Error: snappy: corrupt input (unsupported chunk length: 0) #2325
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Hello, We recently migrated our SEQ logs from a Windows Server to Linux (ubuntu 22.04) Docker container in Azure. {"@t":"2024-11-25T23:51:05.3159073Z","@sp":"8505a9f7897d7c4d","@tr":"8b6237624825ea9f082059edcc8667cc","@mt":"Indexing with {Allocated:0.000} ms allowance","@r":["600000.000"],"@l":"Error","@x":"Flare.Ffi.Result.FlareException: Flare native storage failed (IOError), the task encountered an error in a worker.\n caused by: error evaluating the next record to index\n caused by: snappy: error snappy reading frame header\n caused by: snappy: corrupt input (unsupported chunk length: 0)\n at Seq.Engine.Storage.StorageEngine.QueryInternal(Cursor cursor, NativeCancellationToken nativeCancel, Object[] sharedColumnBuffer, CancellationToken cancel)+MoveNext()\n at Seq.Engine.Events.EventStore.QueryInternal(IEnumerable We tried the Any ideas? Kind regards, |
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Replies: 3 comments 11 replies
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Hi Ibrahim, thanks for your message. If the new install is hosted in an Azure Web App, or using the non-premium Azure Files backing storage, this issue will likely continue to appear; let me know if that's the case. Because this error is in the stored event data, rather than metadata, you'll need to drop the I'm not 100% certain the repair process will cover this case, but if it produces output that should at least identify the problem chunk, and at that point we should be able to provide further steps to sort it out. |
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Hi Nicholas, Thank you for the answer. The new install is on a Linux (ubuntu 22.04) VM with Premium SSD v2 LRS disks attached. Here are the results of the commands:
It seems like flaretl repair didn't find anything. |
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Yeah, not sure how the corruption happened but it probably has to do with our log file migration. Thanks for the improvement and support |
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Hi @ibrahimnamdar;
Moving it to an offline location would be safer than deleting, but yes 👍 - here's the process:
.span
file to a separate storage locationshell
argument*, runflaretl repair --metadata /data/Stream/stream.flare
(* not sure you'll have encountered this, but it would look something like
docker run --rm -it -v (host data path):/data datalust/seq shell
)