Idiomatic Peeking with Java Stream API

The peek() method from the Java Stream API is often misunderstood. Let’s try to clarify how it works and when should be used.

Stream

 

Introduction

Let’s start responsibly by RTFM inspecting peek()’s user’s manual.

Returns a stream consisting of the elements of this stream, additionally performing the provided action on each element as elements are consumed from the resulting stream.
Sounds pretty straightforward. We can use it for applying side-effects for every consumed Stream element:

Stream.of("one", "two", "three")
  .peek(e -> System.out.println(e + " was consumed by peek()."))
  .collect(Collectors.toList());

The result of such operation is not surprising:

one was consumed by peek().
two was consumed by peek().
three was consumed by peek().

Stream/peek Lazy Evaluation

but… what will happen if we replace the terminal collect() operation with a forEach()?

Stream.of("one", "two", "three")
  .peek(e -> System.out.println(e + " was consumed by peek()."))
  .forEach(System.out::println);

It might be tempting to think that we’ll see a series of peek() logs followed by a series of for-each logs but this is not the case:

one was consumed by peek().
one
two was consumed by peek().
two
three was consumed by peek().
three

It gets even more interesting if we get rid of the forEach call:

Stream.of("one", "two", "three")
  .peek(e -> System.out.println(e + " was consumed by peek()."));

the result would be nothing:


As JavaDoc states:

Intermediate operations return a new stream. They are always lazy; executing an intermediate operation such as filter() does not actually perform any filtering, but instead creates a new stream that, when traversed, contains the elements of the initial stream that match the given predicate. Traversal of the pipeline source does not begin until the terminal operation of the pipeline is executed.
So, because of the lazy evaluation Stream pipelines are always being traversed “vertically” and not “horizontally” which allows to avoid doing unnecessary calculations. Additionally, the traversal is triggered only when a terminal method is present. Hence, the observed behaviour.

This is why it’s possible to represent and manipulate infinite sequences using Streams. (Because where do you store an infinite sequence? In the cloud?):

Stream.iterate(0, i -> i + 1)
  .peek(System.out::println)
  .findFirst();

The above operation completes almost immediately because of the lazy character of Stream traversal. Of course, if you try to collect the whole infinite sequence to some data structure, even laziness will not save you.

So, we can see that peek() can’t be treated as an intermediate for-each replacement because it invokes the passed Consumer only on elements that are visited by the Stream.

Unfortunately, Streams do not always behave entirely lazily.

Proper Usage

Further inspection of the official docs reveals a note:

This method exists mainly to support debugging, where you want to see the elements as they flow past a certain point in a pipeline
The point of confusion is the “mainly” word. Let’s have a peek(pun intended) at the English dictionary:

We can see that non-debugging usages are not forbidden nor discouraged.

So, technically, we should be able to, e.g., modify the Stream elements on the fly which would not be possible in the immutable, functional world. Let’s use the infamous mutable java.util.Date:

Stream.of(Date.from(Instant.EPOCH))
  .peek(d -> d.setTime(Long.MAX_VALUE))
  .forEach(System.out::println);

// Sun Aug 17 08:12:55 CET 292278994

and we can observe that the result is far away from the standard epoch, which means the mutating operation was indeed applied.

The problem is that this behaviour is highly deceiving because certain Stream implementations can optimize out peek() calls.

This gets clarified in the early draft of JDK 9’s docs eventually:

In cases where the stream implementation is able to optimize away the production of some or all the elements (such as with short-circuiting operations like findFirst, or in the example described in count()), the action will not be invoked for those elements. (…) An implementation may choose to not execute the stream pipeline (either sequentially or in parallel) if it is capable of computing the count directly from the stream source.
So, now it’s clear that it might not be the best choice if we want to perform some side effects deterministically.

According to this, peek() might not be even that reliable debugging tool after all.

Key Takeaways

  • The peek() method works fine as a debugging tool when we want to see what is being consumed by a Stream
  • It seems to work fine when applying mutating operations but should not be used this way because this behaviour is non-deterministic due to the possibility of certain peek() calls being omitted due to internal optimization
  • The discussion, whether mutation operations should be allowed or not, would never take place if we were restricted to operate only on immutable values
  • We have around 292276977 years before we run out of java.util.Date range
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33rd Degree day 2 review

Second day of 33rd had no keynotes, and thus was even more intense. A good conference is a conference, where every hour you have a hard dilemma, because there are just too many interesting presentations to see. 33rd was definitely such a conference, and the seconds day really shined.

There were two workshops going on through the day, one about JEE6 and another about parallel programming in Java. I was considering both, but decided to go for presentations instead. Being on the Spring side of the force, I know just as much JEE as I need, and with fantastic GPars (which has Fork/Join, actors, STM , and much more), I won't need to go back to Java concurrency for a while.

GEB - Very Groovy browser automation

Luke Daley works for Gradleware, and apart from being cheerful Australian, he's a commiter to Grails, Spock and a guy behind Geb, a  browser automation lib using WebDriver, similar to Selenium a bit (though without IDE and other features).

I have to admit, there was a time where I really hated Selenium. It just felt so wrong to be writing tests that way, slow, unproductive and against the beauty of TDD. For years I've been treating frontend as a completely different animal. Uncle Bob once said at a Ruby conference: "I'll tell you what my solution to frontend tests is: I just don't". But then, you can only go so far with complex GUIs without tests, and once I've started working with Wicket and its test framework, my perspective changed. If Wicked has one thing done right, it's the frontend testing framework. Sure tests are slow, on par with integration tests, but it is way better than anything where the browser has to start up front, and I could finally do TDD with it.

Working with Grails lately, I was more than eager to learn a proper way to do these kind of tests with Groovy.

GEB looks great. You build your own API for every page you have, using CSS selectors, very similar to jQuery, and then write your tests using your own DSL. Sounds a bit complicated, but assuming you are not doing simple HTML pages, this is probably the way to go fast. I'd have to verify that on a project though, since with frontend, too many things look good on paper and than fall out in code.

The presentation was great, Luke managed to answer all the questions and get people interested. On a side note, WebDriver may become a W3C standard soon, which would really easy browser manipulation for us. Apart from thing I expected Geb to have, there are some nice surprises like working with remote browsers (e.g. IE on remote machine), dumping HTML at the end of the test and even making screenshots (assuming you are not working with headless browser).

Micro services - Java, the Unix Way

James Lewis works for ThoughtWorks and gave a presentation, for which alone it was worth to go to Krakow. No, seriously, that was a gem I really didn't see coming. Let me explain what it was about and then why it was such a mind-opener.
ThoughtWorks had a client, a big investment bank, lots of cash, lots of requirements. They spent five weeks getting the analysis done on the highest possible level, without getting into details yet (JEDI: just enough design initially). The numbers were clear: it was enormous, it will take them forever to finish, and what's worse, requirements were contradictory. The system had to have all three guarantees of the CAP theorem, a thing which is PROVED to be impossible.
So how do you deal with such a request? Being ThoughtWorks you probably never say "we can't", and having an investment bank for a client, you already smell the mountains of freshly printed money. This isn't something you don't want to try, it's just scary and challenging as much as it gets.
And then, looking at the requirements and drawing initial architecture, they've reflected, that there is a way to see the light in this darkness, and not to end up with one, monstrous application, which would be hard to finish and impossible to maintain. They have analyzed flows of data, and came up with an idea.
What if we create several applications, each so small, that you can literally "fit it in your head", each communicating with a simple web protocol (Atom), each doing one thing and one thing only, each with it's own simple embedded web server, each working on it's own port, and finding out other services through some location mechanism. What if we don't treat the web as an external environment for our application, but instead build the system as if it was inside the web, with the advantages of all the web solutions, like proxies, caches, just adding a small queue before each service, to be able to turn it off and on, without loosing anything. And we could even use a different technology, with different pair of CAP guarantees, for each of those services/applications.
Now let me tell you why it's so important for me.
If you read this blog, you may have noticed the subtitle "fighting chaos in the Dark Age of Technology". It's there, because for my whole IT life I've been pursuing one goal: to be able to build things, that would be easy to maintain. Programming is a pure pleasure, and as long as you stay near the "hello world" kind of complexity, you have nothing but fun. If we ever feel burned out, demotivated or puzzled, it's when our systems grow so much, that we can no longer understand what's going on. We lose control. And from that point, it's usually just a way downward, towards complete chaos and pain.
All the architecture, all the ideas, practices and patterns, are there for just this reason - to move the border of complexity further, to make the size of "possible to fit in your head" larger. To postpone going into chaos. To bring order and understanding into our systems.
And that really works. With TDD, DDD, CQRS I can build things which are larger in terms of features, and simpler in terms of complexity. After discovering and understanding the methods (XP, Scrum/Kanbad) my next mental shift came with Domain Driven Design. I've learned the building block, the ideas and the main concept of Bounded Contexts. And that you can and should use a different architecture/tools for each of them, simplifying the code with the usage patterns of that specific context in your ming.
That has changed a lot in my life. No longer I have to choose one database, one language and one architecture for the whole application. I can divide and conquer, choose what I want to sacrifice and what advantages I want here, in this specific place of my app, not worrying about other places where it won't fit.
But there is one problem in here: the limit of technologies I'm using, to keep the system simple, and not require omnipotence to be able to maintain, to fix bugs or implement Change Requests.
And here is the accidental solution, ThoughtWorks' micro services bring: if you system is build of the web, of small services that do one thing only, and communicate through simple protocol (like Atom), there is little code to understand, and in case of bugs or Change Requests, you can just tear down one of the services. and build it anew.
James called that "Small enough to throw them away. Rewrite over maintain". Now, isn't that a brilliant idea? Say you have a system like that, build over seven years ago, and you've got a big bag of new requests from your client. Instead of re-learning old technologies, or paying extra effort to try to bring them up-to-date (which is often simply impossible), you decide which services you are going to rewrite using the best tools of your times, and you do it, never having to dig into the original code, except for specification tests.
Too good to be true? Well, there are caveats. First, you need DevOps in your teams, to get the benefits of the web inside your system, and to build in the we as opposite to against it. Second, integration can be tricky. Third, there is not enough of experience with this architecture, to make it safe. Unless... unless you realize, that UNIX was build this way, with small tools and pipes.
That, perhaps. is the best recommendation possible.

Concurrency without Pain in Pure Java

Throughout the whole conference, Grzegorz Duda had a publicly accessible wall, with sticky notes and two sides: what's bad and what's good. One of the note on the "bad" side was saying: "Sławek Sobótka and Paweł Lipiński at the same time? WTF?". 
I had the same thought. I wanted to see both. I was luckier though, since I'm pretty sure I'll yet be able too see their presentations this year, as 33rd is the first conference in a long run of conferences planned for 2012. Not being able to decide which one to see, I've decided to go for Venkat Subramaniam and his talk about concurrency. Unless we are lucky at 4Developers, we probably won't see Venkat again this year.
Unfortunately for me, the talk ("show" seems like a more proper word), was very basic, and while very entertaining, not deep enough for me. Venkat used Closure STM to show how bad concurrency is in pure Java, and how easy it is with STM. What can I say, it's been repeated so often, it's kind of obvious by now.
Venkat didn't have enough time to show the Actor model in Java. That's sad, as the further his talk, the more interesting it was. Perhaps there should be a few 90min sessions next year?

Smarter Testing with Spock

After the lunch, I had a chance to go for Sławek Sobótka again, but this time I've decided to listen to one of the commiters of Spock, the best thing in testing world since Mockito. 
Not really convinced? Gradle is using Spock (not surprisingly), Spring is starting to use Spock. I've had some experience with Spock, and it was fabulous. We even had a Spock workshop at TouK, lately. I wanted to see what Luke Daley can teach me in an hour. 
That was a time well spent. Apart from things I knew already, Luke explained how to share state between tests (@Shared), how to verify exceptions (thrown()), keep old values of variables (old()), how to parametrize description with @Unroll and #parameterName, how to set up data from db or whatever with <<, and a bit more advanced trick with mocking mechanism. Stubbing with closures was especially interesting.

What's new in Groovy 2.0?

Guillaume Laforge is the project lead of Groovy and his presentation was the opposite to what we could see earlier about next versions of Java. Most visible changes were already done in 1.8, with all the AST transformations, and Guillaume spent some time re-introducing them, but then he moved to 2.0, and here apart from multicatch in "throw", the major thing is static compilation and type checking.
We are in the days, were the performance difference between Java and Groovy falls to a mere 20%.  That's really little compared to where it all started from (orders of magnitude). That's cool. Also, after reading some posts and successful stories about Groovy++ use, I'd really like to try static compilation with this language
Someone from the audience asked a good question. Why not use Groovy++ as the base for static compilation instead. It turned out that Groovy++ author was also there. The main reason Guillaume gave, were small differences in how they want to handle internal things. If static compilation works fine with 2.0, Groovy++ may soon die, I guess.

Scala for the Intrigued


For the last talk this day, I've chosen a bit of Scala, by Venkat Subramaniam. That was unfortunately a completely basic introduction, and after spending 15 minutes listening about differences between var and val, I've left to get prepared to the BOF session, which I had with Maciek Próchniak.

BOF: Beautiful failures


I'm not in the position to review my own talk, and conclude whether it's failure was beautiful or not, but there is one things I've learned from it.
Never, under none circumstances, never drink five coffees the day you give a talk. To keep my mind active without being overwhelmed by all the interesting knowledge, I drank those five coffees, and to my surprise, when the talk started, the adrenaline shot brought me over the level, where you loose your breath, your pulse, and you start to loose control over your own voice. Not a really nice experience. I've had the effects of caffeine intoxication for the next two days. Lesson learned, I'm staying away from black beans for some time.
If you want the slides, you can find them here.
And that was the end of the day. We went to the party, to the afterparty, we got drunk, we got the soft-reset of our caches, and there came another day of the conference.

You can find my review from the last day in here.

Sample for lift-ng: Micro-burn 1.0.0 released

During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

Motivation

From time to time our sprints scope is changing. It is not a big deal because we are trying to be agile :-) but Jira's burndowchart in this situation draw a peek. Because in fact that chart shows scope changes not a real burndown. It means, that chart cannot break down an x-axis if we really do more than we were planned – it always stop on at most zero.

Also for better progress monitoring we've started to split our user stories to technical tasks and estimating them. Original burndowchart doesn't show points from technical tasks. I can find motivation of this – user story almost finished isn't finished at all until user can use it. But in the other hand, if we know which tasks is problematic we can do some teamwork to move it on.

So I realize that it is a good opportunity to try some new approaches and tools.

Tools

I've started with lift framework. In the World of Single Page Applications, this framework has more than simple interface for serving REST services. It comes with awesome Comet support. Comet is a replacement for WebSockets that run on all browsers. It supports long polling and transparent fallback to short polling if limit of client connections exceed. In backend you can handle pushes in CometActor. For further reading take a look at Roundtrip promises

But lift framework is also a kind of framework of frameworks. You can handle own abstraction of CometActors and push to client javascript that shorten up your way from server to client. So it was the trigger for author of lift-ng to make a lift with Angular integration that is build on top of lift. It provides AngularActors from which you can emit/broadcast events to scope of controller. NgModelBinders that synchronize your backend model with client scope in a few lines! I've used them to send project state (all sprints and thier details) to client and notify him about scrum board changes. My actor doing all of this hard work looks pretty small:

Lift-ng also provides factories for creating of Angular services. Services could respond with futures that are transformed to Angular promises in-fly. This is all what was need to serve sprint history:

And on the client side - use of service:


In my opinion this two frameworks gives a huge boost in developing of web applications. You have the power of strongly typing with Scala, you can design your domain on Actors and all of this with simplicity of node.js – lack of json trasforming boilerplate and dynamic application reload.

DDD + Event Sourcing

I've also tried a few fresh approaches to DDD. I've organize domain objects in actors. There are SprintActors with encapsulate sprint aggregate root. Task changes are stored as events which are computed as a difference between two boards states. When it should be provided a history of sprint, next board states are computed from initial state and sequence of events. So I realize that the best way to keep this kind of event sourcing approach tested is to make random tests. This is a test doing random changes at board, calculating events and checking if initial state + events is equals to previously created state:



First look

Screenshot of first version:


If you want to look at this closer, check the source code or download ready to run fatjar on github.During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.