JavaChannel’s Interesting Links podcast, episode 12

Welcome to the twelfth ##java podcast. Your hosts are Joseph Ottinger, dreamreal on the IRC channel, and Andrew Lombardi (kinabalu on IRC) from Mystic Coders. It’s Tuesday, January 23, 2018.
As always, this podcast is basically interesting content pulled from various sources, and funneled through the ##java IRC channel on freenode. You can find the show notes at the channel’s website, at javachannel.org; you can find all of the podcasts using the tag (or even “category”) “podcast”, and each podcast is tagged with its own identifier, too, so you can find this one by searching for the tag “podcast-12”.
Not an “interesting link,” but we discuss data formats – JSON, XML, HOCON, YAML, Avro, protobuff, Thrift…

  1. Java 9.0.4 has been released, as part of the scheduled January update. NOTE: This is the final planned release for JDK 9. This is scary; see also Azul’s post, “Java: Stable, Secure and Free. Choose Two out of Three,” which points out that with Java’s new rapid-release schedule, you’re going to have to be out of date, insecure, or financially on the hook to … someone to keep up with security releases. We’ve been wanting new features in Java for a long time; we’ve been wanting more churn in the JVM, too. Looks like we, as an ecosystem, might get to experience what Scala goes through every few months, except at least we have the option of stability somewhere.

  2. Speaking of Scala, we have “10 reasons to Learn Scala Programming Language.” It actually has some decent points to make… but makes them with Scala. That’s dumb. There’s nothing that Scala really offers you that Kotlin doesn’t, and that’s assuming Java 8 and Java 9’s improvements don’t turn your crank themselves. It’s almost got a point with Spark and Kafka (well, it mentions Spark, Play, and Akka, and I’m going to pretend that the author meant to say “Kafka” instead), but… when that’s your real lever for learning a language, it’s time to admit that the language was a mistake.

  3. DZone: “Java 8: Oogway’s Advice on Optional” is yet another attempt to justify Optional in Java. It has a fair point to make: “Optional is not a replacement for the null check. Rather, it tries to tell the caller about the nature of the returned value and implicitly reminds the caller to handle the absent cases.” But … okay. So what? In the end, you still have to write what is effectively pretty simple code, and adding the semantic turns out in practice to mostly add noise to your code without actually making it any better.

  4. DZone: “An Introduction to Hollow Jars”, which I found fascinating but I don’t know why. A “hollow jar” is apparently a deployment mechanism where you have two deployable components: the main one, the “hollow jar” basically has the other component – which is the actual application code – in its classpath, and serves to invoke the entry point of the application. The invoker would theoretically change very rarely, and therefore could be baked into a docker image or some other base image, and the component that changes more often would be soft-loaded at runtime.

JavaChannel's Interesting Links podcast, episode 11

Welcome to the eleventh ##java podcast. I’m Joseph Ottinger, dreamreal on the IRC channel, and it’s Tuesday, 2018 January 16. Andrew Lombardi (kinabalu on IRC) from Mystic Coders is also on the podcast, and this episode has a special guest, Kirk Pepperdine from Kodewerk.
As always, this podcast is basically interesting content pulled from various sources, and funneled through the ##java IRC channel on freenode. You can find the show notes at the channel’s website, at javachannel.org; you can find all of the podcasts using the tag (or even “category”) “podcast”, and each podcast is tagged with its own identifier, too, so you can find this one by searching for the tag “podcast-11”.
This podcast has a lot to say about Meltdown, courtesy of Kirk – who’s a performance expert and one of the people you go to when you really need to figure out what your Java application is doing. The short version is this: Meltdown and Spectre are going to affect everything, due to the way modern CPUs work (listen to the podcast to figure out why – it’s fascinating!) – and Java’s reputation as the environment where you can code and let the JVM magically fix everything for you may be in danger. Intel may have revived the importance of data structures for the JVM singlehandedly – not a bad thing, necessarily, but something Java programmers might have to get used to again.
Kirk also went into the things that make Java 9 worth using – and it’s not modules. It’s the extended APIs and the packaging support, neither of which get mentioned very much because of all the chatter about modules.
The interesting links for this week:

  1. DZone has been putting out a lot of information regarding Java 9’s modules. Up first is “Java 9 Modules Introduction (Part 1)“, which does a pretty good job of walking through Java 9 modules from the basics on up. It’s all command-line based, so no IDE, no Maven, no Gradle – Part 2 promises integration with tooling. But knowing what the tools do is important, so this article is a good introduction, about as good as any other so far.

  2. Another entry from DZone on Java 9 is “Java 9 Module Services”, which could be written to be more clear – it refers to a source repository instead of showing lots of relevant code – but does walk through the old ServiceLoader stuff and then walks through the same mechanism in Java 9.

  3. Speaking of tooling: Baeldung has done a walkthrough of docker-java-api, providingi a guide to a Java client that interfaces with the Docker daemon, providing programmatic management of images, volumes, and networks.

  4. There’s also resilience4j, a fault-tolerance library inspired by Netflix Hystrix.It provides features for limited retries, transaction management, a number of other such things; I haven’t run into a situation where I’ve needed this (transaction management has been enough, generally) but it looks like it might be useful; maybe I’ve made architectural decisions that allow me to avoid using libraries like this because I didn’t want to write the features myself. Maybe if I’d known about this, my choices would be different… hard to say.

  5. Lastly, there’s little-java-functions, a collection of functions that look pretty useful, although not modular at all. This library covers a lot of ground. The lack of modularity probably works against it; since we’ve mentioned Java 9 so much, it’d be nice if it mentioned Java 9 compatibility with modules, but maybe Java isn’t prepared to go that far down the Scala rabbit-hole yet. In the process of recording this, a potential problem with licenses came up – possibly the subject of a future conversation – and the author ended up explicitly licensing the code under Creative Commons, thanks to Andrew.

Javachannel’s Interesting Links podcast, episode 10

Welcome to the tenth ##java podcast. If we were Neanderthals, our lives would be half over by now. As usual, I think, I’m Joseph Ottinger, dreamreal on the IRC channel, and it’s Tuesday, 2018 January 9. Andrew Lombardi, kinabalu on IRC from Mystic Coders is with me again.
As always, this podcast is basically interesting content pulled from various sources, and funneled through the ##java IRC channel on freenode. You can find the show notes at the channel’s website, at javachannel.org; you can find all of the podcasts using the tag (or even “category”) “podcast”, and each podcast is tagged with its own identifier, too, so you can find this one by searching for the tag “podcast-10”. The podcast can also be found on iTunes and I’m trying to figure out if it’d be worth it to put it on Youtube, too – sorry, folks, no video from me. I can’t afford the cameras; every time they take a picture of me, they shatter.
You can submit to the podcast, too, by using the channel bot; ~submit, followed by an interesting url, along with maybe a comment that shows us what you think is interesting about the url. Yes, you have to have a url; this is not necessarily entirely sourced material, but we definitely prefer sourced material over random thoughts.

  1. TechTarget finally gets into the podcast, with Four ways the container ecosystem will evolve in 2018. Kubernetes gets the nod of approval, and… imagine containers being used in IoT. I’m not quite sure how the latter point will work. Is docker communicating with an embedded device, or are they talking about embedded devices RUNNING docker? If so, that’d be challenging. After all, Java’s not been all that successful on constrained devices either, and it has a constrained version. (The other two ways are: increased WIndows adoption in containers, and LinuxKit – derived from the Windows thing.)

  2. Meltdown and Spectre – scary words indeed, and deservedly so. Our benefactors at Intel, whose sponsorship we’d accept mostly because we’re cheap and will take money from ANYONE, have blessed us with horrible security in virtually every chip manufactured in the last decade or so. Meltdown allows a program to access the memory of other programs and the host OS; Spectre also breaks isolation between programs. Fixing this requires replacing your physical CPU or patching your OS; the patches have performance implications. If you’re not patched, start looking for patches today. The JVM is not a good vector for delivering either of these flaws, although yawkat’s been playing around with trying it out; this is not the same as the JVM protecting you from other programs exploiting these flaws. Again, thanks, Intel.

  3. Riccardo Cardin wrote up “Single-Responsibility Principle Done Right on DZone. He’s addressing one of the SOLID principles from Robert Martin, the “Single Responsibility” principle, which states: “A class should have only one reason to change.” Mr. Cardin understandably says that that’s a qualitative assertion and not a quantitative assertion – and he suggests adding cohesion to the definition, so that “only one reason” means that it has a single purpose – be it serving as a rectangle, or interacting with a database, or what-have-you. That’s still qualitative, really, but it’s a good baseline – a data access object should ONLY interact with a database, not perform calculations on the individual objects (although I guess you could bend the definitions to make THAT work, too, in the case of reporting.)

  4. Lorenzo Sciandra wrote up “I thought I understood Open Source – I was wrong,” a well-written post about the open source mindset. He says that he used to see open source as a customer getting a freebie: the maintainers have a product that they give freely to the world. But that’s wrong: open source is all about participation. As soon as you use an open source product, you yourself are an actual owner, even if you’re passive about it; it’s yours, not theirs, and you have a right (and to a degree a responsibility) to participate and contribute to that product. It’s yours. You bit it, you bought it… which means if you find a problem, it’s your responsibility to report and address it.

  5. DZone offered us “A Log Message is Executable Code and Comment”. Basically, the author – Dustin Marx – suggests that using a logger for comments actually is a lot more useful than simple code comments; code comments are easy to ignore (even if your IDE highlights them, you get used to seeing the green or blue marker and just skip over them). But a logger event – especially if the log levels are high enough to not hide, like error or severe levels – isn’t something you can ignore. The danger here, of course, is that your comments can actually affect your runtime; interpolation takes time, so you may end up having guards around your comments, a concept I’m struggling with. But it’s a neat idea – if the logger uses a lambda instead of an interpolated value (the lambda can do the interpolation, after all) the logger can do its own guarding and the performance impact MIGHT be minimal.

  6. Up next: JaVers compared to Envers. This is a comparison between JaVers and Envers. Both are auditing tools for databases, but they have very different mindsets; Envers stores in an “audit” table that shows the history of the data with an additional version number, while JaVers stores a JSON representation of the object. The article’s pretty well-done – and uses Groovy to show functionality. Who knew – people use Groovy for something outside of Gradle? Crazy. Given that the article was written by the author of JaVers, I can’t say it was completely unbiased. It looks like a decent write-up of both tools, and seems like a fairly useful tool if you it’s a requirement for you. Have you needed to use any data auditing tools like this before?

  7. Jiccup is a library inspired by Clojure’s “hiccup” – oddly reminiscent of ECS. It reminds one more of the Jade templating engine over in NodeJS land. You don’t see this thing done much outside of JavaScript libraries (well, except for hiccup, maybe?), so it’s good to see it but it’s really weak compared to what they’ve done with something like Jade. I’m looking forward to seeing if this gets more interest, as it looks like a fairly young project. (ECS is a dead project from Jakarta; each HTML element was represented as an object type, so you’d have an HTML object to which you’d add a head object and a body object, and your body would have a list of paragraph objects… so you’re just building an object model of an HTML page. It was slaughtered, and badly and quickly, by templating.)

  8. “Switch Expressions coming to Java?” mentions a Java enhancement to make switch an expression instead of a statement. I’m all for this, but why limit it to switch? Why not try or if? This is one of those features that made me love Scala – before I realized what a puddle of hacks Scala was in the real world – and makes me enjoy Kotlin today. It’d be interesting to see how this works out – there are semantics that need defining, especially in light of backward compatibility – but I love this idea.

Javachannel's Interesting Links podcast, episode 9

Welcome to the ninth ##java podcast. If we were using octal, we’d be on the eleventh podcast by now. It’s hosted by Joseph Ottinger (dreamreal) and Andrew Lombardi (kinabalu on irc) from Mystic Coders and, as a guest, Tracy Snell (waz) on the IRC channel, and it’s Friday, 2017 December 29.
As always, this podcast is basically interesting content pulled from various sources, and funneled through the ##java IRC channel on freenode. You can find the show notes at the channel’s website, at javachannel.org; you can find all of the podcasts using the tag (or even “category”) “podcast”, and each podcast is tagged with its own identifier, too, so you can find this one by searching for the tag “podcast-9”. The podcast can also be found on iTunes.
You can submit to the podcast, too, by using the channel bot; ~submit, followed by an interesting url, along with maybe a comment that shows us what you think is interesting about the url. Yes, you have to have a url; this is not necessarily entirely sourced material, but we definitely prefer sourced material over random thoughts.

  1. Up first we have Eugen Paraschiv, from Baeldung, with “How Memory Leaks Happen in a Java Application“. Most Java coders don’t really think about memory leaks, because the JVM is so good at, well, not leaking memory – but it’s still doable, especially when you have long-lasting data structures sticking around, like caches, that can retain references to object trees long past their usefulness. Eugen points out the obvious suspects – the use of static, for example, to retain references for the duration of the reference to the class – and also points out String.intern() as a culprit for some. That’s more a Java 7 and earlier problem than a Java 8 problem, since Java 8 handles interned strings differently. He points out unclosed resources as an obvious problem – unreleased filehandles, et cetera – and points out badly defined classes being used in collections (as Object’s implementation of equals() and hashCode() make retrieval difficult and therefore those objects will last as long as the Set does). He follows it all up with some ways to detect memory leaks. Well done article, although some of the approaches that lead to memory leaks are a lot less of an impact than he implies, especially with the current releases of the JVM. (This does not mean that it’s okay to be ignorant.)

  2. “Some notes on null-intolerant Java,” from Dominic Fox, says that ”Null-intolerant Java is Java in which there are no internal null checks”. There are a few variants of this; there’re libraries that guarantee no methods will return null, other forms that use Optional, or just throw exceptions if you use a null when you’re not supposed to, or that will defensively check for null on library entry so that you fail immediately if you try to pass in a null when you’re not supposed to. He also mentions Kotlin’s null-checking – using the word “nugatory” for the first time in my experience. (It means “of no value,” just in case you’re wondering or you’re having difficulty inferring it from context.) His criticism of Kotlin in this case is that the null-checks are there whether you want them or not, and there’s a performance cost to them… but I’m not sure how well or deeply he’s measured. It’s actually a pretty decently written article; he mentions Optional – as he should, really – but also describes it sanely, meaning that he doesn’t say something stupid like “use Optional everywhere for nullable values.”

  3. The Java subreddit r/java has a comment thread called “What are features that make Java stand apart from other languages?” Lots of interesting comments; the JVM features highly, the language’s simplicity features, the ecosystem, even the JCP gets a positive mention or two. It’s an interesting DISCUSSION. What do you think makes Java stand out? One of the things I’ve liked in Java that’s changing, though, is the preference for a single idiom; when you look at Scala, you can achieve a given task in eight wildly incompatible ways, but Java’s historically had ONE way to do most things, and that’s changing. I’m not suggesting that that’s a BAD thing, but it’s something that’s changing. Essential conservatism in motion, folks!

  4. RxTest is a Kotlin library meant to help test RxJava flows. (Is that what RxJava calls their pipeline processing mechanisms? I don’t know.) It’s easy to test the simpler parts of event handling mechanisms – you pass it some input, see if you get the right output – but testing flows tends to be a little more involved, because most of it’s asynchronous and it’s hard to test entire streams of processes. Good idea, expressed cleanly, although if you don’t know Kotlin it might be a good time to learn some of it. (This does not mean there aren’t ways to test RxJava event handling in pure Java – it’s just neat to see DSLs for stuff like this.) Also mentioned in this section: awaitility, a library whose name Joe apparently cannot pronounce.

  5. Along the same topic: DZone also has an article on designing a DSL in Kotlin, entitled “Kotlin DSL: From Theory to Practice.” Oddly enough, it also creates a testing DSL, for a learning environment. You’d think that people would use other problem domains for DSLs more often – but it seems like most examples are build tools or testing libraries. It’s still interesting stuff. Have you ever used or implemented a DSL? How broadly used was it, how successful do you think it was, and why?

  6. Dan Luu wrote up an article called “Computer latency: 1977-2017” (therefore: “-40,” duh), using a keypress and the time it takes to display that key as a measure of latency. He goes into OS mechanics (simpler OSes display faster, regardless of processor speed) and display refresh rates… really fascinating stuff, even if it’s not Java-related at all. (I kinda wish he’d measured a JVM on some of these platforms, although that would expand his testing matrix considerably.) (Also mentioned in this section: Rastan, an old video game. And it’s “Rastan,” not “Rathstan,” which is what Joe was mistranslating it into. Memory is what it is, apparently.)

  7. DZone is back with “Alan Kay Was Wrong (About Him Being Wrong),” an article talking about one of the primary ways to describe how objects interact: “messaging.” (Alan Kay – a person, with a name – is considered one of the fathers of object-oriented programming, BTW.) It used to be that you’d describe an object as “communicating” with another object by way of method calls, so you’d say something like “the model is ‘sent to’ the renderer, with the print method.” Nowadays, if you’re not working with Objective C, that sounds a little quaint, I think, but it’s still a way of thinking about data flow. The article is suggesting that Kay – who questioned the analogy – was absolutely right when you think about the objects in question being representative of modules rather than finely-grained objects. With Java 9 supporting module granularity, who knows – this analogy may be back in vogue when people really start using Java 9 modules in practice.

Well, it’s the end of the calendar year – may the new year bring you health, wealth, happiness, and comfort as you attempt to spread the same. We wish you all the best in everything you do.

Javachannel's Interesting Links podcast, episode 8

Welcome to the eighth ##java podcast. I’m Joseph Ottinger, dreamreal on the IRC channel, and it’s Thursday, 2017 December 20. Andrew Lombardi from Mystic Coders is with me again.
Please don’t forget: this is your podcast, with your content too. You can contribute by using a carrier pigeon and sending us notes encoded with rot13 – twice if you want to be really secure – or by using javabot on the IRC channel, with ~submit and an http link, or you can also write content for the channel blog at javachannel.org, or you can even just tell us that something’s interesting… we’ll pick it up from there.

  1. “Non-Blocking vs. blocking I/O: Go with blocking.” is an article by ##java’s surial. In it, he’s talking about asynchronous code, especially with respect to I/O… and his assertion is that you really don’t want to do it. If you decide you do (and there are reasons to) then you should at least rely on some of the libraries that already exist to make it easier… but he mostly points out that it isn’t worth it for most programmers. Interesting read, especially when you consider that Python and Node.JS live and die on this programming model.

  2. “To self-doubting developers: are you good enough?” is an article meant to make you mediocre programmers feel better about yourselves. It talks about the processes and exercises that we all more or less had to go through to achieve competence. It’s not a long post, but it has some good points; programming is practice and art, just like athletics, really – and sometimes you lose, sometimes you plateau, sometimes you have to put in time that someone else might not have to put in. Sometimes the other guy is a natural at some things, and your effort is required to give you the edge… but the good news is that you can put in the effort.

  3. Jason Whaley posted a link called “Incident review: API and Dashboard outage on 10 October 2017” that went into a Postgres multinode deployment failure. It’s a payments company, so the outage is a pretty big deal for them; the short form is that they had a series of failures at the wrong time, and the postgres installation failed. That’s something we don’t hear about very often – either because people are ashamed of it, or hiding it, or some other more nefarious reason, perhaps. More reasons why I’m a developer and not in DevOps? Some pretty in-depth analysis on multi-master Postgres and unintended consequences of architecture. Appears that aside from the Postgres-specific things mentioned here, it probably is a good idea to regularly introduce fault into your infrastructure to test it, to see where the problems are you didn’t intend. And the automation erodes knowledge.

  4. “Want to Become the Best at What You Do? Read this.” goes over five steps to being all that you can be including quoting “Eye of the Tiger” for added insult. Several of the ideas in here are valid though, focusing on improving your skills / self-improvement and putting yourself out there in a vulnerable way. All the items have a “The Secret” type of vibe around them though, which is a bit of a turn off. Love the process, better yourself, make a positive impact on the world, sounds pretty good.

  5. A user on ##java posted a reference to zerocell – a simple open source library to read Excel spreadsheets into Java POJOs. Apache POI is the go-to for this, but POI is a little long in the tooth; it’s always nice to see people creating new solutions. I don’t have any Excel spreadsheets that I need converted into POJOs handy – and I don’t think I’ve EVER had them… except maybe once.

  6. “Understanding and Overcoming Coder’s Block” is YET ANOTHER lifestyle article for this podcast; it’s addressing those times when someone who might otherwise be a good coder – or writer, or anything – encounters the inability to write anything worthwhile. It’s focused on code, but it’s pretty general even so: reasons include a lack of clarity on what you’re trying to achieve, or a lack of decisiveness about how to solve a problem, or maybe the problem just seems too big to solve, or maybe even that you’re just not all that jazzed about the project you’re working on. It also addresses external factors – you know, real life – that might be getting in the way. Lastly, it includes some tips for each of those problems to perhaps point the way forward.

  7. “The Myth of the Interchangeable Developer” is yet another lifestyle article that points out what we all know but that recruiters and managers seem to be ignorant about: we all have specific skillsets. If I’m a good services developer, it doesn’t necessarily follow that I’m a good UI developer, for example… it doesn’t mean that I can’t learn, but it certainly implies that there’s an extra cost in time or aptitude for me to actually design a UI.

  8. “Understanding Monads: a guide for the perplexed” is an article trying to explain monads yet again. Maybe it’s me, but I’m thinking that monads might be one of those formal terms that’s useful but not useful enough, because they’ve been around forever but people still don’t get them. Maybe there’s a giant set of programmers who shouldn’t be allowed to program… but my feeling is that ‘monad’ is mostly jargon. To me it’s a stateless bit of code that defers state elsewhere, so it’s “functionally pure.” Lots of languages that rely on asynchronous programming have a similar concept, but they don’t necessarily call them “monads” (and they can store state elsewhere, too, so maybe they’re cheating.) It’s a decent article, but if you don’t understand monads, it may not .. actually change anything for you. But maybe it will.

  9. Ah, Project Valhalla. DZone has an article – pretty old now, actually, a month or two – that talks about Valhalla. No Valkyries, unfortunately, but value types instead: object references that are referred to just like primitives. This means that Java might get some forms of reification… but it’s hard to say. The main thing I wanted to see from the article was more clear example code; there’s one that boxes an integer in a generic class, without specifying the integer type, but I’m not actually seeing where there’s a real benefit in code yet.

  10. One of my favorite subjects is up next: “Why Senior Devs Write Dumb Code and How to Spot a Junior From A Mile Away.” Want to find a junior developer? Find someone who spends four hours tuning a bit of code that will run … once every four hours. Overexerting yourself trying to write the perfect bit of code every time… that’s a junior developer. Of course, we all know some senior developers who do the same sort of thing… and we tolerate them, but it’s just tolerance. I don’t write supercomplicated code if I can help it, and I’d rather provide simple code to get something simple done if I can, even if that means I’m wasting a few hundred K of RAM or a few dozen milliseconds. I mean, sure, if we need those milliseconds or that RAM, we can tune for that… but we do that when necessary and not otherwise. A summary might be: hesitate to wax locquacious when your innate desire is to extrude tendrils for others to admire your skill; alternatively, allow their senses to inhale your greatness despite their inability to immediately perceive how impressive your capabilities are, especially in comparison to their own.

Non-Blocking vs. blocking I/O: Go with blocking.

You might have heard or read a various things on the Internet extolling the virtues of writing your applications to be ‘non blocking’. Java offers various libraries that help with this endeavour; Undertow is a java web server that lets you write your servlet handlers non-blocking, for example. XNIO is a more general I/O library that lets you write non-blocking code in simpler fashion.
If you take nothing else away from this article, at the very least use one of those libraries to do your non-blocking work.
But the real point is: don’t write non-blocking code.
That’s right: Don’t write non-blocking code. It’s not worth it. You’re using Java, it ships with a garbage collector. Going non-blocking is like manually cleaning up your garbage: in theory it’s faster, in practice it’s more annoying, more error prone, and performance-wise usually either irrelevant or actually slower.
Said differently: Programming for non-blocking is a lot harder than you think it is, and the performance benefits are far less than you think they are.

What does ‘non-blocking’ mean?

Let’s say you wish to read from a file, so you create a FileInputStream and proceed to call the read() method on it. What happens now? Well, the CPU needs to send a signal that travels to various associated chips on the motherboard, to eventually end up at the disk controller, which will then query some cells in the solid state array and returns this to you. Heaven forbid if you still have a spinning disk, in which case we might have to wait for something as archaic as a motor to spin some metal around and a pick-up-needle like thing to swing in there to read some bits! Even with very fast hardware this process takes ages, at least, as far as the CPU is concerned.

From Your Editor: Want to know more about how your computer actually works and why? A good book to read is Charles Petzold’s Code.

So what happens? Well, the CPU will just… wait. In parlance, the thread executing the read() call ‘blocks’, that is, it’ll stop executing while the disk system fetches the requested bytes, and the CPU is going to go do some other stuff (perhaps fill the audio buffer with the next bit of the music you’re playing in the background, do some compilation, et cetera), and if there’s nothing else to do, it’ll idle for a bit and save power.
Once the disk system has fetched the bytes and returned them to the CPU, the CPU will pick back up where it left off and your read() call returns.
That’s how ‘blocking’ works. Blocking is relevant for lots of things, but it’s almost always going to come up when talking to other systems: Networks, Disks, a database, et cetera: Input/Output, or I/O.
There’s another way to do it, though: ‘non-blocking’ code. (Yes, the quotes are intentional.) In non-blocking, things work a little differently. Instead of the thread freezing when there is no data yet, a non-blocking read() returns the bytes that are available, and execution continues. If you didn’t get it all, well, call it some more, or later. In practice, there are 2 separate strategies to make this work correctly:

  1. The functional/closures/lambda way: You ask for some data, and you provide some code that is to be executed once the data is fetched, and you leave the job of gathering this data (waiting for the disk, for example), and calling this code, to whatever framework you’re using, and it might use non-blocking I/O under the hood.

  2. The multiplexing way: You are a thing that responds to many requests (imagine a web server, designed to handle thousands of simultaneously incoming requests), and if there isn’t yet enough data to respond to some incoming request, you simply… go work on some other request. You round-robin your way through all the requests, handling whatever data there is.

It’s not as fast as you think it’ll be

Generally, ‘non blocking is faster!’ is a usually incorrect oversimplification that is based on the idea that switching threads is very slow. Let’s compare a webserver handling 100 simultaneous requests written with blocking I/O in mind, versus a webserver that is written non-blocking style. The blocking one obviously needs 100 threads to execute simultaneously; most of them will be asleep, waiting for data to either arrive or be sent out to the clients they are handling.
The blocking webserver will be switching active threads a lot. Contrast this to the non-blocking webserver: It might well run on only a single core: The one thread this webserver has will sleep as long as all 100 connections are waiting for I/O, and if even a single one has something to do, the thread awakes, does whatever job is needed for all connections that have data available, and only goes back to sleep when all 100 connections are awaiting I/O.

From Your Editor: The nonblocking approach just described is what Python and Node use nearly exclusively, by the way.

Thus, the theory goes: Switching threads is slow, especially compared to.. simply.. not doing that.
But this is an oversimplified state of affairs: In actual practice, modern kernels are really good at taking care of the bookkeeping that threads require. You can create many thousands of threads in Java and it’ll be fine. Furthermore, your one non-blocking thread model is also switching contexts: Every time it jumps to handling another connection, it needs to look at a completely different chunk of memory. This will usually invalidate the caches on your CPU and loading a new page into cache takes on the order of magnitude of 600 or so CPU operations. The CPU just sits there doing nothing while a new page is loaded into cache. This cost is similar to (and takes a similar duration as) thread switches. You gained nothing.
For more on why you’re not going to see a meaningful performance boost (in fact, why you’ll probably get less performance), check out Paul Thyma’s Presentation “Thousands of Threads and Blocking I/O: The Old Way to Write Java Servers Is New Again (and Way Better)“. Thyma is the operator of mailinator.com; he knows a thing or two about handling a lot of simultaneous traffic.

It’s really, really complicated

The problem with non-blocking is two-fold: First of all, modern CPUs definitely have more than one core, so a web server that has a single thread handling all connections in a non-blocking fashion is actually much slower: All cores but one are idling. You can easily solve this problem by having as many ‘handler threads’ all doing non-blocking operations, as you have cores. But this does mean you get none of the benefits of having a single thread. That is, you do not get to ignore synchronization issues unless you’re willing to pay a huge performance fine (bugs that occur because of the order in which threads execute, so called ‘race conditions’ – these bugs are notoriously hard to find and test for).
Secondly: The point of non-blocking is that you do not block: Whenever you are executing in a non-blocking context it is a bug to call any method or do anything that DOES block. You can NOT talk to a database in a non-blocking handler, because that will, or might, block. You can’t ping a server. Something as simple and innocuous as writing a log might block. The problem is, if you do something that does block, you won’t notice until much later when your server seems to fall over even at a fairly light load. You won’t get a log message or an exception if you mess up and block in a non-blocking context. Your server just stops being able to handle more than a handful of requests (equal to the # of cores you have) in a timely fashion for a while. Whoops! Your big server designed to handle millions of users can’t handle more than 8 people connecting at once because it’s waiting for a log line to be flushed to disk!

From Your Editor: Of course, you could write all of those operations in a nonblocking fashion as well, which is what Python and Node.JS have to do – and there’s a good reason why such things lead to a condition known as “callback hell.” It can be done, obviously; they do it. It’s also incredibly ugly and error-prone; it’s a good example of the “cure” being worse than the “disease.”

This really is a big problem: As a rule, most Java libraries simply do not mention whether or not they block – you can’t rely on documentation and you can’t rely on exceptions either.
Trying to program in this ‘you cannot block!’ world is incredibly complicated.
For a deeper dive into the nuttiness of that programming model, read “What color is your function?” by Bob Nystrom, a language designer on the Dart team.

Soo.. completely useless, huh? Why does it exist, then?

Well, non-blocking probably exists because, like the idea of the tongue map, it’s just a very widespread myth that non-blocking automatically means it’s all going to run significantly faster.
It’s not completely useless, though. The biggest benefit to writing your code non-blocking style, is that you gain full control of buffer sizes. Normally, in the blocking I/O model, most of the state of handling your I/O is stuck in the stack someplace: If you ask an inputstream to read a JSON block, for example, and only half of the data is readily available, half of that data is processed by your thread into the data structures you’re reading that JSON into, and then the thread freezes. That data is now stuck in bits of heap memory, and the rest is in this thread’s stack memory. Contrast to a non-blocking model where you’ll have made a ByteBuffer explicitly and most of the data is in there.
CPU stack, ByteBuffer: Potato, potato: It’s all RAM. The difference is: stacks are at least 1MB, and the same size for each and every thread in the VM. ByteBuffers are fully under your control. You can make them smaller than 1MB, you can dynamically update the size, and you can have different buffer sizes for different connections, for example.
Non-blocking code tends to have a smaller memory footprint because of this, if the coder’s aware and takes advantage of the possibility, and that’s the one saving grace it does offer.
It is up to you to figure out if that benefit is worth the hardship and performance hit of going with the non-blocking model. Generally, RAM is very cheap. I’d wager my bets on the blocking model. After all, we don’t write all our software in hand tuned machine code either!

How to use Scanner

The java.util.Scanner class built into java can be used to read inputs. It can for example be used to set up an interactive command line session, where you prompt the user for stuff and your program acts on what the user types in. You can also point it at a file or network connection if you like.

TL;DR: Do not use nextLine()

Phew, glad we got that out there. If you don’t want to read the rest, just never call that method. Instead, to read a full line of text, you call:

scanner.useDelimiter("\r?\n");
String entireLine = scanner.next();

Creating scanners

To create a scanner, just call its constructor, and pass in the data you want to read from. You have lots of options:

import java.util.Scanner;
import java.io.InputStream;
import java.nio.file.Paths;
import java.nio.charset.StandardCharsets;
Scanner in = new Scanner(System.in);
Scanner in = new Scanner(Paths.get("/path/to/file"), StandardCharsets.UTF_8);
Scanner in = new Scanner("input to read");
try (InputStream raw = MyClass.class.getResource("listOfStates.txt")) {
  Scanner in = new Scanner(raw, StandardCharsets.UTF_8);
}

The above code shows 4 different things you can read with scanner:

  1. “Standard input” – what the user types into the command line.
  2. Files. You can also pass a java.io.File object if you still use the old file API.
  3. A string containing data you want to read. The string is read directly; you can’t pass a file path (see the second example for reading files).
  4. Input streams, byte channels, and Readables.

Note that in all cases where you’re dealing with byte input, you can opt not to explicitly pass along a character encoding, but don’t do this! – this means you get the platform default and you have no idea what that’s going to be. That is a good way to write code that works on your computer but fails elsewhere. When in doubt, pass in StandardCharsets.UTF_8 just like in the examples above.

Reading data from a scanner

To read data from a scanner, first decide what you want to read. Then, call the right next method:

A whole number

Call nextInt(), nextLong(), or nextBigInteger(). If you don’t know what these are, call nextInt().

A number in hexadecimal

Call nextInt(0x10), or nextLong(0x10).

A number with fractional elements (i.e., numbers after a decimal point)

Call nextDouble(). However, be aware that how people type floating point numbers depends on where they live. You may want to call useLocale() first to explicitly set the style.

A boolean value

Call nextBoolean()

A single word

Call next()

A whole sentence

Ah, well, that’s tricky. Do not call nextLine(), that doesn’t do what you might think based on its name. Instead, read the next section.

Tokens?

The way Scanner works is by first reading a so-called ‘token’, and then converting this into the representation you asked for. So, if you call nextInt(), a single token is read and this token is then parsed as an integer. If it isn’t an integer, for example because the user typed hello instead of 85, an InputMismatchException is thrown. Catch this exception if you wish to respond to faulty inputs (I advise not calling hasNextInt() and friends either; but that’s for another article).
By default, ‘read the next token’ is done by reading until end-of-input, or any whitespace (tabs, spaces, enters, anything goes). This means that ‘read the next entire line’ just isn’t a thing scanner can do: That would involve reading multiple tokens.
The trick is to turn ‘the entire line’ into a single token. To do that, just tell Scanner to delimit on something else! The delimiter is what separates tokens. So, to read an entire line, first tell scanner that tokens are separated only by newlines, then just read the next token:

scanner.useDelimiter("\r?\n");
String entireLine = scanner.next();

This sets the delimiter to be the newline character, optionally preceded by the carriage return character (windows formatted text files tend to put that in front of their newlines, other OSes don’t).
If you want to return to whitespace-separated tokens, you just call scanner.reset(), though, note, that also resets useLocale.

So what does nextLine do?

nextLine() is unlike all the other next methods. It doesn’t read tokens. Instead, it just keeps reading characters up to the next newline character and returns what it read. It completely ignores the delimiter. This is problematic, because the next method family reads up to the delimiter but doesn’t ‘consume’ it. Thus, if you write this code:

Scanner scanner = new Scanner(System.in);
System.out.print("Enter your age: ");
int age = scanner.nextInt();
System.out.println("Enter your name: ");
String name = scanner.nextLine();

It won’t work: In the user types 5 and then hits enter, well, the 5 goes to nextInt() and that lone enter is all that nextLine is going to read. But if the user types 5 Jane Doe then you’ll end up with age = 5 and name = "Jane Doe". There’s no real way to try to fix this (you can try to call nextLine() twice but that breaks it for those who type spaces instead of enter); just don’t use nextLine, and change the delimiter instead.

Javachannel’s interesting links podcast, episode 7

Welcome to the seventh ##java podcast. I’m Joseph Ottinger, dreamreal on the IRC channel, and it’s Monday, 2017 November 6. Today feels slightly less anonymous than yesterday.
This week we have a co-host, Andrew Lombardi – kinabalu on ##java – and we also offer our humblest apologies to Ms. Debbie Gibson.
This podcast covers news and interesting things from the ##java IRC channel on Freenode; if you see something interesting that’s related to Java, feel free to submit it to the channel bot, with ~submit and a URL to the interesting thing, or you can also write an article for the channel blog as well; I’m pretty sure that if it’s interesting enough to write about and post on the channel blog, it’s interesting enough to include in the podcast.

  1. Increment Development posted “Center stage: Best practices for staging environments,” an article by Alice Goldfuss that defends and describes the use of the staging environment. “Staging is where you gain confidence in your systems by consensus,” she writes – pointing out that development and testing are for testing known things (“when I do this, does that happen?”), and staging is for testing those things that you think might happen in production but can’t necessarily anticipate as part of development or explicit testing. The author points out that there’s an ongoing debate about this, with some well-known people saying “just test better!” but I’m on Alice’ side personally – staging is where you validate that all that testing didn’t let something get through before deployment to production.

  2. Chase Roberts has written “How to unit test machine learning code.” It’s an interesting article – in that it focuses on expected results for a long pipeline of operations for stuff that’s really hard to test well. Machine learning libraries tend to be black-box tested – throw an input at it, pray a bit, hope you get the expected output, suffer for a while if you don’t – and he’s trying to show a way to avoid this cycle. Short summary: testing is hard. Long summary: know what your algorithms are doing, and test every step along the way.

  3. One of the changes for Java 9’s release was unlimited strength cryptography. Well, all of you laggards on older JVMs might be getting it as well, assuming you update and/or patch – which might be questionable, depending on how far back in the revision cycle you are. If you’re still running Java 6, chances are you don’t update, ever, and this might be a scary process for you because it’s so rare. Do I sound like I’m filled with scorn? I don’t mean to be – pity, maybe, and confusion, but not scorn. (Seriously, folks: update to 8. Or 9. Something moderately current. The pain is coming; putting it off will only make it hurt worse when you run out of time.)

  4. The first of multiple DZone articles for this edition of the podcast: “Switching Java Versions on MacOS” shows you how to use the java_home command on OSX to switch between your multiple JVM installations on OSX easily. This is apparently not a perfect process according to some on ##java, but it’s always worked for me when I’ve tried it – but that’s a very small sample set, so try it yourself and see. (The context of the failure was apparently Apache Ant, and my “success” was really just kicking the tires of Java 9. I’m not saying that the failure is incorrect or user error, by any means.)

  5. Another DZone article: “The JSON-P API: A JSON Processing Primer” shows you a high level overview of JSON-P, with both an object model and a streaming model. The streaming model is more interesting; the object model is a lot like org.json, which… no. Just no. In the end, though, Jackson is probably still your best bet for JSON processing in Java.

  6. Kafka has gone to version 1.0, according to Apache. Kafka is a distributed streaming platform – one way of thinking of it is that it’s a distributed event log, where you can write events that are processed at very high volume by various clients. Every client can have its own offset into the event log, so there’s a lot of flexibility in how you use it. Like most such types of data stores, it’s not a magic bullet for … anything, really, but leveraged properly it really can provide amazing throughput. Administration is great fun; I think I’d rather chew off my own neck than manage a Kafka cluster, but … again, if you need the features, it’s a great product.

  7. Yet another DZone article: “https://dzone.com/articles/an-introduction-to-http2-support-in-java-9” shows us the new HTTP/2 client that’s being incubated in Java 9 – which means it probably won’t be fully realized until the next release of Java (which is itself the subject of another news item.) There are already HTTP/2 libraries for Java: Jetty, Netty, vert.x, OkHttp, and Firefly (among others, probably) – but this one will be part of the Java runtime itself. It looks pretty similar to some of the others already mentioned, but that’s not a bad thing; idiom is good and there probably are only so many ways you can think of building a request and issuing it.

  8. Our third entry from DZone this week: “Machine Learning Algorithms: Which One to Choose for Your Problem” Tries to provide an overview of some of the core factors involved in choosing a machine learning algorithm: supervised vs. unsupervised (or semi-supervised, or reinforced) models, along with some of the models themselves and their applications. There are some examples of problems and math, but it’s got no code whatsoever (and if it did, would probably use Python) – still, it does a good job of going over some of the models and capabilities.

  9. Oh, this seems relevant: Java 10 is coming! … maybe. In an email to the OpenJDK mailing list, Mark Reinhold has revised the version string for Java again – so we might actually get Java 10 instead of Java 18.3 for the next release. Versions are hard to get right – but I think going to a major release version scheme like this (or, rather, staying with a major version scheme) is a good idea, even if the release frequency is boosted. Of course, I also think a major version every year or two is a good thing, so now I’ll probably be complaining about the frequency, but … first world problems, I guess.

  10. Speaking of Java 10, early access builds are available. I don’t know if they have variable inference – “var“, in other words – because I haven’t even truly migrated to Java 9 yet, so I’m far from being ready to test an early access build of 10! But if that’s your stimulant of choice, the builds are there for OSX, Linux, Windows, and even Solaris on SPARC, since even that guy Mike needs to play with Java 10 every now and then.

  11. The next two entries are from DZone, too; they’re on fire. The first one is “Null Safety: Calling Java From Kotlin,” which shows the use of annotations in Java code such that Kotlin doesn’t have to pretend the Java method call can return null. It still can, of course, but in Kotlin, nullable types look and act differently than non-nullable types, so this annotation (@Nonnull(when = When.ALWAYS), if you’re interested) is really a way to suggest to Kotlin that the result is never expected to be null. Really pretty neat stuff.

  12. Lastly, DZone came through with an article about the human mind, applied to programming: “Transcending the Limitations of the Human Mind.” It’s about cognitive capacity, a subject I’ve written about myself in the past; when I wrote about it, I referred to it as “chunking” (we manage only so many chunks of information at a time) and here, it’s the same concept with different terminology. The author – Robert Brautigam – walks through some of the tricks we developers use to manage incredibly detailed deployments with limited cognitive capacity through decomposition, generalization, abstract concept management; he also discusses ways in which our development processes work against our cognitive capacity (where our processes make a given mechanism more expensive cognitively than it otherwise should be, perhaps.) Good article.

Javachannel’s interesting links podcast, episode 6

Welcome to the sixth ##java podcast. I’m Joseph Ottinger, dreamreal on the IRC channel, and it’s Monday, 2017 October 30. Scary! Tomorrow’s Halloween.
This podcast covers news and interesting things from the ##java IRC channel on Freenode; if you see something interesting that’s related to Java, feel free to submit it to the channel bot, with ~submit and a URL to the interesting thing, or you can also write an article for the channel blog as well; I’m pretty sure that if it’s interesting enough to write about and post on the channel blog, it’s interesting enough to include in the podcast. (And guess what? That happened this week. See entry #4!)

  1. First up we have two articles about NoSQL from Matt Raible and Okta.com – “NoSQL Options for Java Developers” and “NoSQL Options for Java Developers, Part II.” They were published almost a month apart. In Part I, Matt mostly focuses on a very general overview of the NoSQL landscape and how he chose what NoSQL products to focus on – which ended up being MongoDB, Redis, Cassandra, Neo4J, and Postgres JSON. In Part II he encourages more of a discussion from some NoSQL luminaries about those five. They’re sharing stories and anecdotes about the databases, and it’s interesting reading, even if a little light on content – but they do have some interesting quips to throw out. One in particular stood out to me: you really should justify using something other than Postgres these days, and while I’m a big proponent of NoSQL, I totally agree. They also point out that some people see NoSQL as a magic bandaid for performance, and that’s simply not the case, at all.
  2. Up next we have “A Gentle Introduction to the Bag-of-Words Model.” The Bag-of-Words is a very common way to help trim down inputs for automated learning, or artificial intelligence; one of the things about AI is that it’s painfully easy to overwhelm systems with irrelevant input. This article introduces one of the most common ways to trim input, by providing a focus on words used most commonly in a bit of text – a corpus – or maybe the least common words in that corpus, too, really. (Which set of words you choose depends somewhat on what you’re trying to do.) Interesting article, fairly well done, I thought. Not heavy on code – in fact, painfully light on code – but bag-of-words is actually really easy to write, so that’s not a big deal.
  3. Java 9 is all the rage these days, even though I don’t know anyone who’s actually deploying it yet. Our next article is “Making JSR 305 Work On Java 9,” which focuses on using the annotations for software defect detection – JSR 305 – along with annotations from javax.annotation, which apparently doesn’t work very well in Java 9, due to the packages being split across multiple jars. Part of the problem is the implementation of the JSR 305 annotations themselves; it’s not really been a problem in the non-modular world, but Java 9 is more strict (and should be) about how modules are implemented. The article shows some workarounds and actually does enable the use of the various annotations (and has some warnings along the way) but I think the greater takeaway is that Java 9 is a sea change for Java. It’s probably one that was necessary – sure, we had OSGi and Java EE to help modularize the JVM, but there were and are crucial limits to those approaches that Java 9 is actually trying to address – but even though it’s been necessary there’s still a lot of pain and technology transfer involved.
  4. We also have some content from ##java denizen yawkat: “How (not) to extend standard collection classes.” It came from a discussion on ##java about someone needing a bounded PriorityQueue. I was being really pragmatic and short-sighted, and suggested just overriding the add() to enforce a limit, but the truth is, that is short-sighted – and yawkat wrote this article discussing why and how to actually extend such classes properly. Very well done, and it’s much appreciated.
  5. Another note about future releases of Java – I was going to say “Java 9” but apparently that numbering system is endangered. There’s a JSR – JSR 383 – for Java 18.3, the release scheduled for March 2018. The main difference I see is in local variable type inference, JEP 286. Type inference is cool – Scala and Kotlin have it and rely on it – and it’s great that Java will get it soon too, but the “Java 18.3” name is going to take some getting used to. I still don’t like it. Maybe this is part of their Halloween pranking: “Boo! It’s Java 18.3!” to which my response is, well, “booooo.”
  6. WildFly 11 Final is available. There are lots of improvements here – not many of them are earth-shattering, I think (and I’m waiting for them to go to WildFly Orange or WildFly Jet Fuel, following Oracle’s ridiculous naming practices – okay, I’ll shut up about how I don’t like “18.3” from here on out.) Anyway, WildFly is the fully open source version of JBossAS; it really is a great product. I prefer it to all of the other Java EE containers these days, even though I usually work on distributed services and not monolithic servers any more. I use a lot of the Java EE APIs without using an actual traditional Java EE container, and that’s the current trend I’m seeing – but I’m pretty sure that my data set is pretty constrained. Congratulations on the release, WildFly people.
  7. InfoQ comes in with the JUnit 5 release announcement. JUnit5 changes some annotations and introduces lambdas into the testing mechanism. It also changes the runner mechanism. It requires Java 8, but that’s okay; everyone should be on Java 8 by now anyway. I really like that JUnit is moving forward; I’m mainly a TestNG user, but TestNG has been pushing JUnit to add features, and I imagine that JUnit will likewise push TestNG to add features. Everyone wins.
  8. Up next we have “Project Loom: Fibers and Continuations for the Java Virtual Machine.” This feels really familiar, actually – there used to be a Continuations feature as part of RIFE, and that was around years ago. But here we have an official continuations and fibers suggestion; fibers are lightweight threads, and continuations allow scheduling of tasks on those lightweight threads. I’m not doing it justice here, but it looks great; it’s a long article, worth the read, notable more for its existence than its actual technical content at this point (but the technical content is a good read. Many other platforms have features like this, so it’s good that Java might get them.)
  9. The Gradle project has published “The State of Gradle Java 9 Support,” an article going over the increasingly popular build tool’s support for and integration with Java 9. Multi-release jars still rely on an external plugin, but the module system is supported by Gradle’s dependency resolution, from the looks of it. This is an excellent practice to have, on Gradle’s part – let people know what is supported, how it works, how to use it, and set the expectation that changes will be discussed and documented. It’s almost like open source; open discussion and knowledge transfer.
  10. Lastly, there’s a call for votes on the OpenJDK mailing lists for a new garbage collector, ZGC. It’s currently a skunkworks project of sorts for Oracle, and is aimed at providing low latency for multi-terabyte heaps, a phrase that gives me the willies. I’ve worked with large heaps before – but mainly through things like Azul’s Zing platform. It’s really neat that the Java ecosystem keeps changing like this, though, in that we gain new feature sets all the time and Java just gets better and better. Now if we could only maintain sane version naming and remember to work together…