To get started, refer to this source code for the models that we’ll be using.
To use these classes to store data, we will first have to create a user.
Then, when a user creates a message, we will append that message to one
or more timelines. If it’s a private message, we’ll append it to the
Inbox timeline and the User’s own
Sent timeline. If it’s
a group message, we’ll append it to the Group’s timeline, as well as to
Buckets and Keys Revisited
Now that we’ve worked out how we will differentiate data in the system, let’s figure out our bucket and key names.
The bucket names are straightforward. We can use
Timelines. The key names, however, are a little more tricky. In past
examples we’ve used sequential integers, but this presents a problem: we
would need a secondary service to hand out these IDs. This service could
easily be a future bottleneck in the system, so let’s use a natural key.
Natural keys are a great fit for key/value systems because both humans
and computers can easily construct them when needed, and most of the
time they can be made unique enough for a KV store.
|Bucket||Key Pattern||Example Key|
Users bucket, we can be certain that we will want each
username to be unique, so let’s use the
username as the key.
Msgs bucket, let’s use a combination of the username and the
posting UTC datetime in an ISO 8601
format. This combination gives us the pattern
which produces keys like
Timelines, we need to differentiate between
timelines, so we can simply add that type into the key name. We will
also want to partition each collection object into some time period,
that way the object doesn’t grow too large (see note below).
Timelines, let’s use the pattern
<groupname>_Inbox_<date> for groups, which will look like
Keeping our story straight with repositories
Now that we’ve figured out our object model, please refer to this source code for the repositories that we’ll be using.
This console application exercises the code that we’ve written.
The repository pattern and
TimelineManager help with a few things:
- It helps us to see if an object exists before creating a new one
- It keeps our buckets and key names consistent
- It provides us with a consistent interface to work with.
While this set of repositories solves many of our problems, it is very minimal and doesn’t cover all the edge cases. For instance, what happens if two different people try to create a user with the same username?
We can also easily “compute” key names now, but how do we quickly look up the last 10 messages a user sent? Many of these answers will be application dependent. If your application shows the last 10 messages in reverse order, for example, you may want to store that set of data in another collection object to make lookup faster. There are drawbacks to every solution, but we recommend seeking out the key/value-based solution first, as it will likely be the quickest.
So to recap, in this chapter we learned:
- How to choose bucket names
- How to choose natural keys based on how we want to partition our data