Amazon Redshift 將不再支援從修補程式 198 開始建立新的 Python UDFs。現有 Python UDF 將繼續正常運作至 2026 年 6 月 30 日。如需詳細資訊，請參閱[部落格文章](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/)。
本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
# SYS 監控檢視
*監控檢視*是 Amazon Redshift 中的系統檢視，用於監控佈建叢集和無伺服器工作群組的查詢和工作負載資源使用情況。這些檢視位於 `pg_catalog` 結構描述中。若要顯示這些檢視提供的資訊，請執行 SQL SELECT 陳述式。
除非另有說明，否則這些檢視可用於 Amazon Redshift 叢集和 Amazon Redshift Serverless 工作群組。
*SYS\$1SERVERLESS\$1USAGE* 只收集 Amazon Redshift Serverless 的使用資料。
**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
記錄在 COPY 或 ANALYZE COMPRESSION 命令期間的壓縮分析操作詳細資訊。
所有使用者都可看見 SYS\$1ANALYZE\$1COMPRESSION\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_ANALYZE_COMPRESSION_HISTORY.html)
## 範例查詢
下列範例由在相同工作階段中執行的最後一項 COPY 命令檢查 `lineitem` 資料表上的壓縮分析詳細資料。
```
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
記錄 [ANALYZE](https://docs.aws.amazon.com/redshift/latest/dg/r_ANALYZE.html) 操作的詳細資訊。
只有超級使用者才能看到 SYS\$1ANALYZE\$1HISTORY。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_ANALYZE_HISTORY.html)
## 範例查詢
```
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 追蹤動態資料遮罩政策套用在參考受 DDM 保護之關係的查詢上的情形。
下列使用者可以看見 SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG：
+ 超級使用者
+ 具有 `sys:operator` 角色的使用者
+ 具有 ACCESS SYSTEM TABLE 許可的使用者
一般使用者將看到 0 列。
請注意，具有 `sys:secadmin` 角色的使用者看不見 SYS\$1APPLIED\$1MASKING\$1POLICY\$1LOG。
如需動態資料遮罩的詳細資訊，請前往 [動態資料遮罩](t_ddm.md)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_APPLIED_MASKING_POLICY_LOG.html)
## 範例查詢
下列範例顯示 `mask_credit_card_full` 遮罩政策已連接至 `credit_db.public.credit_cards` 資料表。
```
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 來檢視 Amazon Redshift 執行以進行自動最佳化之任務的詳細資訊，也稱為自主。如需自動最佳化的詳細資訊，請參閱 [自動資料庫最佳化](c_autonomics.md)。
只有超級使用者可以看到 SYS\$1AUTOMATIC\$1OPTIMIZATION。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_AUTOMATIC_OPTIMIZATION.html)
## 使用須知
無伺服器叢集的 compute\$1type 資料欄將為空，因為我們無法區分主要或主要規模的運算資源。無伺服器叢集運算資源是以 Redshift 處理單元 (RPUs用量來測量。如需詳細資訊，請參閱 [Amazon Redshift Serverless 的運算容量](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-capacity.html)。
## 範例
下列查詢顯示資料表 155259 上執行的自動最佳化。
```
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
```
下列查詢顯示所有執行的自動「VacuumSort」最佳化。如需「VacuumSort」的詳細資訊，請參閱[自動資料表排序](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
記錄 Amazon Redshift 對自動最佳化而定義的資料表執行的自動操作。
只有超級使用者才能看見 SYS\$1AUTO\$1TABLE\$1OPTIMIZATION。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_AUTO_TABLE_OPTIMIZATION.html)
## 範例查詢
在下列範例中，結果中的列顯示 Amazon Redshift 所採取的動作。
```
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
傳回子查詢的 SQL 文字。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_CHILD_QUERY_TEXT.html)
## 範例查詢
在下列範例中，結果中的列顯示 Amazon Redshift 所採取的動作。
```
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
記錄身分驗證嘗試以及連線和中斷連線。
只有超級使用者才能看到 SYS\$1CONNECTION\$1LOG。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_CONNECTION_LOG.html)
## 範例查詢
若要檢視已開啟之連線的詳細資訊，請執行下列查詢。
```
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)
```
下列範例反映失敗的身分驗證嘗試，以及成功的連線和中斷連線。
```
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)
```
下列範例顯示 ODBC 驅動程式的版本、用戶端機器上的作業系統，以及用來連線到 Amazon Redshift 叢集的外掛程式。在此範例中，使用的外掛程式用於使用登入名稱和密碼進行標準 ODBC 驅動程式驗證。
```
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
```
下列範例顯示用戶端電腦上的作業系統版本、驅動程式版本和通訊協定版本。
```
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 來檢視 COPY JOB 命令的詳細資訊。
此檢視包含已建立的 COPY JOB 命令。
所有使用者都可看見 SYS\$1COPY\$1JOB。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_COPY_JOB.html)
# SYS\$1COPY\$1JOB\$1DETAIL
使用 SYS\$1COPY\$1JOB\$1DETAIL 來檢視 COPY JOB 命令的詳細資訊。
此檢視包含已建立的 COPY JOB 命令。如果 COPY JOB 嘗試載入檔案，但載入失敗，則後續自動 COPY JOB 嘗試都會略過該檔案。
所有使用者都可看見 SYS\$1COPY\$1JOB\$1DETAIL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_COPY_JOB_DETAIL.html)
下列範例會傳回一列，代表已擷取項目。
```
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 來檢視有關 COPY JOB 的記錄訊息。
此檢視包含已執行 COPY JOB 中錯誤的相關資訊。
所有使用者都可看見 SYS\$1COPY\$1JOB\$1INFO。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_COPY_JOB_INFO.html)
# SYS\$1COPY\$1REPLACEMENTS
顯示一個日誌，其記錄搭配 ACCEPTINVCHARS 選項的 [COPY](r_COPY.md) 命令何時取代無效的 UTF-8 字元。在至少需要一個取代項目的每個節點上，對於其前 100 個列的每一個都會新增一個日誌項目至 SYS\$1COPY\$1REPLACEMENTS。
您可以使用此檢視來查看有關無伺服器工作群組和已佈建叢集的資訊。
所有使用者都可看見 SYS\$1COPY\$1REPLACEMENTS。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_COPY_REPLACEMENTS.html)
## 範例查詢
下列範例會傳回最新 COPY 操作的取代項目。
```
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
記錄用於追蹤生產者和消費者叢集上資料共用變更的合併檢視。
所有使用者都可看見 SYS\$1DATASHARE\$1CHANGE\$1LOG。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_DATASHARE_CHANGE_LOG.html)
## 範例查詢
下列範例顯示 SYS\$1DATASHARE\$1CHANGE\$1LOG 檢視。
```
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 檢視，可取得跨區域資料共用查詢所造成之跨區域資料傳輸使用量的摘要。SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 彙總區段層級的詳細資料。
只有超級使用者才能看到 SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_DATASHARE_CROSS_REGION_USAGE.html)
## 範例查詢
下列範例顯示 SYS\$1DATASHARE\$1CROSS\$1REGION\$1USAGE 檢視。
```
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
記錄資料共用的活動和使用情況。此檢視僅與消費者叢集相關。
所有使用者都可看見 SYS\$1DATASHARE\$1USAGE\$1CONSUMER。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_DATASHARE_USAGE_CONSUMER.html)
## 範例查詢
下列範例顯示 SYS\$1DATASHARE\$1USAGE\$1CONSUMER 檢視。
```
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
記錄資料共用的活動和使用情況。此檢視僅與生產者叢集相關。
所有使用者都可看見 SYS\$1DATASHARE\$1USAGE\$1PRODUCER。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_DATASHARE_USAGE_PRODUCER.html)
## 範例查詢
下列範例顯示 SYS\$1DATASHARE\$1USAGE\$1PRODUCER 檢視。
```
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 來檢視區段層級的查詢詳細資料。每一列代表特定 WLM 查詢的區段，其中包含處理的列數、處理的位元組數以及 Amazon S3 中外部資料表的分割區資訊等詳細資訊。此檢視中的每一列在 SYS\$1QUERY\$1DETAIL 檢視中也會有一個對應的項目，但此檢視包含與外部查詢處理相關的更多詳細資訊。
所有使用者都可看見 SYS\$1EXTERNAL\$1QUERY\$1DETAIL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_EXTERNAL_QUERY_DETAIL.html)
## 範例查詢
下列查詢會顯示外部查詢詳細資訊。
```
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;
```
輸出範例。
```
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
您可以查詢系統檢視 SYS\$1EXTERNAL\$1QUERY\$1ERROR，以取得有關 Redshift Spectrum 掃描錯誤的資訊。SYS\$1EXTERNAL\$1QUERY\$1ERROR 會顯示記錄錯誤的範例。預設值是每個查詢 10 個項目。
所有使用者都可看見 SYS\$1EXTERNAL\$1QUERY\$1ERROR。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_EXTERNAL_QUERY_ERROR.html)
## 範例查詢
下列查詢會傳回執行資料處理操作的列清單。
```
SELECT * FROM sys_external_query_error;
```
此查詢會傳回類似以下的結果。
```
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 來檢視 Amazon Redshift 使用額外運算資源執行自動最佳化任務的使用期間。如需自動最佳化的詳細資訊，請參閱 [自動資料庫最佳化](c_autonomics.md)。如需使用額外運算資源執行自動最佳化的詳細資訊，請參閱 [配置額外的運算資源以進行自動資料庫最佳化](t_extra-compute-autonomics.md)。
SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION 僅適用於佈建的叢集。
只有超級使用者可以看到 SYS\$1EXTRA\$1COMPUTE\$1FOR\$1AUTOMATIC\$1OPTIMIZATION。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_EXTRA_COMPUTE_FOR_AUTOMATIC_OPTIMIZATION.html)
## 範例
以下是在 2025 年 9 月 16 日尋找自動最佳化的範例查詢。
```
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 會顯示已完成整合執行的相關資訊。
只有超級使用者才能看到 SYS\$1INTEGRATION\$1ACTIVITY。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
如需零 ETL 整合的相關資訊，請參閱 Amazon Redshift 管理指南中的[使用零 ETL 整合](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_INTEGRATION_ACTIVITY.html)
## 範例查詢
下列 SQL 命令會顯示整合的記錄。
```
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 會顯示零 ETL 整合的插入、刪除和更新活動的詳細資訊。每次完成擷取都會新增一列。
超級使用者可以查看此資料表中的所有列。
如需詳細資訊，請參閱[零 ETL 整合](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_INTEGRATION_TABLE_ACTIVITY.html)
## 範例查詢
下列 SQL 命令會顯示擷取的活動。
```
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 會顯示整合的資料表狀態變更日誌。
超級使用者可以查看此資料表中的所有列。
如需詳細資訊，請參閱[使用零 ETL 整合](https://docs.aws.amazon.com//redshift/latest/mgmt/zero-etl-using.html)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_INTEGRATION_TABLE_STATE_CHANGE.html)
## 範例查詢
下列 SQL 命令會顯示整合的記錄。
```
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
傳回資訊以追蹤資料載入或對其進行故障診斷。
此檢視會在每一個資料檔案載入至資料庫資料表時記錄其進度。
所有使用者都可看見此檢視。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_LOAD_DETAIL.html)
## 範例查詢
下列範例傳回上次 COPY 操作的詳細資訊。
```
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)
```
下列查詢包含 TICKIT 資料庫中全新載入之資料表的項目：
```
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)
```
事實上，記錄寫入至此系統檢視的日誌檔案，並不表示已成功遞交載入，做為其包含交易的一部分。若要驗證載入遞交，請查詢 STL\$1UTILITYTEXT 檢視，並尋找與 COPY 交易相對應的 COMMIT 記錄。例如，此查詢會針對 STL\$1UTILITYTEXT 根據子查詢聯結 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 會記錄在特定查詢中使用的 Lambda 使用者定義函數 (LUDFs) 的資訊和指標。
只有超級使用者可以看到 SYS\$1LUDF\$1DETAIL。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_LUDF_DETAIL.html)
## 範例查詢
下列範例在查詢中使用 Lambda UDF，然後顯示如何查詢 SYS\$1LUDF\$1DETAIL 檢視以查看函數執行詳細資訊。
```
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;
```
輸出範例：
```
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 來檢視 COPY 命令錯誤的詳細資料。每一列代表一個 COPY 命令。它包含正在執行和已完成的 COPY 命令。
所有使用者都可看見 SYS\$1LOAD\$1ERROR\$1DETAIL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_LOAD_ERROR_DETAIL.html)
## 範例查詢
下列查詢會顯示特定查詢複製命令的載入錯誤詳細資訊。
```
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;
```
輸出範例。
```
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 來檢視 COPY 命令的詳細資訊。每一列代表一個 COPY 命令，其中包含某些欄位的累計統計資料。它包含正在執行和已完成的 COPY 命令。
所有使用者都可看見 SYS\$1LOAD\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_LOAD_HISTORY.html)
## 範例查詢
下列查詢顯示特定複製命令的載入列、位元組、資料表和資料來源。
```
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;
```
輸出範例。
```
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
```
下列查詢顯示複製命令的載入列、位元組、資料表和資料來源。
```
SELECT query_id,
table_name,
data_source,
loaded_rows,
loaded_bytes
FROM sys_load_history
ORDER BY query_id DESC
LIMIT 10;
```
輸出範例。
```
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
```
下列查詢顯示複製命令的每日載入列和位元組。
```
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;
```
輸出範例。
```
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
結果包括所有具體化視觀表之重新整理歷史記錄的相關資訊。結果包括重新整理類型 (例如手動或自動)，以及最近重新整理的狀態。
所有使用者都可看見 SYS\$1MV\$1REFRESH\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_MV_REFRESH_HISTORY.html)
## 範例查詢
下列查詢顯示具體化視觀表的重新整理歷史記錄。
```
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;
```
此查詢會傳回下列範例輸出：
```
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
結果包括所有具體化視觀表狀態的相關資訊。它包括基底資料表資訊、結構描述屬性，以及有關最近事件的資訊，例如卸除欄。
所有使用者都可看見 SYS\$1MV\$1STATE。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_MV_STATE.html)
## 範例查詢
下列查詢顯示具體化視觀表的狀態。
```
select * from sys_mv_state;
```
此查詢會傳回下列範例輸出：
```
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 檢視來取得預存程序呼叫的相關資訊，包括開始時間、結束時間、預存程序呼叫的狀態，以及巢狀預存程序呼叫的呼叫階層。每次預存程序呼叫會接收查詢 ID。
所有使用者都可看見 SYS\$1PROCEDURE\$1CALL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_PROCEDURE_CALL.html)
## 範例查詢
下列查詢會傳回巢狀預存程序呼叫階層。
```
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;
```
輸出範例。
```
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
所有使用者都可看見 SYS\$1PROCEDURE\$1MESSAGES。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_PROCEDURE_MESSAGES.html)
## 範例查詢
下列查詢顯示 SYS\$1PROCEDURE\$1MESSAGES 的範例輸出。
```
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 來檢視各種指標層級的查詢詳細資訊，其中每一列代表特定指標層級的特定 WLM 查詢的詳細資訊。此檢視包含許多類型的查詢，例如 DDL、DML 和公用程式命令 (例如，複製和卸載)。根據查詢類型的不同，某些欄可能不相關。例如，external\$1scanned\$1bytes 與內部資料表不相關。
所有使用者都可看見 SYS\$1QUERY\$1DETAIL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
**注意**
若要驗證包含已執行查詢的交易是否已成功認可，您需要在系統資料表與 `sys_transaction_history` 資料表之間執行聯結操作。例如：
```
SELECT
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;
```
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_DETAIL.html)
## 使用須知
SYS\$1QUERY\$1DETAIL 可包含步驟、串流、區段和子查詢層級的指標。除了參考 metrics\$1level 欄之外，您還可以根據下表參考 step\$1id、segment\$1id 和 stream\$1id 欄位，以查看某一列顯示的指標層級。
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_DETAIL.html)
## 範例查詢
下列範例會傳回 SYS\$1QUERY\$1DETAIL 的輸出。
以下查詢顯示步驟層級的查詢中繼資料詳細資訊，包括步驟名稱、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;
```
輸出範例。
```
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
```
若要檢視資料庫中的資料表，從最常用到最少使用的順序，請使用下列範例。用您自己的資料庫取代 *sample\$1data\$1dev*。請注意，此查詢將在建立叢集時開始計算查詢，但是當資料倉儲缺少空間時，系統檢視資料不會儲存。
```
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 |
+---------------------------------+-------+
```
下列範例顯示單一 WLM 查詢的各種指標層級。
```
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
顯示已提交供執行之用的查詢的 EXPLAIN 計劃。
所有使用者都可看見 SYS\$1QUERY\$1EXPLAIN。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_EXPLAIN.html)
## 範例查詢
下列範例是單一查詢的 EXPLAIN 計畫。
```
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 來檢視使用者查詢的詳細資料。每一列代表一個使用者查詢，其中包含某些欄位的累計統計資料。此檢視包含許多類型的查詢，例如資料定義語言 (DDL)、資料處理語言 (DML)、複製、卸載和 Amazon Redshift Spectrum。它包含正在執行和已完成的查詢。
所有使用者都可看見 SYS\$1QUERY\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
**注意**
若要驗證包含已執行查詢的交易是否已成功認可，您需要在系統資料表與 `sys_transaction_history` 資料表之間執行聯結操作。例如：
```
SELECT
qh.transaction_id,
qh.query_id,
qh.status AS query_status,
qh.query_type,
TRIM(qh.query_text) AS query_text,
th.status AS transaction_status
FROM
sys_query_history qh
LEFT JOIN
sys_transaction_history th ON qh.transaction_id = th.transaction_id;
```
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_HISTORY.html)
## 範例查詢
下列查詢會傳回執行中和佇列中的查詢。
```
SELECT user_id,
query_id,
transaction_id,
session_id,
status,
trim(database_name) AS database_name,
start_time,
end_time,
result_cache_hit,
elapsed_time,
queue_time,
execution_time
FROM sys_query_history
WHERE status IN ('running','queued')
ORDER BY start_time;
```
輸出範例。
```
user_id | query_id | transaction_id | session_id | status | database_name | start_time | end_time | result_cache_hit | elapsed_time | queue_time | execution_time
---------+----------+----------------+------------+---------+---------------+---------------------------+----------------------------+------------------+--------------+------------+----------------
101 | 760705 | 852337 | 1073832321 | running | tpcds_1t | 2022-02-15 19:03:19.67849 | 2022-02-15 19:03:19.739811 | f | 61321 | 0 | 0
```
下列查詢會傳回特定查詢的查詢開始時間、結束時間、佇列時間、經歷時間、計劃時間及其他中繼資料。
```
SELECT user_id,
query_id,
transaction_id,
session_id,
status,
trim(database_name) AS database_name,
start_time,
end_time,
result_cache_hit,
elapsed_time,
queue_time,
execution_time,
planning_time,
trim(query_text) as query_text
FROM sys_query_history
WHERE query_id = 3093;
```
輸出範例。
```
user_id | query_id | transaction_id | session_id | status | database_name | start_time | end_time | result_cache_hit | elapsed_time | queue_time | execution_time | planning_time | query_text
--------+----------+----------------+------------+------------+---------------+----------------------------+----------------------------+------------------+--------------+------------+----------------+---------------+-------------------------------------
106 | 3093 | 11759 | 1073750146 | success | dev | 2023-03-16 16:53:17.840214 | 2023-03-16 16:53:18.106588 | f | 266374 | 0 | 105725 | 136589 | select count(*) from item;
```
下列查詢會列出10 個最近的 SELECT 查詢。
```
SELECT query_id,
transaction_id,
session_id,
start_time,
elapsed_time,
queue_time,
execution_time,
returned_rows,
returned_bytes
FROM sys_query_history
WHERE query_type = 'SELECT'
ORDER BY start_time DESC limit 10;
```
輸出範例。
```
query_id | transaction_id | session_id | start_time | elapsed_time | queue_time | execution_time | returned_rows | returned_bytes
----------+----------------+------------+----------------------------+--------------+------------+----------------+---------------+----------------
526532 | 61093 | 1073840313 | 2022-02-09 04:43:24.149603 | 520571 | 0 | 481293 | 1 | 3794
526520 | 60850 | 1073840313 | 2022-02-09 04:38:27.24875 | 635957 | 0 | 596601 | 1 | 3679
526508 | 60803 | 1073840313 | 2022-02-09 04:37:51.118835 | 563882 | 0 | 503135 | 5 | 17216
526505 | 60763 | 1073840313 | 2022-02-09 04:36:48.636224 | 649337 | 0 | 589823 | 1 | 652
526478 | 60730 | 1073840313 | 2022-02-09 04:36:11.741471 | 14611321 | 0 | 14544058 | 0 | 0
526467 | 60636 | 1073840313 | 2022-02-09 04:34:11.91463 | 16711367 | 0 | 16633767 | 1 | 575
511617 | 617946 | 1074009948 | 2022-01-20 06:21:54.44481 | 9937090 | 0 | 9899271 | 100 | 12500
511603 | 617941 | 1074259415 | 2022-01-20 06:21:45.71744 | 8065081 | 0 | 7582500 | 100 | 8889
511595 | 617935 | 1074128320 | 2022-01-20 06:21:44.030876 | 1051270 | 0 | 1014879 | 1 | 72
511584 | 617931 | 1074030019 | 2022-01-20 06:21:42.764088 | 609033 | 0 | 485887 | 100 | 8438
```
下列查詢會顯示每日選擇查詢計數和平均查詢經歷時間。
```
SELECT date_trunc('day',start_time) AS exec_day,
status,
COUNT(*) AS query_cnt,
AVG(datediff (microsecond,start_time,end_time)) AS elapsed_avg
FROM sys_query_history
WHERE query_type = 'SELECT'
AND start_time >= '2022-01-14'
AND start_time <= '2022-01-18'
GROUP BY exec_day,
status
ORDER BY exec_day,
status;
```
輸出範例。
```
exec_day | status | query_cnt | elapsed_avg
---------------------+---------+-----------+------------
2022-01-14 00:00:00 | success | 5253 | 56608048
2022-01-15 00:00:00 | success | 7004 | 56995017
2022-01-16 00:00:00 | success | 5253 | 57016363
2022-01-17 00:00:00 | success | 5309 | 55236784
2022-01-18 00:00:00 | success | 8092 | 54355124
```
下列查詢會顯示日常查詢的經歷時間效能。
```
SELECT distinct date_trunc('day',start_time) AS exec_day,
query_count.cnt AS query_count,
Percentile_cont(0.5) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P50_runtime,
Percentile_cont(0.8) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P80_runtime,
Percentile_cont(0.9) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P90_runtime,
Percentile_cont(0.99) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS P99_runtime,
Percentile_cont(1.0) within group(ORDER BY elapsed_time) OVER (PARTITION BY exec_day) AS max_runtime
FROM sys_query_history
LEFT JOIN (SELECT date_trunc('day',start_time) AS day, count(*) cnt
FROM sys_query_history
WHERE query_type = 'SELECT'
GROUP by 1) query_count
ON date_trunc('day',start_time) = query_count.day
WHERE query_type = 'SELECT'
ORDER BY exec_day;
```
輸出範例。
```
exec_day | query_count | p50_runtime | p80_runtime | p90_runtime | p99_runtime | max_runtime
---------------------+-------------+-------------+-------------+-------------+--------------+--------------
2022-01-14 00:00:00 | 5253 | 16816922.0 | 69525096.0 | 158524917.8 | 486322477.52 | 1582078873.0
2022-01-15 00:00:00 | 7004 | 15896130.5 | 71058707.0 | 164314568.9 | 500331542.07 | 1696344792.0
2022-01-16 00:00:00 | 5253 | 15750451.0 | 72037082.2 | 159513733.4 | 480372059.24 | 1594793766.0
2022-01-17 00:00:00 | 5309 | 15394513.0 | 68881393.2 | 160254700.0 | 493372245.84 | 1521758640.0
2022-01-18 00:00:00 | 8092 | 15575286.5 | 68485955.4 | 154559572.5 | 463552685.39 | 1542783444.0
2022-01-19 00:00:00 | 5860 | 16648747.0 | 72470482.6 | 166485138.2 | 492038228.67 | 1693483241.0
2022-01-20 00:00:00 | 1751 | 15422072.0 | 69686381.0 | 162315385.0 | 497066615.00 | 1439319739.0
2022-02-09 00:00:00 | 13 | 6382812.0 | 17616161.6 | 21197988.4 | 23021343.84 | 23168439.0
```
下列查詢顯示查詢類型分佈。
```
SELECT query_type,
COUNT(*) AS query_count
FROM sys_query_history
GROUP BY query_type
ORDER BY query_count DESC;
```
輸出範例。
```
query_type | query_count
------------+-------------
UTILITY | 134486
SELECT | 38537
DDL | 4832
OTHER | 768
LOAD | 768
CTAS | 748
COMMAND | 92
```
下列範例顯示數個查詢之間查詢雜湊結果的差異。請觀察下列查詢：
```
CREATE TABLE test_table (col1 INT);
INSERT INTO test_table VALUES (1),(2);
SELECT * FROM test_table;
SELECT * FROM test_table;
SELECT col1 FROM test_table;
SELECT * FROM test_table WHERE col1=1;
SELECT * FROM test_table WHERE col1=2;
SELECT query_id, TRIM(user_query_hash) AS user_query_hash, TRIM(generic_query_hash) AS generic_query_hash, TRIM(query_text) AS text FROM sys_query_history ORDER BY start_time
DESC LIMIT 10;
```
以下是範例輸出：
```
query_id | user_query_hash | generic_query_hash | text
---------+-----------------+--------------------+----------
24723049 | oPuFtjEPLTs= | oPuFtjEPLTs= | select query_id, trim(user_query_hash) as user_query_hash, trim(generic_query_hash) as generic_query_hash, query_hash_version, trim(query_text) as text from sys_query_history order by start_time\r\ndesc limit 20
24723045 | Gw2Kwdd8m2I= | IwfRu8/XAKI= | select * from test_table where col1=2 limit 100
24723041 | LNw2vx0GDXo= | IwfRu8/XAKI= | select * from test_table where col1=1 limit 100
24723036 | H+qep/c82Y8= | H+qep/c82Y8= | select col1 from test_table limit 100
24723033 | H+qep/c82Y8= | H+qep/c82Y8= | select * from test_table limit 100
24723029 | H+qep/c82Y8= | H+qep/c82Y8= | select * from test_table limit 100
24723023 | 50sirx9E1hU= | uO36Z1a/QYs= | insert into test_table values (1),(2)
24723021 | YSVnlivZHeo= | YSVnlivZHeo= | create table test_table (col1 int)
```
`SELECT * FROM test_table;` 和 `SELECT col1 FROM test_table;` 具有相同的 user\$1query\$1hash 值，因為 test\$1table 只有一欄。`SELECT * FROM test_table WHERE col1=1;` 和 `SELECT * FROM test_table WHERE col1=2;` 具有不同的 user\$1query\$1hash 值，但具有相同的 generic\$1query\$1hash 值，因為兩個查詢除了查詢常值 1 和 2 之外完全一致。
# SYS\$1QUERY\$1TEXT
使用 SYS\$1QUERY\$1TEXT 來檢視所有查詢的查詢文字。每一列代表查詢的查詢文字，最多 4000 個字元，以序列號 0 開始。當查詢陳述式包含超過 4000 個字元時，會藉由遞增每個列的序號來記錄陳述式的其他列。此檢視會記錄所有使用者查詢文字，例如 DDL、公用程式、Amazon Redshift 查詢，以及僅限潛在客戶節點的查詢。
所有使用者都可看見 SYS\$1QUERY\$1TEXT。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_QUERY_TEXT.html)
## 範例查詢
下列查詢會傳回執行中和佇列中的查詢。
```
SELECT user_id,
query_id,
transaction_id,
session_id, start_time,
sequence, trim(text) as text from sys_query_text
ORDER BY sequence;
```
輸出範例。
```
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;
```
下列查詢會傳回已從資料庫中的群組授與或撤銷的許可。
```
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 來檢視 Redshift TEMPLATES 的詳細資訊。
此檢視包含已建立的 TEMPLATES。
所有使用者都可看見 SYS\$1REDSHIFT\$1TEMPLATE。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_REDSHIFT_TEMPLATE.html)
## 範例查詢
下列查詢會傳回目前使用者可見的所有範本：
```
SELECT * FROM SYS_REDSHIFT_TEMPLATE;
```
輸出範例。
```
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
使用 SYS\$1RESTORE\$1LOG 在傳統調整為 RA3 節點大小期間，監控叢集中每個資料表的遷移進度。它會在調整大小作業期間擷取資料遷移的歷史輸送量。如需有關傳統調整為 RA3 節點大小的詳細資訊，請參閱[傳統調整大小](https://docs.aws.amazon.com/redshift/latest/mgmt/managing-cluster-operations.html#classic-resize-faster)。
只有超級使用者才能看到 SYS\$1RESTORE\$1LOG。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_RESTORE_LOG.html)
## 範例查詢
下列查詢會使用 SYS\$1RESTORE\$1LOG 計算資料處理的輸送量。
```
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;
```
輸出範例。
```
data_processed_gb | duration_hr | throughput_gb_per_hr
-------------------+-------------+----------------------
0.91 | 8.37 | 0.11
(1 row)
```
下列查詢顯示所有重新分佈類型。
```
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
使用 SYS\$1RESTORE\$1STATE 可以在傳統調整大小時監視每個資料表的移轉進度。當目標節點類型為 RA3 時，這特別適用。如需有關傳統調整為 RA3 節點大小的詳細資訊，請參閱[傳統調整大小](https://docs.aws.amazon.com/redshift/latest/mgmt/managing-cluster-operations.html#classic-resize-faster)。
只有超級使用者才能看到 SYS\$1RESTORE\$1STATE。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_RESTORE_STATE.html)
## 範例查詢
下列查詢會傳回執行中和佇列中查詢的記錄。
```
SELECT * FROM sys_restore_state;
```
輸出範例。
```
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
```
以下提供資料處理狀態。
```
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;
```
輸出範例。
```
redistribution_status | total_size_gb
-----------------------+---------------
Completed | 0.07
Pending | 0.71
In progress | 0.20
(3 rows)
```
# SYS\$1SCHEMA\$1QUOTA\$1VIOLATIONS
超過結構描述配額時，記錄出現次數、交易 ID 和其他有用的資訊。此系統資料表為 [STL\$1SCHEMA\$1QUOTA\$1VIOLATIONS](r_STL_SCHEMA_QUOTA_VIOLATIONS.md) 的翻譯。
所有使用者都可看見 r\$1SYS\$1SCHEMA\$1QUOTA\$1VIOLATIONS。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_SCHEMA_QUOTA_VIOLATIONS.html)
## 範例查詢
下列查詢顯示配額違規的結果：
```
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;
```
此查詢會傳回所指定結構描述的下列範例輸出：
```
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 來檢視 Amazon Redshift Serverless 資源使用情況的詳細資訊。此系統檢視不適用於已佈建的 Amazon Redshift 叢集。
此檢視包含無伺服器使用量摘要，包括使用多少運算容量來處理查詢，以及使用的 Amazon Redshift 託管儲存量 (1 分鐘精細程度)。運算容量以 Redshift 處理單元 (RPU) 為單位進行測量，並以每秒 RPU 秒為單位執行的工作負載進行計量。RPU 用於處理對資料倉儲中載入的資料的查詢、從 Amazon S3 資料湖查詢或使用聯合查詢從操作資料庫存取的資料。Amazon Redshift 伺服器會在 SYS\$1SERVERLESS\$1USAGE 中保留 7 天的資訊。
如需運算成本帳單的範例，請參閱 [Amazon Redshift Serverless 的計費](https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-billing.html)。
只有超級使用者才能看到 SYS\$1SERVERLESS\$1USAGE。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_SERVERLESS_USAGE.html)
## 使用須知
+ 在某些情況下，compute\$1seconds 為 0，但 charged\$1seconds 大於 0，反之亦然。這是由於在系統檢視中記錄資料的方式所產生的正常行為。若要更準確地呈現無伺服器使用情況詳細資訊，我們建議您彙總資料。
## 範例
若要透過查詢 charged\$1seconds 來取得某個時間間隔內使用的 RPU 小時總費用，請執行下列查詢：
```
select trunc(start_time) "Day",
(sum(charged_seconds)/3600::double precision) * as cost_incurred
from sys_serverless_usage
group by 1
order by 1
```
請注意，間隔期間可能會有閒置時間。閒置時間不會增加至使用的 RPU。
# SYS\$1SESSION\$1HISTORY
使用 SYS\$1SESSION\$1HISTORY 來檢視目前作用中工作階段和工作階段歷史記錄的相關資訊。
所有使用者都可看見 SYS\$1SESSION\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_SESSION_HISTORY.html)
### 範例
下列為 SYS\$1SESSION\$1HISTORY 的範例輸出。
```
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
您可以使用 COPY 命令查詢系統檢視 SYS\$1SPATIAL\$1SIMPLIFY，以取得有關簡化空間幾何物件的資訊。當您在 Shapefile 上使用 COPY 時，您可以指定 SIMPLIFY `tolerance`、SIMPLIFY AUTO 和 SIMPLIFY AUTO `max_tolerance` 擷取選項。簡化的結果摘要在 SYS\$1SPATIAL\$1SIMPLIFY 系統檢視中。
設定 SIMPLIFY AUTO `max_tolerance` 時，此檢視會針對超出大小上限的每個幾何包含一列。設定 SIMPLIFY `tolerance` 時，會儲存整個 COPY 操作的一個列。此列參考 COPY 查詢 ID 和指定的簡化公差。
如需有關載入 shapefile 的相關資訊，請參閱[將 Shapefile 載入 Amazon Redshift](spatial-copy-shapefile.md)。
所有使用者都可看見 SYS\$1SPATIAL\$1SIMPLIFY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_SPATIAL_SIMPLIFY.html)
## 範例查詢
下列查詢會傳回 COPY 簡化的記錄清單。
```
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
記錄透過串流擷取載入之記錄的錯誤。
所有使用者都可看見 SYS\$1STREAM\$1SCAN\$1ERRORS。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_STREAM_SCAN_ERRORS.html)
# SYS\$1STREAM\$1SCAN\$1STATES
記錄透過串流擷取載入之記錄的掃描狀態。
所有使用者都可看見 SYS\$1STREAM\$1SCAN\$1STATES。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/r_SYS_STREAM_SCAN_STATES.html)
下列查詢會顯示特定查詢的串流和主題資料。
```
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
追蹤查詢時，請使用 SYS\$1TRANSACTION\$1HISTORY 來查看交易的詳細資訊。
只有超級使用者才能看到 SYS\$1TRANSACTION\$1HISTORY。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_TRANSACTION_HISTORY.html)
## 範例查詢
```
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
使用者定義函數 (UDF) 執行期間產生的記錄系統定義的錯誤和警告訊息。
只有超級使用者才能看到 SYS\$1UDF\$1LOG。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_UDF_LOG.html)
## 範例查詢
以下範例說明 UDF 如何處理系統定義的錯誤。第一個區塊顯示傳回引數反向之 UDF 函數的定義。當您執行函數並提供 0 做為引數時，函數會傳回錯誤。最後一個陳述式會傳回 SYS\$1UDF\$1LOG 中記錄的錯誤訊息。
```
-- 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
```
下列範例會將記錄且警告訊息新增至 UDF，以至於除以零操作會導致警告訊息，而不是停止並出現錯誤訊息。
```
-- 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 來檢視 UNLOAD 操作的詳細資訊。它會針對 UNLOAD 陳述式所建立的每一個檔案各記錄一列。例如，若 UNLOAD 建立 12 個檔案，則 SYS\$1UNLOAD\$1DETAIL 將包含 12 個對應列。
所有使用者都可看見 SYS\$1UNLOAD\$1DETAIL。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_UNLOAD_DETAIL.html)
## 範例查詢
下列查詢顯示卸載查詢詳細資訊，包括卸載命令的格式、列和檔案計數。
```
select query_id, substring(file_name, 0, 50), transfer_size, file_format from sys_unload_detail;
```
輸出範例。
```
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 來檢視 UNLOAD 命令的詳細資訊。每一列代表一個 UNLOAD 命令，其中包含某些欄位的累計統計資料。它包含正在執行和已完成的 UNLOAD 命令。
所有使用者都可看見 SYS\$1UNLOAD\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_UNLOAD_HISTORY.html)
## 範例查詢
下列查詢顯示卸載查詢詳細資訊，包括卸載命令的格式、列和檔案計數。
```
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;
```
輸出範例。
```
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
記錄資料庫使用者之下列變更的詳細資訊：
+ 建立使用者
+ 捨棄使用者
+ 更改使用者 (重新命名)
+ 更改使用者 (更改屬性)
您可以查詢此檢視，以查看有關無伺服器工作群組和已佈建叢集的資訊。
只有超級使用者才能看到 SYS\$1USERLOG。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_USERLOG.html)
## 範例查詢
下列範例會執行四個使用者動作，然後查詢 SYS\$1USERLOG 資料表。
```
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 來檢視清空查詢的詳細資料。如需 VACUUM 命令的詳細資訊，請參閱[VACUUM](r_VACUUM_command.md)。
所有使用者都可看見 SYS\$1VACUUM\$1HISTORY。超級使用者可以看見所有資料列；一般使用者只能看見自己的資料。如需詳細資訊，請參閱[系統資料表和檢視中資料的可見性](cm_chap_system-tables.md#c_visibility-of-data)。
## 資料表欄
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/zh_tw/redshift/latest/dg/SYS_VACUUM_HISTORY.html)