THE SCENARIO
I have a class that makes use of a request list set by the user. The request list is stored in SharedPreferences. The dilemma I'm facing is to whether to keep an instance of the request list or to read from SharedPreferences every time the request list is needed (which is very frequent).
Also not that Gson is used to deserialize the object.
The code goes like this:
public List<PrayerTimesCalculator.Time> getDefaultRequestList() {
if (mRequestList != null) return mRequestList;
// Try getting request list from preferences;
Gson gson = new Gson();
String json = mSharedPref.getString(KEY_PREF_REQUEST_LIST, null);
Type listType = new TypeToken<List<Time>>() {
}.getType();
mRequestList = gson.fromJson(json, listType);
if (mRequestList != null) return mRequestList;
// Create default list;
mRequestList = Arrays.asList(
Time.DAWN,
Time.MORNING,
Time.AFTERNOON,
Time.EVENING,
Time.MID_NIGHT);
return mRequestList;
}
THE GOAL
My concern is that if I keep around an instance of the request list, and there are multiple instances of this class, an update to the request list in one instance of the class would not be reflected in the rest of the instances until they are recreated.
Thus, I'm leaning towards reading from SharedPreferences unless there is a better way to keep the request list objected updated in all instances.
THE QUESTION
(1) So, how efficient is it to read the same key from SharedPreferences quite frequently by multiple instances of the object? and (2) Is there a better way to keep the request list objected updated in all instances?
So there are a couple of approaches you can take to this.
First, your object is small - re-reading SharedPreferences thousands of times would hardly be noticeable. It's not like SharedPreferences is on a remote drive or has a "bad connection."
Second, if you don't like that answer, then you need a DAO (Data Access Object). SharedPreferences is a form of this already. It provides a means to store and retrieve data with confidence that you have the most recent data available. But, if you feel like you can improve on it's optimization (because it's generic, and this is your app), then you can provide access to you data through a static object that performs both "read" and "write" operations. This will guarantee that access to the object is done with the most recent data. Of course, you will need to be thread aware, etc. (something that is not always guaranteed by SharedPreferences).
Next, you could persist your data in a database and use Cursors or other built-in or custom DAOs. This requires another level of complexity and a lot of overhead, but is useful when several components of your app might need access to the data, provide updates or needs real-time monitoring of changes because background threads or other objects may make modifications that will change your app behavior or result in UI updates.
Last, you could use more complex data stores like a Content Provider. This is really required for cases where you want/need other apps to access data provided by your app (and your app may also consume the data). That's a complex solution and implementation is well outside the scope of this question.
But I mention it because you seem interested in being certain that frequent reads of SharedPreferences is acceptable. It definitely is acceptable - otherwise there would be something else besides it, databases and Content Providers.
Related
I've a simple data that i want to persist on firebase.
This data is a domain class for my relational model (i started with a relational model and now im deciding whenever or not migrate to firebase, but for awhile im working with both... or trying to)
To persist a new instance if my class on firebase i need to do:
Map<String, Object> firebase = new HashMap<String, Object>();
firebase.put("raffleDate", this.giveaway.getRaffleDate());
firebase.put("thumbnailUrl", this.giveaway.getThumbnailUrl());
firebase.put("mustFollowList", this.giveaway.getMustFollowList());
firebase.put("owner", this.giveaway.getOwner());
firebase.put("amountFriendsToIndicate", this.giveaway.getAmountFriendsToIndicate());
firebase.put("mediaId", this.giveaway.getMediaId());
((App) getApplication()).getFirebase().child("giveaways").child(this.giveaway.getMediaId()).setValue(firebase);
because besides these fields Giveaway has one last other field which has a circular reference to itself
#ToMany(referencedJoinProperty = "raffle")
#Expose(deserialize = false, serialize = false)
private List<UserOnGiveaway> attendantsTickets;
This field maps the relatioship between user and its giveaways, UserOnGiveaway class has a reference to User and Giveaway so when i try to persist i get a very long non compreensive error that I can just guess is due some stackoverflow because of the circular reference
The thing is I DONT REALLY CARE ABOUT PERSISTING THIS FIELD, in my actual "hybrid" archtecture i'm using firebase only to persist data shared among users, individual user data is being stored locally on android sqlite
So i would like to know is there any way i can annotate this field to force firebase ignore it?
or is there any parameter is can set on firebase call to do it?
PLEASE do not suggest transient as it will also affect my ORM
PLEASE2 do not suggest changes on domain since i'm giving a try to firebase i wont make any structural changes before decide for it.
thanks
You can use the #Exclude annotation on a field or getter/setter method to omit it from serialization with the Firebase SDK.
I'm a bit confused, as from a long time i am saving the json response directly to an ArrayList> and displaying to my listView, but now, looking on other people code i noticed that they are using POJO class to interact with JSON, Is it is better way? if it is please explain why? cause using POJO means I have to write extra code, But if saving the response directly to the arraylist make my work done, then why should i use a POJO class?
So, Pojo usage better due to OOP pattern, because you work at runtime with your Java object without intermediate Json parse. Manual json parsing too ugly due to code style(its my opinion).
But if saving the response directly to the arraylist make my work done
If, you collect your object in Maps, you can apply different features out of the box(sort, compare etc) to your map, but in case when your map contains POJO instead of JSONS.
Encapsulation. When you work with dates for examples or with type, its pretty good to use getters/setters for data mapping instead of manual parsing again and again.
4.Object scaling and mapping:
Lets image that we have some object user:
public class User{
int id;
#SerializedName("specific_id_for_blah_blah")
private int mSpecId
#SerializedName("date_of_birthaday")
private String mBDay;
public Date getBirthday() {
return new Date(mBDay);
}
}
What I want to say by this example.
You can map your json to POJO with one line of code only
User user = new Gson.fromJson(response, User.class);
Pretty simple isn't?.
Name serialization. When your response contain key name which looks to long or weird, you can use your own style naming with easy changes, just with small annotation. mSpecId returns value of "specific_id_for_blah_blah"
Platform specific encapsulation. You can use only platform specific object at your runtime, instead parsing operations in your business logic. String with data -> Date or Calendar
Also you can override Object methods in your POJO (equals, hashcode, toString) for your logic spec. operations.
If your serverside change some key you can change name of key in POJO instead looking through where you parse it before. IN same case you can add new field and setter/getter, if some of parameter will be added to your response
There is no right and wrong answer here. It all depends on your use case. If your solution works, and you are happy with it, I don't see why do you need to change it.
If I had to choose, I would go with a POJO class to represent the response, but this is a subjective opinion. I think that you have the following benefits:
It's cleaner - having a separate, dedicated class to represent your payload gives you the ability to be more specific in your code. You are no longer manipulating Maps of key - value pairs, but instances of a specific class, that can have a more specific behaviour. You can specify natural ordering, criteria for equality, etc - things that may be useful for your program's logic
It's simpler - I would prefer calling a getter every time then accessing a map by a property name and getting an Object back. The logic of the program will be much simpler and safer.
It's better in terms of OOP best practices - the whole point behind OOP is to have objects, that define properties and behaviours. IMHO, using POJOs to represent responses forces you to adhere more closely to best practices.
There are also some cases that will fit the no - POJO approach better - for example, if you only display your data, not manipulating it in any way inside the app. Or if you want to shave off some time for the complex parsing that may be needed if you are trying to inflate object hierarchies.
My best suggestion is - profile your app, check your use cases and make an educated decision which approach is better.
I'm developing an Android app with Android Annotations. For persistence, I firstly used a Content Provider (very complex) on top of SQLite. Then, I discovered Realm. It seemed very cool until I had to be notified for insertions to make my RecyclerView dynamic. To be notified of insertions, I made a singleton class I called RealmProxy with a proxy method for copyToRealm(), and an interface to implement to be a RealmListener. I called registered listeners in my copyToRealm() method passing them the added RealmObject, so I could populate my SortedList (support library list designed for RecyclerView) RecyclerView Adapter. I also used my RealmListener interface to send new Objects over network as soon as they are saved.
After compiling and running, I got and IllegalStateException (Realm access from incorrect thread. Realm objects can only be accessed on the thread they were created.) because I get the Realm instance from UI thread but I send them over network in a background thread obviously. Why do I get this error ? Whenever my JSON serialization library LoganSquare, based on Jackson calls a getter on my RealmObject in the background to send over network, this exception is thrown. This made me hate Realm thread policy and the fact that fine grained notifications aren't built-in. Also, Realm doesn't allow me to define any custom method. I can't even implement Comparable in a Realm Object.
When I saw Paper (thanks to Android Arsenal and Pushbullet) today, I was very interested in a no headaches JPA solution. It seems very simple, without restriction for Lists, Maps, and any class not extending a special class (Realm requires extending RealmObject and using RealmList instead of generic List which my json<>java didn't liked, forcing me to copy lists).
EDIT:
I discovered SnappyDB today. It uses the same serialization library (Kryo) as Paper, it seems to be very similar to Paper, with more features for keys management.
So my question is the following:
Should I search for workarounds and continue to use Realm, if yes, which workarounds, or should I use Paper, or SnappyDB instead ? Did anyone used Paper or SnappyDB for android?
All the best
If your question is about how to update your Object in UI thread when it gets changed in background, it is actually quite simple.
For example in your UI thread you can do this:
private Dog dog;
private RealmChangeListener listener = new RealmChangeListener() {
#Override
// This will be called when the commitTransaction gets called
// in the background thread
public void onChange() {
// It would changed to "EFG" automatically in next UI loop after
// you updated it in the background thread.
String name = dog.getName();
}
};
#Override
protected void onCreate(Bundle savedInstanceState) {
dog = realm.where(Dog.class).equalTo("id", 42).findFirst();
// Assume it is "ABC" now
String name = dog.getName();
// Register the listener
realm.addChangeListener(listener);
}
And update the dog in th background service like:
// This realm will be a different instance created in this thread.
dog = realm.where(Dog.class).equalTo("id", 42).findFirst();
realm.beginTransaction();
dog.setName("EFG");
realm.commitTransaction();
The IllegalStateException is because of:
The only rule to using Realm across threads is to remember that Realm, RealmObject or RealmResults instances cannot be passed across threads. When you want to access the same data from a different thread, you should simply obtain a new Realm instance (i.e. Realm.getInstance(Context context) or its cousins) and get your objects through a query. The objects will map to the same data on disk, and will be readable & writeable from any thread!
See see doc here
And you probably need RealmBaseAdapter which can make building a ListView with Realm pretty easy. You can find example here.
JPA is not a solution, it's a definition for Java Persistence. Once you choose JPA, you need to find an implementation. In the Java world, the most widely used implementation is Hibernate. Also, you can use Hibernate ORM without using JPA.
On Android, OrmLite provides an implementation for a subset of JPA. But, as it's only a subset, you may as well skip JPA and use the equivalent Ormlite annotations. I use JPA implemented by Hibernate on my server apps, and Ormlite with no JPA on Android. I definitely recommend Ormlite.
I'm still fairly new to RxJava and I'm using it in an Android application. I've read a metric ton on the subject but still feel like I'm missing something.
I have the following scenario:
I have data stored in the system which is accessed via various service connections (AIDL) and I need to retrieve data from this system (1-n number of async calls can happen). Rx has helped me a ton in simplifying this code. However, this entire process tends to take a few seconds (upwards of 5 seconds+) therefore I need to cache this data to speed up the native app.
The requirements at this point are:
Initial subscription, the cache will be empty, therefore we have to wait the required time to load. No big deal. After that the data should be cached.
Subsequent loads should pull the data from cache, but then the data should be reloaded and the disk cache should be behind the scenes.
The Problem: I have two Observables - A and B. A contains the nested Observables that pull data from the local services (tons going on here). B is much simpler. B simply contains the code to pull the data from disk cache.
Need to solve:
a) Return a cached item (if cached) and continue to re-load the disk cache.
b) Cache is empty, load the data from system, cache it and return it. Subsequent calls go back to "a".
I've had a few folks recommend a few operations such as flatmap, merge and even subjects but for some reason I'm having trouble connecting the dots.
How can I do this?
Here are a couple options on how to do this. I'll try to explain them as best I can as I go along. This is napkin-code, and I'm using Java8-style lambda syntax because I'm lazy and it's prettier. :)
A subject, like AsyncSubject, would be perfect if you could keep these as instance states in memory, although it sounds like you need to store these to disk. However, I think this approach is worth mentioning just in case you are able to. Also, it's just a nifty technique to know.
AsyncSubject is an Observable that only emits the LAST value published to it (A Subject is both an Observer and an Observable), and will only start emitting after onCompleted has been called. Thus, anything that subscribes after that complete will receive the next value.
In this case, you could have (in an application class or other singleton instance at the app level):
public class MyApplication extends Application {
private final AsyncSubject<Foo> foo = AsyncSubject.create();
/** Asynchronously gets foo and stores it in the subject. */
public void fetchFooAsync() {
// Gets the observable that does all the heavy lifting.
// It should emit one item and then complete.
FooHelper.getTheFooObservable().subscribe(foo);
}
/** Provides the foo for any consumers who need a foo. */
public Observable<Foo> getFoo() {
return foo;
}
}
Deferring the Observable. Observable.defer lets you wait to create an Observable until it is subscribed to. You can use this to allow the disk cache fetch to run in the background, and then return the cached version or, if not in cache, make the real deal.
This version assumes that your getter code, both cache fetch and non- catch creation, are blocking calls, not observables, and the defer does work in the background. For example:
public Observable<Foo> getFoo() {
Observable.defer(() -> {
if (FooHelper.isFooCached()) {
return Observable.just(FooHelper.getFooFromCacheBlocking());
}
return Observable.just(FooHelper.createNewFooBlocking());
}).subscribeOn(Schedulers.io());
}
Use concatWith and take. Here we assume our method to get the Foo from the disk cache either emits a single item and completes or else just completes without emitting, if empty.
public Observable<Foo> getFoo() {
return FooHelper.getCachedFooObservable()
.concatWith(FooHelper.getRealFooObservable())
.take(1);
}
That method should only attempt to fetch the real deal if the cached observable finished empty.
Use amb or ambWith. This is probably one the craziest solutions, but fun to point out. amb basically takes a couple (or more with the overloads) observables and waits until one of them emits an item, then it completely discards the other observable and just takes the one that won the race. The only way this would be useful is if it's possible for the computation step of creating a new Foo to be faster than fetching it from disk. In that case, you could do something like this:
public Observable<Foo> getFoo() {
return Observable.amb(
FooHelper.getCachedFooObservable(),
FooHelper.getRealFooObservable());
}
I kinda prefer Option 3. As far as actually caching it, you could have something like this at one of the entry points (preferably before we're gonna need the Foo, since as you said this is a long-running operation) Later consumers should get the cached version as long as it has finished writing. Using an AsyncSubject here may help as well, to make sure we don't trigger the work multiple times while waiting for it to be written. The consumers would only get the completed result, but again, that only works if it can be reasonably kept around in memory.
if (!FooHelper.isFooCached()) {
getFoo()
.subscribeOn(Schedulers.io())
.subscribe((foo) -> FooHelper.cacheTheFoo(foo));
}
Note that, you should either keep around a single thread scheduler meant for disk writing (and reading) and use .observeOn(foo) after .subscribeOn(...), or otherwise synchronize access to the disk cache to prevent concurrency issues.
I’ve recently published a library on Github for Android and Java, called RxCache, which meets your needs about caching data using observables.
RxCache implements two caching layers -memory and disk, and it counts with several annotations in order to configure the behaviour of every provider.
It is highly recommended to use with Retrofit for data retrieved from http calls. Using lambda expression, you can formulate expression as follows:
rxCache.getUser(retrofit.getUser(id), () -> true).flatmap(user -> user);
I hope you will find it interesting :)
Take a look at the project below. This is my personal take on things and I have used this pattern in a number of apps.
https://github.com/zsiegel/rxandroid-architecture-sample
Take a look at the PersistenceService. Rather than hitting the database (or MockService in the example project) you could simply have a local list of users that are updated with the save() method and just return that in the get().
Let me know if you have any questions.
Say I have a Java Bean object which is serializable. I want to store it away safely when an Activity goes through onDestroy() on purpose (i.e. onSaveInstanceState() is not called).
I am looking for a way which doesn't involve creating a database and write the object to that (mostly since a) Android's DB API is horrible and b) since databases make application updates a nightmare, because there is no decent support for applying migrations).
I thought about serializing the object to a ByteArrayOutputStream, base64 encode that and write it to a SharedPreferences file as a string. Or is that too far off?
UPDATE
Maybe that serialize-to-string idea wasn't that bad after all, seems to work out pretty well. Here's what I'm doing now:
public static String objectToString(Serializable object) {
ByteArrayOutputStream out = new ByteArrayOutputStream();
try {
new ObjectOutputStream(out).writeObject(object);
byte[] data = out.toByteArray();
out.close();
out = new ByteArrayOutputStream();
Base64OutputStream b64 = new Base64OutputStream(out);
b64.write(data);
b64.close();
out.close();
return new String(out.toByteArray());
} catch (IOException e) {
e.printStackTrace();
}
return null;
}
public static Object stringToObject(String encodedObject) {
try {
return new ObjectInputStream(new Base64InputStream(
new ByteArrayInputStream(encodedObject.getBytes()))).readObject();
} catch (Exception e) {
e.printStackTrace();
}
return null;
}
in onDestroy() I can then simply write the Base64 string to a preference file, where it's safe until I read it again during the next activity launch. It's a lot faster than I expected and unless your beans carry huge amounts of data, it works pretty well. And even better, you don't have to maintain a DB schema.
Still, I'm curious about how others do this.
I am looking for a way which doesn't
involve creating a database and write
the object to that (mostly since a)
Android's DB API is horrible and b)
since databases make application
updates a nightmare, because there is
no decent support for applying
migrations).
Android's API is actually fairly reasonable, mostly because it's a thin wrapper over the SQLite API, and the SQLite API is fairly reasonable for an embedded database. Moreover, Android does provide assistance for schema upgrades on app upgrades, via SQLiteOpenHelper.
It's a lot faster than I expected and
unless your beans carry huge amounts
of data, it works pretty well.
I have heard of many more developers running away screaming from serialization than I have heard of people having long term success with it. Just within the past few days, here on SO #android, I had an exchange with somebody trying desperately to rip serialization out of his app by the roots.
And even better, you don't have to maintain a DB schema.
Oh yes you do. What do you think is going to happen when you update your application and your class is modified? Doing the bookkeeping to figure out how to deserialize old versions of the class from a new version of a class is a chore and is one of the reasons developers abandon serialization. Also, do not forget that serialization is not transactional, whereas SQLite is.
I was also looking for a nice approach of un/marshalling any beans or activity states. We all know how much Activity's onStoreInstanceState() and onRestoreInstanceState() is a pain.
My acitivities simply store their states in onPause() and restore them in onCreate() lifecycle hooks via direct object serialization.
Serialization via a String like you do, is of course possible but less suitable for big data and causes a lot of overhead. Moreover Preferences are actually there to store preferences, not data :) Unfortunately, the Parcelable / Parcel what we could use for this purpose, does not recommend to store to persistent storage.
So what's left over is a simple object serialization - fortunately android SDK has implementation of the ObjectInputStream and ObjectOutputStream classes with all drawbacks and benefits - like we would also do in a non-android Java world, a simple:
ObjectOutputStream.writeObject(yourPojo)
would do the magic for us, (remember to implement the Serializable marker-interface)
Also, you may want to look in following APIs of a Context - ContextWrapper - Activity, which are very useful to cache local data (such as images) etc:
.getCacheDir()
.getDir()
.openFileInput()
.openFileOutput()
happy hacking :)