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Rewrite Python project to Java - worth it? [closed]

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First of all, I love Python, and I currently use it for most stuff. However, as a PhD student, I mostly implement prototypes for testing and evaluating ideas. This also includes that I'm usually the only one coding, and that -- while I certainly try to write half-way efficient code -- performance is not a primary issue. And for quick prototyping, Python is for me just neat.
Now I consider to go with some of my stuff more "serious", i.e., to bring it into a productive environment, make it better maintainable, and maybe more efficient. So I wonder if it's worthy to rewrite my code to, say, Java (with which I'm also reasonably familiar). I know that Python is not slow, but things like Java's static typing including seems to make it less prone to errors on a larger scale, particularly when different people work on the same project.

It's only worth it if it solves a real problem, note, that problem could be
I want to learn something better
I need it to go faster to reduce power requirements in my colo.
I need to hire more people and the talent pool for [insert language here]
is too small.
Insert innumerable real problems here.
Python and Java are both suitable for production. Write it in whatever makes it easiest to solve the problems you and or your team are facing and if you want to preempt some problems make sure you've done your homework. Plenty of projects have died because they chose C/C++ believing performance was going to be a major factor without thinking about the extra effort involved in using these language well.
You mentioned maintainability. You're likely to require more code to rewrite it in Java and there's a direct correlation between Bugs and LOC. It's up for debate which one is easier to maintain. I'm sure both camps believe theirs is.
Of the two which one do you enjoy coding with the most?

The crucial question is this one: "Java's static typing including seems to make it less prone to errors on a larger scale". The crucial word here is "seems." Sure, Java will help you catch this one particular type of error. But how important is that, and what do you have to pay for it? The overhead imposed by Java's type system means that you have to write more lines of code, which means reduced productivity. I've used both and I have no doubt that I'm more productive in Python. I have found that type-related bugs in Python are generally easy to find and fix. Keep in mind that in a professional environment you're not going to ship code without testing it pretty carefully. The bottom line for a programming environment is productivity - usable functionality per unit of effort, not the number of bugs you found and fixed during development.
My advice: if you have a working project written in Python, don't rewrite it unless you're certain there's a benefit.

Java is inherently object oriented. Alternatively python is procedural.
As far as the ability of the language to handle large projects you can make do with either.
As far as producing more usable products I would recommend java script as opposed to java because of its viability in the browser. By embedding your js in a publicly hosted website you allow people with no coding knowledge to run your project seamlessly in the browser.
Further more all the GUI design features of HTML are available at your disposal.
That said any language has it's ups and downs and anything I've said here is simply my perception.

Benefits of Custom Designed Algorithms

In many languages, for me specifically, Java and C++, there is an massive standard library. Many classic problems in computer science, search, sorting, hashing etc etc... are implemented in this library. My question is, are there any benefits of say implementing one's own algorithm versus simply using the library's version? Are there any particular instances were this would be true?
I only ask because in school a huge deal of time is spent on say sorting, however in my actual code I have found no reason to utilize this knowledge when people have already implemented and optimized a sorting algorithm in both Java and C++.
EDIT: I discussed this at length with a professor I know and I posted his response, can anyone think of more to add to it?

Most of the time, the stock library functions will be more performant than anything you'll custom code.
If you have a highly specific (as opposed to a generic) problem, you may find a performance gain by coding a specialized function, but as a developer you should make a conscious effort to not "reinvent the wheel."

Sorting is a good example to consider. If you know nothing whatsoever about the data to be sorted, except how to compare elements, then the standard sort algorithms fare well. In this situation, in C++, the STL sort will do fine.
But sometimes you know more about your data. For example, if your data consists of uniformly distributed numbers, a radix sort can be much faster. But radix sort is 'invasive' in the sense that it needs to know more about your data than simply whether one number is bigger than another. That makes it harder to write a generic interface that can be shared by everyone. So STL lacks radix sort and for this case you can do better by writing your own code.

In general, standard libraries contain very fast code for very general problems. If you have a specific problem, you can in many cases do better than the library. Of course, you may eventually come across a complex problem which is not solved by a library, in which case the knowledge you have gained from studying solutions to solved problems could prove invaluable.

In college, or school, or if learning as a recreational programmer, you will be (or in my strident opinion, you should be) encouraged to implement a subset of these things yourself. Why? To learn. Tackling the implementation of an important already invented wheel (the B-Tree) for me was one of the most formative experiences of my time in college.
Sure I would agree that as a developer you should make an effort not to reinvent the wheel, but when learning through formative experiences, different rules apply. I read somewhere else on this forum that to use something at abstraction level N, it is a very good idea to have a working knowledge of abstraction level N-1, and be familiar with level N-2. I would agree. In addition to being formative, it prepares you for the day when you do encounter a problem when the stock libraries are not a good fit. Believe me this can happen in your 50 year career. If you are learning fundamentals such as data structures, where the end goal is not the completeness of your finished product but, instead, self improvement, it is time well spent to "re-invent the wheel".

Is pre-algebra/algebra/trigonometry/calculus worth learning?
I can't tell if this is a "am I wasting my time/money in school" aimed question or if this is a sincere question of if your own version is going to be better.
As for wasting your time/money in school: If all you want to do is take pot shots at developing a useful application, then you're absolutely wasting your time by learning about these already-implemented algorithms -- you just need to kludge something together that works good 'nuff.
On the other hand if you're trying to make something that really matters, needs to be fast, and needs to be the right tool for the right job -- well, then it often doesn't exist already and you'll be back at some site like Stack Overflow asking first or second year computer science questions because you're not familiar enough with existing techniques to roll your own variations.
Depending on my job, I've been on both sides. Do I need to develop it fast, or does it have to work well? For fast application programming, it's stock functions galore unless there's a performance or functionality hindrance I absolutely must resolve. For professional game programming it has to run blazing fast. That's when the real knowledge kicks into memory management, IO access optimization, computational geometry, low level and algorithmic optimization, and all sorts of clever fun. And it's rarely ever a stock implementation that gets the job done.
And did I learn most of that in school? No, because already knew most of it, but the degrees helped without a doubt. On the other hand you don't know most of it (otherwise you wouldn't be asking), so yes, in short: It is worthwhile.
Some specific examples:
If you ever want to make truly amazing games, live and breath algorithms so you can code what other people can't. If you want to make fun games that aren't particularly amazing, use stock code and focus on design. It's limiting, but it's faster development.
If you want to program embedded devices (a rather large market), often stock code just won't do. Often there's a code or data memory constraint that the library implementations won't satisfy.
If you need serious server performance from modest hardware, stock code won't do. (See this Slashdot entry.)
If you ever want to do any interesting phone development the resource crunch requires you to get clever, even often for "boring" applications. (User experience is everything, and the stock sort function on a large section of data is often just too slow.)
Often the libraries you're restricted to using don't do what you need. (For example, C# doesn't have a "stable" sort method. I run into this annoyance all the time and have since written my own solution.)
If you're dealing with large amounts of data (most businesses have it these days) you'll end up running into situations where an interface is too slow and needs some clever workarounds, often involving good use of custom data structures.

Those libraries offer you tested implementations that work well, so the rule of thumb is to use those implementations. If you have a very particular/complex problem where you can use some domain knowledge you have a case were you will need to implement your own version of an algorithm.
I remember an example Bill Pugh gave in his programming languages class where they analyzed the performance of a complex application and they realized a faulty custom implementation of a sorting algorithm by a programmer (that code was used many times in the real runs of the application) was responsible for 90% performance decrease!

After discussing this at length with professor of Computer Science, here were his opinions:
Reasons to Use Libraries
1. You are writing code with a deadline.
There is no sense in hampering your ability to complete a project in a quick and timely manner. That's why libraries are written after all, to save time and avoid "reinventing the wheel"
2. If you want to optimize your code fully.
Chances are the team of incredibly talented people who wrote the algorithm in Java or C++'s or whoever's library did a far better job at optimizing their algorithm for that language in however long it took them than you can possibly do in an hour or two. Or four.
3. You've already done previously solved this problem.
If you have already solved this problem and have a good complete understanding of how it is designed you don't need to labor over a complex solution as you don't stand to gain much benefit.
That being said, there are still many reasons to make your own solution.
Reasons to Do It Yourself
1. A fundamental understanding of problem solving techniques and algorithms are completely necessary once you reach a problem that is better optimized by a non-library solution.
If you have a highly specified problem, such things often come up when working with networking or gaming or such. It becomes invaluable to be able to spot situations in which a specific algorithm will outperform the libraries version.
2. Having a very good understanding of algorithms and their design and use makes you much more valuable in the work place.
Any halfway decent programmer can write a function to compare two objects and then toss them into a library function, however the one that is able to spot a situation and ultimately improve the programs functionality and speed is going to be looked upon well by management.
3. Having the concept of how to do something is often just as, if not more so, valuable than being able to do it.
With an outstanding knowledge of Java's libraries and how to use them, chances are you can field any problem in java with reasonable success. However when you get hired to work in erlang you're going to have some rough times ahead. Where if you had known how and not merely what Java's libraries did, you could move those ideas to any language.
4. We as programmers are never truly satisfied with merely having something "work".
Chances are that you have an itch to understand why things work. It was this curiosity that probably drove you to this area of study. Don't deny this curiosity! Encourage it and learn to your hearts content.
5. Finally, there is a huge feeling of success and accomplishment that comes with creating your own personal way of sorting or hashing etc.
Just imagine how cool your friends will see you when you proclaim that you can find the shortest path between 2 vertices in n log(n) time! On a serious note, it is very rewarding to know that you are completely capable of understanding and choosing an optimum solution based on knowledge. Not what some library gives you.

Haskell vs JVM performance [closed]

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I want to write a backend system for a web site (it'll be a custom search-style service). It needs to be highly concurrent and fast. Given my wish for concurrency, I was planning on using a functional language such as Haskell or Scala.
However, speed is also a priority. http://benchmarksgame.alioth.debian.org results appear to show that Java is almost as fast as C/C++, Scala is generally pretty good, but Haskell ranges from slower to a lot slower for most tasks.
Does anyone have any performance benchmarks/experience of using Haskell vs Scala vs Java for performing highly concurrent tasks?
Some sites I've seen suggest that Scala has memory leaks which could be terrible for long running services such as this one.
What should I write my service in, or what should I take into account before choosing (performance and concurrency being the highest priorities)?
Thanks

This question is superficially about performance of code compiled with GHC vs code running on the JVM. But there are a lot of other factors that come into play.
People
Is there a team working on this, or just you?
How familiar/comfortable is that team with these languages?
Is this a language you (all) want to invest time in learning?
Who will maintain it?
Behavior
How long is this project expected to live?
When, if ever, is downtime acceptable?
What kind of processing will this program do?
Are there well-known libraries that can aid you in this?
Are you willing to roll your own library? How difficult would this be in that language?
Community
How much do you plan to draw from open source?
How much do you plan to contribute to open source?
How lively and helpful is the community
on StackOverflow
on irc
on Reddit
working on open source components that you might make use of
Tools
Do you need an IDE?
Do you need code profiling?
What kind of testing do you want to do?
How helpful is the language's documentation? And for the libraries you will use?
Are there tools to fill needs you didn't even know you had yet?
There are a million and one other factors that you should consider. Whether you choose Scala, Java, or Haskell, I can almost guarantee that you will be able to meet your performance requirements (meaning, it probably requires approximately the same amount of intelligence to meet your performance requirements in any of those languages). The Haskell community is notoriously helpful, and my limited experience with the Scala community has been much the same as with Haskell. Personally I am starting to find Java rather icky compared to languages that at least have first-class functions. Also, there are a lot more Java programmers out there, causing a proliferation of information on the internet about Java, for better (more likely what you need to know is out there) or worse (lots of noise to sift through).
tl;dr I'm pretty sure performance is roughly the same. Consider other criteria.

You should pick the language that you know the best and which has the best library support for what you are trying to accomplish (note that Scala can use Java libraries). Haskell is very likely adequate for your needs, if you learn enough to use it efficiently, and the same for Scala. If you don't know the language reasonably well, it can be hard to write high-performance code.
My observation has been that one can write moderately faster and more compact high-performance parallel code in Scala than in Haskell. You can't just use whatever most obviously comes to mind in either language, however, and expect it to be blazing fast.
Scala doesn't have actor-related memory leaks any more except if you use the default actors in a case where either you're CPU-limited so messages get created faster than they're consumed, or you forget to process all your messages. This is a design choice rather than a bug, but can be the wrong design choice for certain types of fault-tolerant applications. Akka overcomes these problems by using a different implementation of actors.

Take a look at the head-to-head comparison. For some problems ghc and java7-server are very close. For equally many, there's a 2x difference, and for only one there's a 5x difference. That problem is k-nucleotide for which the GHC version uses a hand-rolled mutable hashtable since there isn't a good one in the stdlibs. I'd be willing to bet that some of the new datastructures work provides better hashtables than that one now.
In any case, if your problem is more like the first set of problems (pure computation) then there's not a big performance difference and if its more like the second (typically making essential use of mutation) then even with mutation you'll probably notice somewhat of a performance difference.
But again, it really depends on what you're doing. If you're searching over a large data set, you'll tend to be IO bound. If you're optimizing traversal of an immutable structure, haskell will be fine. If you're mutating a complex structure, then you may (depending) pay somewhat more.
Additionally, GHC's lightweight green threads can make certain types of server applications extremely efficient. So if the serving/switching itself would tend to be a bottleneck, then GHC may have the leg up.
Speed is well and good to care about, but the real difference is between using any compiled language and any scripting language. Beyond that, only in certain HPC situations are the sorts of differences we're talking about really going to matter.

The shootout benchmark assumes the same algorithm is used in all implementations. This gives the most advantage to C/C++ (which is the reference implementation in most cases) and languages like it. If you were to use a different approach which suited a different language, this is disqualified.
If you start with a problem which more naturally described in Haskell it will perform best in that language (or one very much like it)
Often when people talk about using concurrency they forget the reason they are doing it is to make the application faster. There are plenty of examples where using multiple threads is not much faster or much much slower. I would start with an efficient single threaded implementation, as profiled/tuned as you can make it and then consider what could be performed concurrently. If its not faster this more than one CPU, don't make it concurrent.
IMHO: Performance is your highest priority (behind correctness), concurrency is only a priority in homework exercise.

Does anyone have any performance benchmarks/experience of using
Haskell vs Scala vs Java for performing highly concurrent tasks?
Your specific solution architecture matters - it matters a lot.

I would say Scala, but then I have been experimenting with Scala so my preference would definitely be Scala. Any how, I have seen quite a few high performance multi-threaded applications written in Java, so I am not sure why this nature of an application would mandate going for FP. I would suggest you write a very small module based on what your application would need in both scala and haskell and measure the performance on your set up. And, may I also add clojure to the mix ? :-) I suspect you may want to stay with java, unless you are looking at benefiting from any other feature of the language you choose.

Learning Java so I can get at clojure [closed]

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I have a history of hating Java, having used it pretty regularly in the late 90's during the 'slow as balls' era. As such, I never really learned it well. From what I understand, Java is actually a pretty good language to use these days. I've been thinking about diving into it because of Jython and Clojure. That is to say, I'd like to program in Java and use inline Jython or Clojure where appropriate. But truthfully, I'll probably just be programming in Jython/jRuby and calling up clojure from there.
Which brings me to my question. I know both of these languages can be called from Java, but is that necessarily good practice? Should I even bother learning java if I just want to use Jython as the primary language? Seeing as how that's a large part of my motivations here, I'd like to know that I'm not terribly misguided before jumping in. I'm aware there is a very high risk for projects to become a kludge if done in multiple languages like this.
I'm still learning about the JVM and the like, so I apologize if this question is painfully obvious.

Jython can be viewed as a cross compiler from Python to the Java Virtual Machine. As such, to get the most out of Jython you'll obviously have to learn Python, and probably will need to learn Java.
You can skip some of the Java learning, but at the end of the day, Java and the JVM grew up together. That means that Java code tends to lend understanding of the JVM. It is possible to gain understanding of the JVM without Java, but that's not a path well travelled. Any Jython code that imports a Java library will immediately have you searching Java documentation, so if you avoid leaning Java you're going to learn it piecemeal anyway.
You will have to decide if a piecemeal approach or a formal approach is more appropriate for you and your situation. A lot of deciding which path to take is knowing how you learn best.
As far as the "slow as balls" period of the 90's, that's when I was learning Java. Personally, I feel it is better to describe it as "slow as balls if you did incredibly stupid things with Java". Now I think people have built up a sufficient skill set to avoid translating C directly into Java. That said, I do occasionally encounter the 2000+ line method, so perhaps I'm being a bit rosy in my projection. The entire JVM is laid out in such a manner that good object oriented code runs faster, and if you're constantly trying to go to "other" objects for all the data you need locally, you'll just stack thrash the JVM.
Regardless of opinions, the JVM is now the hot Java item. There has been "other language" support by one means or the other for over a decade now; however, the excitement around Domain Specific Languages seems to have sparked an interest in compilation technologies and the JVM. The other languages benefit from the JVM being an easy target to hit with built-in cross platform support, excellent performance, huge availability of libraries, and generally good documentation. Learning Java and the JVM will help you with a lot of the JVM supported languages, as many of them don't flesh out their library space in favour of hooking into a pure Java library.

I'd say it's worth knowing Java even if you plan on only using other JVM languages. I use JRuby and Scala, and have played around with Clojure. If you are building things to run on the JVM, knowing Java is a bit like knowing C when working natively–you don't have to know C, but if you do, you can write the bits that need speed in C and wrap them in a Ruby or Python library or whatnot.
It's worth knowing the basic principles of how Java works in terms of things like interfaces and annotations and how the classpath works because otherwise you are working with basically a leaky abstraction. What happens when your interop isn't very good? This is especially true if you are planning to do Clojure and Jython!
The other reason to know Java is simply because if you are using code in the Java ecosystem, you have to be able to read and write Java. You need to write a library? Yes, you can probably write it in Clojure, but if you want other JVM language users to be able to use it, you should probably have written it in good, idiomatic Java. Scala is close enough to Java for this purpose; Clojure or Ruby or Python, not so much. Just being able to read and comprehend Java programs is very important too.
The other great benefit is simply that you get more libraries and they are better tested. You need a double-ended queue? Check the Java Collections Framework. Good random number generation? java.security.SecureRandom. UIs? Well, Swing, AWT and SWT are... okay, bad example. Knowing the benefits and shortcomings of these only comes from doing some Java programming and learning the various ways not to suck at Java.

From a couple of years experience of using Clojure (plus many more years of Java...) here is my perspective:
You don't strictly need any Java experience to write Clojure code - Clojure is a full language in its own right and you can write perfectly capable programs without using any Java.
You will need to set up the JVM environment - the Java environment has some rules about where code gets loaded from (i.e. the "classpath") that need to be followed to get a working environment. Not a big deal, and most IDEs will do it for you, but it can be a hurdle for people completely new to the JVM world. I'd suggest careful following of the setup instructions for whichever IDE/toolset you choose.
There are some Java-related concepts that are helpful to understand - for example, Clojure harnesses Java exception handling features with (try ... (catch ...)) etc. so it's useful to be somewhat familiar with the Java approach to exception handling.
Ultimately you will probably want to use Java APIs - bacause a huge amount of the value of being on the JVM in the first place is in having access to the huge diversity of libraries and tools that are available in the Java ecosystem. You don't need to write any Java code to use Java APIs from Clojure, but you do need to know enough Java (method signatures, data types etc.) to be able to read the JavaDoc documentation of the APIs and convert this into an appropriate Clojure function call. Often, this is as simple as (.someJavaMethod someJavaObject param1 param2) but sometimes it can be more complex (e.g. when you need to instantiate a subclass of some Java class to pass as a parameter)
Java isn't a bad language to learn anyway - while I'll readily admit Java has some weak points (as do all languages!), it's still a great, simple, high performance, cross-platform, object-oriented language that has a lot of value. Even if you only do a few short tutorials and never write anything substantial in Java, I'd still recommend it for the learning experience.
I believe most of the above would also apply to Jython.

I can't speak for Jython, but if you want to really get to grips with clojure, you want to understand its trade-offs compared to Java, especially wrt memory/gc and the basics of Clojure/Java interop. You also need at least an abstract understanding of how the clojure collections are implemented unless you really don't care about performance - that's not to say that clojure is particularly inefficient, but more the opposite: the implementation of its immutable collections is fairly unique and tailored to clojure's stance on persistence and performance and it helps to understand the underlying details when you're trying to improve on performance issues.
For all of that, I don't think you actually need a lot of Java knowledge. Being able to read Java fairly well, a basic understanding of the concepts, and a knowledge of where to find the documentation is probably enough.
I think if you want to do a hybrid Clojure/Jython project the interoperation details are most crucial. That probably means you have to know in some detail how classes, interfaces, some of the standard library and (to a minimal extend) generics work in Java and how to deal with all of those in your chosen languages since the interoperation necessarily reduces to the more basic Java constructs. Some of this is tricky and can be confusing, and in clojure's case at least the documentation often refers back to Java concepts and documentation for obvious reasons, so you have to make sure you read both, closely.

I would definitely learn java and learn it well, not only because Clojure is built on top of the JVM but also to get anything done you will be calling Java libraries all the time, and you may even need to dip into Java occassionally.
On another note it would be expand your mind to understand Java's OO concepts and pain poaints too and this will enhance your undersatnding of Clojure too.

Above all, study the Java libraries. Part of the joy of using the JVM is having access to "it's already been done" libraries, as well as to parts of the core language that accomplish certain tasks with optimum performance on the JVM. In addition, some languages (e.g. Clojure) purposefully dip directly into Java and don't completely discourage it in your own code, so if you want to be able to read others' code Java basics are a must.
As for the rest of "learning Java" (design patterns, concurrency in Java, etc.), I wouldn't waste your time unless/until specific projects requirements demand it.

Knowing C++, how long does it take to learn Java? [closed]

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I am a competent C++ developer. I understand and use polymorphism, templates, the STL, and I have a solid grasp of how streams work. For all practical purposes, I've done no Java development. I'm sure some of you were in a similar situation at one point when you had to learn Java. How long did it take you to become a competent Java programmer?

I think that learning the language is not difficult. In fact, I used to be a full time C++ developer, and at some point I started writing Java code. But the thing is that I don't remember ever learning Java, so I guess I just figured it as I went. I've been doing full time Java for a long time now.
If you are well familiar with C++, you may want to read a list of the major differences (e.g., everything is dynamically-bound) and then start practicing on an environment (just download Eclipse). The small differences are the main thing you would have to get adjusted to.
Now that Java supports generics, one of the major switching pains is gone. Multiple inheritance, while not supported, is not a big deal if you get used to interfaces, and in fact having interfaces rather than abstract classes with pure virtual functions (PVFs) improves readability.
To me Java is a nice and friendly and relaxing sandboxed version of C++. I don't have to worry about general protection faults (GPFs), I don't have to worry about memory leaks, I don't have to worry about messing with pointers. However, don't let that confuse you, there are still plenty of opportunities to screw up royally, and they're sometimes even nastier to detect.
Just take the leap. If you have the instinct, it shouldn't be a problem.

I went the opposite way. Started with Java, then moved to C and C++. For my own personal experience, it was much easier to learn Java than C/C++ (C++ especially).
Java in many ways is meant to be C++ with many of the undefined and unnecessarily complicated portions removed or simplified. IMHO, it had great success with that goal. As a result it's a very easy language to learn and use. Especially for someone who is familiar with C++.
The actual time it will take is very dependent upon the person learning the language. However, I think it's safe to say it will take less time to become competent in Java than it did in C++.

Shouldn't be too bad. The syntax and classes should be very easy for you to grasp. There are some differences but none of it is too challenging.
The hardest part is more about learning the packages, since those will be different. The built in Java classes and functions, and then to use Java in a practical manner, you'll need to learn J2EE or whatever you might be actually using it for. The latter part will probably take more of your time than the language itself.

If you're already a competent programmer (especially in C++) then Java doesn't take long to learn at all. The books I would recommend (in order) for anyone who wants to learn Java are:
Head First Java
Thinking in Java
Effective Java
You may find that you zip through Head First Java rather quickly, given your experience. For that reason I suggest you check it out of the library and skim it before moving on to Thinking in Java.
Also check out Sun's Java Tutorials.

C++ to Java: 1 week.
Java to C++: 1 month.

As Tom Hawtin wrote, the key issue is how you define competent.
You'll be able to pick-up the language fairly easily, but it's the idioms and the libraries that you will have to learn. And there are quite a few differences between niches you work in (e.g. embedded or enterprise), and between libraries that supposedly solve the same problems. Here are a few examples:
In business/enterprise apps, you generally work with databases. There you can have:
plain JDBC
SQL mapper (iBatis), wrapper around verbose and repetitive JDBC
ORM solution (Hibernate), with a philosophy of it's own
With desktop UIs, you have two competing platforms:
Swing, a part of JRE
SWT/JFace, from Eclispe foundation, originated by IBM, with native UI support
Web frameworks are too many to mention, with different ideas of representing the UI, configuration, folder/package structure etc.
DI (dependency injection) is common in business apps, either by 3rd party frameworks like Spring, or as a part of EJB3 standard. But, I don't think it is ever used in embedded set-up.
It would be fair to say this is just a tip of the iceberg.

Back in 1995 when I did it, it took me about half a day to get comfortable with the tools and basic ideas, a day or two to get the language, a week to get the more obscure parts of the language (there were less of them at the time) and a month to get the libraries (there were WAY less of them at that time).
Now I would guess that the tools and basic language will take as much time, a couple of weeks to a month for the obscure parts of the language (depends on what parts you hit, and when). The basic libraries will be a month to two months (java.lang, java.util, and a few others). The remaining class libraries 6 months to forever depending on what you need to learn and how often the keep updating them :-)

I know C++, and had to work with Java once and picked it up in 2 weeks. Of course there were quite a few surprises but it's easy.

I have C++ background. Picking up Java took me few days - the language seems really simple - at least its basis. I still consult my Java guru - google quite a bit, but it's usually a matter of exploring API and standard libraries. Java has some annoyances, but you should spot most of them them easily and quickly.
I was recommended Thinking in Java (there's an ebook for free), but was never persistent enough to read through it. I don't write rocket-science code in Java and to do it, my skills are sufficient.
Having said that, it would be good to have better formal knowledge of the language. At the moment I'm thinking about studying for SCJP, which seems a sensible way of learning, plus you will get well-recoginized programming certificate once you pass it (I've heard it's not worth much, but still it may be a motivation...).
You can also try Java Black Belt - the answers frequenty surprises me. After taking few tests I wonder how my programs even compile, which suggests I'm probably not the most competent Java programmer around :)

How would you define competent? For my money, most professional (as in they do it for money) Java programmers never manage to reach competent.

These days, a programming language derives much of its power from its libraries and accepted idioms.
While it takes relatively short time to learn the Java language, learning to use the available libraries (collections, io, etc.) effectively will probably take significantly more time.

I think there are two approaches to meaning of term "competent Java programmer".
If it is about lexems, syntax and terms of OOP I began to completly understand Java before 2 (two) days of learning.
But firstly you will be charmed by impossibility to shoot your own leg ;)
But if it is case of embeded class system (i.e. packages), APIs references, tips-and-tricks and etc., it takes about half-year to feel yourself friendly with Java. I think.

I too learnt C++ first and then Java. It took very less time as I was already familiar with OOPS concepts. In the initial phase of learning I was really happy with new concepts in Jave like garbage collector. I referred The Complete Reference by Herbert Schildt and it did help me to get the syntax quickly.

I started from C++ and learned C#/.NET. That didn't take long.
As C#/.NET is developed very near to Java (they used many of Java's base techniques such as GC, reference classes, JIT, ...) I think it is not that hard to learn Java.

I would go with six to eight weeks.

Shouldn't take you more than a day or two to learn the language, but you might have to spend a few weeks on the class library: how to use collections, the concurreny package, reflection, logging, swing/awt, dynamic proxies, MBeans etc.

i learned c++ at a small age of 15 and became a professional software programmer. But when i searched for job there was only job available for java developers.I thought it was hard to change my language.So just for trial i Downloaded java compiler and just for fun typed some code and i found it is not much different than c++. and only after 6 hours of research and learning i became a java developer .so it is very easy to switch between c++ to java.