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<@U04SE163WC8> why do some connections get stuck a...
# ask-ai
t
@kapa.ai why do some connections get stuck at times and the following lines are seen multiple times in the logs:
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2024-07-17 10:50:31 destination > INFO pool-3-thread-1 i.a.c.i.d.a.b.BufferManager(printQueueInfo):89 [ASYNC QUEUE INFO] Global: max: 307.2 MB, allocated: 10 MB (10.0 MB), %% used: 0.03255208335354433 | State Manager memory usage: Allocated: 10 MB, Used: 0 bytes, percentage Used 0.0
2024-07-17 10:50:31 destination > INFO pool-6-thread-1 i.a.c.i.d.a.FlushWorkers(printWorkerInfo):128 [ASYNC WORKER INFO] Pool queue size: 0, Active threads: 0
k
Based on the information provided in the knowledge sources, it appears that the issue of connections getting stuck and the repeated log lines you're seeing could be related to the "printQueueInfo" method in the BufferManager class and the "printWorkerInfo" method in the FlushWorkers class. These methods are part of the Airbyte's data integration engine and are responsible for managing memory allocation and worker threads during data synchronization. The log lines you're seeing are informational messages that provide insights into the memory usage and worker thread status at a given point in time. The "printQueueInfo" method logs the maximum memory available for buffer allocation, the amount of memory currently allocated, and the percentage of memory used. The "printWorkerInfo" method logs the size of the worker pool queue and the number of active threads. However, the knowledge sources do not provide specific reasons why some connections might get stuck. It could be due to various factors such as network issues, source/destination service limitations, or issues with the data being processed. For a more accurate diagnosis, it would be helpful to have more detailed logs or error messages. If the issue persists, it's recommended to raise a [Github issue](https://github.com/airbytehq/airbyte/issues) on the Airbyte repository or post a question on the [Airbyte discussion forum](https://discuss.airbyte.io/). Knowledge sources: - [Github Issue (closed): [destination-redshift] Sync stuck in "printQueueInfo" method > Original post Part 3](https://github.com/airbytehq/airbyte/issues/34620) - [Github Issue (closed): [destination-redshift] Sync stuck in "printQueueInfo" method > Original post Part 2](https://github.com/airbytehq/airbyte/issues/34620) - [Github Issue (closed): [destination-redshift] Sync stuck in "printQueueInfo" method > Original post Part 4](https://github.com/airbytehq/airbyte/issues/34620) - [Github Issue (closed): [destination-redshift] Sync stuck in "printQueueInfo" method > Original post Part 1](https://github.com/airbytehq/airbyte/issues/34620)
t
@kapa.ai this is with a postgres source and destination connector.
k
A message from kapa.ai
Based on the provided knowledge sources, there are a few known issues and limitations with the Postgres source and destination connectors that could potentially cause connections to get stuck. For the Postgres source connector: - It currently does not handle schemas larger than 4MB. - Changing a column data type or removing a column might break connections. - Adding a new table to a connection in CDC mode may become a temporary bottleneck. For the Postgres destination connector: - It relies on sending files to the database's temporary storage to then load in bulk. If your Postgres database does not have access to the 
/tmp
file system, data loading will not succeed. However, the specific log lines you're seeing are more related to the internal workings of Airbyte's data integration engine rather than specific to the Postgres connectors. They provide insights into the memory usage and worker thread status during data synchronization. If you're experiencing issues with connections getting stuck, it's recommended to check if any of the known limitations apply to your case. If the issue persists, consider raising a [Github issue](https://github.com/airbytehq/airbyte/issues) on the Airbyte repository or post a question on the [Airbyte discussion forum](https://discuss.airbyte.io/). Knowledge sources: - [Documentation > Integrations > Sources > Postgres > Troubleshooting Postgres Sources > Connector Limitations > General Limitations](https://docs.airbyte.com/integrations/sources/postgres/postgres-troubleshooting#general-limitations) - [Documentation > Integrations > Destinations > Postgres > Troubleshooting Postgres Destinations > Connector Limitations > Vendor-Specific Connector Limitations](https://docs.airbyte.com/integrations/destinations/postgres/postgres-troubleshooting#vendor-specific-connector-limitations)
t
@kapa.ai these are the exact lines in the logs before its start repeating the printQueueInfo
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2024-07-17 10:46:23 destination > INFO main i.a.i.b.d.t.DefaultTyperDeduper(prepareFinalTables):154 Preparing tables
2024-07-17 10:46:23 destination > INFO type-and-dedupe i.a.i.b.d.t.DefaultTyperDeduper(prepareTablesFuture$lambda$4):187 Final Table exists for stream table_name
k
A message from kapa.ai
The log lines you provided indicate that the destination connector is preparing the final tables for data loading. The 
DefaultTyperDeduper
class is responsible for ensuring that the final tables are ready to receive data. The line 
Final Table exists for stream table_name
means that the final table for the stream 
table_name
already exists in the destination database. If the table didn't exist, the connector would create it. The 
printQueueInfo
method, which you see repeating in the logs, is part of Airbyte's internal data buffering system. It prints information about the memory usage and the status of worker threads. This method is called periodically to provide insights into the state of the system during data synchronization. If your sync process is stuck and keeps printing 
printQueueInfo
, it might be due to some issues with the data synchronization. It could be a temporary network issue, a problem with the source or destination connector, or a bug in Airbyte. If the issue persists, consider raising a [Github issue](https://github.com/airbytehq/airbyte/issues) on the Airbyte repository or post a question on the [Airbyte discussion forum](https://discuss.airbyte.io/). Be sure to include as much information as possible, including the full logs and the versions of Airbyte and the connectors you're using.
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