SYS_QUERY_HISTORY

使用 SYS_QUERY_HISTORY 查看用户查询的详细信息。每行代表一个用户查询，其中包含某些字段的累积统计数据。此视图包含许多类型的查询，例如数据定义语言 (DDL)、数据操作语言 (DML)、复制、卸载和 Amazon Redshift Spectrum。它包含正在运行和已完成的查询。

SYS_QUERY_HISTORY 对所有用户可见。超级用户可以查看所有行；普通用户只能查看其自己的数据。有关更多信息，请参阅系统表和视图中的数据可见性。

表列

列名称	数据类型	描述
user_id	integer	提交查询的用户标识符。
query_id	bigint	查询标识符。
query_label	character(320)	查询的短名称。
transaction_id	bigint	事务标识符。
session_id	integer	运行查询进程的进程标识符。
database_name	character(128)	在发起查询时用户连接到的数据库的名称。
query_type	character(32)	查询类型，例如，SELECT、INSERT、UPDATE、UNLOAD COPY、COMMAND、DDL、UTILITY、CTAS 和 OTHER。
status	character(10)	查询的状态。有效值：planning、queued、running、returning、failed、canceled 和 success。
result_cache_hit	布尔值	指示查询是否匹配结果缓存。
start_time	timestamp	查询开始的时间。
end_time	timestamp	查询完成的时间。
elapsed_time	bigint	在查询上花费的总时间（微秒）。
queue_time	bigint	在服务类查询队列上花费的总时间（微秒）。
execution_time	bigint	在服务类中运行的总时间（微秒）。
error_message	character(512)	查询失败的原因。
returned_rows	bigint	返回到客户端的行数。
returned_bytes	bigint	返回到客户端的字节数。
query_text	character(4000)	查询字符串。此字符串可能会被截断。
redshift_version	character(256)	查询运行时的 Amazon Redshift 版本。
usage_limit	character(150)	查询达到的使用限制 ID 的列表。
compute_type	varchar(32)	指示查询运行在主集群还是并发扩展集群上。可能的值为 `primary`（查询在主集群上运行）、`secondary`（查询在辅助集群上运行）或 `primary-scale`（查询在并发集群上运行）。这仅适用于预调配的集群。
compile_time	bigint	在编译上花费的总时间（微秒）。
planning_time	bigint	在规划查询时花费的总时间（微秒）。
lock_wait_time	bigint	等待关系锁定所花费的总时间（微秒）。

示例查询

以下查询返回了正在运行的查询和已排队的查询。


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;

示例输出。


 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

以下查询返回了特定查询的查询开始时间、结束时间、排队时间、已用时间、计划时间和其他元数据。


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;

示例输出。


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;

以下示例列出了 10 个最近的 SELECT 查询。


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;

示例输出。



 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

以下查询显示了每日 Select 查询的计数和平均查询用时。


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;

示例输出。


      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

以下查询显示了每日查询所用时间性能。


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;

示例输出。



      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

以下查询显示了查询类型分布。


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

示例输出。


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

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SYS_QUERY_DETAIL

SYS_QUERY_TEXT