Passing Complex Hashes to Sidekiq Jobs

Question

From the Best Practices Guide to using Sidekiq, I understand it's best to pass "string, integer, float, boolean, null(nil), array and hash" as arguments to the job.

I often just pass the id of a persisted object to my jobs, but due to latency constraints I need to save the object after running the job.

The non-persisted object I'm working with contains a mixture of data types:

#MyObject<00x000>{
id: nil
start_time: Fri, 11 Dec 2020 08:45:00 PST -08:00 (*this is a TimeWithZone object)
rate: 18.0 (*this is a BigDecimal object)
...
}

I plan to pass this object to my job by converting it to a hash first:

MyJob.perform_async(my_object.attributes)

and then later persist the object like so:

MyObject.new(my_object_hash).save

My question is, is this safe? Even though I am passing a 'simple' datatype to Sidekiq, it actually contains complex objects. Am I going to lose precision?

Thank you!

Answer 1

This sounds like a "potayto, potahto" solution. You are not not using the serialisation of Sidekiq, but instead serialize it yourself.

Let's have a look at why sidekiq has this rule:

Even if they did serialize correctly, what happens if your queue backs up and that quote object changes in the meantime? [...] Don't pass symbols, named parameters, keyword arguments or complex Ruby objects (like Date or Time!) as those will not survive the dump/load round trip correctly.

I like to add a third:

Serializing state makes it impossible to distinguish between persisted and ethereal (in-memory, memoized, lazy-loaded etc) data. E.g. a def sent_mails; @sent_mails ||= Mail.for(user_id: id); end now gets serialized: do you want that?

The solution is also provided by sidekiq:

Don't save state to Sidekiq, save simple identifiers. Look up the objects once you actually need them in your perform method.

The XY problem here

Your real problem is not where or how to serialize state. Because sidekiq warns against serializing state regardless of where and how you do this.

The problem you need to solve is either how to store state somewhere where it can be stored properly. Or to avoid storing the state at all: not in redis/sidekiq, nor in the storage that is giving you problems.

Latency

Is your storage slow? Is it not a validation, a serialisation, some side-effect of storage that is slow?

Can you improve this by making it a two-step: insert the state and update/enrich/validate it async later? If you are using Rails, it won't help you here, or might even work against you, but a common model is to store objects in a special "queue" table or events queue; e.g. kafka is famous for this.

When e.g. storage happens over a slow network to a slow API, this is probably unsolvable, but when storage happens in a local database, there are decades of solutions to improve write performance here that you can use. Both inside your database, or with some specialised queue for state-storage (sidekiq is not such a specialised storage queue) depending on the tech used to store. E.g. Linux will allow you to store through memory, making writes to disk really quick, but removing the guarantee that it was really written to disk.

E.g. In a bookkeeping api, we would store the validated object in PostgreSQL and then have async jobs add expensive attributes to this later (e.g. state that had to be retrieved from legacy APIs or through complex calculations).

E.g. in a write-heavy GIS system, we would store objects into a "to_process_places" table, that was monitored by tooling which processes the Places. It all really depends on your domain, and requirements.

Not using state.

A common solution is not to make objects, but use the actual payload by the customer. Just send the HTTP payload (in rails, the params) along and leave it at that. Maybe merge in a header (like the Request Date) or filter out some data (header tokens or cookies).

If your controller can operate with this data, so can a delayed job. Instead of building objects in the controller, leave that to the delayed job. This can even result in really neat and lean controllers: all they do is (some authentication and authorization and then) call the proper job and pass it a sanitized params.

Obviously this requires trade-offs like not being able to validate in-sync, but to give such info over email, push-notification, or delayed response instead, depending on your requirements (e.g. a large CSV import could just email any validation issues, but a login request might need to get immediate response if the login is invalid).

It also requires some thought: you probably don't want to send the Base64 encoded CSV along to sidekiq, but instead write the file to a (temp) storage and pass the filename/url along instead. This might sound obvious, because it is: file uploads are essentially an implementation of the earlier mentioned "temporary state storage": you don't pass the entire PDF/high-res-header-image/CSV along to sidekiq, but store it somewhere so sidekiq can pick it up later to process it. Why should the other attributes not employ the same pattern if passing them along to sidekiq is problematic?

Answer 2

The most important part from the best practices you linked is

Complex Ruby objects do not convert to JSON

Therefore you're not supposed to pass instances of a model to a worker. If you're using Sidekiq workers, you should comply with this statement and the hash you're passing should be just fine. I am not exactly sure about the TimeWithZone object, but you could try converting this to a JSON or to a string as they do in the best practices guide.

However, if you're using ActiveJob instead of Sidekiq workers (does your Job inherit from ApplicationJob or does it include Sidekiq::Worker ?), then you don't have that problem because ActiveJob uses Global ID to convert objects into a String. And then before performing the job is deserializing the object again. Meaning you can pass an object to your job.

my_object = MyObject.find(1)
my_object.to_global_id #=> #<GlobalID:0x000045432da2344 [...] gid://your_app_name/MyObject/1>>
serialized_my_object = my_object.to_global_id.to_s

my_object = GlobalID.find(serialized_my_object)

You can find more information here https://github.com/toptal/active-job-style-guide#active-record-models-as-arguments

Answer 3

After doing some experimentation on the Time objects in my job, I found that I am losing nanosecond precision at the other end of the job.

my_object.start_time
=> Mon, 21 Dec 2020 11:35:50 PST -08:00
my_object.strftime('%Y-%m-%d %H:%M:%S.%N')
=> "2020-12-21 11:35:50.151893000"

You can see here, we have precision including 6 digits after the decimal. (see this answer for more about 'strftime')

Once we call JSON methods on the object:

generated = JSON.generate(my_object.attributes))
=> \"start_time\":\"2020-12-21T11:35:50.151-08:00\"

You can see here we are down to 3 digits of precision after the decimal. The remaining 3 digits are lost at this point.

parsed = JSON.parse(generated)
parsed[‘start_time’] = "2020-12-21T11:35:50.151-08:00"

It appears at the most basic level, the JSON library recursively calls as_json on each of the key-value pairs in the hash. So really it depends on how your particular object implements as_json.

This issue caused test failures that involved querying our db for persisted objects (initialized with something like, start_time = Time.zone.now (!)) that are meant to overlap in time exactly with our MyObject class. Once the half-baked my_object blueprints made it through Sidekiq, they lost a sliver of precision, causing a slight misalignment.

One way to hack away at this issue is by monkey patching the Time class.

In our case, a better solution was to go in the opposite direction and to not use so much precision in our tests. The my_object in the example is something that a human user will have on their calendar; in production we never receive so much precision from clients. So instead we fixed our tests by instructing some of our test objects to use something like Time.zone.now.beginning_of_minute, rather than Time.zone.now. We intentionally removed precision to fix the issue, as well as more closely mirror reality.