Migrating a project from java 8 to java 9

Now that Java 9 is out, I decided to migrate to it my pet project, which is around 120K lines of java.

The first step is to just start compiling and running against jdk9, without using any of its features yet.

This is an account of the surprisingly few issues that I encountered during this first step and how I resolved them.

Issue #1: Object.finalize() has been deprecated.

A Hacker's Tale (With a Human Side)

Screenshot of Borland Turbo Debugger found on the interwebz, possibly the same version that I was using back then.

This is a hacking story from my University years. It ends with a nice bit about human qualities. 

Grumpy Posts

Besides the delicate grumpiness which is gratuitously scattered throughout this blog like the golden rays of light in a gentle sunset, there exist a few blog posts which have been written with the express purpose of venting out some major grumpiness.

Here is a list of them:

On UML (oh, do not get me started)

The Wild, Wild Web

On JUnit's random order of test method execution

On UUIDs and GUIDs

On scripting languages

Why Oracle sucks

The GWX (Get Windows 10) KB3035583 trojan horse

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(The list will be extended as more posts are added.)

Rich Hickey - Simple Made Easy

"Simple Made Easy" presentation by Rich Hickey from the InfoQ Software Development Conference, recorded at Strangeloop 2011

Watch the presentation here: https://www.infoq.com/presentations/Simple-Made-Easy 

(the slideshow plays alongside with the video.)

My notes on the presentation:

"Simplicity is prerequisite for reliability" - Edsger W. Dijkstra

Simple vs. Complex, Easy vs. Hard

What is wrong with UUIDs and GUIDs

Introduction

Universally Unique Identifiers (UUIDs) otherwise known as Globally Unique Identifiers (GUIDs) are 128-bit numbers that are often used to identify information. In its canonical representation, a UUID looks like this: 2205cf3e-139c-4abc-be2d-e29b692934b0.

The Wikipedia entry for Universally Unique Identifier (⬀) says that they are for practical purposes unique and that while the probability that a UUID will be duplicated is not zero, it is so close to zero as to be negligible. Wikipedia then does the math and shows that if 103 trillion UUIDs are generated, the chance of duplication among them is one in a billion.

Despite the infinitesimally small chances of receiving a duplicate UUID, there exist programmers out there who are afraid of this actually happening, and who will not hesitate to suspect duplicate UUIDs as being responsible for an observed malfunction rather than first look for a bug in their code. Clearly, these folks do not understand the meaning of infinitesimally small chance, so let me try to explain it:

Infinitessimally small chance means practically impossible to happen, and the practically part is only mentioned for scientific correctness: practically, you can disregard the word practically and consider it as simply impossible to happen.

Great. Now, let me tell you why I hate UUIDs.

6 videos from TechSummit Amsterdam 2017 (Jun 1st)

A couple of weeks ago some of us went to the TechSummit conference organized by LeaseWeb.  Here is a list of the talks that I attended, along with a short description for each.

The first presentation was “Shaving my head made me a better programmer” by Alex Qin, which was about what it is like to be a woman, and specifically a programmer, in the U.S. tech industry.  (And in the University before that.)  She talked about the inequality, the sexism, and the harassment.   She mentioned that she once gave a talk in a really big conference about accessibility in the U.S., and afterwards she was asked “How do I talk to women at bars?”  The head-shaving part refers to how changing her appearance resulted in being taken more seriously.  It was quite an interesting talk, though I suspect that in Amsterdam, she was to a large extent preaching to the choir.

 

My notes on the Fielding Dissertation (REST)

These are my notes on Roy T. Fielding's famous Ph.D. dissertation "Architectural Styles and the Design of Network-based Software Architecture"

What follows are excerpts from the dissertation, with my notes usually in parentheses.

Roy Thomas Fielding is: chief Scientist in some tech company; Chairman, Apache Software Foundation; Visiting Scholar, W3C @ MIT CS Lab; etc; Publications, Honors, Awards, Fellowships etc. Involved in the authoring of the Internet standards for the Hypertext Transfer Protocol (HTTP) and Uniform Resource Identifiers (URI).

Abstract:

"The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia system."

(He makes it sound as if it was designed this way on purpose.)

"In order to identify [...] aspects of the Web that needed improvement and avoid undesirable modifications, a model for the modern Web architecture was needed to guide its design, definition, and deployment."

(So, he admits the need to build a model after the fact.)

"An architectural style is a named, coordinated set of architectural constraints."

YouTube: Roy T. Fielding: Understanding the REST Style

A youtube videoclip titled "Roy T. Fielding: Understanding the REST Style"

Quote: "It's really an accessible piece of work.  It is not full of equations.  There is one equation.  The equation is there just to have an equation, by the way."

For my notes on REST, see other post: "My notes on the Fielding Dissertation (REST)"

https://blog.michael.gr/2017/06/my-notes-on-fielding-dissertation-rest.html

On scripting languages

Foreword

Historically, the difference between scripting languages and real programming languages has been understood as the presence or absence of a compilation step. However, in recent decades the distinction has blurred; from time to time we have seen:

• Interpreters for languages that were originally meant to be compiled.
• Compilers for languages that were originally meant to be interpreted.
• Scripting engines internally converting source code to bytecode before interpreting it.
• Real languages compiling to bytecode which is then mostly interpreted and rarely converted to machine code.

So, compiled vs. interpreted does not seem to be the real differentiating factor; nonetheless, we can usually tell a scripting language when we see one. So, what is it that we see?

Devoxx 2016 Belgium - Microservices Evolution: How to break your monolithic database by Edson Yanaga

My notes on Devoxx 2016 Belgium - Microservices Evolution: How to break your monolithic database by Edson Yanaga (I attended this conference)

Reduce maintenance window
Achieve zero downtime deployments
"Code is easy, state is hard"
Changes in a database schema from one version to another are called database migrations
Tools: Flyweight Liquibase
Migrations require back and forward compatibility
Baby steps = Smallest Possible Batch Size
Too many rows = Long Locks
Shard your updates (not updating the entire table in one go)

Renaming a column
    ALTER TABLE customers RENAME COLUMN wrong TO correct;
   becomes:
        ALTER TABLE customers ADD COLUMN correct VARCHAR(20);
   UPDATE customers SET correct = wrong WHERE id < 100;
   UPDATE customers SET correct = wrong WHERE id >= 100 AND id < 200;
   ...
   (later) ALTER TABLE customers DELETE COLUMN wrong;

Adding a column
ADD COLUMN, setting NULL/DEFAULT value/computed value
Next release: Use Column

Renaming / Changeing Type / Format of a Column:
Next version: ADD COLUMN, Copy data using small shards
Next release: Code reads from old column and writes to both
Next release: Code reads from new column and writes to both
Next release: Code reads and writes from new column
Next release: Delete old column

Deleting a column
    Next version: Stop using the column but keep updating the column
Next version: Delete the column

For migrating from a monolithic application with a monolithic database to many microservices with own database each:
    Using Event Sourcing
        tool: debezium.io
    You tell it which tables you want to monitor, and from then on it monitors them
and generates an event for each DDL/DML statement you issue.
The event is propagated to as many event consumers as you want.
So, microservices can receive these events and update their own databases.

"HTTP and REST are incredibly slow"