I am taking course Functional Programming Principles in Scala | Coursera on Scala.
I fail to understand with immutability , so many functions and so much dependencies on recursion , how is Scala is really suitable for real world applications.
I mean coming from imperative languages I see a risk of StackOverflow or Garbage Collection kicking in and with multiple copies of everything I am running Out Of Memory
What I a missing here?
Stack overflow: it's possible to make your recursive function tail recursive. Add #tailrec from scala.annotation.tailrec to make sure your function is 100% tail recursive. This is basically a loop.
Most importantly recursive solutions is only one of many patterns available. See "Effective Java" why mutability is bad. Immutable data is much better suitable for large applications: no need to synchronize access, client can't mess with data internals, etc. Immutable structures are very efficient in many cases. If you add an element to the head of a list: elem :: list all data is shared between 2 lists - awesome! Only head is created and pointed to the list. Imagine that you have to create a new deep clone of a list every time client asks for.
Expressions in Scala are more succinct and maybe more lazy - create filter and map and all that applied as needed. You can do the same in Java but ceremony takes forever so usually devs just create multiple temp collections on the way.
Martin Odersky defines mutability as a dependence on time/history. That's very interesting because you can use var inside of a function as long as no other code can be affected in any way, i.e. results are always the same.
Look at Option[T] and compare to null. Use them in for comprehensions. Exception becomes really exceptional and Option, Try, Box, Either communicate failures in a very nice way.
Scala allows to write more modular and generic code with less effort compared to Java.
Find a good piece of Scala code and try to see how you would do it in Java - it will be self evident.
Real world applications are getting more event-driven which involves passing around data across different processes or systems needing immutable data structures
In most of the cases we are either manipulating data or waiting on a resource.
In that case its easy to hook in a callback with Actors
Take a look at
http://pavelfatin.com/scala-for-project-euler/
Which gives you some examples on using functions like map fllter etc. Functions like these are used routinely by Ruby applications
Combination of immutability and recursion avoids a lot of stackoverflow problems. This come in handly while dealing with event driven applications
akka.io is a classic example which could have been build very concisely in scala.
Related
This question is formulated in Scala 3/Dotty but should be generalised to any language NOT in MetaML family.
The Scala 3 macro tutorial:
https://docs.scala-lang.org/scala3/reference/metaprogramming/macros.html
Starts with the The Phase Consistency Principle, which explicitly stated that free variables defined in a compilation stage CANNOT be used by the next stage, because its binding object cannot be persisted to a different compiler process:
... Hence, the result of the program will need to persist the program state itself as one of its parts. We don’t want to do this, hence this situation should be made illegal
This should be considered a solved problem given that many distributed computing frameworks demands the similar capability to persist objects across multiple computers, the most common kind of solution (as observed in Apache Spark) uses standard serialisation/pickling to create snapshots of the binded objects (Java standard serialization, twitter Kryo/Chill) which can be saved on disk/off-heap memory or send over the network.
The tutorial itself also suggested the possibility twice:
One difference is that MetaML does not have an equivalent of the PCP - quoted code in MetaML can access variables in its immediately enclosing environment, with some restrictions and caveats since such accesses involve serialization. However, this does not constitute a fundamental gain in expressiveness.
In the end, ToExpr resembles very much a serialization framework
Instead, Both Scala 2 & Scala 3 (and their respective ecosystem) largely ignores these out-of-the-box solutions, and only provide default methods for primitive types (Liftable in scala2, ToExpr in scala3). In addition, existing libraries that use macro relies heavily on manual definition of quasiquotes/quotes for this trivial task, making source much longer and harder to maintain, while not making anything faster (as JVM object serialisation is an highly-optimised language component)
What's the cause of this status quo? How do we improve it?
When learning Scala, one of the first things I learned was that every function returns something. There is no "void"-function/method as there is, for instance in Java. Thus many Scala-functions are true functions, in a mathematic way, and objects can remain largely stateless.
Now I learned that the actor model is a very popular model among functional languages like Scala. However, actors promote a fire-and-forget style of programming, and callers usually don't expect callees to directly reply to messages (except when using the "ask"/"?"-method). Therefore, actors need to remember some sort of state.
Am I right assuming that the actor model is more like a trade-off between scalability and maintainability (due to its statefulness), and could sometimes even be considered an anti-pattern?
Yes you're essentially right (I'm not quite sure what you have in mind when you say scalability vs maintainability).
Actors are popular in Scala because of Akka (which presumably is in turn popular because of the support it gets from Lightbend). It is, not however, the case that actors are overwhelmingly popular in general in the functional programming world (although implementations exist for all the languages I'm thinking of). Below are my vastly simplified impressions (so take them with the requisite amount of salt) of two other FP language communities, both of which use actors (far?) less frequently than Scala does.
The Haskell community tends to use either STM/channels (often in an STM context). Straight up MVars also get used surprisingly often.
The Clojure community sometimes touts its own built-in version of STM, but its flagship concurrency model is really core.async, which is at its heart again channels.
As an aside STM, channels, and actors can all be layered upon one another; its sort of weird to compare them as if they were mutually exclusive approaches. In practice though it's rare to see them all used in tandem.
Actors do indeed involve state (and in the case of Akka skirt type safety) and as a result are very expressive and can pretty much do anything concurrency-wise. In this way they're similar to side-effectful functions, which are more expressive than pure functions. Indeed actors in a way are the pure essence of OO, with all its pros and cons.
As such there is a sizable chunk of the Scala community that would say yes, if most of the time when you face concurrency issues, you're using actors, that's probably an anti-pattern.
If you can, try to get away with just using Futures or scalaz.concurrent.Tasks. In return for less expressiveness you get more composability.
If your problem naturally lends itself to a single, global state (e.g. in the form of global invariants that you want to enforce), think about STM. In the Scala community, although an STM library exists, my impression is that STM is usually emulated by using actors.
If your concurrency problems mainly revolves around streaming multiple sources of data, think about using one of Scala's streaming libraries.
Actors are specifically a tool in the toolbox for handling and distributing state. So yes, they should have state - if they don't then you just could use Futures.
Please note however that Actors (at least Akka Actors) handle distribution (running location-transparently on multiple nodes) which neither functions of Futures are able to do. The concurrency aspects of Actors are a result of them handling the more complex case - networking. In that sense, Actors unify the remote case with the local case, by making the remote case be first-class. And as it turns out, on networks messaging is exactly what you can both count and build on if you want reliable, resilient and also fast systems.
Hope this answers the "big picture" part of your question.
I know that Immutable objects offer several advantages over mutable objects like they are easier to reason about than mutable ones, they do not have complex state spaces that change over time, we can pass them around freely, they make safe hash table keys etc etc.So my question is what are the disadvantages of immutable objects??
Quoting from Effective Java:
The only real disadvantage of immutable classes is that they require a
separate object for each distinct value. Creating these objects can be
costly, especially if they are large. For example, suppose that you
have a million-bit BigInteger and you want to change its low-order
bit:
BigInteger moby = ...;
moby = moby.flipBit(0);
The flipBit method
creates a new BigInteger instance, also a million bits long, that
differs from the original in only one bit. The operation requires time
and space proportional to the size of the BigInteger. Contrast this to
java.util.BitSet. Like BigInteger, BitSet represents an arbitrarily
long sequence of bits, but unlike BigInteger, BitSet is mutable. The
BitSet class provides a method that allows you to change the state of
a single bit of a millionbit instance in constant time.
Read the full item on Item 15: Minimize mutability
Apart from possible performance drawbacks (possible! because with the complexity of GC and HotSpot optimisations, immutable structures are not necessarily slower) - one drawback can be that state must now be threaded through your whole application. For simple applications or tiny scripts the effort to maintain state this way might be too high to buy you concurrency safety.
For example think of a GUI framework like Swing. It would be definitely possible to write a GUI framework entirely using immutable structures and one main "unsafe" outer loop, and I guess this has been done in Haskell. Some of the problems of maintaining nested immutable state can be addressed for example with lenses. But managing all the interactions (registering listeners etc.) may get quite involved, so you might instead want to introduce new abstractions such as functional-reactive or hybrid-reactive GUIs.
Basically you lose some of OO's encapsulation by going all immutable, and when this becomes a problem there are alternative approaches such as actors or STM.
I work with Scala on a daily basis. Immutability has certain key advantages as we all know. However sometimes it's just plain easier to allow mutable content in some situations. Here's a contrived example:
var counter = 0
something.map {e =>
...
counter += 1
}
Of course I could just have the map return a tuple with the payload and count, or use a collection.size if available. But in this case the mutable counter is arguably more clear. In general I prefer immutability but also allow myself to make exceptions.
To answer this question I would quote Programming in Scala, second Edition, chapter "Next Steps in Scala", item 11, by Lex Spoon, Bill Venners and Martin Odersky :
The Scala perspective, however, is that val and var are just two different tools in your toolbox, both useful, neither inherently evil. Scala encourages you to lean towards vals, but ultimately reach for the best tool given the job at hand.
So I would say that just as for programming languages, val and var solves different problems : there is no "disavantage / avantage" without context, there is just a problem to solve, and both of val / var address differently the problem.
Hope it helps, even if it does not provide a concrete list of pros / cons !
In the Eclipse APIs, the return and argument types are mostly arrays instead of collections. An example is the members method on IContainer, which returns IResources[].
I am interested in why this is the case. Maybe it is one of the following:
The APIs were designed before generics generics were available, so IResource[] was better than just Collection or List
Memory concerns, e.g. ArrayList internally holds an array which has more space than is needed (to offer an efficient implementation of add), whereas an array is always constructed for just the needed target size
It's not possible to add/remove elements on an array, so it is safe for iterating (but defensive copying is still necessary, because one can still change elements, e.g. set them to null)
Does anyone have any insights or other ideas why the API was developed that way?
Posting this as an answer, so it can be accepted.
Eclipse predates generics and they are really serious about API stability. Also, at the low level of SWT passing arrays seems to be used to reflect the operating system APIs that are being wrapped. Once you have a bunch of tooling using Arrays I guess it makes sense to keep things consistent. Also note that arrays aren't subject to all of the type erasure issues when using reflection.
Yeah, I hear you as far as the collections api being generally much easier to work with for dynamic lists of items.
For example, when analyzing live stockmarket data I expose a method to my clients
def onTrade(trade: Trade) {
}
The clients may choose to do anything from counting the number of trades, calculating averages, storing high lows, price comparisons and so on. The method I expose returns nothing and the clients often use vars and mutable structures for their computation. For example when calculating the total trades they may do something like
var numTrades = 0
def onTrade(trade: Trade) {
numTrades += 1
}
A single onTrade call may have to do six or seven different things. Is there any way to reconcile this type of flexibility with a functional paradigm? In other words a return type, vals and nonmutable data structures
You might want to look into Functional Reactive Programming. Using FRP, you would express your trades as a stream of events, and manipulate this stream as a whole, rather than focusing on a single trade at a time.
You would then use various combinators to construct new streams, for example one that would return the number of trades or highest price seen so far.
The link above contains links to several Haskell implementations, but there are probably several Scala FRP implementations available as well.
One possibility is using monads to encapsulate state within a purely functional program. You might check out the Scalaz library.
Also, according to reports, the Scala team is developing a compiler plug-in for an effect system. Then you might consider providing an interface like this to your clients,
def callbackOnTrade[A, B](f: (A, Trade) => B)
The clients define their input and output types A and B, and define a pure function f that processes the trade. All "state" gets encapsulated in A and B and threaded through f.
Callbacks may not be the best approach, but there are certainly functional designs that can solve such a problem. You might want to consider FRP or a state-monad solution as already suggested, actors are another possibility, as is some form of dataflow concurrency, and you can also take advantage of the copy method that's automatically generated for case classes.
A different approach is to use STM (software transactional memory) and stick with the imperative paradigm whilst still retaining some safety.
The best approach depends on exactly how you're persisting the data and what you're actually doing in these state changes. As always, let a profiler be your guide if performance is critical.