Errors are inevitable. The developer’s job is to be prepared for whatever is likely to come up — and to try and be prepared for anything that conceivably could come up. Couchbase gives you a lot of flexibility, but it is recommended that you equip yourself with an understanding of the possibilities.
As covered here, the Java SDK ships with three different APIs, allowing you to structure your application the way you want.
That guide also covers how errors are actually returned (e.g. via
Mono) and handled, so this document will focus instead on specific errors, along with a broader look at error handling strategies.
The KV Service exposes several common errors that can be encountered - both during development, and to be handled by the production app. Here we will cover some of the most common errors.
If a particular key cannot be found it is raised as an
On the other hand if the key already exists and should not (e.g. on an insert) then it is raised as a
Couchbase provides optimistic concurrency using CAS.
Each document gets a CAS value on the server, which is changed on each mutation.
When you get a document you automatically receive its CAS value, and when replacing the document, if you provide that CAS the server can check that the document has not been concurrently modified by another agent in-between. If it has, it returns
CasMismatchException, and the most appropriate response is to simply retry it:
There are situations with any distributed system in which it is simply impossible to know for sure if the operation completed successfully or not.
Take this as an example: your application requests that a new document be created on Couchbase Server. This completes, but, just before the server can notify the client that it was successful, a network switch dies and the application’s connection to the server is lost. The client will timeout waiting for a response and will raise a
TimeoutException, but it’s ambiguous to the app whether the operation succeeded or not.
TimeoutException is one ambiguous error, another is
DurabilityAmbiguousException, which can returned when performing a durable operation. This similarly indicates that the operation may or may not have succeeded: though when using durability you are guaranteed that the operation will either have been applied to all replicas, or none.
Given the inevitability of ambiguity, how is the application supposed to handle this?
It really needs to be considered case-by-case, but the general strategy is to become certain if the operation succeeded or not, and to retry it if required.
For instance, for inserts, they can simply be retried to see if they fail on
DocumentExistsException, in which case the operation was successful:
Idempotent operations are those that can be applied multiple times and only have one effect. Repeatedly setting an email field is idempotent - increasing a counter by one is not.
Some operations we can view as idempotent as they will fail with no effect after the first success - such as inserts.
Idempotent operations are much easier to handle, as on ambiguous error results (
TimeoutException) the operation can simply be retried.
Most key-value operations are idempotent. For those that aren’t, such as a Sub-Document
arrayAppend call, or a counter increment, the application should, on an ambiguous result, first read the document to see if that change was applied.
Errors & Exception handling is an expansive topic. Here, we have covered examples of the kinds of exception scenarios that you are most likely to face. More fundamentally, you also need to weigh up concepts of durability.
Diagnostic methods are available to check on the health of the cluster.
Logging methods are dependent upon the platform and SDK used. We offer recommendations and practical examples.