Table Reader timed out

Hello everyone,
We have a workflow which reads from a db, writes to tables on the server, and runs two parallel processes to read the tables and extract different data from them. The table reader nodes run at approximately the same time. We’ve found that about once a week one of the table reader nodes times out. It happens seemingly randomly, within one or the other of the two parallel processes, and usually on the same table reader node (which reads the largest table, about 433 MB).

The message provided is:
Table Reader 0:995:0:938
Read timed out

We’ve looked through the logs and cannot seem to identify a specific reason why this is happening. Just that it happens on the same workflow about once a week. I’m wondering if the ‘Connection timeout’ in the node configuration may play a role, or if we need to serialize the two processes instead of running them in parallel. I’ve run a basic test by creating two table reader nodes in a generic workflow and have them read the same table, starting each at various intervals apart to see if I could create a conflict, but the only result seems to be the second node takes a few seconds longer to complete than the first.

Any help would be appreciated.


Hello Eric,

As it is stated in the node description the mentioned Connect timeout could be triggered by parallel execution of bigger tables:
Connect timeout (ms)
Timeout in milliseconds for connecting and reading remote resources (in case of reading from a remote location).

The easiest way to elaborate if the issue is caused by a parallel execution of the two nodes would be to set a dependency between the two. Just connect the variable ports of the two Table Reader nodes (one on the right upper corner as the first to execute, the other one on the left upper corner as the dependent one).


Please check out if this helps you. The other possible way would be to raise the timeout.


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Thank you Michael. I’ve passed your suggestion on to the workflow developer who will be testing soon. I will respond with the result. It might take a while to determine if the issue is resolved since it seems to be an intermittent issue.


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