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How to handle object version mismatches?
Sometimes my transaction fails because the object version changed. How do I avoid or handle this issue reliably?
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When your transaction fails due to an object version mismatch, it means the object you're interacting with has already been updated by another transaction before yours was processed. To handle this, you need to make sure you're always using the latest object version. You can do this by fetching fresh object data right before building and signing your transaction. This keeps your inputs in sync with the chain. If you're batching or queueing transactions, always re-check the object state just before signing to avoid stale versions. In most cases, using the latest object reference from `getObject` or your app state will help prevent this issue.
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2When your transaction fails due to an object version mismatch, it means the object you're interacting with has already been updated by another transaction before yours was processed. To handle this, you need to make sure you're always using the latest object version. You can do this by fetching fresh object data right before building and signing your transaction. This keeps your inputs in sync with the chain. If you're batching or queueing transactions, always re-check the object state just before signing to avoid stale versions. In most cases, using the latest object reference from getObject
or your app state will help prevent this issue.
When you try to update or delete an object in a system that uses versioning (like many databases or APIs), the action can fail if the object's version has changed since you last accessed it. This usually happens when another process modifies the object before your update goes through. To handle this, you should always fetch the latest version of the object just before you make any changes. If you're working in a system that supports optimistic locking, make sure your update includes the current version number, and if it fails due to a version mismatch, catch the error and retry the operation after refreshing the data. This way, you avoid overwriting newer changes made by others and reduce the chances of transaction failure due to outdated information. You can also design your system to queue changes or use merge strategies when real-time updates aren't feasible.
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