从补丁 198 开始，Amazon Redshift 将不再支持创建新的 Python UDF。现有的 Python UDF 将继续正常运行至 2026 年 6 月 30 日。有关更多信息，请参阅[博客文章](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/)。
# SYS 监控视图
*监控视图*是 Amazon Redshift 中用于监控预置集群和无服务器工作组的查询和工作负载资源使用情况的系统视图。这些视图位于 `pg_catalog` 架构中。要显示这些视图提供的信息，请运行 SQL SELECT 语句。
除非另有说明，否则这些视图适用于 Amazon Redshift 集群和 Amazon Redshift Serverless 工作组。
*SYS\$1SERVERLESS\$1USAGE* 仅会收集 Amazon Redshift Serverless 的使用情况数据。
**Topics**
+ [SYS\$1ANALYZE\$1COMPRESSION\$1HISTORY](r_SYS_ANALYZE_COMPRESSION_HISTORY.md)
+ [SYS\$1ANALYZE\$1HISTORY](SYS_ANALYZE_HISTORY.md)
+ [SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG](SYS_APPLIED_MASKING_POLICY_LOG.md)
+ [SYS\$1AUTOMATIC\$1OPTIMIZATION](SYS_AUTOMATIC_OPTIMIZATION.md)
+ [SYS\$1AUTO\$1TABLE\$1OPTIMIZATION](r_SYS_AUTO_TABLE_OPTIMIZATION.md)
+ [SYS\$1CHILD\$1QUERY\$1TEXT](SYS_CHILD_QUERY_TEXT.md)
+ [SYS\$1CONNECTION\$1LOG](SYS_CONNECTION_LOG.md)
+ [SYS\$1COPY\$1JOB](SYS_COPY_JOB.md)
+ [SYS\$1COPY\$1JOB\$1DETAIL](SYS_COPY_JOB_DETAIL.md)
+ [SYS\$1COPY\$1JOB\$1INFO](SYS_COPY_JOB_INFO.md)
+ [SYS\$1COPY\$1REPLACEMENTS](SYS_COPY_REPLACEMENTS.md)
+ [SYS\$1DATASHARE\$1CHANGE\$1LOG](SYS_DATASHARE_CHANGE_LOG.md)
+ [SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE](r_SYS_DATASHARE_CROSS_REGION_USAGE.md)
+ [SYS\$1DATASHARE\$1USAGE\$1CONSUMER](SYS_DATASHARE_USAGE_CONSUMER.md)
+ [SYS\$1DATASHARE\$1USAGE\$1PRODUCER](SYS_DATASHARE_USAGE_PRODUCER.md)
+ [SYS\$1EXTERNAL\$1QUERY\$1DETAIL](SYS_EXTERNAL_QUERY_DETAIL.md)
+ [SYS\$1EXTERNAL\$1QUERY\$1ERROR](SYS_EXTERNAL_QUERY_ERROR.md)
+ [SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION](SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION.md)
+ [SYS\$1INTEGRATION\$1ACTIVITY](r_SYS_INTEGRATION_ACTIVITY.md)
+ [SYS\$1INTEGRATION\$1TABLE\$1ACTIVITY](r_SYS_INTEGRATION_TABLE_ACTIVITY.md)
+ [SYS\$1INTEGRATION\$1TABLE\$1STATE\$1CHANGE](r_SYS_INTEGRATION_TABLE_STATE_CHANGE.md)
+ [SYS\$1LOAD\$1DETAIL](SYS_LOAD_DETAIL.md)
+ [SYS\$1LUDF\$1DETAIL](SYS_LUDF_DETAIL.md)
+ [SYS\$1LOAD\$1ERROR\$1DETAIL](SYS_LOAD_ERROR_DETAIL.md)
+ [SYS\$1LOAD\$1HISTORY](SYS_LOAD_HISTORY.md)
+ [SYS\$1MV\$1REFRESH\$1HISTORY](SYS_MV_REFRESH_HISTORY.md)
+ [SYS\$1MV\$1STATE](SYS_MV_STATE.md)
+ [SYS\$1PROCEDURE\$1CALL](SYS_PROCEDURE_CALL.md)
+ [SYS\$1PROCEDURE\$1MESSAGES](SYS_PROCEDURE_MESSAGES.md)
+ [SYS\$1QUERY\$1DETAIL](SYS_QUERY_DETAIL.md)
+ [SYS\$1QUERY\$1EXPLAIN](SYS_QUERY_EXPLAIN.md)
+ [SYS\$1QUERY\$1HISTORY](SYS_QUERY_HISTORY.md)
+ [SYS\$1QUERY\$1TEXT](SYS_QUERY_TEXT.md)
+ [SYS\$1REDSHIFT\$1TEMPLATE](SYS_REDSHIFT_TEMPLATE.md)
+ [SYS\$1RESTORE\$1LOG](SYS_RESTORE_LOG.md)
+ [SYS\$1RESTORE\$1STATE](SYS_RESTORE_STATE.md)
+ [SYS\$1SCHEMA\$1QUOTA\$1VIOLATIONS](r_SYS_SCHEMA_QUOTA_VIOLATIONS.md)
+ [SYS\$1SERVERLESS\$1USAGE](SYS_SERVERLESS_USAGE.md)
+ [SYS\$1SESSION\$1HISTORY](SYS_SESSION_HISTORY.md)
+ [SYS\$1SPATIAL\$1SIMPLIFY](SYS_SPATIAL_SIMPLIFY.md)
+ [SYS\$1STREAM\$1SCAN\$1ERRORS](r_SYS_STREAM_SCAN_ERRORS.md)
+ [SYS\$1STREAM\$1SCAN\$1STATES](r_SYS_STREAM_SCAN_STATES.md)
+ [SYS\$1TRANSACTION\$1HISTORY](SYS_TRANSACTION_HISTORY.md)
+ [SYS\$1UDF\$1LOG](SYS_UDF_LOG.md)
+ [SYS\$1UNLOAD\$1DETAIL](SYS_UNLOAD_DETAIL.md)
+ [SYS\$1UNLOAD\$1HISTORY](SYS_UNLOAD_HISTORY.md)
+ [SYS\$1USERLOG](SYS_USERLOG.md)
+ [SYS\$1VACUUM\$1HISTORY](SYS_VACUUM_HISTORY.md)
# SYS\$1ANALYZE\$1COMPRESSION\$1HISTORY
记录在 COPY 或 ANALYZE COMPRESSION 命令期间压缩分析操作的详细信息。
SYS\$1ANALYZE\$1COMPRESSION\$1HISTORY 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_ANALYZE_COMPRESSION_HISTORY.html)
## 示例查询
以下示例检查在同一个会话中运行的最后一个 COPY 命令对 `lineitem` 表执行压缩分析的详细信息。
```
select transaction_id, table_id, btrim(table_name) as table_name, column_position, old_encoding, new_encoding, mode
from sys_analyze_compression_history
where transaction_id = (select transaction_id from sys_query_history where query_id = pg_last_copy_id()) order by column_position;
transaction_id | table_id | table_name | column_position | old_encoding | new_encoding | mode
-----------------+-------------+------------+-----------------+-----------------+-----------------+-------------
8196 | 248126 | lineitem | 0 | mostly32 | mostly32 | ON
8196 | 248126 | lineitem | 1 | mostly32 | lzo | ON
8196 | 248126 | lineitem | 2 | lzo | delta32k | ON
8196 | 248126 | lineitem | 3 | delta | delta | ON
8196 | 248126 | lineitem | 4 | bytedict | bytedict | ON
8196 | 248126 | lineitem | 5 | mostly32 | mostly32 | ON
8196 | 248126 | lineitem | 6 | delta | delta | ON
8196 | 248126 | lineitem | 7 | delta | delta | ON
8196 | 248126 | lineitem | 8 | lzo | zstd | ON
8196 | 248126 | lineitem | 9 | runlength | zstd | ON
8196 | 248126 | lineitem | 10 | delta | lzo | ON
8196 | 248126 | lineitem | 11 | delta | delta | ON
8196 | 248126 | lineitem | 12 | delta | delta | ON
8196 | 248126 | lineitem | 13 | bytedict | zstd | ON
8196 | 248126 | lineitem | 14 | bytedict | zstd | ON
8196 | 248126 | lineitem | 15 | text255 | zstd | ON
(16 rows)
```
# SYS\$1ANALYZE\$1HISTORY
记录 [ANALYZE](https://docs.aws.amazon.com/redshift/latest/dg/r_ANALYZE.html) 操作的详细信息。
SYS\$1ANALYZE\$1HISTORY 只对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_ANALYZE_HISTORY.html)
## 示例查询
```
user_id | transaction_id | database_name | schema_name | table_name | table_id | is_automatic | Status | start_time | end_time | rows | modified_rows | analyze_threshold_percent | last_analyze_time
---------+----------------+---------------+-------------+---------------------+----------+--------------+--------+----------------------------+----------+-----------------+------+---------------+---------------------------+---------------------
101 | 8006 | dev | public | test_table_562bf8dc | 110427 | f | Full | 2023-09-21 18:33:08.504646 | 2023-09-21 18:33:24.296498 | 5 | 5 | 0 | 2000-01-01 00:00:00
```
# SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG
使用 SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG 跟踪动态数据掩蔽策略在引用受 RLS 保护关系的查询上的应用情况。
SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG 对以下用户可见：
+ 超级用户
+ 拥有 `sys:operator` 角色的用户
+ 拥有 ACCESS SYSTEM TABLE 权限的用户
常规用户将看到 0 行。
请注意，拥有 `sys:secadmin` 角色的用户看不到 SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG。
有关动态数据屏蔽的更多信息，请参阅[动态数据掩蔽](t_ddm.md)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_APPLIED_MASKING_POLICY_LOG.html)
## 示例查询
以下示例显示 `mask_credit_card_full` 屏蔽策略已附加到 `credit_db.public.credit_cards` 表中。
```
select policy_name, database_name, relation_name, schema_name, relation_kind
from sys_applied_masking_policy_log;
policy_name | database_name | relation_name | schema_name | relation_kind
----------------------+---------------+---------------+-------------+---------------
mask_credit_card_full | credit_db | credit_cards | public | table
(1 row)
```
# SYS\$1AUTOMATIC\$1OPTIMIZATION
使用 SYS\$1AUTOMATIC\$1OPTIMIZATION 可查看有关 Amazon Redshift 为自动优化（也称为自动处理）而运行的任务的详细信息。有关自动优化的更多信息，请参阅[自动数据库优化](c_autonomics.md)。
SYS\$1AUTOMATIC\$1OPTIMIZATION 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_AUTOMATIC_OPTIMIZATION.html)
## 使用说明
对于无服务器集群，compute\$1type 列将为空，因为我们没有区分主计算资源和主扩展计算资源。无服务器集群计算资源以 Redshift 处理器（RPU）用量为单位。有关更多信息，请参阅 [Amazon Redshift Serverless 的计算容量](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-capacity.html)。
## 示例
下面的查询显示对表 155259 执行的自动优化。
```
SELECT pid, trim(task_type) as task_type,
trim(database) as database,
trim(status) as status,
trim(event) as event,
event_time
from SYS_AUTOMATIC_OPTIMIZATION
WHERE object_ids like '%155259%'
AND status = 'Task completed successfully';
task_type | database | status | event | event_time
------------+----------------+-----------------------------+-----------+----------------------------
VacuumSort | tpcds_100g_oob | Task completed successfully | Completed | 2025-12-22 07:27:15.943018
```
以下查询显示所有已执行的自动“VacuumSort”优化。有关“VacuumSort”的更多信息，请参阅[自动表排序](t_Reclaiming_storage_space202.md#automatic-table-sort)。
```
SELECT trim(task_type) as task_type,
trim(database) as database,
trim(object_type) as object_type,
trim(object_ids) as object_ids,
trim(status) as status,
trim(event) as event,
event_time
from SYS_AUTOMATIC_OPTIMIZATION
WHERE task_type like '%VacuumSort%'
AND status = 'Task completed successfully';
task_type | database | object_type | object_ids | status | event | event_time
------------+----------------+-------------+------------+-----------------------------+-----------+----------------------------
VacuumSort | tpcds_100g_oob | table | 155301 | Task completed successfully | Completed | 2025-12-22 07:14:00.065391
VacuumSort | tpcds_100g_oob | table | 155303 | Task completed successfully | Completed | 2025-12-22 07:14:09.158251
VacuumSort | tpcds_100g_oob | table | 155291 | Task completed successfully | Completed | 2025-12-22 07:17:06.61164
VacuumSort | tpcds_100g_oob | table | 155293 | Task completed successfully | Completed | 2025-12-22 07:17:37.015069
VacuumSort | tpcds_100g_oob | table | 155281 | Task completed successfully | Completed | 2025-12-22 07:18:54.903935
VacuumSort | tpcds_100g_oob | table | 155279 | Task completed successfully | Completed | 2025-12-22 07:20:13.960002
VacuumSort | tpcds_100g_oob | table | 155271 | Task completed successfully | Completed | 2025-12-22 07:21:26.095549
VacuumSort | tpcds_100g_oob | table | 155267 | Task completed successfully | Completed | 2025-12-22 07:22:48.119249
VacuumSort | tpcds_100g_oob | table | 155269 | Task completed successfully | Completed | 2025-12-22 07:24:12.010424
VacuumSort | tpcds_100g_oob | table | 155263 | Task completed successfully | Completed | 2025-12-22 07:25:35.958388
VacuumSort | tpcds_100g_oob | table | 155265 | Task completed successfully | Completed | 2025-12-22 07:26:40.580395
VacuumSort | tpcds_100g_oob | table | 155259 | Task completed successfully | Completed | 2025-12-22 07:27:15.943018
(12 rows)
```
# SYS\$1AUTO\$1TABLE\$1OPTIMIZATION
记录 Amazon Redshift 对自动优化定义的表执行的自动操作。
SYS\$1AUTO\$1TABLE\$1OPTIMIZATION 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_AUTO_TABLE_OPTIMIZATION.html)
## 示例查询
在以下示例中，结果中的行显示了由 Amazon Redshift 执行的操作。
```
SELECT table_id, alter_table_type, status, event_time, alter_from
FROM SYS_AUTO_TABLE_OPTIMIZATION;
table_id | alter_table_type | status | event_time | alter_from
----------+---------------------+------------------------------------------------------+-----------------------------+-----------------
118082 | sortkey | Start | 2020-08-22 19:42:20.727049 |
118078 | sortkey | Start | 2020-08-22 19:43:54.728819 |
118082 | sortkey | Start | 2020-08-22 19:42:52.690264 |
118072 | sortkey | Start | 2020-08-22 19:44:14.793572 |
118082 | sortkey | Failed | 2020-08-22 19:42:20.728917 |
118078 | sortkey | Complete | 2020-08-22 19:43:54.792705 | SORTKEY: None;
118086 | sortkey | Complete | 2020-08-22 19:42:00.72635 | SORTKEY: None;
118082 | sortkey | Complete | 2020-08-22 19:43:34.728144 | SORTKEY: None;
118072 | sortkey | Skipped:Retry exceeds the maximum limit for a table. | 2020-08-22 19:44:46.706155 |
118086 | sortkey | Start | 2020-08-22 19:42:00.685255 |
118082 | sortkey | Start | 2020-08-22 19:43:34.69531 |
118072 | sortkey | Start | 2020-08-22 19:44:46.703331 |
118082 | sortkey | Checkpoint: progress 14.755079% | 2020-08-22 19:42:52.692828 |
118072 | sortkey | Failed | 2020-08-22 19:44:14.796071 |
116723 | sortkey | Abort:This table is not AUTO. | 2020-10-28 05:12:58.479233 |
110203 | distkey | Abort:This table is not AUTO. | 2020-10-28 05:45:54.67259 |
```
# SYS\$1CHILD\$1QUERY\$1TEXT
返回子查询的 SQL 文本。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_CHILD_QUERY_TEXT.html)
## 示例查询
在以下示例中，结果中的行显示了由 Amazon Redshift 执行的操作。
```
SELECT * from sys_child_query_text where query_id = '34487366' order by child_query_sequence asc, sequence asc;
user_id | query_id | child_query_sequence | sequence | text
--------|----------|----------------------|----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
100 | 34899339 | 1 | 0 | /* RQEV2-aY6ZZ1ZpQK */\nwith venue as (\n select venueid,\n venuename,\n venuestate\n from venue\n), event as (\n select eventid,\n venueid,\n date
100 | 34899339 | 1 | 1 | id,\n eventname\n from event\n where eventname like '3 Doors Down'\n), users as (\n select userid\n from users\n), sales as (\n select salesid,\n pricepaid,
100 | 34899339 | 1 | 2 | \n eventid,\n buyerid\n from sales\n)\nselect e.eventname,\n v.venuename,\n count(distinct(u.userid)) as unique_customers,\n sum(s.pricepaid) as total_sal
100 | 34899339 | 1 | 3 | es\nfrom venue as v inner join event e on v.venueid = e.venueid\ninner join sales s on e.eventid = s.eventid inner join users u on s.buyerid = u.userid\ngroup by 1,2\norder by 4 desc limit 100
```
# SYS\$1CONNECTION\$1LOG
记录身份验证尝试以及连接与断开连接。
SYS\$1CONNECTION\$1LOG 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_CONNECTION_LOG.html)
## 示例查询
要查看打开连接的详细信息，请运行以下查询。
```
select record_time, user_name, database_name, remote_host, remote_port
from sys_connection_log
where event = 'initiating session'
and session_id not in
(select session_id from sys_connection_log
where event = 'disconnecting session')
order by 1 desc;
record_time | user_name | database_name | remote_host | remote_port
--------------------+-------------+-----------------+---------------+---------------------------------
2014-11-06 20:30:06 | rdsdb | dev | [local] |
2014-11-06 20:29:37 | test001 | test | 10.49.42.138 | 11111
2014-11-05 20:30:29 | rdsdb | dev | 10.49.42.138 | 33333
2014-11-05 20:28:35 | rdsdb | dev | [local] |
(4 rows)
```
以下示例反映了一次失败的身份验证尝试和一次成功的连接与断开连接。
```
select event, record_time, remote_host, user_name
from sys_connection_log order by record_time;
event | record_time | remote_host | user_name
-----------------------+----------------------------+---------------+---------
authentication failure | 2012-10-25 14:41:56.96391 | 10.49.42.138 | john
authenticated | 2012-10-25 14:42:10.87613 | 10.49.42.138 | john
initiating session | 2012-10-25 14:42:10.87638 | 10.49.42.138 | john
disconnecting session | 2012-10-25 14:42:19.95992 | 10.49.42.138 | john
(4 rows)
```
以下示例显示了 ODBC 驱动程序的版本、客户端计算机上的操作系统以及用于连接到 Amazon Redshift 集群的插件。在此示例中，使用的插件用于使用登录名和密码进行标准 ODBC 驱动程序身份验证。
```
select driver_version, os_version, plugin_name from sys_connection_log;
driver_version | os_version | plugin_name
----------------------------------------+-----------------------------------+--------------------
Amazon Redshift ODBC Driver 1.4.15.0001 | Darwin 18.7.0 x86_64 | none
Amazon Redshift ODBC Driver 1.4.15.0001 | Linux 4.15.0-101-generic x86_64 | none
```
以下示例显示了客户端计算机上的操作系统版本、驱动程序版本和协议版本。
```
select os_version, driver_version, protocol_version from sys_connection_log;
os_version | driver_version | protocol_version
--------------------------------+------------------------------+--------------------
Linux 4.15.0-101-generic x86_64 | Redshift JDBC Driver 2.0.0.0 | 2
Linux 4.15.0-101-generic x86_64 | Redshift JDBC Driver 2.0.0.0 | 2
Linux 4.15.0-101-generic x86_64 | Redshift JDBC Driver 2.0.0.0 | 2
```
# SYS\$1COPY\$1JOB
使用 SYS\$1COPY\$1JOB 查看 COPY JOB 命令的详细信息。
此视图包含已创建的 COPY JOB 命令。
SYS\$1COPY\$1JOB 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_COPY_JOB.html)
# SYS\$1COPY\$1JOB\$1DETAIL
使用 SYS\$1COPY\$1JOB\$1DETAIL 查看 COPY JOB 命令的详细信息。
此视图包含已创建的 COPY JOB 命令。如果 COPY JOB 尝试加载文件但加载失败，则在将来的自动 COPY JOB 尝试时会跳过该文件。
SYS\$1COPY\$1JOB\$1DETAIL 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_COPY_JOB_DETAIL.html)
以下示例返回一行，其中包含摄取的条目。
```
SELECT * FROM SYS_COPY_JOB_DETAIL WHERE status ilike '%ingested%' limit 1;
user_id | 100
database_name | dev
job_name | many_job_4_3
job_id | 110702
file_location | saral-sqs-system4623202051-0
file_name | frenzy-9/4623202051/file_0_107
file_size | 11302
file_etag | 51b2d78ac5b5aecf4ee6f8374815ad19
modification_time | 2024-07-15 20:43:14
enqueue_time | 2024-07-15 20:44:24
status | Ingested
```
# SYS\$1COPY\$1JOB\$1INFO
使用 SYS\$1COPY\$1JOB\$1INFO 查看记录的有关 COPY JOB 的消息。
此视图包含有关已运行的 COPY JOB 中的错误的信息。
SYS\$1COPY\$1JOB\$1INFO 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_COPY_JOB_INFO.html)
# SYS\$1COPY\$1REPLACEMENTS
显示当无效的 UTF-8 字符由带有 ACCEPTINVCHARS 选项的 [COPY](r_COPY.md) 命令替换时所记录的日志。对于每个至少需要一次替换的节点切片上的前 100 行，将针对每行向 SYS\$1COPY\$1REPLACEMENTS 添加一个日志条目。
您可以使用此视图查看有关无服务器工作组和预置集群的信息。
SYS\$1COPY\$1REPLACEMENTS 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_COPY_REPLACEMENTS.html)
## 示例查询
以下示例返回最近的 COPY 操作中的替换。
```
select query_idp, table_id, file_name, line_number, colname
from sys_copy_replacements
where query = pg_last_copy_id();
query_id | table_id | file_name | line_number | column_name
---------+----------+-------------------------------------------------------+-------------+--------
96 | 26 | s3://DOC-EXAMPLE-BUCKET/allusers_pipe.txt | 123 | city
96 | 26 | s3://DOC-EXAMPLE-BUCKET/allusers_pipe.txt | 456 | city
96 | 26 | s3://DOC-EXAMPLE-BUCKET/allusers_pipe.txt | 789 | city
96 | 26 | s3://DOC-EXAMPLE-BUCKET/allusers_pipe.txt | 012 | city
96 | 26 | s3://DOC-EXAMPLE-BUCKET/allusers_pipe.txt | 119 | city
...
```
# SYS\$1DATASHARE\$1CHANGE\$1LOG
记录用于跟踪创建器和使用者集群上的数据共享更改的综合视图。
SYS\$1DATASHARE\$1CHANGE\$1LOG 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_DATASHARE_CHANGE_LOG.html)
## 示例查询
以下示例显示了 SYS\$1DATASHARE\$1CHANGE\$1LOG 视图。
```
SELECT DISTINCT action
FROM sys_datashare_change_log
WHERE share_object_name LIKE 'tickit%';
action
-----------------------
"ALTER DATASHARE ADD"
```
# SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE
使用 SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 视图，可以获取跨区域数据共享查询所导致的跨区域数据传输使用情况的摘要。SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 汇总了段级别的详细信息。
SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_DATASHARE_CROSS_REGION_USAGE.html)
## 示例查询
以下示例显示了 SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 视图。
```
SELECT query_id, segment_id, transferred_data, source_region
from sys_datashare_cross_region_usage
where query_id = pg_last_query_id()
order by query_id, segment_id;
query_id | segment_id | transferred_data | source_region
-----------+------------+------------------+---------------
200048 | 2 | 4194304 | us-west-1
200048 | 2 | 4194304 | us-east-2
```
# SYS\$1DATASHARE\$1USAGE\$1CONSUMER
记录数据共享的活动和使用情况。此视图仅与使用者集群相关。
SYS\$1DATASHARE\$1USAGE\$1CONSUMER 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_DATASHARE_USAGE_CONSUMER.html)
## 示例查询
以下示例显示了 SYS\$1DATASHARE\$1USAGE\$1CONSUMER 视图。
```
SELECT request_type, status, trim(error) AS error
FROM sys_datashare_usage_consumer
request_type | status | error_message
----------------+--------+---------------
"GET RELATION" | 0 |
```
# SYS\$1DATASHARE\$1USAGE\$1PRODUCER
记录数据共享的活动和使用情况。此视图仅与创建器集群有关。
SYS\$1DATASHARE\$1USAGE\$1PRODUCER 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_DATASHARE_USAGE_PRODUCER.html)
## 示例查询
以下示例显示了 SYS\$1DATASHARE\$1USAGE\$1PRODUCER 视图。
```
SELECT DISTINCT
FROM sys_datashare_usage_producer
WHERE object_name LIKE 'tickit%';
request_type
------------------
"GET RELATION"
```
# SYS\$1EXTERNAL\$1QUERY\$1DETAIL
使用 SYS\$1EXTERNAL\$1QUERY\$1DETAIL 查看段级别查询的详细信息。每行代表来自特定 WLM 查询的一段，其中包含 Amazon S3 中处理的行数、处理的字节数以及外部表的分区信息等详细信息。此视图除了具有与外部查询处理相关的更多详细信息之外，每一行还将在 SYS\$1QUERY\$1DETAIL 视图中有一个相应条目。
SYS\$1EXTERNAL\$1QUERY\$1DETAIL 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_EXTERNAL_QUERY_DETAIL.html)
## 示例查询
以下查询显示了外部查询详细信息。
```
SELECT query_id,
segment_id,
start_time,
end_time,
total_partitions,
qualified_partitions,
scanned_files,
returned_rows,
returned_bytes,
trim(external_query_text) query_text,
trim(file_location) file_location
FROM sys_external_query_detail
ORDER BY query_id, start_time DESC
LIMIT 2;
```
示例输出。
```
query_id | segment_id | start_time | end_time | total_partitions | qualified_partitions | scanned_files | returned_rows | returned_bytes | query_text | file_location
----------+------------+----------------------------+----------------------------+------------------+----------------------+---------------+---------------+----------------+------------+---------------
763251 | 0 | 2022-02-15 22:32:23.312448 | 2022-02-15 22:32:24.036023 | 3 | 3 | 3 | 38203 | 2683414 | |
763254 | 0 | 2022-02-15 22:32:40.17103 | 2022-02-15 22:32:40.839313 | 3 | 3 | 3 | 38203 | 2683414 | |
```
# SYS\$1EXTERNAL\$1QUERY\$1ERROR
您可以查询 SYS\$1EXTERNAL\$1QUERY\$1ERROR 系统视图，以获取有关 Redshift Spectrum 扫描错误的信息。SYS\$1EXTERNAL\$1QUERY\$1ERROR 显示所记录的错误的示例。每个查询默认显示 10 个条目。
SYS\$1EXTERNAL\$1QUERY\$1ERROR 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_EXTERNAL_QUERY_ERROR.html)
## 示例查询
以下查询将返回所执行数据处理操作的行列表。
```
SELECT * FROM sys_external_query_error;
```
该查询返回的结果类似于以下内容。
```
user_id query_id file_location rowid column_name original_value modified_value trigger action action_value error_code
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:0 league_name Barclays Premier League Barclays Premier Lea UNSPECIFIED TRUNCATE 156
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:0 league_nspi 34595 32767 UNSPECIFIED OVERFLOW_VALUE 199
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:1 league_nspi 34151 32767 UNSPECIFIED OVERFLOW_VALUE 199
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:2 league_name Barclays Premier League Barclays Premier Lea UNSPECIFIED TRUNCATE 156
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:2 league_nspi 33223 32767 UNSPECIFIED OVERFLOW_VALUE 199
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:3 league_name Barclays Premier League Barclays Premier Lea UNSPECIFIED TRUNCATE 156
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:3 league_nspi 32808 32767 UNSPECIFIED OVERFLOW_VALUE 199
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:4 league_nspi 32790 32767 UNSPECIFIED OVERFLOW_VALUE 199
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:5 league_name Spanish Primera Division Spanish Primera Divi UNSPECIFIED TRUNCATE 156
100 1574007 s3://spectrum-uddh/league/spi_global_rankings.0:6 league_name Spanish Primera Division Spanish Primera Divi UNSPECIFIED TRUNCATE 156
```
# SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION
使用 SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION 可查看 Amazon Redshift 使用额外的计算资源运行自动优化任务的使用期。有关自动优化的更多信息，请参阅[自动数据库优化](c_autonomics.md)。有关使用额外的计算资源运行的自动优化的更多信息，请参阅[分配额外的计算资源来执行自动数据库优化](t_extra-compute-autonomics.md)。
SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION 仅适用于预置集群。
SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION.html)
## 示例
以下是一个查询示例，用于查找 2025 年 9 月 16 日执行的自动优化。
```
SELECT *
FROM sys_extra_compute_for_automatic_optimization
WHERE start_time BETWEEN '2025-09-16 00:00:00' AND '2025-09-16 23:59:59';
start_time | end_time | query_count | compute_seconds
---------------------+---------------------+-------------+-----------------
2025-09-16 00:00:00 | 2025-09-16 00:00:59 | 1 | 59
2025-09-16 00:01:05 | 2025-09-16 00:01:58 | 2 | 53
```
# SYS\$1INTEGRATION\$1ACTIVITY
SYS\$1INTEGRATION\$1ACTIVITY 显示有关已完成集成运行的详细信息。
SYS\$1INTEGRATION\$1ACTIVITY 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
有关零 ETL 集成的信息，请参阅《Amazon Redshift 管理指南》中的[使用零 ETL 集成](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_INTEGRATION_ACTIVITY.html)
## 示例查询
以下 SQL 命令显示集成日志。
```
select * from sys_integration_activity;
integration_id | target_database | source | checkpoint_name | checkpoint_type | checkpoint_bytes | last_commit_timestamp | modified_tables | integration_start_time | integration_end_time
--------------------------------------+-----------------+--------+---------------------------------------------+------------------+------------------+-------------------------+-----------------+----------------------------+----------------------------
76b15917-afae-4447-b7fd-08e2a5acce7b | demo1 | MySQL | checkpoints/checkpoint_3_241_3_510.json | cdc | 762 | 2023-05-10 23:00:14.201 | 1 | 2023-05-10 23:00:45.054265 | 2023-05-10 23:00:46.339826
76b15917-afae-4447-b7fd-08e2a5acce7b | demo1 | MySQL | checkpoints/checkpoint_3_16329_3_17839.json | cdc | 13488 | 2023-05-11 01:33:57.411 | 2 | 2023-05-11 02:19:09.440121 | 2023-05-11 02:19:16.090492
76b15917-afae-4447-b7fd-08e2a5acce7b | demo1 | MySQL | checkpoints/checkpoint_3_5103_3_5532.json | cdc | 1657 | 2023-05-10 23:13:14.205 | 2 | 2023-05-10 23:13:23.545487 | 2023-05-10 23:13:25.652144
```
# SYS\$1INTEGRATION\$1TABLE\$1ACTIVITY
SYS\$1INTEGRATION\$1TABLE\$1ACTIVITY 显示零 ETL 集成的插入、删除和更新活动的详细信息。对于每次完成的摄取都会添加一行。
超级用户可以查看此表中的所有行。
有关更多信息，请参阅[零 ETL 集成](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_INTEGRATION_TABLE_ACTIVITY.html)
## 示例查询
以下 SQL 命令显示集成的活动。
```
select * from sys_integration_table_activity;
integration_id | checkpoint_name | target_database | schema_name | table_name | table_id | record_time | transaction_id | inserted_rows | deleted_rows | updated_rows | bytes_ingested
--------------------------------------+-----------------+-----------------+-------------+-------------------+--------------+----------------------------+-----------------+----------------+--------------+--------------+---------------
4798e675-8f9f-4686-b05f-92c538e19629 | | sample_test2 | sample | SampleTestChannel | 111276 | 2023-05-12 12:40:30.656625 | 7736 | 2 | 0 | 0 | 125
```
# SYS\$1INTEGRATION\$1TABLE\$1STATE\$1CHANGE
SYS\$1INTEGRATION\$1TABLE\$1STATE\$1CHANGE 显示有关集成的表状态更改日志的详细信息。
超级用户可以查看此表中的所有行。
有关更多信息，请参阅[使用零 ETL 集成](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_INTEGRATION_TABLE_STATE_CHANGE.html)
## 示例查询
以下 SQL 命令显示集成日志。
```
select * from sys_integration_table_state_change;
integration_id | database_name | schema_name | table_name | new_state | table_last_replicated_checkpoint | state_change_reason | record_time
--------------------------------------+---------------+-------------+------------+-----------+-------------------------------------+---------------------+----------------------------
99108e72-1cfd-414f-8cc0-0216acefac77 | perfdb | sbtest80t3s | sbtest79 | Synced | {"txn_seq":9834,"txn_id":126597515} | | 2023-09-20 19:39:50.087868
99108e72-1cfd-414f-8cc0-0216acefac77 | perfdb | sbtest80t3s | sbtest56 | Synced | {"txn_seq":9834,"txn_id":126597515} | | 2023-09-20 19:39:45.54005
99108e72-1cfd-414f-8cc0-0216acefac77 | perfdb | sbtest80t3s | sbtest50 | Synced | {"txn_seq":9834,"txn_id":126597515} | | 2023-09-20 19:40:20.362504
99108e72-1cfd-414f-8cc0-0216acefac77 | perfdb | sbtest80t3s | sbtest18 | Synced | {"txn_seq":9834,"txn_id":126597515} | | 2023-09-20 19:40:32.544084
99108e72-1cfd-414f-8cc0-0216acefac77 | perfdb | sbtest40t3s | sbtest23 | Synced | {"txn_seq":9834,"txn_id":126597515} | | 2023-09-20 15:49:05.186209
```
# SYS\$1LOAD\$1DETAIL
返回用于跟踪或排查数据加载的信息。
此视图记录了在每个数据文件加载到数据库表中时的进度。
此视图对所有用户可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_LOAD_DETAIL.html)
## 示例查询
以下示例返回上次 COPY 操作的详细信息。
```
select query_id, trim(file_name) as file, record_time
from sys_load_detail
where query_id = pg_last_copy_id();
query_id | file | record_time
----------+----------------------------------+----------------------------
28554 | s3://dw-tickit/category_pipe.txt | 2013-11-01 17:14:52.648486
(1 row)
```
以下查询包含 TICKIT 数据库中初次加载表时的条目：
```
select query_id, trim(file_name), record_time
from sys_load_detail
where file_name like '%tickit%' order by query_id;
query_id | btrim | record_time
----------+--------------------------+----------------------------
22475 | tickit/allusers_pipe.txt | 2013-02-08 20:58:23.274186
22478 | tickit/venue_pipe.txt | 2013-02-08 20:58:25.070604
22480 | tickit/category_pipe.txt | 2013-02-08 20:58:27.333472
22482 | tickit/date2008_pipe.txt | 2013-02-08 20:58:28.608305
22485 | tickit/allevents_pipe.txt| 2013-02-08 20:58:29.99489
22487 | tickit/listings_pipe.txt | 2013-02-08 20:58:37.632939
22593 | tickit/allusers_pipe.txt | 2013-02-08 21:04:08.400491
22596 | tickit/venue_pipe.txt | 2013-02-08 21:04:10.056055
22598 | tickit/category_pipe.txt | 2013-02-08 21:04:11.465049
22600 | tickit/date2008_pipe.txt | 2013-02-08 21:04:12.461502
22603 | tickit/allevents_pipe.txt| 2013-02-08 21:04:14.785124
22605 | tickit/listings_pipe.txt | 2013-02-08 21:04:20.170594
(12 rows)
```
向此系统视图的日志文件写入一个记录的事实并不表示加载操作已作为其所属的事务的一部分成功提交。要验证加载提交，请查询 STL\$1UTILITYTEXT 视图并查找与 COPY 事务对应的 COMMIT 记录。例如，此查询基于针对 STL\$1UTILITYTEXT 的子查询联接 SYS\$1LOAD\$1DETAIL 和 STL\$1QUERY：
```
select l.query_id,rtrim(l.file_name),q.transaction_id
from sys_load_detail l, sys_query_text q
where l.query_id=q.query_id
and exists
(select xid from stl_utilitytext where xid=q.transaction_id and rtrim("text")='COMMIT');
query_id | rtrim | transaction_id
----------+---------------------------+-----------------
22600 | tickit/date2008_pipe.txt | 68311
22480 | tickit/category_pipe.txt | 68066
7508 | allusers_pipe.txt | 23365
7552 | category_pipe.txt | 23415
7576 | allevents_pipe.txt | 23429
7516 | venue_pipe.txt | 23390
7604 | listings_pipe.txt | 23445
22596 | tickit/venue_pipe.txt | 68309
22605 | tickit/listings_pipe.txt | 68316
22593 | tickit/allusers_pipe.txt | 68305
22485 | tickit/allevents_pipe.txt | 68071
7561 | allevents_pipe.txt | 23429
7541 | category_pipe.txt | 23415
7558 | date2008_pipe.txt | 23428
22478 | tickit/venue_pipe.txt | 68065
526 | date2008_pipe.txt | 2572
7466 | allusers_pipe.txt | 23365
22482 | tickit/date2008_pipe.txt | 68067
22598 | tickit/category_pipe.txt | 68310
22603 | tickit/allevents_pipe.txt | 68315
22475 | tickit/allusers_pipe.txt | 68061
547 | date2008_pipe.txt | 2572
22487 | tickit/listings_pipe.txt | 68072
7531 | venue_pipe.txt | 23390
7583 | listings_pipe.txt | 23445
(25 rows)
```
# SYS\$1LUDF\$1DETAIL
SYS\$1LUDF\$1DETAIL 记录在特定查询中使用的 Lambda 用户定义函数（LUDF）的信息和指标。
SYS\$1LUDF\$1DETAIL 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_LUDF_DETAIL.html)
## 示例查询
以下示例在查询中使用 Lambda UDF，然后演示如何查询 SYS\$1LUDF\$1DETAIL 视图以查看函数执行详细信息。
```
SET SESSION AUTHORIZATION regular_user;
CREATE EXTERNAL FUNCTION exfunc_sum(INT,INT) RETURNS INT STABLE
LAMBDA 'lambda_sum'
IAM_ROLE 'arn:aws:iam::123456789012:role/Redshift-Exfunc-Test';
CREATE TABLE t_sum(c1 int, c2 int);
INSERT INTO t_sum VALUES (4,5), (6,7);
SELECT exfunc_sum(c1,c2) FROM t_sum;
-- Switch to super user in order to inspect records in the LUDF SYS view.
SET SESSION AUTHORIZATION super_user;
select * from sys_ludf_detail;
```
示例输出：
```
user_id | transaction_id | query_id | function_oid | function_position | stream_id | segment_id | step_id | lambda_function_name | start_time | end_time | total_duration | invocations | total_rows | input_bytes | output_bytes
---------+----------------+----------+--------------+-------------------+-----------+------------+---------+----------------------+----------------------------+----------------------------+----------------+-------------+------------+-------------+--------------
100 | 1463 | 1544 | 111055 | 0 | 0 | 0 | 2 | lambda_sum | 2026-01-06 17:23:25.165898 | 2026-01-06 17:23:25.165898 | 414 | 1 | 2 | 277 | 18
(1 row)
```
# SYS\$1LOAD\$1ERROR\$1DETAIL
使用 SYS\$1LOAD\$1ERROR\$1DETAIL 查看 COPY 命令错误的详细信息。每行代表一个 COPY 命令。它包含正在运行和已完成的 COPY 命令。
SYS\$1LOAD\$1ERROR\$1DETAIL 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_LOAD_ERROR_DETAIL.html)
## 示例查询
以下查询显示了特定查询的复制命令的加载错误详情。
```
SELECT query_id,
table_id,
start_time,
trim(file_name) AS file_name,
trim(column_name) AS column_name,
trim(column_type) AS column_type,
trim(error_message) AS error_message
FROM sys_load_error_detail
WHERE query_id = 762949
ORDER BY start_time
LIMIT 10;
```
示例输出。
```
query_id | table_id | start_time | file_name | column_name | column_type | error_message
----------+----------+----------------------------+------------------------------------------+-------------+-------------+------------------------------------------------
762949 | 137885 | 2022-02-15 22:14:46.759151 | s3://load-test/copyfail/wrong_format_000 | id | int4 | Invalid digit, Value 'a', Pos 0, Type: Integer
762949 | 137885 | 2022-02-15 22:14:46.759151 | s3://load-test/copyfail/wrong_format_001 | id | int4 | Invalid digit, Value 'a', Pos 0, Type: Integer
```
# SYS\$1LOAD\$1HISTORY
使用 SYS\$1LOAD\$1HISTORY 查看 COPY 命令的详细信息。每行代表一个 COPY 命令，其中包含某些字段的累积统计数据。它包含正在运行和已完成的 COPY 命令。
SYS\$1LOAD\$1HISTORY 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_LOAD_HISTORY.html)
## 示例查询
以下查询显示了特定复制命令的加载行、字节、表和数据源。
```
SELECT query_id,
table_name,
data_source,
loaded_rows,
loaded_bytes
FROM sys_load_history
WHERE query_id IN (6389,490791,441663,74374,72297)
ORDER BY query_id,
data_source DESC;
```
示例输出。
```
query_id | table_name | data_source | loaded_rows | loaded_bytes
----------+------------------+-----------------------------------------------------------------------+-------------+---------------
6389 | store_returns | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/store_returns/ | 287999764 | 1196240296158
72297 | web_site | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/web_site/ | 54 | 43808
74374 | ship_mode | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/ship_mode/ | 20 | 1320
441663 | income_band | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/income_band/ | 20 | 2152
490791 | customer_address | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/customer_address/ | 6000000 | 722924305
```
以下查询显示了复制命令的加载行、字节、表和数据源。
```
SELECT query_id,
table_name,
data_source,
loaded_rows,
loaded_bytes
FROM sys_load_history
ORDER BY query_id DESC
LIMIT 10;
```
示例输出。
```
query_id | table_name | data_source | loaded_rows | loaded_bytes
----------+------------------------+-----------------------------------------------------------------------------+-------------+-----------------
491058 | web_site | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/web_site/ | 54 | 43808
490947 | web_sales | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/web_sales/ | 720000376 | 22971988122819
490923 | web_returns | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/web_returns/ | 71997522 | 96597496325
490918 | web_page | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/web_page/ | 3000 | 1320
490907 | warehouse | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/warehouse/ | 20 | 1320
490902 | time_dim | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/time_dim/ | 86400 | 1320
490876 | store_sales | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/store_sales/ | 2879987999 | 151666241887933
490870 | store_returns | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/store_returns/ | 287999764 | 1196405607941
490865 | store | s3://load-test/data-sources/tpcds/2.8.0/textfile/1T/store/ | 1002 | 365507
```
以下查询显示了复制命令的每日加载行和字节。
```
SELECT date_trunc('day',start_time) AS exec_day,
SUM(loaded_rows) AS loaded_rows,
SUM(loaded_bytes) AS loaded_bytes
FROM sys_load_history
GROUP BY exec_day
ORDER BY exec_day DESC;
```
示例输出。
```
exec_day | loaded_rows | loaded_bytes
---------------------+-------------+------------------
2022-01-20 00:00:00 | 6347386005 | 258329473070606
2022-01-19 00:00:00 | 19042158015 | 775198502204572
2022-01-18 00:00:00 | 38084316030 | 1550294469446883
2022-01-17 00:00:00 | 25389544020 | 1033271084791724
2022-01-16 00:00:00 | 19042158015 | 775222736252792
2022-01-15 00:00:00 | 19834245387 | 798122849155598
2022-01-14 00:00:00 | 75376544688 | 3077040926571384
```
# SYS\$1MV\$1REFRESH\$1HISTORY
结果包括有关所有实体化视图的刷新历史记录的信息。结果包括刷新类型（例如手动或自动）以及最近刷新的状态。
SYS\$1MV\$1REFRESH\$1HISTORY 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_MV_REFRESH_HISTORY.html)
## 示例查询
以下查询显示了实体化视图的刷新历史记录。
```
SELECT user_id,
session_id,
transaction_id,
database_name,
schema_name,
mv_id,
mv_name,
refresh_type,
status,
start_time,
end_time,
duration,
consumer_account,
consumer_region,
consumer_namespace
from sys_mv_refresh_history;
```
查询返回以下示例输出：
```
user_id | session_id | transaction_id | database_name | schema_name | mv_id | mv_name | refresh_type | status | start_time | end_time | duration | consumer_account | consumer_region | consumer_namespace
---------+------------+----------------+---------------+----------------------------+--------+--------------------+----------------+------------------------------------------------------------------------------------------------------+----------------------------+----------------------------+-----------+------------------+-----------------+------------------------------------
1 | 1073815659 | 15066 | dev | test_stl_mv_refresh_schema | 203762 | mv_incremental | Manual | MV was already updated | 2023-10-26 15:59:20.952179 | 2023-10-26 15:59:20.952866 | 687 | | |
1 | 1073815659 | 15068 | dev | test_stl_mv_refresh_schema | 203771 | mv_nonincremental | Manual | MV was already updated | 2023-10-26 15:59:21.008049 | 2023-10-26 15:59:21.008658 | 609 | | |
1 | 1073815659 | 15070 | ext_db | producer_schema | 203779 | producer_mv | Manual | Refresh successfully updated MV incrementally | 2023-10-26 15:59:21.064252 | 2023-10-26 15:59:21.064885 | 633 | 0123456789 | us-east-1 | 623d8ff2-4391-4381-83d7-177caa6767af
1 | 1073815659 | 15074 | dev | test_stl_mv_refresh_schema | 203762 | mv_incremental | Manual | Refresh successfully updated MV incrementally | 2023-10-26 15:59:29.693329 | 2023-10-26 15:59:43.482842 | 13789513 | | |
1 | 1073815659 | 15076 | dev | test_stl_mv_refresh_schema | 203771 | mv_nonincremental | Manual | Refresh successfully recomputed MV from scratch | 2023-10-26 15:59:43.550184 | 2023-10-26 15:59:47.880833 | 4330649 | | |
1 | 1073815659 | 15078 | dev | test_stl_mv_refresh_schema | 203779 | mv_refresh_error | Manual | Refresh failed due to an internal error | 2023-10-26 15:59:47.949052 | 2023-10-26 15:59:52.494681 | 4545629 | | |
1 | 1073815659 | 15071 | dev | test_stl_mv_refresh_schema | 203778 | mv_test | Manual | Cascade refresh failed because materialized view test_stl_mv_refresh_schema.child was not refreshed. | 2023-10-26 15:30:21.432252 | 2023-10-26 15:30:21.432252 | 532 | | |
1 | 1073815659 | 15071 | dev | test_stl_mv_refresh_schema | 203761 | child | Manual | Refresh failed due to an internal error. | 2023-10-26 15:30:21.432252 | 2023-10-26 15:30:21.432252 | 532 | | |
1 | 1073815659 | 15069 | dev | test_stl_mv_refresh_schema | 203778 | mv_test | Manual | Cascade refresh skipped because materialized view test_stl_mv_refresh_schema.child was not refreshed.| 2023-10-26 15:21:43.550369 | 2023-10-26 15:21:43.550369 | 633
1 | 1073815659 | 15069 | dev | test_stl_mv_refresh_schema | 203761 | child | Manual | Refresh failed due to an internal error. | 2023-10-26 15:21:43.550369 | 2023-10-26 15:21:43.550369 | 633
(10 rows)
```
# SYS\$1MV\$1STATE
结果包括有关所有实体化视图的状态的信息。这包括基表信息、架构属性和有关最近事件（例如删除列）的信息。
SYS\$1MV\$1STATE 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_MV_STATE.html)
## 示例查询
以下查询显示了实体化视图状态。
```
select * from sys_mv_state;
```
查询返回以下示例输出：
```
user_id | transaction_id | database_name | event_desc | start_time | base_table_database_name | base_table_schema | base_table_name | mv_schema | mv_name | state
---------+----------------+---------------+-----------------------------+----------------------------+--------------------------+-------------------+---------------------+-------------+----------------------------+--------------
106 | 12720 | tickit_db | TRUNCATE | 2023-07-26 14:59:12.788268 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_a1f3f862 | Recompute
106 | 12724 | tickit_db | ALTER TABLE ALTER DISTSTYLE | 2023-07-26 14:59:51.409014 | tickit_db | mv_schema | test_table_58102435 | mv_schema | materialized_view_ca746631 | Recompute
106 | 12720 | tickit_db | Column was renamed | 2023-07-26 14:59:12.822928 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5750a8d4 | Unrefreshable
106 | 12727 | tickit_db | Table was renamed | 2023-07-26 15:00:08.051244 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5750a8d4 | Unrefreshable
106 | 12720 | tickit_db | Column was renamed | 2023-07-26 14:59:12.857755 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5750a8d4 | Unrefreshable
106 | 12727 | tickit_db | Table was renamed | 2023-07-26 15:00:08.051358 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5ef0d754 | Unrefreshable
106 | 12720 | tickit_db | TRUNCATE | 2023-07-26 14:59:12.788159 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5750a8d4 | Recompute
106 | 12720 | tickit_db | Column was renamed | 2023-07-26 14:59:12.857799 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_a1f3f862 | Unrefreshable
106 | 12720 | tickit_db | TRUNCATE | 2023-07-26 14:59:12.788327 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_5ef0d754 | Recompute
106 | 12727 | tickit_db | ALTER TABLE ALTER SORTKEY | 2023-07-26 15:00:08.006235 | tickit_db | mv_schema | test_table_58102435 | mv_schema | materialized_view_ca746631 | Recompute
106 | 12720 | tickit_db | Column was renamed | 2023-07-26 14:59:12.82297 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_a1f3f862 | Unrefreshable
106 | 12727 | tickit_db | Table was renamed | 2023-07-26 15:00:08.051321 | tickit_db | mv_schema | test_table_95d6d861 | mv_schema | materialized_view_a1f3f862 | Unrefreshable
```
# SYS\$1PROCEDURE\$1CALL
使用 SYS\$1PROCEDURE\$1CALL 视图以获取有关存储过程调用的信息，包括开始时间、结束时间、存储过程调用的状态以及嵌套存储过程调用的调用层次结构。每个存储过程调用接受一个查询 ID。
SYS\$1PROCEDURE\$1CALL 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_PROCEDURE_CALL.html)
## 示例查询
以下查询返回嵌套存储过程调用的层次结构。
```
select query_id, datediff(seconds, start_time, end_time) as elapsed_time, status, trim(query_text) as call, caller_procedure_query_id from sys_procedure_call;
```
示例输出。
```
query_id | elapsed_time | status | call | caller_procedure_query_id
----------+--------------+---------+--------------------------------------------------+---------------------------
3087 | 18 | success | CALL proc_bd906c98c45443ffa165e9552056902d(1) | 3085
3085 | 18 | success | CALL proc_bd906c98c45443ffa165e9552056902d_2(1); |
(2 rows)
```
# SYS\$1PROCEDURE\$1MESSAGES
SYS\$1PROCEDURE\$1MESSAGES 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_PROCEDURE_MESSAGES.html)
## 示例查询
以下查询显示了 SYS\$1PROCEDURE\$1MESSAGES 的示例输出。
```
select transaction_id, query_id, record_time, log_level, trim(message), line_number from sys_procedure_messages;
```
```
transaction_id | query_id | record_time | log_level | btrim | line_number
---------------+----------+----------------------------+-----------+---------------------------+-------------
25267 | 80562 | 2023-07-17 14:38:31.910136 | NOTICE | test_notice_msg_b9f1e749 | 8
25267 | 80562 | 2023-07-17 14:38:31.910002 | LOG | test_log_msg_833c7420 | 6
25267 | 80562 | 2023-07-17 14:38:31.910111 | INFO | test_info_msg_651373d9 | 7
25267 | 80562 | 2023-07-17 14:38:31.910154 | WARNING | test_warning_msg_831c5747 | 9
(4 rows)
```
# SYS\$1QUERY\$1DETAIL
使用 SYS\$1QUERY\$1DETAIL 查看不同指标级别的查询的详细信息，每行表示有关给定指标级别的特定 WLM 查询的详细信息。此视图包含许多类型的查询，例如 DDL、DML 和实用程序命令（例如：复制和卸载）。根据查询类型，某些列可能不相关。例如，external\$1scanned\$1bytes 与内部表无关。
SYS\$1QUERY\$1DETAIL 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](cm_chap_system-tables.md#c_visibility-of-data)。
**注意**
要验证包含已执行查询的事务是否成功提交，您需要在系统表和 `sys_transaction_history` 表之间执行联接操作。例如：
```
SELECT
th.transaction_id,
qd.query_id,
th.status AS transaction_status
FROM
sys_query_detail qd
LEFT JOIN sys_query_history qh ON qd.query_id = qh.query_id
LEFT JOIN sys_transaction_history th on qh.transaction_id = th.transaction_id;
```
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_QUERY_DETAIL.html)
## 使用说明
SYS\$1QUERY\$1DETAIL 可以包含步骤、流、段和子查询级别的指标。除了引用 metrics\$1level 列外，还可以根据下表，通过引用 step\$1id、segment\$1id 和 stream\$1id 字段来查看给定行显示的指标级别。
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_QUERY_DETAIL.html)
## 示例查询
以下示例返回了 SYS\$1QUERY\$1DETAIL 的输出。
以下查询显示了步骤级别的查询元数据详细信息，包括步骤名称、input\$1bytes、output\$1bytes、input\$1rows、output\$1rows。
```
SELECT query_id,
child_query_sequence,
stream_id,
segment_id,
step_id,
trim(step_name) AS step_name,
duration,
input_bytes,
output_bytes,
input_rows,
output_rows
FROM sys_query_detail
WHERE query_id IN (193929)
ORDER BY query_id,
stream_id,
segment_id,
step_id DESC;
```
示例输出。
```
query_id | child_query_sequence | stream_id | segment_id | step_id | step_name | duration | input_bytes | output_bytes | input_rows | output_rows
----------+----------------------+-----------+------------+---------+------------+-----------------+-------------+--------------+------------+-------------
193929 | 2 | 0 | 0 | 3 | hash | 37144 | 0 | 9350272 | 0 | 292196
193929 | 5 | 0 | 0 | 3 | hash | 9492 | 0 | 23360 | 0 | 1460
193929 | 1 | 0 | 0 | 3 | hash | 46809 | 0 | 9350272 | 0 | 292196
193929 | 4 | 0 | 0 | 2 | return | 7685 | 0 | 896 | 0 | 112
193929 | 1 | 0 | 0 | 2 | project | 46809 | 0 | 0 | 0 | 292196
193929 | 2 | 0 | 0 | 2 | project | 37144 | 0 | 0 | 0 | 292196
193929 | 5 | 0 | 0 | 2 | project | 9492 | 0 | 0 | 0 | 1460
193929 | 3 | 0 | 0 | 2 | return | 11033 | 0 | 14336 | 0 | 112
193929 | 2 | 0 | 0 | 1 | project | 37144 | 0 | 0 | 0 | 292196
193929 | 1 | 0 | 0 | 1 | project | 46809 | 0 | 0 | 0 | 292196
193929 | 5 | 0 | 0 | 1 | project | 9492 | 0 | 0 | 0 | 1460
193929 | 3 | 0 | 0 | 1 | aggregate | 11033 | 0 | 201488 | 0 | 14
193929 | 4 | 0 | 0 | 1 | aggregate | 7685 | 0 | 28784 | 0 | 14
193929 | 5 | 0 | 0 | 0 | scan | 9492 | 0 | 23360 | 292196 | 1460
193929 | 4 | 0 | 0 | 0 | scan | 7685 | 0 | 1344 | 112 | 112
193929 | 2 | 0 | 0 | 0 | scan | 37144 | 0 | 7304900 | 292196 | 292196
193929 | 3 | 0 | 0 | 0 | scan | 11033 | 0 | 13440 | 112 | 112
193929 | 1 | 0 | 0 | 0 | scan | 46809 | 0 | 7304900 | 292196 | 292196
193929 | 5 | 0 | 0 | -1 | | 9492 | 12288 | 0 | 0 | 0
193929 | 1 | 0 | 0 | -1 | | 46809 | 16384 | 0 | 0 | 0
193929 | 2 | 0 | 0 | -1 | | 37144 | 16384 | 0 | 0 | 0
193929 | 4 | 0 | 0 | -1 | | 7685 | 28672 | 0 | 0 | 0
193929 | 3 | 0 | 0 | -1 | | 11033 | 114688 | 0 | 0 | 0
```
要按从最常用到最不常用的顺序查看数据库中的表，请使用以下示例。将 *sample\$1data\$1dev* 替换为您自己的数据库。请注意，此查询将计算从创建集群时开始的查询数量，但当您的数据仓库空间不足时，不会保存系统视图数据。
```
SELECT table_name, COUNT (DISTINCT query_id)
FROM SYS_QUERY_DETAIL
WHERE table_name LIKE 'sample_data_dev%'
GROUP BY table_name
ORDER BY COUNT(*) DESC;
+---------------------------------+-------+
| table_name | count |
+---------------------------------+-------+
| sample_data_dev.tickit.venue | 4 |
| sample_data_dev.myunload1.venue | 3 |
| sample_data_dev.tickit.listing | 1 |
| sample_data_dev.tickit.category | 1 |
| sample_data_dev.tickit.users | 1 |
| sample_data_dev.tickit.date | 1 |
| sample_data_dev.tickit.sales | 1 |
| sample_data_dev.tickit.event | 1 |
+---------------------------------+-------+
```
以下示例显示了单个 WLM 查询的不同指标级别。
```
SELECT query_id, child_query_sequence, stream_id, segment_id, step_id, step_name, start_time, end_time, metrics_level
FROM sys_query_detail
WHERE query_id = 1553 AND step_id = -1
ORDER BY stream_id, segment_id, step_id;
query_id | child_query_sequence | stream_id | segment_id | step_id | step_name | start_time | end_time | metrics_level
----------+----------------------+-----------+------------+---------+-----------+----------------------------+----------------------------+---------------
1553 | 1 | -1 | -1 | -1 | | 2024-10-17 02:28:49.814721 | 2024-10-17 02:28:49.847838 | child query
1553 | 1 | 0 | -1 | -1 | | 2024-10-17 02:28:49.814721 | 2024-10-17 02:28:49.835609 | stream
1553 | 1 | 0 | 0 | -1 | | 2024-10-17 02:28:49.824677 | 2024-10-17 02:28:49.830372 | segment
1553 | 1 | 1 | -1 | -1 | | 2024-10-17 02:28:49.835624 | 2024-10-17 02:28:49.845773 | stream
1553 | 1 | 1 | 1 | -1 | | 2024-10-17 02:28:49.84088 | 2024-10-17 02:28:49.842388 | segment
1553 | 1 | 1 | 2 | -1 | | 2024-10-17 02:28:49.835926 | 2024-10-17 02:28:49.844396 | segment
1553 | 1 | 2 | -1 | -1 | | 2024-10-17 02:28:49.846949 | 2024-10-17 02:28:49.847838 | stream
1553 | 1 | 2 | 3 | -1 | | 2024-10-17 02:28:49.847013 | 2024-10-17 02:28:49.847485 | segment
(8 rows)
```
# SYS\$1QUERY\$1EXPLAIN
显示已提交供执行的查询的 EXPLAIN 计划。
SYS\$1QUERY\$1EXPLAIN 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_QUERY_EXPLAIN.html)
## 示例查询
以下示例是单个查询的 EXPLAIN 计划。
```
SELECT * FROM sys_query_explain WHERE query_id = 612635 ORDER BY plan_node_id;
userid | query_id | child_query_sequence | plan_node_id | plan_parent_id | plan_node | plan_info
--------+----------+----------------------+--------------+----------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
100 | 612635 | 1 | 1 | 0 | XN Limit (cost=3604047533041.00..3604047533041.25 rows=100 width=20) |
100 | 612635 | 1 | 2 | 1 | -> XN Merge (cost=3604047533041.00..3604047533148.02 rows=42809 width=20) | Merge Key: sum(b.totalprice)
100 | 612635 | 1 | 3 | 2 | -> XN Network (cost=3604047533041.00..3604047533148.02 rows=42809 width=20) | Send to leader
100 | 612635 | 1 | 4 | 3 | -> XN Sort (cost=3604047533041.00..3604047533148.02 rows=42809 width=20) | Sort Key: sum(b.totalprice)
100 | 612635 | 1 | 5 | 4 | -> XN HashAggregate (cost=2604047529640.76..2604047529747.78 rows=42809 width=20) |
100 | 612635 | 1 | 6 | 5 | -> XN Hash Join DS_DIST_NONE (cost=15104956.16..2602364653507.34 rows=336575226684 width=20) | Hash Cond: (("outer".listid = "inner".listid) AND ("outer".sellerid = "inner".sellerid))
100 | 612635 | 1 | 7 | 6 | -> XN Seq Scan on listing b (cost=0.00..7884677.12 rows=788467712 width=24) |
100 | 612635 | 1 | 8 | 6 | -> XN Hash (cost=7063797.76..7063797.76 rows=706379776 width=8) |
100 | 612635 | 1 | 9 | 8 | -> XN Seq Scan on sales a (cost=0.00..7063797.76 rows=706379776 width=8) |
(9 rows)
```
# SYS\$1QUERY\$1HISTORY
使用 SYS\$1QUERY\$1HISTORY 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\$1QUERY\$1HISTORY 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](cm_chap_system-tables.md#c_visibility-of-data)。
**注意**
要验证包含已执行查询的事务是否成功提交，您需要在系统表和 `sys_transaction_history` 表之间执行联接操作。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;
```
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_QUERY_HISTORY.html)
## 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
```
下面的示例显示了多个查询之间的查询哈希结果差异。观察以下查询：
```
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;
```
以下是输出示例：
```
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，因为 test\$1table 只有一列。`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，因为这两个查询在查询字面值 1 和 2 之外是相同的。
# SYS\$1QUERY\$1TEXT
使用 SYS\$1QUERY\$1TEXT 查看所有查询的查询文本。每行代表最多 4000 个字符的查询的查询文本（从序列号 0 开始）。当查询语句包含超过 4000 个字符时，通过增加每行的序列号来为该语句记录额外的行。此视图记录所有用户查询文本，例如 DDL、实用程序、Amazon Redshift 查询和仅限领导节点的查询。
SYS\$1QUERY\$1TEXT 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_QUERY_TEXT.html)
## 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, start_time,
sequence, trim(text) as text from sys_query_text
ORDER BY sequence;
```
示例输出。
```
user_id | query_id | transaction_id | session_id | start_time | sequence | text
--------+----------+-----------------+------------+----------------------------+----------+----------------------------------------------------------------------------------------------------------------------
100 | 4 | 1396 | 1073750220 | 2023-04-28 16:44:55.887184 | 0 | SELECT trim(text) as text, sequence FROM sys_query_text WHERE query_id = pg_last_query_id() AND user_id > 1 AND start
_time > '2023-04-28 16:44:55.922705+00:00'::timestamp order by sequence;
```
以下查询返回已在数据库的组中授予或撤消的权限。
```
SELECT
SPLIT_PART(text, ' ', 1) as grantrevoke,
SPLIT_PART((SUBSTRING(text, STRPOS(UPPER(text), 'GROUP'))), ' ', 2) as group,
SPLIT_PART((SUBSTRING(text, STRPOS(UPPER(text), ' '))), 'ON', 1) as type,
SPLIT_PART((SUBSTRING(text, STRPOS(UPPER(text), 'ON'))), ' ', 2) || ' ' || SPLIT_PART((SUBSTRING(text, STRPOS(UPPER(text), 'ON'))), ' ', 3) as entity
FROM SYS_QUERY_TEXT
WHERE (text LIKE 'GRANT%' OR text LIKE 'REVOKE%') AND text LIKE '%GROUP%';
+-------------+----------+--------+----------+
| grantrevoke | group | type | entity |
+-------------+----------+--------+----------+
| GRANT | bi_group | SELECT | TABLE t1 |
| GRANT | bi_group | SELECT | TABLE t1 |
| GRANT | bi_group | SELECT | TABLE t1 |
| GRANT | bi_group | USAGE | TABLE t1 |
| GRANT | bi_group | SELECT | TABLE t1 |
| GRANT | bi_group | SELECT | TABLE t1 |
+-------------+----------+--------+----------+
```
# SYS\$1REDSHIFT\$1TEMPLATE
使用 SYS\$1REDSHIFT\$1TEMPLATE 查看 Redshift TEMPLATES 的详细信息。
此视图包含已创建的 TEMPLATES。
SYS\$1REDSHIFT\$1TEMPLATE 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_REDSHIFT_TEMPLATE.html)
## 示例查询
以下查询返回当前用户可见的所有模板：
```
SELECT * FROM SYS_REDSHIFT_TEMPLATE;
```
示例输出。
```
database_name | schema_name | template_name | template_type | create_time | last_modified_time | owner_id | last_modified_by | template_parameters
---------------+-------------+--------------------+---------------+----------------------------+----------------------------+----------+------------------+---------------------
dev | s1 | shapefile_template | 1 | 2025-12-17 22:42:02.079758 | 2025-12-17 22:42:02.079758 | 101 | 101 | {
"SIMPLIFY_AUTO": 0.000001,
"SHAPEFILE": 1,
"COMPRESSION_UPDATE": 0
}
dev | s2 | orc_template | 1 | 2025-12-17 22:42:23.582815 | 2025-12-17 22:42:23.582815 | 101 | 101 | {
"ORC": "serializetojson_default"
}
dev | s1 | csv_template | 1 | 2025-12-17 22:43:01.822361 | 2025-12-17 22:43:01.822361 | 101 | 101 | {
"ENCRYPTED": 1,
"CSV": 1,
"ENCODING": 1,
"DELIMITER": ","
}
(3 rows)
```
# SYS\$1RESTORE\$1LOG
在经典大小调整期间，使用 SYS\$1RESTORE\$1LOG 监控集群中每个表迁入 RA3 节点的进度。它捕获调整大小操作期间数据迁移的历史吞吐量。有关经典调整 RA3 节点大小的更多信息，请参阅[经典调整大小](https://docs.aws.amazon.com/redshift/latest/mgmt/managing-cluster-operations.html#classic-resize-faster)。
SYS\$1RESTORE\$1LOG 仅对超级用户可见。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_RESTORE_LOG.html)
## 示例查询
以下查询使用 SYS\$1RESTORE\$1LOG 计算数据处理的吞吐量。
```
SELECT
ROUND(sum(delta_data_processed) / 1024.0, 2) as data_processed_gb,
ROUND(datediff(sec, min(event_time), max(event_time)) / 3600.0, 2) as duration_hr,
ROUND(data_processed_gb/duration_hr, 2) as throughput_gb_per_hr
from sys_restore_log;
```
示例输出。
```
data_processed_gb | duration_hr | throughput_gb_per_hr
-------------------+-------------+----------------------
0.91 | 8.37 | 0.11
(1 row)
```
以下查询显示所有再分配类型。
```
SELECT * from sys_restore_log ORDER BY event_time;
```
```
database_name | schema_name | table_name | table_id | action | total_data_processed | delta_data_processed | event_time | table_size | message | redistribution_type
---------------+----------------------+----------------------+----------+-----------------------------+----------------------+----------------------+----------------------------+------------+---------+--------------------------
dev | schemaaaa877096d844d | customer_key | 106424 | Redistribution started | 0 | | 2024-01-05 02:18:00.744977 | 325 | | Restore Distkey Table
dev | schemaaaa877096d844d | dp30907_t2_autokey | 106430 | Redistribution started | 0 | | 2024-01-05 02:18:02.756675 | 90 | | Restore Distkey Table
dev | schemaaaa877096d844d | dp30907_t2_autokey | 106430 | Redistribution completed | 90 | 90 | 2024-01-05 02:23:30.643718 | 90 | | Restore Distkey Table
dev | schemaaaa877096d844d | customer_key | 106424 | Redistribution completed | 325 | 325 | 2024-01-05 02:23:45.998249 | 325 | | Restore Distkey Table
dev | schemaaaa877096d844d | dp30907_t1_even | 106428 | Redistribution started | 0 | | 2024-01-05 02:23:46.083849 | 30 | | Rebalance Disteven Table
dev | schemaaaa877096d844d | dp30907_t5_auto_even | 106436 | Redistribution started | 0 | | 2024-01-05 02:23:46.855728 | 45 | | Rebalance Disteven Table
dev | schemaaaa877096d844d | dp30907_t5_auto_even | 106436 | Redistribution completed | 45 | 45 | 2024-01-05 02:24:16.343029 | 45 | | Rebalance Disteven Table
dev | schemaaaa877096d844d | dp30907_t1_even | 106428 | Redistribution completed | 30 | 30 | 2024-01-05 02:24:20.584703 | 30 | | Rebalance Disteven Table
dev | schemaefd028a2a48a4c | customer_even | 130512 | Redistribution started | 0 | | 2024-01-05 04:54:55.641741 | 190 | | Restore Disteven Table
dev | schemaefd028a2a48a4c | customer_even | 130512 | Redistribution checkpointed | 29.4342113157737 | 29.4342113157737 | 2024-01-05 04:55:04.770696 | 190 | | Restore Disteven Table
(8 rows)
```
# SYS\$1RESTORE\$1STATE
在经典大小调整期间，使用 SYS\$1RESTORE\$1STATE 监控每个表的迁移进度。当目标节点类型为 RA3 时，这特别适用。有关经典调整 RA3 节点大小的更多信息，请参阅[经典调整大小](https://docs.aws.amazon.com/redshift/latest/mgmt/managing-cluster-operations.html#classic-resize-faster)。
SYS\$1RESTORE\$1STATE 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_RESTORE_STATE.html)
## 示例查询
以下查询返回正在运行的查询和已排队的查询的记录。
```
SELECT * FROM sys_restore_state;
```
示例输出。
```
userid | database_name | schema_id | table_id | table_name | redistribution_status | precentage_redistributed | redistribution_type
--------+---------------+-----------+----------+----------------+-----------------------+--------------------------+-------------------------
1 | test1 | 124865 | 124878 | customer_key_4 | Pending | 0 | Rebalance Disteven Table
1 | dev | 124865 | 124874 | customer_key_3 | Pending | 0 | Rebalance Disteven Table
1 | dev | 124865 | 124870 | customer_key_2 | Completed | 100 | Rebalance Disteven Table
1 | dev | 124865 | 124866 | customer_key_1 | In progress | 13.52 | Restore Distkey Table
```
以下是数据处理状态。
```
SELECT
redistribution_status, ROUND(SUM(block_count) / 1024.0, 2) AS total_size_gb
FROM sys_restore_state sys inner join stv_tbl_perm stv
on sys.table_id = stv.id
GROUP BY sys.redistribution_status;
```
示例输出。
```
redistribution_status | total_size_gb
-----------------------+---------------
Completed | 0.07
Pending | 0.71
In progress | 0.20
(3 rows)
```
# SYS\$1SCHEMA\$1QUOTA\$1VIOLATIONS
记录超出架构限额时的匹配项、事务 ID 和其他有用信息。此系统表是 [STL\$1SCHEMA\$1QUOTA\$1VIOLATIONS](r_STL_SCHEMA_QUOTA_VIOLATIONS.md) 的转换。
r\$1SYS\$1SCHEMA\$1QUOTA\$1VIOLATIONS 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_SCHEMA_QUOTA_VIOLATIONS.html)
## 示例查询
以下查询显示违反限额的结果：
```
SELECT user_id, TRIM(schema_name) "schema_name", quota, disk_usage, record_time FROM
sys_schema_quota_violations WHERE SCHEMA_NAME = 'sales_schema' ORDER BY timestamp DESC;
```
此查询返回指定 schema 的以下示例输出：
```
user_id| schema_name | quota | disk_usage | record_time
-------+--------------+-------+------------+----------------------------
104 | sales_schema | 2048 | 2798 | 2020-04-20 20:09:25.494723
(1 row)
```
# SYS\$1SERVERLESS\$1USAGE
使用 SYS\$1SERVERLESS\$1USAGE 查看资源的 Amazon Redshift Serverless 使用情况的详细信息。此系统视图不适用于预置 Amazon Redshift 集群。
此视图包含无服务器使用情况摘要，包括用于处理查询的计算容量数量以及以 1 分钟粒度使用的 Amazon Redshift 托管式存储量。计算容量以 Redshift 处理单元 (RPU) 为单位衡量，并按每秒计量以 RPU 秒为单位运行的工作负载。RPU 用于处理对数据仓库中加载数据的查询、从 Amazon S3 数据湖查询或使用联合查询从操作数据库访问。Amazon Redshift Serverless 可在 SYS\$1SERVERLESS\$1USAGE 中将信息保留 7 天时间。
有关计算成本计费的示例，请参阅 [Amazon Redshift Serverless 的计费](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-billing.html)。
SYS\$1SERVERLESS\$1USAGE 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_SERVERLESS_USAGE.html)
## 使用说明
+ 在某些情况下，compute\$1seconds 为 0，但 charged\$1seconds 大于 0，反之亦然。这是由于在系统视图中记录数据的方式而导致的正常行为。为了更准确地表示无服务器使用情况的详细信息，我们建议聚合数据。
## 示例
要通过查询 charged\$1seconds 获取一段时间间隔内使用的 RPU 小时数的总费用，请运行以下查询：
```
select trunc(start_time) "Day",
(sum(charged_seconds)/3600::double precision) * as cost_incurred
from sys_serverless_usage
group by 1
order by 1
```
请注意，在此时间间隔内可能会有空闲时间。空闲时间不会增加使用的 RPU。
# SYS\$1SESSION\$1HISTORY
使用 SYS\$1SESSION\$1HISTORY 查看有关当前活动的会话和会话历史记录的信息。
SYS\$1SESSION\$1HISTORY 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_SESSION_HISTORY.html)
### 示例
以下是 SYS\$1SESSION\$1HISTORY 的示例输出。
```
select * from sys_session_history;
user_id | session_id | database_name | status | session_timeout | start_time | end_time
---------+------------+------------------+--------+-----------------+----------------------------+----------------------------
1 | 1073971370 | dev | closed | 0 | 2023-07-17 15:50:12.030104 | 2023-07-17 15:50:12.123218
1 | 1073979694 | dev | closed | 0 | 2023-07-17 15:50:24.117947 | 2023-07-17 15:50:24.131859
1 | 1073873049 | dev | closed | 0 | 2023-07-17 15:49:29.067398 | 2023-07-17 15:49:29.070294
1 | 1073873086 | database18127a4a | closed | 0 | 2023-07-17 15:49:29.119018 | 2023-07-17 15:49:29.125925
1 | 1073832112 | dev | closed | 0 | 2023-07-17 15:49:29.164688 | 2023-07-17 15:49:29.179631
1 | 1073987697 | dev | closed | 0 | 2023-07-17 15:49:29.26749 | 2023-07-17 15:49:29.273034
1 | 1073922429 | dev | closed | 0 | 2023-07-17 15:49:33.35315 | 2023-07-17 15:49:33.367499
1 | 1073766783 | dev | closed | 0 | 2023-07-17 15:49:45.38237 | 2023-07-17 15:49:45.396902
1 | 1073807506 | dev | active | 0 | 2023-07-17 15:51:48 |
```
# SYS\$1SPATIAL\$1SIMPLIFY
您可以查询系统视图 SYS\$1SPATIAL\$1SIMPLIFY，以使用 COPY 命令获取有关简化空间几何对象的信息。在 shapefile 上使用 COPY 时，您可以指定 SIMPLIFY `tolerance`、SIMPLIFY AUTO 和 SIMPLIFY AUTO `max_tolerance` 摄入选项。简化的结果在 SYS\$1SPATIAL\$1SIMPLIFY 系统视图中进行总结。
当设置 SIMPLIFY AUTO `max_tolerance` 时，此视图为每个超出最大大小的几何体都包含一行。当设置 SIMPLIFY `tolerance` 时，则存储整个 COPY 操作的一行。此行引用 COPY 查询 ID 和指定的简化容差。
有关加载 shapefile 的更多信息，请参阅[将 shapefile 加载到 Amazon Redshift](spatial-copy-shapefile.md)。
SYS\$1SPATIAL\$1SIMPLIFY 对所有用户均可见。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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_SPATIAL_SIMPLIFY.html)
## 示例查询
以下查询返回 COPY 简化的记录的列表。
```
SELECT * FROM sys_spatial_simplify;
query_id | line_number | maximum_tolerance | initial_size | simplified | final_size | final_tolerance
----------+-------------+-------------------+--------------+------------+------------+----------------------
20 | 1184704 | -1 | 1513736 | t | 1008808 | 1.276386653895e-05
20 | 1664115 | -1 | 1233456 | t | 1023584 | 6.11707814796635e-06
```
# SYS\$1STREAM\$1SCAN\$1ERRORS
记录通过串流摄取加载的记录的错误。
SYS\$1STREAM\$1SCAN\$1ERRORS 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_STREAM_SCAN_ERRORS.html)
# SYS\$1STREAM\$1SCAN\$1STATES
记录通过串流摄取加载的记录的扫描状态。
SYS\$1STREAM\$1SCAN\$1STATES 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/r_SYS_STREAM_SCAN_STATES.html)
以下查询显示了特定查询的串流和主题数据。
```
select query_id,mv_name::varchar,external_schema_name::varchar,stream_name::varchar,sum(scanned_rows) total_records,
sum(scanned_bytes) total_bytes from sys_stream_scan_states where query in (5401180,8601939) group by 1,2,3,4;
query_id | mv_name | external_schema_name | stream_name | total_records | total_bytes
------------+----------------+----------------------+-----------------+---------------+----------------
5401180 | kinesistest | kinesis | kinesisstream | 1493255696 | 3209006490704
8601939 | msktest | msk | mskstream | 14677023 | 31056580668
(2 rows)
```
# SYS\$1TRANSACTION\$1HISTORY
跟踪查询时，使用 SYS\$1TRANSACTION\$1HISTORY 查看事务的详细信息。
SYS\$1TRANSACTION\$1HISTORY 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_TRANSACTION_HISTORY.html)
## 示例查询
```
select * from sys_transaction_history order by transaction_start_time desc;
user_id | transaction_id | isolation_level | status | transaction_start_time | commit_start_time | commit_end_time | blocks_committed | undo_transaction_id
---------+----------------+-----------------+------------+----------------------------+----------------------------+----------------------------+------------------+---------------------
100 | 1310 | Serializable | committed | 2023-08-27 21:03:11.822205 | 2023-08-28 21:03:11.825287 | 2023-08-28 21:03:11.854883 | 17 | -1
101 | 1345 | Serializable | committed | 2023-08-27 21:03:12.000278 | 2023-08-28 21:03:12.003736 | 2023-08-28 21:03:12.030061 | 17 | -1
102 | 1367 | Serializable | committed | 2023-08-27 21:03:12.1532 | 2023-08-28 21:03:12.156124 | 2023-08-28 21:03:12.186468 | 17 | -1
100 | 1370 | Serializable | committed | 2023-08-27 21:03:12.199316 | 2023-08-28 21:03:12.204854 | 2023-08-28 21:03:12.238186 | 24 | -1
100 | 1408 | Serializable | committed | 2023-08-27 21:03:53.891107 | 2023-08-28 21:03:53.894825 | 2023-08-28 21:03:53.927465 | 17 | -1
100 | 1409 | Serializable | rolledback | 2023-08-27 21:03:53.936431 | 2000-01-01 00:00:00 | 2023-08-28 21:04:08.712532 | 0 | 1409
101 | 1415 | Serializable | committed | 2023-08-27 21:04:24.283188 | 2023-08-28 21:04:24.289196 | 2023-08-28 21:04:24.374318 | 25 | -1
101 | 1416 | Serializable | committed | 2023-08-27 21:04:24.38818 | 2023-08-28 21:04:24.391688 | 2023-08-28 21:04:24.415135 | 17 | -1
100 | 1417 | Serializable | rolledback | 2023-08-27 21:04:24.424252 | 2000-01-01 00:00:00 | 2023-08-28 21:04:28.354826 | 0 | 1417
101 | 1418 | Serializable | rolledback | 2023-08-27 21:04:24.425195 | 2000-01-01 00:00:00 | 2023-08-28 21:04:28.680355 | 0 | 1418
100 | 1420 | Serializable | committed | 2023-08-27 21:04:28.697607 | 2023-08-28 21:04:28.702374 | 2023-08-28 21:04:28.735541 | 23 | -1
101 | 1421 | Serializable | committed | 2023-08-27 21:04:28.744854 | 2023-08-28 21:04:28.749344 | 2023-08-28 21:04:28.779029 | 23 | -1
101 | 1423 | Serializable | committed | 2023-08-27 21:04:28.78942 | 2023-08-28 21:04:28.791556 | 2023-08-28 21:04:28.817485 | 16 | -1
100 | 1430 | Serializable | committed | 2023-08-27 21:04:28.917788 | 2023-08-28 21:04:28.919993 | 2023-08-28 21:04:28.944812 | 16 | -1
102 | 1494 | Serializable | committed | 2023-08-27 21:04:37.029058 | 2023-08-28 21:04:37.033137 | 2023-08-28 21:04:37.062001 | 16 | -1
```
# SYS\$1UDF\$1LOG
记录在执行用户定义的函数 (UDF) 期间生成的系统定义的错误和警告消息。
SYS\$1UDF\$1LOG 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_UDF_LOG.html)
## 示例查询
以下示例说明 UDF 如何处理系统定义的错误。第一个块显示了返回参数的逆参数的 UDF 函数的定义。在运行函数并提供 0 作为参数时，函数返回错误。最后一条语句返回在 SYS\$1UDF\$1LOG 中记录的错误消息。
```
-- Create a function to find the inverse of a number.
CREATE OR REPLACE FUNCTION f_udf_inv(a int)
RETURNS float
IMMUTABLE AS $$return 1/a
$$ LANGUAGE plpythonu;
-- Run the function with 0 to create an error.
Select f_udf_inv(0);
-- Query SYS_UDF_LOG to view the message.
Select query_id, record_time, message::varchar from sys_udf_log;
query_id | record_time | message
----------+----------------------------+-------------------------------------------------------
2211 | 2023-08-23 15:53:11.360538 | ZeroDivisionError: integer division or modulo by zero line 2, in f_udf_inv\n return 1/a\n
```
以下示例将日志记录和警告消息添加到 UDF 中，以便被零除运算生成警告消息而不是停止并显示错误消息。
```
-- Create a function to find the inverse of a number and log a warning if you input 0.
CREATE OR REPLACE FUNCTION f_udf_inv_log(a int)
RETURNS float IMMUTABLE
AS $$
import logging
logger = logging.getLogger() #get root logger
if a==0:
logger.warning('You attempted to divide by zero.\nReturning zero instead of error.\n')
return 0
else:
return 1/a
$$ LANGUAGE plpythonu;
-- Run the function with 0 to trigger the warning.
Select f_udf_inv_log(0);
-- Query SYS_UDF_LOG to view the message.
Select query_id, record_time, message::varchar from sys_udf_log;
query_id | record_time | message
----------+----------------------------+-------------------------------------------------------------------------------
0 | 2023-08-23 16:10:48.833503 | WARNING: You attempted to divide by zero.\nReturning zero instead of error.\n
```
# SYS\$1UNLOAD\$1DETAIL
使用 SYS\$1UNLOAD\$1DETAIL 查看 UNLOAD 操作的详细信息。这会为由 UNLOAD 语句创建的每个文件记录一行。例如，如果 UNLOAD 创建 12 个文件，则 SYS\$1UNLOAD\$1DETAIL 将包含 12 个对应的行。
SYS\$1UNLOAD\$1DETAIL 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_UNLOAD_DETAIL.html)
## 示例查询
以下查询显示了卸载查询详细信息，包括卸载命令的格式、行和文件计数。
```
select query_id, substring(file_name, 0, 50), transfer_size, file_format from sys_unload_detail;
```
示例输出。
```
query_id | substring | transfer_size | file_format
----------+-------------------------------------------------------------+---------------+-------------
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0000_part_00.gz | 395886 | Text
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0001_part_00.gz | 406444 | Text
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0002_part_00.gz | 409431 | Text
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0003_part_00.gz | 403051 | Text
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0004_part_00.gz | 413592 | Text
9272 | s3://amzn-s3-demo-bucket/my_unload_doc_venue0005_part_00.gz | 395689 | Text
(6 rows)
```
# SYS\$1UNLOAD\$1HISTORY
使用 SYS\$1UNLOAD\$1HISTORY 查看 UNLOAD 命令的详细信息。每行代表一个 UNLOAD 命令，其中包含某些字段的累积统计数据。它包含正在运行和已完成的 UNLOAD 命令。
SYS\$1UNLOAD\$1HORITY 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_UNLOAD_HISTORY.html)
## 示例查询
以下查询显示了卸载查询详细信息，包括卸载命令的格式、行和文件计数。
```
SELECT query_id,
file_format,
start_time,
duration,
unloaded_rows,
unloaded_files_count
FROM sys_unload_history
ORDER BY query_id,
file_format limit 100;
```
示例输出。
```
query_id | file_format | start_time | duration | unloaded_rows | unloaded_files_count
----------+-------------+----------------------------+----------+---------------+----------------------
527067 | Text | 2022-02-09 05:18:35.844452 | 5932478 | 10 | 1
```
# SYS\$1USERLOG
记录数据库用户的以下更改的详细信息。
+ 创建用户
+ 删除用户
+ 更改用户（重命名）
+ 更改用户（更改属性）
您可以查询此视图，以查看有关无服务器工作组和预置集群的信息。
SYS\$1USERLOG 仅对超级用户可见。有关更多信息，请参阅 [系统表和视图中的数据可见性](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_USERLOG.html)
## 示例查询
以下示例执行四个用户操作，然后查询 SYS\$1USERLOG 视图。
```
CREATE USER userlog1 password 'Userlog1';
ALTER USER userlog1 createdb createuser;
ALTER USER userlog1 rename to userlog2;
DROP user userlog2;
SELECT user_id, user_name, original_user_name, action, has_create_db_privs, is_superuser from SYS_USERLOG order by record_time desc;
```
```
user_id | user_name | original_user_name | action | has_create_db_privs | is_superuser
--------+------------+--------------------+---------+---------------------+------------
108 | userlog2 | | drop | 1 | 1
108 | userlog2 | userlog1 | rename | 1 | 1
108 | userlog1 | | alter | 1 | 1
108 | userlog1 | | create | 0 | 0
(4 rows)
```
# SYS\$1VACUUM\$1HISTORY
使用 SYS\$1VACUUM\$1HISTORY 查看 vacuum 查询的详细信息。有关 VACUUM 命令的信息，请参阅[VACUUM](r_VACUUM_command.md)。
SYS\$1VACUUM\$1HISTORY 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](cm_chap_system-tables.md#c_visibility-of-data)。
## 表列
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_cn/redshift/latest/dg/SYS_VACUUM_HISTORY.html)