Simply copy from Loading data from multiple sources with RxJava
Suppose I have some Data

that I query from the network. I could simply hit the network each time I need the data, but caching the data on disk and in memory would be much more efficient.

More specifically, I want a setup that: Occasionally performs queries from the network for fresh data. Retrieves data as quickly as possible otherwise (by caching network results).

I'd like to present an implementation of this setup usingRxJava.

Basic Pattern

Given an Observable for each source (network, disk and memory), we can construct a simple solution using two operators, concat() and first() .
concat() takes multiple Observables and concatenates their sequences. first() emits only the first item from a sequence. Therefore, if you use concat().first() , it retrieves the first item emitted by multiple sources.
Let's see it in action:

// Our sources (left as an exercise for the reader)
Observable memory = ...;  
Observable disk = ...;  
Observable network = ...;

// Retrieve the first source with data
Observable source = Observable  
  .concat(memory, disk, network)
  .first();

The key to this pattern is that concat() only subscribes to each child Observable when it needs to. There's no unnecessary querying of slower sources if data is cached, sincefirst() will stop the sequence early. In other words, if memory returns a result, then we won't bother going to disk or network. Conversely, if neither memory nor disk have data, it'll make a new network request.
Note that the order of the source Observables in concat() matters, since it's checking them one-by-one.

Stale Data

Unfortunately, now our data-saving code is working a little toowell! It's always returning the same data, no matter how out-of-date it is. Remember, we'd like to go back to the server occasionally for fresh data.
The solution is in first() , which can also perform filtering. Just set it up to reject data that isn't worthy:

Observable source = Observable  
  .concat(memory, diskWithCache, networkWithSave)
  .first(data -> data.isUpToDate());

Now we'll only emit the first item that qualifies as up-to-date. Thus, if one of our sources has stale Data , we'll continue on to the next one until we find fresh Data .

first() vs. takeFirst()

As an alternative to using first() for this pattern, you could also use [ takeFirst() (http://reactivex.io/RxJava/javadoc/rx/Observable.html#takeFirst(rx.functions.Func1)).
The difference between the two calls is that first() will throw a NoSuchElementException if none of the sources emits valid data, whereas takeFirst() will simply complete without exception.
Which you use depends on whether you need to explicitly handle a lack of data or not.