Amazon Redshift 將不再支援從修補程式 198 開始建立新的 Python UDFs。現有 Python UDF 將繼續正常運作至 2026 年 6 月 30 日。如需詳細資訊，請參閱[部落格文章](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/)。

本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

# SYS\$1QUERY\$1HISTORY
<a name="SYS_QUERY_HISTORY"></a>

使用 SYS\$1QUERY\$1HISTORY 來檢視使用者查詢的詳細資料。每一列代表一個使用者查詢，其中包含某些欄位的累計統計資料。此檢視包含許多類型的查詢，例如資料定義語言 (DDL)、資料處理語言 (DML)、複製、卸載和 Amazon Redshift Spectrum。它包含正在執行和已完成的查詢。

所有使用者都可看見 SYS\$1QUERY\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。

**注意**  
若要驗證包含已執行查詢的交易是否已成功認可，您需要在系統資料表與 `sys_transaction_history` 資料表之間執行聯結操作。例如：  

```
SELECT 
    qh.transaction_id,
    qh.query_id,
    qh.status AS query_status,
    qh.query_type,
    TRIM(qh.query_text) AS query_text,
    th.status AS transaction_status
FROM 
    sys_query_history qh
LEFT JOIN 
    sys_transaction_history th ON qh.transaction_id = th.transaction_id;
```

## 資料表欄
<a name="SYS_QUERY_HISTORY-table-columns"></a>

[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_HISTORY.html)

## 範例查詢
<a name="SYS_QUERY_HISTORY-sample-queries"></a>

下列查詢會傳回執行中和佇列中的查詢。

```
SELECT user_id,
       query_id,
       transaction_id,
       session_id,
       status,
       trim(database_name) AS database_name,
       start_time,
       end_time,
       result_cache_hit,
       elapsed_time,
       queue_time,
       execution_time
FROM sys_query_history
WHERE status IN ('running','queued')
ORDER BY start_time;
```

輸出範例。

```
 user_id | query_id | transaction_id | session_id | status  | database_name |        start_time         |          end_time          | result_cache_hit | elapsed_time | queue_time | execution_time
---------+----------+----------------+------------+---------+---------------+---------------------------+----------------------------+------------------+--------------+------------+----------------
     101 |   760705 |         852337 | 1073832321 | running | tpcds_1t      | 2022-02-15 19:03:19.67849 | 2022-02-15 19:03:19.739811 | f                |        61321 |          0 |              0
```

下列查詢會傳回特定查詢的查詢開始時間、結束時間、佇列時間、經歷時間、計劃時間及其他中繼資料。

```
SELECT user_id,
       query_id,
       transaction_id,
       session_id,
       status,
       trim(database_name) AS database_name,
       start_time,
       end_time,
       result_cache_hit,
       elapsed_time,
       queue_time,
       execution_time,
       planning_time,
       trim(query_text) as query_text
FROM sys_query_history
WHERE query_id = 3093;
```

輸出範例。

```
user_id | query_id | transaction_id | session_id |   status   | database_name |         start_time         |          end_time          | result_cache_hit | elapsed_time | queue_time | execution_time | planning_time | query_text
--------+----------+----------------+------------+------------+---------------+----------------------------+----------------------------+------------------+--------------+------------+----------------+---------------+-------------------------------------
    106 |     3093 |          11759 | 1073750146 | success    | dev           | 2023-03-16 16:53:17.840214 | 2023-03-16 16:53:18.106588 | f                |       266374 |          0 |         105725 |        136589 | select count(*) from item;
```

下列查詢會列出10 個最近的 SELECT 查詢。

```
SELECT query_id,
       transaction_id,
       session_id,
       start_time,
       elapsed_time,
       queue_time,
       execution_time,
       returned_rows,
       returned_bytes
FROM sys_query_history
WHERE query_type = 'SELECT'
ORDER BY start_time DESC limit 10;
```

輸出範例。

```
 query_id | transaction_id | session_id |         start_time         | elapsed_time | queue_time | execution_time | returned_rows | returned_bytes
----------+----------------+------------+----------------------------+--------------+------------+----------------+---------------+----------------
   526532 |          61093 | 1073840313 | 2022-02-09 04:43:24.149603 |       520571 |          0 |         481293 |             1 |           3794
   526520 |          60850 | 1073840313 | 2022-02-09 04:38:27.24875  |       635957 |          0 |         596601 |             1 |           3679
   526508 |          60803 | 1073840313 | 2022-02-09 04:37:51.118835 |       563882 |          0 |         503135 |             5 |          17216
   526505 |          60763 | 1073840313 | 2022-02-09 04:36:48.636224 |       649337 |          0 |         589823 |             1 |            652
   526478 |          60730 | 1073840313 | 2022-02-09 04:36:11.741471 |     14611321 |          0 |       14544058 |             0 |              0
   526467 |          60636 | 1073840313 | 2022-02-09 04:34:11.91463  |     16711367 |          0 |       16633767 |             1 |            575
   511617 |         617946 | 1074009948 | 2022-01-20 06:21:54.44481  |      9937090 |          0 |        9899271 |           100 |          12500
   511603 |         617941 | 1074259415 | 2022-01-20 06:21:45.71744  |      8065081 |          0 |        7582500 |           100 |           8889
   511595 |         617935 | 1074128320 | 2022-01-20 06:21:44.030876 |      1051270 |          0 |        1014879 |             1 |             72
   511584 |         617931 | 1074030019 | 2022-01-20 06:21:42.764088 |       609033 |          0 |         485887 |           100 |           8438
```

 下列查詢會顯示每日選擇查詢計數和平均查詢經歷時間。

```
SELECT date_trunc('day',start_time) AS exec_day,
       status,
       COUNT(*) AS query_cnt,
       AVG(datediff (microsecond,start_time,end_time)) AS elapsed_avg
FROM sys_query_history
WHERE query_type = 'SELECT'
AND start_time >= '2022-01-14'
AND start_time <= '2022-01-18'
GROUP BY exec_day,
         status
ORDER BY exec_day,
         status;
```

輸出範例。

```
      exec_day       | status  | query_cnt | elapsed_avg
---------------------+---------+-----------+------------
 2022-01-14 00:00:00 | success |      5253 |  56608048
 2022-01-15 00:00:00 | success |      7004 |  56995017
 2022-01-16 00:00:00 | success |      5253 |  57016363
 2022-01-17 00:00:00 | success |      5309 |  55236784
 2022-01-18 00:00:00 | success |      8092 |  54355124
```

下列查詢會顯示日常查詢的經歷時間效能。

```
SELECT distinct date_trunc('day',start_time) AS exec_day,
       query_count.cnt AS query_count,
       Percentile_cont(0.5) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P50_runtime,
       Percentile_cont(0.8) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P80_runtime,
       Percentile_cont(0.9) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P90_runtime,
       Percentile_cont(0.99) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P99_runtime,
       Percentile_cont(1.0) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS max_runtime
FROM sys_query_history
LEFT JOIN (SELECT  date_trunc('day',start_time) AS day, count(*) cnt
           FROM sys_query_history
           WHERE query_type = 'SELECT'
           GROUP by 1) query_count
ON date_trunc('day',start_time) = query_count.day
WHERE query_type = 'SELECT'
ORDER BY exec_day;
```

輸出範例。

```
      exec_day       | query_count | p50_runtime | p80_runtime | p90_runtime | p99_runtime  | max_runtime
---------------------+-------------+-------------+-------------+-------------+--------------+--------------
 2022-01-14 00:00:00 |        5253 |  16816922.0 |  69525096.0 | 158524917.8 | 486322477.52 | 1582078873.0
 2022-01-15 00:00:00 |        7004 |  15896130.5 |  71058707.0 | 164314568.9 | 500331542.07 | 1696344792.0
 2022-01-16 00:00:00 |        5253 |  15750451.0 |  72037082.2 | 159513733.4 | 480372059.24 | 1594793766.0
 2022-01-17 00:00:00 |        5309 |  15394513.0 |  68881393.2 | 160254700.0 | 493372245.84 | 1521758640.0
 2022-01-18 00:00:00 |        8092 |  15575286.5 |  68485955.4 | 154559572.5 | 463552685.39 | 1542783444.0
 2022-01-19 00:00:00 |        5860 |  16648747.0 |  72470482.6 | 166485138.2 | 492038228.67 | 1693483241.0
 2022-01-20 00:00:00 |        1751 |  15422072.0 |  69686381.0 | 162315385.0 | 497066615.00 | 1439319739.0
 2022-02-09 00:00:00 |          13 |   6382812.0 |  17616161.6 |  21197988.4 |  23021343.84 |   23168439.0
```

下列查詢顯示查詢類型分佈。

```
SELECT query_type,
       COUNT(*) AS query_count
FROM sys_query_history
GROUP BY query_type
ORDER BY query_count DESC;
```

輸出範例。

```
 query_type | query_count
------------+-------------
 UTILITY    |      134486
 SELECT     |       38537
 DDL        |        4832
 OTHER      |         768
 LOAD       |         768
 CTAS       |         748
 COMMAND    |          92
```

下列範例顯示數個查詢之間查詢雜湊結果的差異。請觀察下列查詢：

```
CREATE TABLE test_table (col1 INT);

INSERT INTO test_table VALUES (1),(2);

SELECT * FROM test_table;

SELECT * FROM test_table;

SELECT col1 FROM test_table;

SELECT * FROM test_table WHERE col1=1;

SELECT * FROM test_table WHERE col1=2;

SELECT query_id, TRIM(user_query_hash) AS user_query_hash, TRIM(generic_query_hash) AS generic_query_hash, TRIM(query_text) AS text FROM sys_query_history ORDER BY start_time
DESC LIMIT 10;
```

以下是範例輸出：

```
query_id | user_query_hash | generic_query_hash | text
---------+-----------------+--------------------+----------
24723049 | oPuFtjEPLTs=    | oPuFtjEPLTs=       | select query_id, trim(user_query_hash) as user_query_hash, trim(generic_query_hash) as generic_query_hash, query_hash_version, trim(query_text) as text from sys_query_history order by start_time\r\ndesc limit 20
24723045 | Gw2Kwdd8m2I=    | IwfRu8/XAKI=       | select * from test_table where col1=2 limit 100
24723041 | LNw2vx0GDXo=    | IwfRu8/XAKI=       | select * from test_table where col1=1 limit 100
24723036 | H+qep/c82Y8=    | H+qep/c82Y8=       | select col1 from test_table limit 100
24723033 | H+qep/c82Y8=    | H+qep/c82Y8=       | select * from test_table limit 100
24723029 | H+qep/c82Y8=    | H+qep/c82Y8=       | select * from test_table limit 100
24723023 | 50sirx9E1hU=    | uO36Z1a/QYs=       | insert into test_table values (1),(2)
24723021 | YSVnlivZHeo=    | YSVnlivZHeo=       | create table test_table (col1 int)
```

`SELECT * FROM test_table;` 和 `SELECT col1 FROM test_table;` 具有相同的 user\$1query\$1hash 值，因為 test\$1table 只有一欄。`SELECT * FROM test_table WHERE col1=1;` 和 `SELECT * FROM test_table WHERE col1=2;` 具有不同的 user\$1query\$1hash 值，但具有相同的 generic\$1query\$1hash 值，因為兩個查詢除了查詢常值 1 和 2 之外完全一致。