に最初に処理した値を保持し、すでに存在するキーの後続の値を無視します。部分集約の状態をマージする際も、マージ先の状態にすでに存在する値が保持されます。
+
+「最初に処理した」とは処理順序を指し、挿入順序を指すものではありません。スキャン、並列実行、部分集約の状態をマージする順序によって保持される値が変わる可能性があるため、重複キーに対して選ばれる値がクエリ間で同じになるとは限りません。外側の
 `ORDER BY` は結果の行を並べ替えるだけで、重複キーに対して保持される値は決定しません。
+
+## 構文
+
+```sql
+MAP_AGG(<expr1>, <expr2>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr1>` | キーとして使用する式。対応する型: 
Bool、TinyInt、SmallInt、Integer、BigInt、LargeInt、Float、Double、Decimal、Date、Datetime、String。
 |
+| `<expr2>` | 値として使用する式。対応する型: 
Bool、TinyInt、SmallInt、Integer、BigInt、LargeInt、Float、Double、Decimal、Date、Datetime、String。
 |
+
+## 戻り値
+
+Map 型の値を返します。グループ内に有効なデータがない場合は、空の Map を返します。
+
+## 例
+
+```sql
+-- setup
+CREATE TABLE nation (
+    n_nationkey INT,
+    n_name STRING,
+    n_regionkey INT
+) DISTRIBUTED BY HASH(n_nationkey) BUCKETS 1
+PROPERTIES ("replication_num" = "1");
+INSERT INTO nation VALUES
+    (0, 'ALGERIA', 0),
+    (1, 'ARGENTINA', 1),
+    (2, 'BRAZIL', 1),
+    (3, 'CANADA', 1);
+```
+
+```sql
+select `n_regionkey`, map_agg(`n_nationkey`, `n_name`) from `nation` group by 
`n_regionkey`;
+```
+
+```text
++-------------+-----------------------------------------+
+| n_regionkey | map_agg(`n_nationkey`, `n_name`)        |
++-------------+-----------------------------------------+
+|           0 | {0:"ALGERIA"}                           |
+|           1 | {1:"ARGENTINA", 2:"BRAZIL", 3:"CANADA"} |
++-------------+-----------------------------------------+
+```
+
+```sql
+select map_agg(`n_name`, `n_nationkey` % 5) from `nation`;
+```
+
+```text
++------------------------------------------------------+
+| map_agg(`n_name`, `n_nationkey` % 5)                 |
++------------------------------------------------------+
+| {"ALGERIA":0, "ARGENTINA":1, "BRAZIL":2, "CANADA":3} |
++------------------------------------------------------+
+```
+
+```sql
+select map_agg(`n_name`, `n_nationkey` % 5) from `nation` where n_nationkey is 
null;
+```
+
+```text
++--------------------------------------+
+| map_agg(`n_name`, `n_nationkey` % 5) |
++--------------------------------------+
+| {}                                   |
++--------------------------------------+
+```
+
+次のクエリには重複するキーが含まれるため、結果に含まれるキーと値の組は一つだけです。最初に処理される値に応じて、結果は `{1:"a"}` または 
`{1:"b"}` になります。出力例を以下に示します。
+
+```sql
+SELECT MAP_AGG(k, v) AS result
+FROM (
+    SELECT 1 AS k, 'a' AS v
+    UNION ALL
+    SELECT 1 AS k, 'b' AS v
+) AS input;
+```
+
+```text
++---------+
+| result  |
++---------+
+| {1:"a"} |
++---------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md
new file mode 100644
index 00000000000..80d342dceed
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md
@@ -0,0 +1,96 @@
+---
+{
+    "title": "MAX_BY",
+    "language": "ja",
+    "description": "MAX_BY 関数は、指定した列の最大値に対応する値を返します。"
+}
+---
+
+## 説明
+
+MAX_BY 関数は、指定した列の最大値に対応する値を返します。
+
+## 構文
+
+```sql
+MAX_BY(<expr1>, <expr2>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr1>` | 
対応する値を指定する式。Bool、TinyInt、SmallInt、Int、BigInt、LargeInt、Float、Double、Decimal、String、Date、Datetime、Array、Map、Struct
 型をサポートします。 |
+| `<expr2>` | 
最大値を求める式。Bool、TinyInt、SmallInt、Int、BigInt、LargeInt、Float、Double、Decimal、String、Date、Datetime、Array
 型をサポートします。 |
+
+## 戻り値
+
+<expr1> と同じデータ型の値を返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 例
+
+```sql
+-- setup
+create table tbl(
+    k1 int,
+    k2 int,
+    arr ARRAY<INT>,
+    mp MAP<STRING, INT>,
+    st STRUCT<a: INT, b: STRING>,
+) distributed by hash(k1) buckets 1
+properties ("replication_num"="1");
+insert into tbl values
+    (0, 100, [1,2,3], {"x": 1, "y": 4}, NAMED_STRUCT("a", 1, "b", "x")),
+    (1, 4,   [5, 6],  {"x": 2, "y": 3}, NAMED_STRUCT("a", 2, "b", "y")),
+    (4, 1,   [7],     {"x": 3, "y": 2}, NAMED_STRUCT("a", 3, "b", "z")),
+    (3, 1,   [8],     {"x": 4, "y": 1}, NAMED_STRUCT("a", 4, "b", "r"));
+```
+
+```sql
+select max_by(k1, k2) from tbl;
+```
+
+```text
++----------------+
+| max_by(k1, k2) |
++----------------+
+|              0 |
++----------------+
+```
+
+```sql
+select max_by(arr, k1), max_by(mp, k1), max_by(st, k1) from tbl;
+```
+
+```text
++-----------------+----------------+------------------+
+| max_by(arr, k1) | max_by(mp, k1) | max_by(st, k1)   |
++-----------------+----------------+------------------+
+| [7]             | {"x":3, "y":2} | {"a":3, "b":"z"} |
++-----------------+----------------+------------------+
+```
+
+```sql
+select max_by(k1, arr), max_by(mp, arr), max_by(st, arr), max_by(arr, arr) 
from tbl;
+```
+
+```text
++-----------------+-----------------+------------------+------------------+
+| max_by(k1, arr) | max_by(mp, arr) | max_by(st, arr)  | max_by(arr, arr) |
++-----------------+-----------------+------------------+------------------+
+|               3 | {"x":4, "y":1}  | {"a":4, "b":"r"} | [8]              |
++-----------------+-----------------+------------------+------------------+
+```
+
+```sql
+select max_by(k1, k2) from tbl where k1 is null;
+```
+
+```text
++----------------+
+| max_by(k1, k2) |
++----------------+
+|           NULL |
++----------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-map.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-map.md
new file mode 100644
index 00000000000..31b0237c687
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-map.md
@@ -0,0 +1,115 @@
+---
+{
+    "title": "MAX_MAP",
+    "language": "ja",
+    "description": "MAX_MAP 関数は MAP の値をキーごとに集約し、各キーの最大値を返します。"
+}
+---
+
+## 説明
+
+MAX_MAP 関数は MAP の値をキーごとに集約し、各キーの NULL 以外の最大値を含む MAP を返します。
+
+## 使用上の注意
+
+返される MAP のエントリの順序は保証されません。安定した順序が必要な場合は 
`map_keys`、`map_values`、`array_sort`、`array_sortby` を使用してください。NULL 
キーは通常のキーとして集約され、すべての NULL キーは同じ結果エントリに属します。
+
+## 構文
+
+```sql
+MAX_MAP(<map_expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| --- | --- |
+| `<map_expr>` | MAP 式。MAP の値型は MAX 集約関数で比較可能である必要があります。 |
+
+## 戻り値
+
+`<map_expr>` と同じキー型の MAP を返します。DecimalV2 の値型では、戻り値の値型は対応する DecimalV3 
型になります。それ以外の値型では、入力 MAP と同じ値型を返します。
+
+グループ内に有効な入力行がない場合は空の MAP を返します。キーが存在しても、そのキーに対応する値がすべて NULL の場合、そのキーの値は NULL 
になります。
+
+## 使用例
+
+```sql
+-- setup
+CREATE TABLE map_agg_example (
+    id INT,
+    m MAP<INT, INT>,
+    ms MAP<INT, STRING>
+) DISTRIBUTED BY HASH(id) BUCKETS 1
+PROPERTIES ("replication_num" = "1");
+
+INSERT INTO map_agg_example VALUES
+    (1, MAP(1, 10, 2, 20), MAP(1, 'b', 2, 'x')),
+    (1, MAP(2, 5, 3, 30), MAP(1, 'a', 3, NULL)),
+    (2, MAP(1, 7, 4, NULL), MAP(2, 'z')),
+    (2, CAST(MAP() AS MAP<INT, INT>), CAST(MAP() AS MAP<INT, STRING>));
+```
+
+```text
+Query OK
+```
+
+```sql
+SELECT id,
+       array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT id, MAX_MAP(m) AS result
+    FROM map_agg_example
+    GROUP BY id
+) t
+ORDER BY id;
+```
+
+```text
++------+-----------+--------------+
+| id   | keys      | values       |
++------+-----------+--------------+
+|    1 | [1, 2, 3] | [10, 20, 30] |
+|    2 | [1, 4]    | [7, null]    |
++------+-----------+--------------+
+```
+
+```sql
+SELECT id,
+       array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT id, MAX_MAP(ms) AS result
+    FROM map_agg_example
+    GROUP BY id
+) t
+ORDER BY id;
+```
+
+```text
++------+-----------+----------------+
+| id   | keys      | values         |
++------+-----------+----------------+
+|    1 | [1, 2, 3] | ["b", "x", null] |
+|    2 | [2]       | ["z"]          |
++------+-----------+----------------+
+```
+
+```sql
+SELECT array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT MAX_MAP(m) AS result
+    FROM map_agg_example
+    WHERE id = 100
+) t;
+```
+
+```text
++------+--------+
+| keys | values |
++------+--------+
+| []   | []     |
++------+--------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max.md
new file mode 100644
index 00000000000..bedd93f7fd5
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max.md
@@ -0,0 +1,124 @@
+---
+{
+    "title": "MAX",
+    "language": "ja",
+    "description": "MAX 関数は、式の NULL 以外の値のうち最大の値を返します。"
+}
+---
+
+## 説明
+
+MAX 関数は、式の NULL 以外の値のうち最大の値を返します。
+
+## 構文
+
+```sql
+MAX(<expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr>` | 最大値を求める式。サポートされる型は String, Time, Date, DateTime, Timestamptz, 
IPv4, IPv6, TinyInt, SmallInt, Integer, BigInt, LargeInt, Float, Double, 
Decimal, Array です。 |
+
+## 戻り値
+
+入力式と同じデータ型の値を返します。
+グループ内のすべてのレコードで式の値が NULL の場合は、NULL を返します。
+
+
+## 例
+
+```sql
+-- setup
+create table t1(
+        k1 int,
+        k_string varchar(100),
+        k_decimal decimal(10, 2),
+        k_array array<int>
+) distributed by hash (k1) buckets 1
+properties ("replication_num"="1");
+insert into t1 values 
+    (1, 'apple', 10.01, [10, 20, 30]),
+    (1, 'banana', 20.02, [10, 20]),
+    (2, 'orange', 30.03, [10, 20, 40]),
+    (2, null, null, [10, 20, null]),
+    (3, null, null, null);
+```
+
+```sql
+select k1, max(k_string) from t1 group by k1;
+```
+
+String 型の場合: 各グループの文字列の最大値を返します。
+
+```text
++------+---------------+
+| k1   | max(k_string) |
++------+---------------+
+|    1 | banana        |
+|    2 | orange        |
+|    3 | NULL          |
++------+---------------+
+```
+
+```sql
+select k1, max(k_decimal) from t1 group by k1;
+```
+
+Decimal 型の場合: 高精度の小数値の最大値を返します。
+
+```text
++------+----------------+
+| k1   | max(k_decimal) |
++------+----------------+
+|    1 |          20.02 |
+|    2 |          30.03 |
+|    3 |           NULL |
++------+----------------+
+```
+
+```sql
+select k1, max(k_array) from t1 group by k1;
+```
+
+Array 型の場合: 各グループの配列の最大値を返します（要素を順に比較し、null を最小の要素として扱います）。
+
+```text
++------+--------------+
+| k1   | max(k_array) |
++------+--------------+
+|    1 | [10, 20, 30] |
+|    2 | [10, 20, 40] |
+|    3 | NULL         |
++------+--------------+
+```
+
+```sql
+select max(k_string) from t1 where k1 = 3;
+```
+
+グループ内のすべての値が NULL の場合は、NULL を返します。
+
+```text
++---------------+
+| max(k_string) |
++---------------+
+| NULL          |
++---------------+
+```
+
+```sql
+select max(k_string) from t1;
+```
+
+すべてのデータの中から最大値を返します。
+
+```text
++---------------+
+| max(k_string) |
++---------------+
+| orange        |
++---------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/median.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/median.md
new file mode 100644
index 00000000000..0a4c50858b9
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/median.md
@@ -0,0 +1,73 @@
+---
+{
+    "title": "MEDIAN",
+    "language": "ja",
+    "description": "MEDIAN 関数は式の中央値を返します。percentile(expr, 0.5) と同等です。"
+}
+---
+
+## 説明
+
+MEDIAN 関数は式の中央値を返します。percentile(expr, 0.5) と同等です。
+
+## 構文
+
+```sql
+MEDIAN(<expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr>` | 中央値を計算する式。Double、Float、LargeInt、BigInt、Int、SmallInt、TinyInt 
型をサポートします。 |
+
+## 戻り値
+
+入力式と同じデータ型を返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 例
+
+```sql
+-- setup
+create table log_statis(
+    datetime datetime,
+    scan_rows int
+) distributed by hash(datetime) buckets 1
+properties ("replication_num"="1");
+insert into log_statis values
+    ('2025-08-25 10:00:00', 10),
+    ('2025-08-25 10:00:00', 50),
+    ('2025-08-25 10:00:00', 100),
+    ('2025-08-25 11:00:00', 20),
+    ('2025-08-25 11:00:00', 30),
+    ('2025-08-25 11:00:00', 40);
+```
+
+```sql
+select datetime, median(scan_rows) from log_statis group by datetime;
+```
+
+```text
+select datetime, median(scan_rows) from log_statis group by datetime;
++---------------------+-------------------+
+| datetime            | median(scan_rows) |
++---------------------+-------------------+
+| 2025-08-25 10:00:00 |                50 |
+| 2025-08-25 11:00:00 |                30 |
++---------------------+-------------------+
+```
+
+```sql
+select median(scan_rows) from log_statis where scan_rows is null;
+```
+
+```text
+select median(scan_rows) from log_statis where scan_rows is null;
++-------------------+
+| median(scan_rows) |
++-------------------+
+|              NULL |
++-------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-by.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-by.md
new file mode 100644
index 00000000000..0bc56acef07
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-by.md
@@ -0,0 +1,96 @@
+---
+{
+    "title": "MIN_BY",
+    "language": "ja",
+    "description": "MIN_BY 関数は、指定した列の最小値に対応する値を返します。"
+}
+---
+
+## 説明
+
+MIN_BY 関数は、指定した列の最小値に対応する値を返します。
+
+## 構文
+
+```sql
+MIN_BY(<expr1>, <expr2>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr1>` | 
対応する値を指定する式。Bool、TinyInt、SmallInt、Int、BigInt、LargeInt、Float、Double、Decimal、String、Date、Datetime、Array、Map、Struct
 型をサポートします。 |
+| `<expr2>` | 
最小値を求める式。Bool、TinyInt、SmallInt、Int、BigInt、LargeInt、Float、Double、Decimal、String、Date、Datetime、Array
 型をサポートします。 |
+
+## 戻り値
+
+<expr1> と同じデータ型の値を返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 例
+
+```sql
+-- setup
+create table tbl(
+    k1 int,
+    k2 int,
+    arr ARRAY<INT>,
+    mp MAP<STRING, INT>,
+    st STRUCT<a: INT, b: STRING>,
+) distributed by hash(k1) buckets 1
+properties ("replication_num"="1");
+insert into tbl values
+    (0, 100, [1,2,3], {"x": 1, "y": 4}, NAMED_STRUCT("a", 1, "b", "x")),
+    (1, 4,   [5, 6],  {"x": 2, "y": 3}, NAMED_STRUCT("a", 2, "b", "y")),
+    (4, 1,   [7],     {"x": 3, "y": 2}, NAMED_STRUCT("a", 3, "b", "z")),
+    (3, 1,   [8],     {"x": 4, "y": 1}, NAMED_STRUCT("a", 4, "b", "r"));
+```
+
+```sql
+select min_by(k1, k2) from tbl;
+```
+
+```text
++----------------+
+| min_by(k1, k2) |
++----------------+
+|              3 |
++----------------+
+```
+
+```sql
+select min_by(arr, k1), min_by(mp, k1), min_by(st, k1) from tbl;
+```
+
+```text
++-----------------+----------------+------------------+
+| min_by(arr, k1) | min_by(mp, k1) | min_by(st, k1)   |
++-----------------+----------------+------------------+
+| [1, 2, 3]       | {"x":1, "y":4} | {"a":1, "b":"x"} |
++-----------------+----------------+------------------+
+```
+
+```sql
+select min_by(k1, arr), min_by(mp, arr), min_by(st, arr), min_by(arr, arr) 
from tbl;
+```
+
+```text
++-----------------+-----------------+------------------+------------------+
+| min_by(k1, arr) | min_by(mp, arr) | min_by(st, arr)  | min_by(arr, arr) |
++-----------------+-----------------+------------------+------------------+
+|               0 | {"x":1, "y":4}  | {"a":1, "b":"x"} | [1, 2, 3]        |
++-----------------+-----------------+------------------+------------------+
+```
+
+```sql
+select min_by(k1, k2) from tbl where k1 is null;
+```
+
+```text
++----------------+
+| min_by(k1, k2) |
++----------------+
+|           NULL |
++----------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-map.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-map.md
new file mode 100644
index 00000000000..d26d4863977
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min-map.md
@@ -0,0 +1,115 @@
+---
+{
+    "title": "MIN_MAP",
+    "language": "ja",
+    "description": "MIN_MAP 関数は MAP の値をキーごとに集約し、各キーの最小値を返します。"
+}
+---
+
+## 説明
+
+MIN_MAP 関数は MAP の値をキーごとに集約し、各キーの NULL 以外の最小値を含む MAP を返します。
+
+## 使用上の注意
+
+返される MAP のエントリの順序は保証されません。安定した順序が必要な場合は 
`map_keys`、`map_values`、`array_sort`、`array_sortby` を使用してください。NULL 
キーは通常のキーとして集約され、すべての NULL キーは同じ結果エントリに属します。
+
+## 構文
+
+```sql
+MIN_MAP(<map_expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| --- | --- |
+| `<map_expr>` | MAP 式。MAP の値型は MIN 集約関数で比較可能である必要があります。 |
+
+## 戻り値
+
+`<map_expr>` と同じキー型の MAP を返します。DecimalV2 の値型では、戻り値の値型は対応する DecimalV3 
型になります。それ以外の値型では、入力 MAP と同じ値型を返します。
+
+グループ内に有効な入力行がない場合は空の MAP を返します。キーが存在しても、そのキーに対応する値がすべて NULL の場合、そのキーの値は NULL 
になります。
+
+## 使用例
+
+```sql
+-- setup
+CREATE TABLE map_agg_example (
+    id INT,
+    m MAP<INT, INT>,
+    ms MAP<INT, STRING>
+) DISTRIBUTED BY HASH(id) BUCKETS 1
+PROPERTIES ("replication_num" = "1");
+
+INSERT INTO map_agg_example VALUES
+    (1, MAP(1, 10, 2, 20), MAP(1, 'b', 2, 'x')),
+    (1, MAP(2, 5, 3, 30), MAP(1, 'a', 3, NULL)),
+    (2, MAP(1, 7, 4, NULL), MAP(2, 'z')),
+    (2, CAST(MAP() AS MAP<INT, INT>), CAST(MAP() AS MAP<INT, STRING>));
+```
+
+```text
+Query OK
+```
+
+```sql
+SELECT id,
+       array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT id, MIN_MAP(m) AS result
+    FROM map_agg_example
+    GROUP BY id
+) t
+ORDER BY id;
+```
+
+```text
++------+-----------+-------------+
+| id   | keys      | values      |
++------+-----------+-------------+
+|    1 | [1, 2, 3] | [10, 5, 30] |
+|    2 | [1, 4]    | [7, null]   |
++------+-----------+-------------+
+```
+
+```sql
+SELECT id,
+       array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT id, MIN_MAP(ms) AS result
+    FROM map_agg_example
+    GROUP BY id
+) t
+ORDER BY id;
+```
+
+```text
++------+-----------+----------------+
+| id   | keys      | values         |
++------+-----------+----------------+
+|    1 | [1, 2, 3] | ["a", "x", null] |
+|    2 | [2]       | ["z"]          |
++------+-----------+----------------+
+```
+
+```sql
+SELECT array_sort(map_keys(result)) AS keys,
+       array_sortby(map_values(result), map_keys(result)) AS values
+FROM (
+    SELECT MIN_MAP(m) AS result
+    FROM map_agg_example
+    WHERE id = 100
+) t;
+```
+
+```text
++------+--------+
+| keys | values |
++------+--------+
+| []   | []     |
++------+--------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min.md
new file mode 100644
index 00000000000..49c697db810
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/min.md
@@ -0,0 +1,123 @@
+---
+{
+    "title": "MIN",
+    "language": "ja",
+    "description": "MIN 関数は、式の NULL 以外の値のうち最小値を返します。"
+}
+---
+
+## 説明
+
+MIN 関数は、式の NULL 以外の値のうち最小値を返します。
+
+## 構文
+
+```sql
+MIN(<expr>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<expr>` | 
最小値を求める式。String、Time、Date、DateTime、Timestamptz、IPv4、IPv6、TinyInt、SmallInt、Integer、BigInt、LargeInt、Float、Double、Decimal、Array
 型をサポートします。 |
+
+## 戻り値
+
+入力式と同じデータ型を返します。
+グループ内のすべての行で式の値が NULL の場合は、NULL を返します。
+
+## 例
+
+```sql
+-- setup
+create table t1(
+        k1 int,
+        k_string varchar(100),
+        k_decimal decimal(10, 2),
+        k_array array<int>
+) distributed by hash (k1) buckets 1
+properties ("replication_num"="1");
+insert into t1 values 
+    (1, 'apple', 10.01, [10, 20, 30]),
+    (1, 'banana', 20.02, [10, 20]),
+    (2, 'orange', 30.03, [10, 20, 40]),
+    (2, null, null, [10, 20, null]),
+    (3, null, null, null);
+```
+
+```sql
+select k1, min(k_string) from t1 group by k1;
+```
+
+文字列型: グループごとに文字列の最小値を返します。
+
+```text
++------+---------------+
+| k1   | min(k_string) |
++------+---------------+
+|    1 | apple         |
+|    2 | orange        |
+|    3 | NULL          |
++------+---------------+
+```
+
+```sql
+select k1, min(k_decimal) from t1 group by k1;
+```
+
+Decimal 型: 高精度の小数値の最小値を返します。
+
+```text
++------+----------------+
+| k1   | min(k_decimal) |
++------+----------------+
+|    1 |          10.01 |
+|    2 |          30.03 |
+|    3 |           NULL |
++------+----------------+
+```
+
+```sql
+select k1, min(k_array) from t1 group by k1;
+```
+
+Array 型: グループごとに最小の配列値を返します (要素を順に比較し、NULL を最小の要素とみなします)。
+
+```text
++------+----------------+
+| k1   | min(k_array)   |
++------+----------------+
+|    1 | [10, 20]       |
+|    2 | [10, 20, null] |
+|    3 | NULL           |
++------+----------------+
+```
+
+```sql
+select min(k_string) from t1 where k1 = 3;
+```
+
+グループ内のすべての値が NULL の場合は NULL を返します。
+
+```text
++---------------+
+| min(k_string) |
++---------------+
+| NULL          |
++---------------+
+```
+
+```sql
+select min(k_string) from t1;
+```
+
+すべてのデータの中から最小値を返します。
+
+```text
++---------------+
+| min(k_string) |
++---------------+
+| apple         |
++---------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-array.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-array.md
new file mode 100644
index 00000000000..e1b9a64345c
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-array.md
@@ -0,0 +1,108 @@
+---
+{
+    "title": "PERCENTILE_APPROX_ARRAY",
+    "language": "ja",
+    "description": "PERCENTILE_APPROX_ARRAY は共有の T-Digest 
状態を使い、一回の集約で複数の近似パーセンタイルを計算します。"
+}
+---
+
+## 説明
+
+`PERCENTILE_APPROX_ARRAY` は一回の集約で複数の近似パーセンタイルを計算します。入力値から一つの T-Digest 
を構築し、共有状態から指定された各パーセンタイルを評価するため、各パーセンタイルに `PERCENTILE_APPROX` を別々に呼び出すより効率的です。
+
+:::note
+この関数は 4.2.0 以降でサポートされます。
+:::
+
+## 構文
+
+```sql
+PERCENTILE_APPROX_ARRAY(<col>, <quantiles> [, <compression>])
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | パーセンタイルを計算する数値式。値は `DOUBLE` に変換され、`NULL` 値は無視されます。 |
+| `<quantiles>` | 定数の `ARRAY<DOUBLE>`。各要素は有限かつ NULL 以外で、`[0.0, 1.0]` 
の範囲にある必要があります。結果は配列と同じ順序で返され、重複するレベルも保持されます。空配列も指定できます。 |
+| `<compression>` | 省略可能な定数の `DOUBLE`。範囲は `[2048, 10000]` 
です。値が大きいほど一般に精度が上がりますが、メモリ使用量も増えます。デフォルトは `10000` で、有限でない値や有効範囲外の値を指定した場合も 
`10000` を使用します。 |
+
+## 戻り値
+
+`ARRAY<DOUBLE>` を返します。`<quantiles>` の各要素に対応する近似パーセンタイルを一つずつ含みます。`<quantiles>` 
が空の場合、またはグループ内に NULL 以外の入力値がない場合は空配列を返します。パーセンタイルのレベルが無効な場合や、`<quantiles>` に 
NULL 要素が含まれる場合はエラーになります。
+
+## 使用例
+
+```sql
+CREATE TABLE percentile_approx_array_example (
+    id INT,
+    value DOUBLE NULL
+) DUPLICATE KEY(id)
+DISTRIBUTED BY HASH(id) BUCKETS 1
+PROPERTIES ("replication_num" = "1");
+
+INSERT INTO percentile_approx_array_example VALUES
+    (1, 1.0), (2, 2.0), (3, 3.0), (4, NULL),
+    (5, 10.0), (6, 20.0), (7, 30.0), (8, 100.0);
+```
+
+デフォルトの圧縮レベルで複数の近似パーセンタイルを計算する場合:
+
+```sql
+SELECT percentile_approx_array(value, [0.0, 0.25, 0.5, 0.75, 1.0]) AS 
percentiles
+FROM percentile_approx_array_example;
+```
+
+```text
++--------------------------+
+| percentiles              |
++--------------------------+
+| [1, 2.25, 10, 27.5, 100] |
++--------------------------+
+```
+
+圧縮レベルを明示的に指定する場合:
+
+```sql
+SELECT percentile_approx_array(value, [0.25, 0.5, 0.75], 2048) AS percentiles
+FROM percentile_approx_array_example;
+```
+
+```text
++------------------+
+| percentiles      |
++------------------+
+| [2.25, 10, 27.5] |
++------------------+
+```
+
+入力がすべて NULL の場合は空配列を返します:
+
+```sql
+SELECT percentile_approx_array(CAST(NULL AS DOUBLE), [0.0, 0.5, 1.0]) AS 
percentiles
+FROM percentile_approx_array_example;
+```
+
+```text
++-------------+
+| percentiles |
++-------------+
+| []          |
++-------------+
+```
+
+パーセンタイルの配列が空の場合も空配列を返します:
+
+```sql
+SELECT percentile_approx_array(value, []) AS percentiles
+FROM percentile_approx_array_example;
+```
+
+```text
++-------------+
+| percentiles |
++-------------+
+| []          |
++-------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-weighted.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-weighted.md
new file mode 100644
index 00000000000..5f9f17d0787
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx-weighted.md
@@ -0,0 +1,111 @@
+---
+{
+    "title": "PERCENTILE_APPROX_WEIGHTED",
+    "language": "ja",
+    "description": "PERCENTILEAPPROXWEIGHTED 関数は重み付きの近似パーセンタイルを計算します。"
+}
+---
+
+## 説明
+
+`PERCENTILE_APPROX_WEIGHTED` 
関数は重み付きの近似パーセンタイルを計算します。値の重要度を考慮する場合に使用します。`PERCENTILE_APPROX` 
の重み付き版であり、各値に重みを指定できます。
+
+主な特徴:
+1. 重みの指定: 各値に対応する重みを割り当てられ、最終的なパーセンタイル計算に反映されます。
+2. メモリ効率: 固定サイズのメモリを使用します。カーディナリティが低い列 (データ量は多いが異なる要素は少ない列) でもメモリ使用量を抑えられます。
+3. 調整可能な精度: 圧縮パラメータで精度と性能のバランスを調整できます。
+
+## 構文
+
+```sql
+PERCENTILE_APPROX_WEIGHTED(<col>, <weight>, <p> [, <compression>])
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | パーセンタイルを計算する列。Double 型をサポートします。 |
+| `<weight>` | 重みの列。正の数である必要があります。Double 型をサポートします。 |
+| `<p>` | パーセンタイル値。範囲は `[0.0, 1.0]` です。たとえば `0.99` は第 `99` パーセンタイルを表します。 |
+| `<compression>` | 省略可能な引数。Double 型をサポートします。圧縮率の範囲は `[2048, 10000]` 
です。値が大きいほど精度が上がる一方、メモリ使用量も増えます。省略した場合、または範囲外の場合は `10000` を使用します。 |
+
+## 戻り値
+
+計算した重み付き近似パーセンタイルを表す `DOUBLE` 型の値を返します。
+グループ内に有効なデータがない場合は `NULL` を返します。
+
+## 使用例
+
+```sql
+-- Create sample table
+CREATE TABLE weighted_scores (
+    student_id INT,
+    score DECIMAL(10, 2),
+    weight INT
+) DUPLICATE KEY(student_id)
+DISTRIBUTED BY HASH(student_id) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+
+-- Insert example data
+INSERT INTO weighted_scores VALUES
+(1, 85.5, 1),   -- Normal homework score, weight 1
+(2, 90.0, 2),   -- Important homework score, weight 2
+(3, 75.5, 1),
+(4, 95.5, 3),   -- Very important homework, weight 3
+(5, 88.0, 2),
+(6, 92.5, 2),
+(7, 78.0, 1),
+(8, 89.5, 2),
+(9, 94.0, 3),
+(10, 83.5, 1);
+
+-- Calculate weighted scores distribution
+SELECT 
+    -- Calculate 90th percentile for different compression ratios
+    percentile_approx_weighted(score, weight, 0.9) as p90_default,          -- 
Default compression ratio
+    percentile_approx_weighted(score, weight, 0.9, 2048) as p90_fast,       -- 
Lower compression ratio, faster
+    percentile_approx_weighted(score, weight, 0.9, 10000) as p90_accurate   -- 
Higher compression ratio, more accurate
+FROM weighted_scores;
+```
+
+```text
++------------------+------------------+------------------+
+| p90_default      | p90_fast         | p90_accurate     |
++------------------+------------------+------------------+
+| 95.3499984741211 | 95.3499984741211 | 95.3499984741211 |
++------------------+------------------+------------------+
+```
+
+
+```sql
+select percentile_approx_weighted(if(score>95,score,null), weight, 0.9) from 
weighted_scores;
+```
+
+NULL 以外の入力値のみを対象とします。
+
+```text
++------------------------------------------------------------------+
+| percentile_approx_weighted(if(score>95,score,null), weight, 0.9) |
++------------------------------------------------------------------+
+|                                                             95.5 |
++------------------------------------------------------------------+
+```
+
+```sql
+select percentile_approx_weighted(score, weight, 0.9, null) from 
weighted_scores;
+```
+
+すべての入力値が NULL の場合、関数は NULL を返します。
+
+```text
++------------------------------------------------------+
+| percentile_approx_weighted(score, weight, 0.9, null) |
++------------------------------------------------------+
+|                                                 NULL |
++------------------------------------------------------+
+```
+
+
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx.md
new file mode 100644
index 00000000000..65a16358f9f
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-approx.md
@@ -0,0 +1,107 @@
+---
+{
+    "title": "PERCENTILE_APPROX",
+    "language": "ja",
+    "description": "PERCENTILEAPPROX 関数は、主に大規模データセットの近似パーセンタイルを計算します。"
+}
+---
+
+## 説明
+
+`PERCENTILE_APPROX` 関数は、主に大規模データセットの近似パーセンタイルを計算します。`PERCENTILE` 
関数と比べて、次の特徴があります:
+
+1. メモリ効率: 固定サイズのメモリを使用します。カーディナリティが低い列 (データ量は多いが異なる要素は少ない列) でも、メモリ使用量を抑えられます。
+2. 処理性能: カーディナリティが低い大規模データセットに適し、計算を高速に実行できます。
+3. 調整可能な精度: 圧縮パラメータで精度と性能のバランスを調整できます。
+
+
+## 構文
+
+```sql
+PERCENTILE_APPROX(<col>, <p> [, <compression>])
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | パーセンタイルを計算する列。Double 型をサポートします。 |
+| `<p>` | パーセンタイル値。Double 型の定数で、範囲は `[0.0, 1.0]` です。たとえば `0.99` は第 99 
パーセンタイルを表します。定数である必要があります。 |
+| `<compression>` | 省略可能な圧縮レベル。Double 型で範囲は `[2048, 10000]` 
です。値が大きいほど精度は上がりますが、メモリ使用量も増えます。省略した場合、または範囲外の場合、デフォルトは `10000` です。 |
+
+## 戻り値
+
+指定した列の近似パーセンタイルを Double 型で返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 使用例
+
+```sql
+-- setup
+CREATE TABLE response_times (
+    request_id INT,
+    response_time DECIMAL(10, 2)
+) DUPLICATE KEY(`request_id`)
+DISTRIBUTED BY HASH(`request_id`) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+INSERT INTO response_times VALUES
+(1, 10.5),
+(2, 15.2),
+(3, 20.1),
+(4, 25.8),
+(5, 30.3),
+(6, 35.7),
+(7, 40.2),
+(8, 45.9),
+(9, 50.4),
+(10, 100.6);
+```
+
+```sql
+-- Calculate 99th percentile using different compression levels
+SELECT 
+    percentile_approx(response_time, 0.99) as p99_default,          -- Default 
compression
+    percentile_approx(response_time, 0.99, 2048) as p99_fast,       -- Lower 
compression, faster
+    percentile_approx(response_time, 0.99, 10000) as p99_accurate   -- Higher 
compression, more accurate
+FROM response_times;
+```
+
+```text
++-------------------+-------------------+-------------------+
+| p99_default       | p99_fast          | p99_accurate      |
++-------------------+-------------------+-------------------+
+| 100.5999984741211 | 100.5999984741211 | 100.5999984741211 |
++-------------------+-------------------+-------------------+
+```
+
+```sql
+SELECT percentile_approx(if(response_time>90,response_time,NULL), 0.5) FROM 
response_times;
+```
+
+NULL 以外のデータのみを計算します。
+
+```text
++-----------------------------------------------------------------+
+| percentile_approx(if(response_time>90,response_time,NULL), 0.5) |
++-----------------------------------------------------------------+
+|                                               100.5999984741211 |
++-----------------------------------------------------------------+
+```
+
+```sql
+SELECT percentile_approx(NULL, 0.99) FROM response_times;
+```
+
+すべての入力データが NULL の場合は NULL を返します。
+
+```text
++-------------------------------+
+| percentile_approx(NULL, 0.99)  |
++-------------------------------+
+|                          NULL  |
++-------------------------------+
+```
+
+
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-array.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-array.md
new file mode 100644
index 00000000000..90bc1d503e7
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile-array.md
@@ -0,0 +1,104 @@
+---
+{
+    "title": "PERCENTILE_ARRAY",
+    "language": "ja",
+    "description": "PERCENTILEARRAY 関数は、複数の正確なパーセンタイル値を一度に計算します。"
+}
+---
+
+## 説明
+
+`PERCENTILE_ARRAY` 関数は複数の正確なパーセンタイル値を一度に計算します。主に小規模なデータセットに適しています。
+
+主な特徴:
+1. 正確な計算: 近似値ではなく正確なパーセンタイル値を返します。
+2. 一括処理: 一回の操作で複数のパーセンタイルを計算できます。
+3. 適用範囲: 小規模なデータセットの処理に最も適しています。
+
+
+## 構文
+
+```sql
+PERCENTILE_ARRAY(<col>, <array_p>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | 正確なパーセンタイルを計算する列。Double、Float、LargeInt、BigInt、Int、SmallInt、TinyInt 
型をサポートします。 |
+| `<array_p>` | パーセンタイルの配列。各要素は Array<Double> 型の定数で、値は `[0.0, 1.0]` 
の範囲にある必要があります。例: `[0.5, 0.95, 0.99]`。 |
+
+## 戻り値
+
+計算したパーセンタイル値を含む DOUBLE 型の配列を返します。
+グループ内に有効なデータがない場合は空配列を返します。
+
+
+## 使用例
+
+```sql
+-- setup
+CREATE TABLE sales_data (
+    id INT,
+    amount DECIMAL(10, 2)
+) DUPLICATE KEY(`id`)
+DISTRIBUTED BY HASH(`id`) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+INSERT INTO sales_data VALUES
+(1, 10.5),
+(2, 15.2),
+(3, 20.1),
+(4, 25.8),
+(5, 30.3),
+(6, 35.7),
+(7, 40.2),
+(8, 45.9),
+(9, 50.4),
+(10, 100.6);
+```
+
+```sql
+SELECT percentile_array(amount, [0.25, 0.5, 0.75, 0.9]) as percentiles
+FROM sales_data;
+```
+
+複数のパーセンタイルを計算します。
+
+```text
++-----------------------------------------------------+
+| percentiles                                         |
++-----------------------------------------------------+
+| [21.525000000000002, 33, 44.475, 55.41999999999998] |
++-----------------------------------------------------+
+```
+
+```sql
+SELECT percentile_array(if(amount>90, amount, NULL), [0.5, 0.99]) FROM 
sales_data;
+```
+
+NULL 以外のデータのみを計算します。
+
+```text
++------------------------------------------------------------+
+| percentile_array(if(amount>90, amount, NULL), [0.5, 0.99]) |
++------------------------------------------------------------+
+| [100.6, 100.6]                                             |
++------------------------------------------------------------+
+```
+
+```sql
+SELECT percentile_array(NULL, [0.5, 0.99]) FROM sales_data;
+```
+
+すべての入力データが NULL の場合は空配列を返します。
+
+```text
++-------------------------------------+
+| percentile_array(NULL, [0.5, 0.99]) |
++-------------------------------------+
+| []                                  |
++-------------------------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile.md
new file mode 100644
index 00000000000..49a493400cf
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile.md
@@ -0,0 +1,103 @@
+---
+{
+    "title": "PERCENTILE",
+    "language": "ja",
+    "description": "小規模なデータセットに適した、正確なパーセンタイルを計算します。指定した列を降順にソートします。"
+}
+---
+
+## 説明
+
+小規模なデータセットに適した、正確なパーセンタイルを計算します。まず指定した列を降順にソートし、正確な p 番目のパーセンタイルを取得します。`p` の値は 
`0` から `1` の間です。`p` 
が正確な位置を指さない場合は、隣接する値を[線形補間](https://en.wikipedia.org/wiki/Linear_interpolation)して
 `p` の位置の値を返します。これは二つの数値の平均ではないことに注意してください。特殊なケース:
+
+## 構文
+
+```sql
+PERCENTILE(<col>, <p>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | 正確なパーセンタイルを計算する列。Double、Float、LargeInt、BigInt、Int、SmallInt、TinyInt 
型をサポートします。 |
+| `<p>` | 計算する正確なパーセンタイルを指定する定数。サポートされる型は Double、範囲は `[0.0, 1.0]` 
です。二番目の引数は定数である必要があります。 |
+
+## 戻り値
+
+指定した列の正確なパーセンタイルを Double 型で返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 使用例
+
+```sql
+-- Setup
+CREATE TABLE sales_data
+(
+    product_id INT,
+    sale_price DECIMAL(10, 2)
+) DUPLICATE KEY(`product_id`)
+DISTRIBUTED BY HASH(`product_id`) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+INSERT INTO sales_data VALUES
+(1, 10.00),
+(1, 15.00),
+(1, 20.00),
+(1, 25.00),
+(1, 30.00),
+(1, 35.00),
+(1, 40.00),
+(1, 45.00),
+(1, 50.00),
+(1, 100.00);
+```
+
+```sql
+SELECT 
+    percentile(sale_price, 0.5)  as median_price,     -- Median
+    percentile(sale_price, 0.75) as p75_price,        -- 75th percentile
+    percentile(sale_price, 0.90) as p90_price,        -- 90th percentile
+    percentile(sale_price, 0.95) as p95_price,        -- 95th percentile
+    percentile(null, 0.99)       as p99_null          -- Null value at 99th 
percentile
+FROM sales_data;
+```
+
+販売価格の複数のパーセンタイルを計算します。
+
+```text
++--------------+-----------+-------------------+-------------------+----------+
+| median_price | p75_price | p90_price         | p95_price         | p99_null |
++--------------+-----------+-------------------+-------------------+----------+
+|         32.5 |     43.75 | 54.99999999999998 | 77.49999999999994 |     NULL |
++--------------+-----------+-------------------+-------------------+----------+
+```
+
+```sql
+select percentile(if(sale_price>90,sale_price,NULL), 0.5) from sales_data;
+```
+
+計算には NULL 以外の入力値のみを使用します。
+
+```text
++----------------------------------------------------+
+| percentile(if(sale_price>90,sale_price,NULL), 0.5) |
++----------------------------------------------------+
+|                                                100 |
++----------------------------------------------------+
+```
+
+```sql
+select percentile(sale_price, NULL) from sales_data;
+```
+
+すべての入力値が NULL の場合は NULL を返します。
+
+```text
++------------------------------+
+| percentile(sale_price, NULL) |
++------------------------------+
+|                         NULL |
++------------------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile_reservoir.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile_reservoir.md
new file mode 100644
index 00000000000..b74c1c7e4fd
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/percentile_reservoir.md
@@ -0,0 +1,90 @@
+---
+{
+    "title": "PERCENTILE_RESERVOIR",
+    "language": "ja",
+    "description": "この関数は、最大 8192 件のリザーバーと乱数生成器を使ってリザーバーサンプリングを行います。"
+}
+---
+
+## 説明
+
+この関数は、最大 8192 
件のリザーバーと乱数生成器を使って[リザーバーサンプリング](https://en.wikipedia.org/wiki/Reservoir_sampling)を行います。これを使用して位置
 `p` の近似パーセンタイルを計算します。
+`p` の値は `0` から `1` の間です。
+これは二つの数値の平均ではないことに注意してください。
+
+## 構文
+
+```sql
+PERCENTILE_RESERVOIR(<col>, <p>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<col>` | 近似パーセンタイルを計算する列。Double 型をサポートします。 |
+| `<p>` | 計算する近似パーセンタイルを指定する定数。Double 型をサポートし、範囲は `[0.0, 1.0]` です。 |
+
+## 戻り値
+
+指定した列の近似パーセンタイルを `DOUBLE` 型で返します。
+- 入力列が `NULL` の場合は `NULL` を返します
+
+## 使用例
+
+```sql
+-- Create sample table
+CREATE TABLE sales_data
+(
+    product_id INT,
+    sale_price DECIMAL(10, 2)
+) DUPLICATE KEY(`product_id`)
+DISTRIBUTED BY HASH(`product_id`) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+
+-- Insert sample data
+INSERT INTO sales_data VALUES
+(1, 10.00),
+(1, 15.00),
+(1, 20.00),
+(1, 25.00),
+(1, 30.00),
+(1, 35.00),
+(1, 40.00),
+(1, 45.00),
+(1, 50.00),
+(1, 100.00);
+
+-- Calculate different percentiles of sales prices
+SELECT 
+    percentile_reservoir(sale_price, 0.5)  as median_price,     -- Median
+    percentile_reservoir(sale_price, 0.75) as p75_price,        -- 75th 
percentile
+    percentile_reservoir(sale_price, 0.90) as p90_price,        -- 90th 
percentile
+    percentile_reservoir(sale_price, 0.95) as p95_price,        -- 95th 
percentile
+    percentile_reservoir(null, 0.99)       as p99_null          -- Null value 
at 99th percentile
+FROM sales_data;
+```
+
+```text
++--------------+-----------+-------------------+-------------------+----------+
+| median_price | p75_price | p90_price         | p95_price         | p99_null |
++--------------+-----------+-------------------+-------------------+----------+
+|         32.5 |     43.75 | 54.99999999999998 | 77.49999999999994 |     NULL |
++--------------+-----------+-------------------+-------------------+----------+
+```
+
+```sql
+select percentile_reservoir(sale_price, NULL) from sales_data;
+```
+
+すべての入力値が NULL の場合は NULL を返します。
+
+```text
++------------------------------+
+| percentile_reservoir(sale_price, NULL) |
++------------------------------+
+|                         NULL |
++------------------------------+
+```
\ No newline at end of file
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/quantile-union.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/quantile-union.md
new file mode 100644
index 00000000000..21ba058f135
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/quantile-union.md
@@ -0,0 +1,93 @@
+---
+{
+    "title": "QUANTILE_UNION",
+    "language": "ja",
+    "description": "QUANTILEUNION 関数は分位数計算の複数の中間結果を統合します。"
+}
+---
+
+## 説明
+
+`QUANTILE_UNION` 関数は分位数計算の複数の中間結果を統合します。通常は `QUANTILE_STATE` 
と併用し、多段階の分位数計算が必要な場合に適しています。
+
+## 構文
+
+```sql
+QUANTILE_UNION(<query_state>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<query_state>` | 集約するデータ。QuantileState 型をサポートします。 |
+
+## 戻り値
+
+後続の分位数計算に使用する QuantileState 型の集約状態を返します。
+グループ内に有効なデータがない場合は NULL を返します。
+
+## 使用例
+
+```sql
+-- setup
+CREATE TABLE response_times (
+    request_id INT,
+    response_time DOUBLE,
+    region STRING
+) DUPLICATE KEY(request_id)
+DISTRIBUTED BY HASH(request_id) BUCKETS AUTO
+PROPERTIES (
+    "replication_allocation" = "tag.location.default: 1"
+);
+INSERT INTO response_times VALUES
+(1, 10.5, 'east'),
+(2, 15.2, 'east'),
+(3, 20.1, 'west'),
+(4, 25.8, 'east'),
+(5, 30.3, 'west'),
+(6, 35.7, 'east'),
+(7, 40.2, 'west'),
+(8, 45.9, 'east'),
+(9, 50.4, 'west'),
+(10, 100.6, 'east');
+```
+
+```sql
+SELECT 
+    region,
+    QUANTILE_PERCENT(
+        QUANTILE_UNION(
+            TO_QUANTILE_STATE(response_time, 2048)
+        ),
+        0.5
+    ) AS median_response_time
+FROM response_times
+GROUP BY region;
+```
+
+地域別の応答時間の第 50 パーセンタイルを計算します。
+
+```text
++--------+----------------------+
+| region | median_response_time |
++--------+----------------------+
+| west   |                35.25 |
+| east   |                30.75 |
++--------+----------------------+
+```
+
+```sql
+SELECT QUANTILE_UNION(TO_QUANTILE_STATE(response_time, 2048))
+FROM response_times where response_time is null;
+```
+
+グループ内に有効なデータがない場合は NULL を返します。
+
+```text
++--------------------------------------------------------+
+| QUANTILE_UNION(TO_QUANTILE_STATE(response_time, 2048)) |
++--------------------------------------------------------+
+| NULL                                                   |
++--------------------------------------------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgx.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgx.md
new file mode 100644
index 00000000000..5f54778f8d3
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgx.md
@@ -0,0 +1,64 @@
+---
+{
+    "title": "REGR_AVGX",
+    "language": "ja",
+    "description": "グループ内の NULL 以外のペアについて、独立変数 (x) の平均を返します。"
+}
+---
+
+## 説明
+
+独立変数 `x` の平均を、グループ内の NULL 以外の `(y, x)` ペアについて返します。`x` は独立変数、`y` は従属変数です。
+
+## 構文
+
+```sql
+REGR_AVGX(<y>, <x>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<y>` | 従属変数。Double 型をサポートします。 |
+| `<x>` | 独立変数。Double 型をサポートします。 |
+
+## 戻り値
+
+`x` の平均を表す Double 型の値を、NULL 以外の `(y, x)` ペアについて返します。
+グループ内に行がない場合、またはすべての行で式が NULL の場合、関数は `NULL` を返します。
+
+## 使用例
+
+```sql
+CREATE TABLE test_regr (
+  `id` int,
+  `x` double,
+  `y` double
+) DUPLICATE KEY (`id`)
+DISTRIBUTED BY HASH(`id`) BUCKETS AUTO
+PROPERTIES (
+  "replication_allocation" = "tag.location.default: 1"
+);
+
+INSERT INTO test_regr VALUES
+(1, 0, NULL),
+(2, 1, 3),
+(2, 2, 5),
+(2, 3, 7),
+(2, 4, 9),
+(2, 5, NULL);
+```
+
+```sql
+SELECT id, REGR_AVGX(y, x) FROM test_regr GROUP BY id ORDER BY id;
+```
+
+```text
++------+--------------------+
+| id   | REGR_AVGX(y, x)    |
++------+--------------------+
+|    1 |               NULL |
+|    2 |                2.5 |
++------+--------------------+
+```
diff --git 
a/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md
 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md
new file mode 100644
index 00000000000..db8dfc1b869
--- /dev/null
+++ 
b/i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md
@@ -0,0 +1,64 @@
+---
+{
+    "title": "REGR_AVGY",
+    "language": "ja",
+    "description": "グループ内の NULL 以外のペアについて、従属変数 (y) の平均を返します。"
+}
+---
+
+## 説明
+
+従属変数 `y` の平均を、グループ内の NULL 以外の `(y, x)` ペアについて返します。`x` は独立変数、`y` は従属変数です。
+
+## 構文
+
+```sql
+REGR_AVGY(<y>, <x>)
+```
+
+## パラメータ
+
+| パラメータ | 説明 |
+| -- | -- |
+| `<y>` | 従属変数。Double 型をサポートします。 |
+| `<x>` | 独立変数。Double 型をサポートします。 |
+
+## 戻り値
+
+`y` の平均を表す Double 型の値を、NULL 以外の `(y, x)` ペアについて返します。
+グループ内に行がない場合、またはすべての行で式が NULL の場合、関数は `NULL` を返します。
+
+## 使用例
+
+```sql
+CREATE TABLE test_regr (
+  `id` int,
+  `x` double,
+  `y` double
+) DUPLICATE KEY (`id`)
+DISTRIBUTED BY HASH(`id`) BUCKETS AUTO
+PROPERTIES (
+  "replication_allocation" = "tag.location.default: 1"
+);
+
+INSERT INTO test_regr VALUES
+(1, 0, NULL),
+(2, 1, 3),
+(2, 2, 5),
+(2, 3, 7),
+(2, 4, 9),
+(2, 5, NULL);
+```
+
+```sql
+SELECT id, REGR_AVGY(y, x) FROM test_regr GROUP BY id ORDER BY id;
+```
+
+```text
++------+------------------+
+| id   | REGR_AVGY(y, x)  |
++------+------------------+
+|    1 |             NULL |
+|    2 |              6.0 |
++------+------------------+
+```
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.json
new file mode 100644
index 00000000000..a9784b3a305
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/intersect-count",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md",
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"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/intersect-count.md",
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+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.464Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/kurt.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/kurt.json
new file mode 100644
index 00000000000..e4d756a7668
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/kurt.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/kurt",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md",
+    "targetPath": 
"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/kurt.md",
+    "sourceCommit": "f9184fac0bbfb81ef27a7f834ad53f1764cc8929",
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+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.465Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.json
new file mode 100644
index 00000000000..8a5f6b59274
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/linear-histogram",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md",
+    "targetPath": 
"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/linear-histogram.md",
+    "sourceCommit": "f9184fac0bbfb81ef27a7f834ad53f1764cc8929",
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+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.465Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/map-agg.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/map-agg.json
new file mode 100644
index 00000000000..51c6f40e32d
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/map-agg.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/map-agg",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md",
+    "targetPath": 
"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/map-agg.md",
+    "sourceCommit": "f9184fac0bbfb81ef27a7f834ad53f1764cc8929",
+    "sourceHash": 
"584b406e88d5e2512e263e2412517792e0a081262f89ba1fdc047b31a557961c",
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+    "translatedAt": "2026-10-14T05:12:57.465Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-by.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-by.json
new file mode 100644
index 00000000000..13c95e1261c
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-by.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/max-by",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md",
+    "targetPath": 
"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/max-by.md",
+    "sourceCommit": "f9184fac0bbfb81ef27a7f834ad53f1764cc8929",
+    "sourceHash": 
"c6f6527a6dc7431aeffce1dfcb4e8fd5298789427b44d30310ae99faf37a2302",
+    "sourceTechnicalHash": 
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+    "reviewStatus": "machine",
+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.465Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-map.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-map.json
new file mode 100644
index 00000000000..bc5fdceaf43
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/max-map.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
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a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/median.json
 
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a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/percentile-array.json
 
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"4f691c6bdb12cc70c1b2f1478c1bdecb6fee2281dbc45b32a1f96833f3dc4e66",
+    "reviewStatus": "machine",
+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.466Z",
+    "glossaryVersion": "0"
+  }
+}
diff --git 
a/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.json
 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.json
new file mode 100644
index 00000000000..e14e4c0e277
--- /dev/null
+++ 
b/translations/state/ja/pages/default/4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.json
@@ -0,0 +1,20 @@
+{
+  "schemaVersion": 1,
+  "page": {
+    "pluginId": "default",
+    "version": "4.x",
+    "docId": "sql-manual/sql-functions/aggregate-functions/regr-avgy",
+    "locale": "ja",
+    "sourceLocale": "en",
+    "sourcePath": 
"versioned_docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md",
+    "targetPath": 
"i18n/ja/docusaurus-plugin-content-docs/version-4.x/sql-manual/sql-functions/aggregate-functions/regr-avgy.md",
+    "sourceCommit": "f9184fac0bbfb81ef27a7f834ad53f1764cc8929",
+    "sourceHash": 
"76300d327b8c8625684ab73bb52fb12d31dcfa0ac057a7cf5fd91e241e1ead53",
+    "sourceTechnicalHash": 
"9eb994d7f506358e4099b31962fd73e76d5de2a032da4374e8685aa901db8ded",
+    "targetHash": 
"79a611e85a1bbf78cfe6089662dbf0c5248f6996f8212ea2f99bb7b126b4af18",
+    "reviewStatus": "machine",
+    "ownership": "machine",
+    "translatedAt": "2026-10-14T05:12:57.466Z",
+    "glossaryVersion": "0"
+  }
+}


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(doris-website) branch master updated: docs(i18n): translate 20 Japanese pages for T09-4X-060 (#4252)

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