Tag: kafka

JavaChannel’s Interesting Links podcast, episode 14

Welcome to the fourteenth ##java podcast. Your hosts, as usual, are Joseph Ottinger, dreamreal on the IRC channel, and Andrew Lombardi from Mystic Coders (kinabalu on the channel), and it’s Wednesday, February 7, 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-14”.

  1. javan-warty-pig is a fuzzer for Java. Basically, a fuzzer generates lots of potential inputs for a test; for example, if you were going to write a test to parse a number, well, you’d generate inputs like empty text, or “this is a test” or various numbers, and you’d expect that your tests would validate errors or demonstrate compliance to number conversion (this is a way of saying “it would parse the numbers.”) A Fuzzer generates this sort of thing largely randomly, and is a good way of really stressing the inputs for the methods; the fuzzer has no regard for boundary conditions, so it’s usually a good way of making sure you’ve covered cases. The question, therefore, becomes: would you use a fuzzer, or HAVE you used a fuzzer? Do you even see the applicability of such a tool? There’s no doubt that it can be useful, but potential doesn’t mean that the potential will be leveraged.

  2. Simon Levermann, mentioned last week for having released pwhash, wrote up an article for the channel blog detailing its use and reason for existing. Thank you, Simon!

  3. Scala is in a complex fight to overthrow Java, from DZone. Is the author willing to share the drugs they’re on? Scala’s been getting a ton of public notice lately – it’s like the Scala advocates finally figured out that everything Scala brought to the table, Kotlin does better, and with far less toxicity. If kotlin wanted to take aim at Scala, there’d be no contest – Kotlin would win immediately, unless “used in Spark and Kafka” were among the criteria for deciding a winner. It’s a fair criterion, though, honestly; Spark and Kafka are in fairly wide deployment. But Scala is incidental for them, and chances are that their developers would really rather have used something a lot more kind to them, like Kotlin, rather than Scala.

  4. More of the joys of having a super-rapid release cycle in Java: according to a post on the openjdk mailing list, bugs marked as critical are basically being ignored because the java 9 project is being shuttered. It’s apparently on to Java 10. This is going to take some getting used to. It’s good to have the new features, I guess, after wondering for years if Java would get things like lambdas, multiline strings, and so forth, but the rapid abandonment of releases before we even have a chance to see widespread adoption of the runtimes is… strange.

  5. James Ward posted Open Sourcing “Get You a License”, about a tool that allows you to pull up licenses for an entire github organization – and issue pull requests that automatically add a license for the various projects that need one. Brilliant idea. Laziness is the brother of invention, that’s what Uncle Grandpa always said.

JavaChannel’s Interesting Links podcast, episode 13

Welcome to the thirteenth ##java podcast. It’s Tuesday, January 30, 2018. Your hosts are Joseph Ottinger (dreamreal on IRC) and Andrew Lombardi (kinabalu on IRC) from Mystic Coders. We have a guest this podcast: Cedric Beust, who’s always been very active in the Java ecosystem, being a factor in Android and author of TestNG as well as JCommander and other tools – and it’s fair to say that if you’ve used modern technology, Cedric’s actually had something to do with it. Really.
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-13”.
A topic of discussion from ##java last week centers on code coverage: what numbers are “good”? What numbers can be expected? What’s a good metric to consider? Joseph likes (apparently) absurdly high numbers, like 90% or higher; Cedric recommends 50% code coverage as a good baseline; Andrew targets 70%. Expect a poll in the channel on this! It’s a really good discussion, but it’s not really going to be summarized here; listen to the podcast!

  1. Grizzly – an HTTP server library based on NIO – has been donated to EE4J. That’s not particularly interesting in and of itself, but there’s a question of whether all the projects being donated to EE4J imply an abandonment of Java EE as a container stack. It may not be; after all, EE4J is an umbrella just like Java EE itself is, so this may be very much what we should expect – which makes pointing it out as news rather odd. (The original item was from Reddit.)

  2. Pivotal gave us a really interesting article, called “Understanding When to use RabbitMQ or Apache Kafka.” Kafka and RabbitMQ are both sort of message-oriented, but there’s a lot of confusion about when you’d use one against the other; this article discusses both RabbitMQ’s and Kafka’s strengths and weaknesses. It would have been nicer to talk about AMQP as opposed to RabbitMQ, but the article works nonetheless. Kafka is a high-performance message streaming library; it’s not transactional in the traditional sense; it’s incredibly fast. AMQP is slower (but still really fast, make no mistake) and provides traditional pub/sub and point to point messaging models. The main point of the article, though, is that if you need something other than a traditional model, Kafka is there… but it’s going to involve some effort.

  3. Gradle 4.5 has been released. It’s supposedly faster than it was, and has improvements for C/C++ programmers. It also has better documentation among other changes; Gradle’s good, and this release is important, but it’s not earth-shattering. This discussion veered off quickly and sharply to Cedric’s homegrown build tool, kobalt – and mentioned Eclipse’ Aether library, since migrated to Apache under the maven-resolver project.

  4. More Java 9 shenanigans: Java EE modules – including CORBA, specifically – aren’t part of the unnamed module in Java 9. This comes to us courtesy of InfoQ, which pointed out CORBA specifically – CORBA being harder to reach isn’t really a big deal, I’d think, because nobody’s intentionally dealt with it who hasn’t absolutely had to. And it’s not really a Java EE module, really, so pointing out the removal along with Java EE is accurate but misleading. What does this mean? Well, if you’re using one of the nine modules removed, you’re likely to have to include flags at compilation and runtime to make these modules visible for your app. (See http://openjdk.java.net/jeps/320 for the actual Java Enhancement Proposal.)

  5. There’s a Java Enhancement Proposal for multiline strings. It’s in draft, but has Brian Goetz’ support; this is one of those features that Java doesn’t have that’s left people wondering why for a long time, I think – every other JVM language seems to include it. This doesn’t come up very often – if it was actually all that critical it would have been done a long time ago – but it’ll be nice to see it when (and if) it does make it into Java. It’s done with backticks; it does not use interpolation. Interesting, though.

  6. Baeldung has an article called “The Trie Data Structure in Java,” which, well, presents a Trie. It’s a good article, and explains the data structure really well – but doesn’t explain why you’d use a Trie as opposed to some other similar data structures. Tries represent a tradeoff between data size and speed; Tries tend to be incredibly fast while being more memory-hungry than some of their counterparts. Incidentally: there’s a question of pronunciation! “Trie” is typically pronounced the same was as “tree” is – while Joe pronounces it like “try” and struggled mightily to concede to peer pressure and say “tree.” Naturally, he was inconsistent about it; early pronunciation was in fact like “try” but, as stated, convention says “tree.” And it is a tree structure…

  7. Simon Levermann, sonOfRa on the channel, published a reference to his new pwhash project, a result of a series of discussions that seem to have gone on for a few weeks on the channel. It’s a password hashing library; it provides a unified interface to a set of hashing algorithms, like argon2 and bcrypt.

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.

Interesting Links – 8/May/2017

Interesting Links, 2017-Feb-2