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Noil
Noil
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It turned out that the problem with the RAM was due to an abnormal use of the RAM allocated to PAMGuard. When I used a backup version of the database, the problem disappeared. Hence, I discovered that it was a problem with the dataset, that was corrupted for whatever reason. As corrupting a dataset with PAMGuard can be quite easily, if someone sees an abnormal drainage in the memory, try to use an older version of the dataset. It's probably the reason. Even with large dataset, the memory used it'smemory should never belowbe above around 1000 MB.

It turned out that the problem with the RAM was due to an abnormal use of the RAM allocated to PAMGuard. When I used a backup version of the database, the problem disappeared. Hence, I discovered that it was a problem with the dataset, that was corrupted for whatever reason. As corrupting a dataset with PAMGuard can be quite easily, if someone sees an abnormal drainage in the memory, try to use an older version of the dataset. It's probably the reason. Even with large dataset, the memory used it's never below around 1000 MB.

It turned out that the problem with the RAM was due to an abnormal use of the RAM allocated to PAMGuard. When I used a backup version of the database, the problem disappeared. Hence, I discovered that it was a problem with the dataset, that was corrupted for whatever reason. As corrupting a dataset with PAMGuard can be quite easily, if someone sees an abnormal drainage in the memory, try to use an older version of the dataset. It's probably the reason. Even with large dataset, the used memory should never be above around 1000 MB.

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Cristina Marcolin
Cristina Marcolin
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It turned out that the problem with the RAM was due to an abnormal use of the RAM allocated to PAMGuard. When I used a backup version of the database, the problem disappeared. Hence, I discovered that it was a problem with the dataset, that was corrupted for whatever reason. As corrupting a dataset with PAMGuard can be quite easily, if someone sees an abnormal drainage in the memory, try to use an older version of the dataset. It's probably the reason. Even with large dataset, the memory used it's never below around 1000 MB.