Sql error 57014

NpgsqlException 57014: canceling statement due to user request #3052

Hi, i use version(4.1.4) from GitHUb> Fix4.1.4 branch,
I get this Exception, after execution application that call single select query.
that this occurs only when the I was open connection to excute SQL Command

SQL Command：Select payment.payment_id,payment.customer_id,payment.staff_idFrom public.payment

Further technical details

Npgsql version:4.1.4.0
PostgreSQL version:PostgreSQL 11.3 (Debian 11.3-1.pgdg90+1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 6.3.0-18+deb9u1) 6.3.0 20170516, 64-bit
Operating system: Windows 10 Enterprise

The text was updated successfully, but these errors were encountered:

The exception indicates that someone is cancelling your query (e.g. by calling NpgsqlCommand.Cance or triggering a cancellation token), but it’s not possible to know who that is only from the exception trace posted above. Any chance you can post a minimal code sample that shows the error? Also, are you using any additional layers on top of Npgsql (e.g. Dapper)?

It’s possible that the command was cancelled even by a different instance of the application if pgbouncer is used with enabled pooling. Why so? To cancel a command you need the second connection because of the nature of PostgreSQL, and the connection Id is required too. The driver remembers the received id, but it’s a physical id which doesn’t correspond to the current connection from bouncer.

There is something to watch out for regarding this error. I’ve seen the error when using Dapper and iterating over a result set using a foreach. The results are being read a row at a time (not read into an array/list and then iterated over). The exception below results in an NpgsqlException (the one you list above) in my global exception handler that is outside the foreach loop. To see the actual exception, I found that I have to put a try/catch block within the foreach loop itself. So, I think the exception can still appear even if the connection wasn’t cancelled on the back end. Though I think I am actually running into that problem also (intermittent dropped connections when querying a PostgreSQL instance in Amazon’s cloud). I just tested it by intentionally throwing an exception in the body of the foreach to see what kind of exception is throw to the global exception handler I have in my Main() method.

I think the behavior that I’m seeing may actually be a bug. Here’s my stack trace. The problem is that Dispose() is throwing an exception. The rules for Dispose() say that it should never throw an exception if I remember correctly.

@jemiller0 which version of Npgsql are you using? #2372 should have taken care of this for 5.0.0. Regardless, can you please open a separate issue if there’s a problem?

Thanks @roji. I’m using .NET Framework. It looked like 5.0.0 required .NET 5. So, I’m currently using 4.1.6.

Don’t be cheated by the version number. It’s accidentally aligned with .NET 5 because Microsoft skipped version for due to .NET Framework. The provider is available for .NET Standard 2 and above.

Thanks @YohDeadfall. I can confirm that 5.0.0 does indeed appear to fix the problem. I like the new behavior much better. The old behavior was very confusing.

Good, closing the issue then.

@YohDeadfall I don’t know if it fixes the problem that @jack0718 had when he created this issue. Mine was actually the one in #2372.

@roji @YohDeadfall I just wanted to say, I think you guys are doing a great job. I can’t remember what the other issues were, but, I ran into a weird issue here or there and remember @roji responding and problems being fixed. It is very refreshing to run into a problem like the one with Dispose() throwing exceptions and having developers fix it straight away. This stands in stark contrast to a lot of other projects that I’ve had experience with. So, thanks, and keep up the good work.

Mostly all cancellation stuff was made by @vonzshik, he did a lot just before 5.0 and now is a member of the crew. Another big feature was made by @Brar, it’s replication support. So it’s not just Shay and me (: Anyway, thank you for the kind words!

Источник

«SQLSTATE: 57014, SQLCODE: -952» error when you use the BizTalk Adapter for DB2 in a Host Integration Server 2010 environment

Symptoms

When you use the Microsoft BizTalk Adapter for DB2 to issue queries against an IBM DB2 database, queries that take longer than 30 seconds to return any data may fail. Additionally, you receive an error message that resembles the following:

Processing was cancelled due to an interrupt. SQLSTATE: 57014, SQLCODE: -952

Cause

This problem occurs because the CommandTimeout property in the DB2 Transport properties is hard-coded to a time-out value of 30 seconds. Other time-out values that you may set do not override the hard-coded value.

Resolution

Cumulative update information

The fix that resolves this problem is included in cumulative update package 7 for Host Integration Server 2010. For more information about how to obtain the cumulative update package, see Cumulative update package 7 for Host Integration Server 2010.

Status

Microsoft has confirmed that this is a problem in the Microsoft products that are listed in the «Applies to» section.

More Information

This update adds support for a configurable CommandTimeout property for the BizTalk Adapter for DB2.

The third-party products that this article discusses are manufactured by companies that are independent of Microsoft. Microsoft makes no warranty, implied or otherwise, about the performance or reliability of these products.

Источник

How do I troubleshoot an AWS DMS task that is failing with error message «ERROR: canceling statement due to statement timeout»?

Last updated: 2022-10-12

I’m migrating data to or from my on-premises PostgreSQL database using AWS Database Migration Service (AWS DMS). The AWS DMS task runs normally for a while, and then the task fails with an error. How do I troubleshoot and resolve these errors?

Short description

If the PostgreSQL database is the source of your migration task, then AWS DMS gets data from the table during the full load phase. Then, AWS DMS reads from the write-ahead logs (WALs) that are kept by the replication slot during the change data capture (CDC) phase.

If the PostgreSQL database is the target, then AWS DMS gets the data from the source and creates CSV files in the replication instance. Then, AWS DMS runs a COPY command to insert those records into the target during the full load phase.

But, during the CDC phase, AWS DMS runs the exact DML statements from the source WAL logs in transactional apply mode. For batch apply mode, AWS DMS also creates CSV files during the CDC phase. Then, it runs a COPY command to insert the net changes to the target.

When AWS DMS tries to either get data from source or put data in the target, it uses the default timeout setting of 60 seconds. If the source or target is heavily loaded or there are locks in the tables, then AWS DMS can’t finish running those commands within 60 seconds. So, the task fails with an error that says «canceling statement due to statement timeout,» and you see one of these entries in the log:

«]E: RetCode: SQL_ERROR SqlState: 57014 NativeError: 1 Message: ERROR: canceling statement due to statement timeout; Error while executing the query [1022502] (ar_odbc_stmt.c:2738)»

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392))»

To troubleshoot and resolve these errors, follow these steps:

• Identify the cause of long run times for commands.
• Increase the timeout value and check the slot creation timeout value.
• Troubleshoot slot creation issues.

Resolution

Identify the cause of long run times for commands

To find the command that failed to run during the timeout period, review the AWS DMS task log and the table statistics section of the task. You can also find this information in the PostgreSQL error log file if the parameter log_min_error_statement is set to ERROR or a lower severity. After identifying the command that failed, you can find the failed table names. See this example error message from the PostgreSQL error log:

To find locks on the associated tables, run this command in the source or target (depending where the error is appearing):

If you find any PIDs that are blocked, stop or terminate the blocked PID by running this command:

Because dead rows, or «tuples,» can increase SELECT time, check for large numbers of dead rows in the source tables by running this command:

Check to see if the failed target table has primary keys or unique indexes. If the table has no primary keys or unique indexes, then a full table scan is performed during the running of any UPDATE statement. This table scan can take a long time.

Increase the timeout value

AWS DMS uses the executeTimeout extra connection attribute in both the source and target endpoints. The default value for executeTimeout is 60 seconds, so AWS DMS times out if a query takes longer than 60 seconds to run.

If the error appears in Source_Unload or Source_Capture, then set the timeout value for executeTimeout in the source. If the error appears in Target_Load or Target_Apply, set the timeout value for executeTimeout in the target. Increase the timeout value setting by following these steps:

2. Choose Endpoints from the navigation pane.

3. Choose the PostgreSQL endpoint.

4. Choose Actions, and select Modify.

5. Expand the Endpoint-specific settings section.

6. In the field for Extra connection attributes, enter this value:

8. From the Endpoints pane, choose the name of your PostgreSQL endpoint.

9. From the Connections section, the Status of the endpoint changes from Testing to Successful.

You can increase (in milliseconds) the statement_timeout parameter in the PostgreSQL DB instance. The default value is , which turns off timeouts for any query. You can also increase the lock_timeout parameter. The default value is , which turns off timeouts for locks.

Troubleshoot slot creation issues

If the timeout occurred when you created the replication slot in the PostgreSQL database, then you see log entries similar to the following:

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392)»

You can increase this timeout by configuring the TransactionConsistencyTimeout parameter in the Task settings section. The default value is 600 seconds.

PostgreSQL can’t create the replication slot if there are any active locks in the database user tables. Check for locks by running this command:

Then, to test whether the error has been resolved, run this command to manually create the replication slot in the source PostgreSQL database:

If the command still can’t create the slot, then you might need to work with a PostgreSQL DBA to identify the bottleneck and configure your database. If the command is successful, delete the slot that you just created as a test:

Источник

Postgresql error: отмена заявления из-за запроса пользователя

Что вызывает эту ошибку в postgresql?

Мои версии программного обеспечения:

PostgreSQL 9.1.6 on x86_64-redhat-linux-gnu, compiled by gcc (GCC) 4.7.2 20120921 (Red Hat 4.7.2-2), 64-bit».

Мой драйвер postgresql: postgresql-9.2-1000.jdbc4.jar

Использование версии java: Java 1.7

Clue: моя база данных postgresql находится на твердотельном жестком диске, и эта ошибка происходит случайно, а иногда и вовсе.

ОТВЕТЫ

Ответ 1

Мы выяснили причину этой проблемы. Это объясняется ошибкой реализации setQueryTimeout() в последних драйверах JDBC 9.2-100x. Это может не произойти, если вы открываете/закрываете соединение вручную, но очень часто происходит с пулом соединений на месте, а autocommit — false. В этом случае setQueryTimeout() следует вызывать с ненулевым значением (например, используя аннотацию Spring framework @Transactional (timeout = xxx)).

Оказывается, всякий раз, когда исключение SQL возникает во время выполнения инструкции, таймер отмены не отменяется и остается в живых (как он реализован). Из-за объединения, соединение позади не закрыто, но возвращается в пул. Позже, когда таймер отмены срабатывает, он случайным образом отменяет запрос, связанный в настоящее время с соединением, с которым был создан этот таймер. В настоящий момент это совершенно другой запрос, который объясняет эффект случайности.

Предлагаемое обходное решение — отказаться от setQueryTimeout() и вместо этого использовать конфигурацию PostgreSQL (statement_timeout). Он не обеспечивает такой же уровень гибкости, но, по крайней мере, всегда работает.

Ответ 2

Если вы получаете эту ошибку без использования транзакций

Пользователь попросил отменить выражение. Заявление делает именно то, что ему говорят. Вопрос в том, кто просил это выражение быть отменено?

Посмотрите на каждую строку вашего кода, которая подготавливает SQL для выполнения. У вас может быть какой-то метод, применимый к утверждению, которое отменяет утверждение при некоторых обстоятельствах, например:

В моем случае, что случилось, я установил тайм-аут запроса на 25 секунд, и когда вставка заняла больше времени. Он передал исключение «отмена из-за исключения пользователя».

Если вы получаете эту ошибку при использовании транзакций:

Если вы получите это исключение, дважды проверьте весь свой код, который выполняет транзакции SQL.

Если у вас есть запрос, который находится в транзакции, и вы забываете совершить транзакцию, а затем используете это соединение, чтобы делать что-то еще, где вы работаете, как если бы вы не находились в транзакции, может быть поведение undefined, которое производит это исключение.

Убедитесь, что весь код, выполняющий транзакцию, очищается после себя. Убедитесь, что транзакция начинается, выполняются работы, выполняется больше работы, а транзакция откатывается или фиксируется, а затем убедитесь, что соединение осталось в состоянии autocommit=true .

Если это ваша проблема, тогда исключение не бросается туда, где вы забыли очистить себя, это происходит где-то долго после того, как вы не смогли очистить после транзакции, сделав это неуловимым исключением для отслеживания. Обновление соединения (закрытие и получение нового) очистит его.

Ответ 3

Это предполагает, что ошибка ошибки гонки в jarb jar файле для postgresql отвечает за указанную выше ошибку. (состояние гонки описано здесь: http://postgresql.1045698.n5.nabble.com/ERROR-canceling-query-due-to-user-request-td2077761.html)

Обходной путь 1, периодически обновлять соединение с базой данных

Один из способов — закрыть соединение с базой данных и периодически создавать новое подключение к базе данных. После того, как каждые несколько тысяч операторов sql просто закрывают соединение и воссоздают его. Затем по какой-то причине эта ошибка больше не выбрасывается.

Обходной путь 2, включите ведение журнала

Если вы включаете ведение журнала на уровне драйвера JDBC при настройке драйвера, то в некоторых ситуациях проблема состояния гонки нейтрализуется:

Обходной путь 3, поймать исключение и повторно инициализировать соединение

Вы также можете попробовать поймать конкретное исключение, повторно инициализировать соединение и повторить попытку запроса.

Обходной путь 4, дождитесь появления jQuery jgbc jgbc с исправлением ошибки

Я думаю, что проблема может быть связана со скоростью моего SSD-накопителя. Если вы получите эту ошибку, сообщите, как ее последовательно воспроизводить здесь, есть разработчики, очень заинтересованные в раздавливании этой ошибки.

Ответ 4

В дополнение к предложениям Эрика вы можете видеть, что оператор отменяет, когда:

• Администратор или другое соединение, зарегистрированное как один и тот же пользователь, использует pg_cancel_backend , чтобы попросить ваш сеанс отменить его текущий оператор
• Администратор отправляет сигнал на бэкэнд PostgreSQL, который запускает ваш оператор
• Администратор запрашивает fast выключение или перезапуск сервера PostgreSQL

Проверьте задания cron или инструменты управления загрузкой, которые могут отменить длительные запросы.

Источник

AWS support for Internet Explorer ends on 07/31/2022. Supported browsers are Chrome, Firefox, Edge, and Safari.
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NpgsqlException 57014: canceling statement due to user request #3052

Comments

jack0718 commented Jul 3, 2020 •

Hi, i use version(4.1.4) from GitHUb> Fix4.1.4 branch,
I get this Exception, after execution application that call single select query.
that this occurs only when the I was open connection to excute SQL Command

SQL Command：Select payment.payment_id,payment.customer_id,payment.staff_idFrom public.payment

Further technical details

Npgsql version:4.1.4.0
PostgreSQL version:PostgreSQL 11.3 (Debian 11.3-1.pgdg90+1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 6.3.0-18+deb9u1) 6.3.0 20170516, 64-bit
Operating system: Windows 10 Enterprise

The text was updated successfully, but these errors were encountered:

roji commented Jul 5, 2020

The exception indicates that someone is cancelling your query (e.g. by calling NpgsqlCommand.Cance or triggering a cancellation token), but it’s not possible to know who that is only from the exception trace posted above. Any chance you can post a minimal code sample that shows the error? Also, are you using any additional layers on top of Npgsql (e.g. Dapper)?

YohDeadfall commented Jul 5, 2020

It’s possible that the command was cancelled even by a different instance of the application if pgbouncer is used with enabled pooling. Why so? To cancel a command you need the second connection because of the nature of PostgreSQL, and the connection Id is required too. The driver remembers the received id, but it’s a physical id which doesn’t correspond to the current connection from bouncer.

jemiller0 commented Dec 1, 2020

There is something to watch out for regarding this error. I’ve seen the error when using Dapper and iterating over a result set using a foreach. The results are being read a row at a time (not read into an array/list and then iterated over). The exception below results in an NpgsqlException (the one you list above) in my global exception handler that is outside the foreach loop. To see the actual exception, I found that I have to put a try/catch block within the foreach loop itself. So, I think the exception can still appear even if the connection wasn’t cancelled on the back end. Though I think I am actually running into that problem also (intermittent dropped connections when querying a PostgreSQL instance in Amazon’s cloud). I just tested it by intentionally throwing an exception in the body of the foreach to see what kind of exception is throw to the global exception handler I have in my Main() method.

jemiller0 commented Dec 1, 2020

I think the behavior that I’m seeing may actually be a bug. Here’s my stack trace. The problem is that Dispose() is throwing an exception. The rules for Dispose() say that it should never throw an exception if I remember correctly.

roji commented Dec 2, 2020

@jemiller0 which version of Npgsql are you using? #2372 should have taken care of this for 5.0.0. Regardless, can you please open a separate issue if there’s a problem?

jemiller0 commented Dec 2, 2020

Thanks @roji. I’m using .NET Framework. It looked like 5.0.0 required .NET 5. So, I’m currently using 4.1.6.

YohDeadfall commented Dec 2, 2020

Don’t be cheated by the version number. It’s accidentally aligned with .NET 5 because Microsoft skipped version for due to .NET Framework. The provider is available for .NET Standard 2 and above.

jemiller0 commented Dec 2, 2020

Thanks @YohDeadfall. I can confirm that 5.0.0 does indeed appear to fix the problem. I like the new behavior much better. The old behavior was very confusing.

Источник

Npgsql.NpgsqlException canceling statement due to user request Error «57014» #615

Comments

elcooleperco commented May 22, 2015

Hi, i use stable version(2.2.5) from Nuget
I get this Exception, after execution application that call several select,insert and update query.
The oddity is that this occurs only when the application is run on the same computer where the database instance. I was test it under windows and linux using 9.4 version postgres.
If i divide application and database, application can work more than week, and now problem.
This is console Application its use one connection and use it in loop.

This is stack trace

Unhandled Exception:
Npgsql.NpgsqlException:
canceling statement due to user request
Severity: ERROR
Code: 57014
at Npgsql.NpgsqlState+d__0.MoveNext () [0x00000] in unknown>:0
at Npgsql.ForwardsOnlyDataReader.GetNextResponseObject (Boolean cleanup) [0x00000] in :0
[ERROR] FATAL UNHANDLED EXCEPTION: Npgsql.NpgsqlException:
canceling statement due to user request
Severity: ERROR
Code: 57014
at Npgsql.NpgsqlState+d__0.MoveNext () [0x00000] in :0
at Npgsql.ForwardsOnlyDataReader.GetNextResponseObject (Boolean cleanup) [0x00000] in :0

This is postgres log its work fine less one minute, than million row like this

2015-05-22 23:48:09 MSK [9764-1] dbadmin@z ERROR: canceling statement due to user request
2015-05-22 23:48:09 MSK [9764-2] dbadmin@z STATEMENT: Select 1 from ProcessedFiles where MD5=((‘c41c119716eb47f78dba267bda26c42e’)::text) AND ShortName=((‘contractProcedure_0123300007914000016_
51526115.xml’)::text) AND (Processed=TRUE OR Ignore=TRUE) LIMIT 1;
2015-05-22 23:49:08 MSK [9789-1] dbadmin@z ERROR: canceling statement due to user request
2015-05-22 23:49:08 MSK [9789-2] dbadmin@z STATEMENT: Select 1 from ProcessedFiles where MD5=((’38a42f4b89258ef0de19c601e93fd743′)::text) AND ShortName=((‘contractProcedure_0323300042614000002_
51526178.xml’)::text) AND (Processed=TRUE OR Ignore=TRUE) LIMIT 1;
2015-05-23 00:02:42 MSK [9920-1] dbadmin@z ERROR: canceling statement due to user request
2015-05-23 00:02:42 MSK [9920-2] dbadmin@z STATEMENT: SET statement_timeout = 20000
2015-05-23 00:03:01 MSK [9980-1] dbadmin@z ERROR: canceling statement due to user request

The text was updated successfully, but these errors were encountered:

Источник

How do I troubleshoot an AWS DMS task that is failing with error message «ERROR: canceling statement due to statement timeout»?

Last updated: 2022-10-12

I’m migrating data to or from my on-premises PostgreSQL database using AWS Database Migration Service (AWS DMS). The AWS DMS task runs normally for a while, and then the task fails with an error. How do I troubleshoot and resolve these errors?

Short description

If the PostgreSQL database is the source of your migration task, then AWS DMS gets data from the table during the full load phase. Then, AWS DMS reads from the write-ahead logs (WALs) that are kept by the replication slot during the change data capture (CDC) phase.

If the PostgreSQL database is the target, then AWS DMS gets the data from the source and creates CSV files in the replication instance. Then, AWS DMS runs a COPY command to insert those records into the target during the full load phase.

But, during the CDC phase, AWS DMS runs the exact DML statements from the source WAL logs in transactional apply mode. For batch apply mode, AWS DMS also creates CSV files during the CDC phase. Then, it runs a COPY command to insert the net changes to the target.

When AWS DMS tries to either get data from source or put data in the target, it uses the default timeout setting of 60 seconds. If the source or target is heavily loaded or there are locks in the tables, then AWS DMS can’t finish running those commands within 60 seconds. So, the task fails with an error that says «canceling statement due to statement timeout,» and you see one of these entries in the log:

«]E: RetCode: SQL_ERROR SqlState: 57014 NativeError: 1 Message: ERROR: canceling statement due to statement timeout; Error while executing the query [1022502] (ar_odbc_stmt.c:2738)»

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392))»

To troubleshoot and resolve these errors, follow these steps:

• Identify the cause of long run times for commands.
• Increase the timeout value and check the slot creation timeout value.
• Troubleshoot slot creation issues.

Resolution

Identify the cause of long run times for commands

To find the command that failed to run during the timeout period, review the AWS DMS task log and the table statistics section of the task. You can also find this information in the PostgreSQL error log file if the parameter log_min_error_statement is set to ERROR or a lower severity. After identifying the command that failed, you can find the failed table names. See this example error message from the PostgreSQL error log:

To find locks on the associated tables, run this command in the source or target (depending where the error is appearing):

If you find any PIDs that are blocked, stop or terminate the blocked PID by running this command:

Because dead rows, or «tuples,» can increase SELECT time, check for large numbers of dead rows in the source tables by running this command:

Check to see if the failed target table has primary keys or unique indexes. If the table has no primary keys or unique indexes, then a full table scan is performed during the running of any UPDATE statement. This table scan can take a long time.

Increase the timeout value

AWS DMS uses the executeTimeout extra connection attribute in both the source and target endpoints. The default value for executeTimeout is 60 seconds, so AWS DMS times out if a query takes longer than 60 seconds to run.

If the error appears in Source_Unload or Source_Capture, then set the timeout value for executeTimeout in the source. If the error appears in Target_Load or Target_Apply, set the timeout value for executeTimeout in the target. Increase the timeout value setting by following these steps:

2. Choose Endpoints from the navigation pane.

3. Choose the PostgreSQL endpoint.

4. Choose Actions, and select Modify.

5. Expand the Endpoint-specific settings section.

6. In the field for Extra connection attributes, enter this value:

8. From the Endpoints pane, choose the name of your PostgreSQL endpoint.

9. From the Connections section, the Status of the endpoint changes from Testing to Successful.

You can increase (in milliseconds) the statement_timeout parameter in the PostgreSQL DB instance. The default value is , which turns off timeouts for any query. You can also increase the lock_timeout parameter. The default value is , which turns off timeouts for locks.

Troubleshoot slot creation issues

If the timeout occurred when you created the replication slot in the PostgreSQL database, then you see log entries similar to the following:

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392)»

You can increase this timeout by configuring the TransactionConsistencyTimeout parameter in the Task settings section. The default value is 600 seconds.

PostgreSQL can’t create the replication slot if there are any active locks in the database user tables. Check for locks by running this command:

Then, to test whether the error has been resolved, run this command to manually create the replication slot in the source PostgreSQL database:

If the command still can’t create the slot, then you might need to work with a PostgreSQL DBA to identify the bottleneck and configure your database. If the command is successful, delete the slot that you just created as a test:

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«SQLSTATE: 57014, SQLCODE: -952» error when you use the BizTalk Adapter for DB2 in a Host Integration Server 2010 environment

Symptoms

When you use the Microsoft BizTalk Adapter for DB2 to issue queries against an IBM DB2 database, queries that take longer than 30 seconds to return any data may fail. Additionally, you receive an error message that resembles the following:

Processing was cancelled due to an interrupt. SQLSTATE: 57014, SQLCODE: -952

Cause

This problem occurs because the CommandTimeout property in the DB2 Transport properties is hard-coded to a time-out value of 30 seconds. Other time-out values that you may set do not override the hard-coded value.

Resolution

Cumulative update information

The fix that resolves this problem is included in cumulative update package 7 for Host Integration Server 2010. For more information about how to obtain the cumulative update package, see Cumulative update package 7 for Host Integration Server 2010.

Status

Microsoft has confirmed that this is a problem in the Microsoft products that are listed in the «Applies to» section.

More Information

This update adds support for a configurable CommandTimeout property for the BizTalk Adapter for DB2.

The third-party products that this article discusses are manufactured by companies that are independent of Microsoft. Microsoft makes no warranty, implied or otherwise, about the performance or reliability of these products.

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Vlad Mihalcea

Posted on July 10, 2019 by vladmihalcea

Query timeout with JPA and Hibernate

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Introduction

In this article, we are going to see what is the best way to set up the query timeout interval with JPA and Hibernate.

Setting the query timeout allows you to cancel slow-running queries that would, otherwise, put pressure on database resources.

The “javax.persistence.query.timeout” JPA query hint

As I explained in this article, the Java Persistence API defines the notion of query hint, which unlike what its name might suggest, it has nothing to do with database query hints. The JPA query hint is a Java Persistence provider customization option.

JPA provides support for setting a timeout interval on a given entity or SQL query via the javax.persistence.query.timeout query hint:

The timeout value is defined in milliseconds, so the JPQL query above will time out after 50 milliseconds unless the result set is being fetched prior to the timeout threshold.

The “org.hibernate.timeout” Hibernate query hint

Hibernate also provides the org.hibernate.timeout query hint, which unlike its JPA counterpart, takes the timeout interval in seconds:

The Hibernate Query timeout property

If you unwrap the JPA javax.persistence.Query to the Hibernate-specific org.hibernate.query.Query interface that extends the JPA query specification, you can get access to the Hibernate query extension methods which allow you to set a SQL-level comment, hint or provide a timeout threshold.

Just like it was the case with the org.hibernate.timeout query hint, the setTimeout method takes the timeout interval in seconds, so the JPQL query above will time out after one second unless the query finishes faster.

Testing time

To see how the query timeout works, consider the following example:

When running the PostgreSQL query above, the database is going to throw a query_canceled exception:

Auto-applying the timeout interval to Hibernate queries

If you want to apply the query timeout automatically to all Hibernate queries, then you should pass the JPA javax.persistence.query.timeout query hint as a property:

And, then you execute the following JPQL query:

Then Hibernate is going to throw the query timeout exception even if we didn’t explicitly specify the timeout interval on the JPQL query:

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Conclusion

Setting the query timeout interval is very useful, as otherwise, slow running queries will keep the database connection acquired over long period of times, therefore, putting pressure on concurrency and scalability.

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How do I troubleshoot an AWS DMS task that is failing with error message «ERROR: canceling statement due to statement timeout»?

Last updated: 2022-10-12

I’m migrating data to or from my on-premises PostgreSQL database using AWS Database Migration Service (AWS DMS). The AWS DMS task runs normally for a while, and then the task fails with an error. How do I troubleshoot and resolve these errors?

Short description

If the PostgreSQL database is the source of your migration task, then AWS DMS gets data from the table during the full load phase. Then, AWS DMS reads from the write-ahead logs (WALs) that are kept by the replication slot during the change data capture (CDC) phase.

If the PostgreSQL database is the target, then AWS DMS gets the data from the source and creates CSV files in the replication instance. Then, AWS DMS runs a COPY command to insert those records into the target during the full load phase.

But, during the CDC phase, AWS DMS runs the exact DML statements from the source WAL logs in transactional apply mode. For batch apply mode, AWS DMS also creates CSV files during the CDC phase. Then, it runs a COPY command to insert the net changes to the target.

When AWS DMS tries to either get data from source or put data in the target, it uses the default timeout setting of 60 seconds. If the source or target is heavily loaded or there are locks in the tables, then AWS DMS can’t finish running those commands within 60 seconds. So, the task fails with an error that says «canceling statement due to statement timeout,» and you see one of these entries in the log:

«]E: RetCode: SQL_ERROR SqlState: 57014 NativeError: 1 Message: ERROR: canceling statement due to statement timeout; Error while executing the query [1022502] (ar_odbc_stmt.c:2738)»

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392))»

To troubleshoot and resolve these errors, follow these steps:

• Identify the cause of long run times for commands.
• Increase the timeout value and check the slot creation timeout value.
• Troubleshoot slot creation issues.

Resolution

Identify the cause of long run times for commands

To find the command that failed to run during the timeout period, review the AWS DMS task log and the table statistics section of the task. You can also find this information in the PostgreSQL error log file if the parameter log_min_error_statement is set to ERROR or a lower severity. After identifying the command that failed, you can find the failed table names. See this example error message from the PostgreSQL error log:

To find locks on the associated tables, run this command in the source or target (depending where the error is appearing):

If you find any PIDs that are blocked, stop or terminate the blocked PID by running this command:

Because dead rows, or «tuples,» can increase SELECT time, check for large numbers of dead rows in the source tables by running this command:

Check to see if the failed target table has primary keys or unique indexes. If the table has no primary keys or unique indexes, then a full table scan is performed during the running of any UPDATE statement. This table scan can take a long time.

Increase the timeout value

AWS DMS uses the executeTimeout extra connection attribute in both the source and target endpoints. The default value for executeTimeout is 60 seconds, so AWS DMS times out if a query takes longer than 60 seconds to run.

If the error appears in Source_Unload or Source_Capture, then set the timeout value for executeTimeout in the source. If the error appears in Target_Load or Target_Apply, set the timeout value for executeTimeout in the target. Increase the timeout value setting by following these steps:

2. Choose Endpoints from the navigation pane.

3. Choose the PostgreSQL endpoint.

4. Choose Actions, and select Modify.

5. Expand the Endpoint-specific settings section.

6. In the field for Extra connection attributes, enter this value:

8. From the Endpoints pane, choose the name of your PostgreSQL endpoint.

9. From the Connections section, the Status of the endpoint changes from Testing to Successful.

You can increase (in milliseconds) the statement_timeout parameter in the PostgreSQL DB instance. The default value is , which turns off timeouts for any query. You can also increase the lock_timeout parameter. The default value is , which turns off timeouts for locks.

Troubleshoot slot creation issues

If the timeout occurred when you created the replication slot in the PostgreSQL database, then you see log entries similar to the following:

«]E: test_decoding_create_replication_slot(. ) — Unable to create slot ‘lrcyli7hfxcwkair_00016402_8917165c_29f0_4070_97dd_26e78336e01b’ (on execute(. ) phase) [1022506] (postgres_test_decoding.c:392)»

You can increase this timeout by configuring the TransactionConsistencyTimeout parameter in the Task settings section. The default value is 600 seconds.

PostgreSQL can’t create the replication slot if there are any active locks in the database user tables. Check for locks by running this command:

Then, to test whether the error has been resolved, run this command to manually create the replication slot in the source PostgreSQL database:

If the command still can’t create the slot, then you might need to work with a PostgreSQL DBA to identify the bottleneck and configure your database. If the command is successful, delete the slot that you just created as a test:

Источник

AWS DMS ERROR: Cancelling statement due to statement timeout

by Nicky Mathew | Aug 3, 2021

AWS DMS ERROR: Cancelling statement due to statement timeout occurs when we migrate data to or from the on-premises PostgreSQL database using AWS DMS.

Here, at Bobcares, we assist our customers with several AWS queries as part of our AWS Support Services.

Today, let us see how to troubleshoot and resolve these errors.

AWS DMS ERROR: Cancelling statement due to statement timeout

AWS DMS uses the default timeout setting of 60 seconds while executing commands to either get data from the source or put data in the target.

Suppose, the source or target is heavily loaded or there are locks in the tables. Then it can’t finish executing within 60 seconds.

As a result, the task fails with an error and we see the following entry in the log:

How to Troubleshoot and Resolve?

To troubleshoot and resolve this, our Support Techs recommend the steps below.

Identify the cause of long execution times for commands

Initially, we review the AWS DMS task log and the table statistics section of the task to find the command that failed.

In addition, we can find it in the PostgreSQL error log file if the parameter log_min_error_statement is set to ERROR or a lower severity.

Once we identify the command, we can find the failed table names.

For instance, the below is an example error message from the PostgreSQL error log:

Then, to find locks on the associated tables, we run the following command in the source or target:

Suppose we found PIDs that are blocked. Then we need to stop or “kill” it using:

Since the dead rows or “tuples” can increase SELECT time, we check for large numbers of dead rows in the source tables:

Later we check to see whether or not the failed target table has primary keys or unique indexes.

Increase the timeout value

As we know, the default value for executeTimeout is 60 seconds. Let us now see how our Support Techs increase this value.

1. Initially, we open the AWS DMS console.
2. Then from the navigation pane, we select Endpoints > PostgreSQL endpoint > Actions > Modify.
3. We expand the Endpoint-specific settings section.
4. In the field for Extra connection attributes, we enter:
5. Then we select, Save.
6. From the Endpoints pane, we select the name of the PostgreSQL endpoint.
7. From the Connections section, the Status of the endpoint will change from Testing to Successful.

Troubleshoot slot creation issues

Suppose the timeout occurs when we create the replication slot in the PostgreSQL database. Then we will see log entries similar to the following:

To resolve this issue, we use version 3.1.4 for which the default timeout for this command is 600 seconds.

We can also increase this timeout. To do so, we need to configure the TransactionConsistencyTimeout parameter in the Task settings section.

If there are any active locks in the database user tables, PostgreSQL can’t create the replication slot.

To check for locks, we run:

Then, we test whether the error has been resolved.

To do so, we run the following command to manually create the replication slot in the source PostgreSQL database:

If the command is successful, we delete the test slot:

Finally, we restart the migration task.

If the command still fails, then we need to work with a PostgreSQL DBA to identify and configure the database.

[Need help with the AWS DMS ERROR? We’d be happy to assist]

Conclusion

In short, we saw how our Support Techs fix this error for our customers.

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SQL HowTo: наперегонки со временем



В PostgreSQL несложно написать запрос, который уйдет в глубокую рекурсию или просто будет выполняться гораздо дольше, чем нам хотелось бы. Как от этого защититься?

А чтобы еще и полезную работу сделать? Например, набрать следующий сегмент данных при постраничной навигации со сложным условием фильтрации.

statement_timeout

Очевидное решение — использовать те средства, которые нам дает для этого сама база: установить устраивающее нас значение параметра statement_timeout:

Задаёт максимальную длительность выполнения оператора, при превышении которой оператор прерывается.

Ну-ка, ну-ка. Возьмем тестовый запрос, который ждет 20 раз по 100ms и попробуем остановить его через секунду:

Таки да, «в бесконечность» наш запрос не ушел, но и полезного мы ничего не получили — то есть попросту нагрузили базу бесполезной работой.

Неужели нет способа заставить запрос успеть вернуть хоть что-то за отмеренное ему время?



clock_timestamp

Оказывается, есть, если использовать одну из не очень известных функций работы с датой/временем — clock_timestamp:

Источник

PostgreSQL: ERROR – canceling statement due to statement timeout

This article is half-done without your Comment! *** Please share your thoughts via Comment ***

PostgreSQL Error like “canceling statement due to statement timeout” – I love this error message because the developer should know the tentative require total execution time of their queries or functions.

In a real-time application, we must analyze the average execution time for our queries so that System Admin or Database Admin can allocate resource workload appropriately.

I completely disagree with Developers for arguments like why we need to inform tentative execution time of our query?.

Because for example, today you execute your query and it took two mins so tomorrow, it might complete in around two mins only.

For this query, we can set timeout up to 5 mins, but if it is taking more than 5 mins, then the developer should check for that query.

So error like “canceling statement due to statement timeout” which helps a lot to identify this kind of long running query.

If your query starts to take more time, there are mainly two reasons:
1. Query is same, but the number of records increases in table
2. DBA forget to execute VACUUM ANALYZE or ANALYZE

So here my suggestion is, DBA can set a timeout value for mission critical query or we can also set threshold value so that we can check the status of a query before killing it.

Источник

Ошибка canceling statement due to statement timeout

Использую PGSQL. Есть таблица записей

1000 000 записей

При авторизации пользователя в аккаунт идет пересчет поля salary в целом по аккаунту для всех пользователей

Плохо разбираюсь в тебе блокировок в PGSQL, просьба подсказать как исправить ситуацию с точки зрения блокировок, в какую сторону смотреть?

Перемещено hobbit из general



Тебе дали изолированные транзакции. Нет не хочу, хочу жрать блокировки.



Зачем вообще нужно statement_timeout = ‘5000ms’ ? Оно даже на одинаковых объёмах данных в 100% случаев гарантированно не отрабоает.



Смысл такой, что если уже есть блокировка, то ждем 5 сек., если не дождались, то падаем с ошибкой



У нас кремниевой долине, для синхронизации данных в двух базах Кулибины родили следующий алгоритм: (1) сначала проверяется номер ревизии двух баз, если на приёмнике устаревшая ревизия, (2) начинается обновление до актуальной на основе базы-источника, (3) в конце сравниваются данные на идентичность.

Редко, но бывает случаются сбои в матрице, когда источник изменился на момент выполнения шага (2). Тогда происходит откат изменений и процесс просто запускается повторно. Задача с тем, что в ОП не один в один, но краеугольный камень в виде возможности словить обновление во время уже запущенного обновления присутствует.

Не фонтан, но возня с блокировками на мой, не обременённый большим опытом работы с БД взгляд, выглядит менее предсказуемо. Гарантий, что апдейт в принципе выполнится за n секунд нет.

Испытываю скудность в ассортименте предложений, кроме банального увеличения таймаута, ну и посмотреть план запроса на возможность оптимизации — как ещё извернуться в данной ситуации самому было бы интересно узнать.



общий запрос обновления по аккаунту (большой аккаунт) выполняется долго > 5 секунд

При авторизации пользователя в аккаунт идет пересчет поля salary в целом по аккаунту для всех пользователей

Не понял, ты что, всем пользователям проставляешь одинаковое значение salary?

Источник

Troubleshooting