I’ve been building web UIs in Angular and React for the last few years, and I’ve started to greatly prefer React. Extracting and using UI components is just easier and, for lack of a better word, more JavaScripty.

Extracting components in React

Say I notice that I’m creating multiple <span> elements with the same class and icon:

function Main() {
  return (
    <div>
      <span class="alert-tag"><i class="fa alert"></i>foo</span>
      <span class="alert-tag"><i class="fa alert"></i>bar</span>
      <span class="alert-tag"><i class="fa alert"></i>baz</span>
    </div>
  );
}

It’s trivial to refactor this repeated element into its own <Alert> component function within the same file:

function Main() {
  return (
    <div>
      <Alert>foo</Alert>
      <Alert>bar</Alert>
      <Alert>baz</Alert>
    </div>
  );
}

function Alert({ children }) {
  return (<span class="alert-tag"><i class="fa alert"></i>{children}</span>);
}

Super easy, uses JavaScript’s native language constructs, and I was able to do it all within the same file (but I can easily move Alert() elsewhere for wider re-use if needed). It’s just like extracting a function in a “regular” programming language, it’s something you do without even thinking about it.

I recently read 2 papers that I’d highly recommend if you ever wonder about the underpinnings of modern relational databases:

What Goes Around Comes Around (Stonebraker and Hellerstein, 2005)

This is an opinionated history of database architectures from roughly 1970 to 2005, and it’s got some serious credentials behind it – Michael Stonebraker was the driving force behind Postgres and many other things. It’s an easy read, and it’s a good explanation of how relational DBs and SQL came to (mostly) rule the world. It was written amidst a lot of hype over XML databases, and it (rightly, in retrospect) critiques XML DBs and suggests that they won’t see much commercial adoption.

One interesting bit: Stonebraker and Hellerstein do not like SQL, and they claim that it became dominant largely because of IBM’s dominance in the marketplace during the 1980’s. Which leads us to the next item…

A Critique of the SQL Database Language (Chris Date, 1983)

This was cited approvingly in the 1st paper as a “scathing critique of the semantics of SQL”, which caught my eye - virtually every database supports SQL, how bad can it be?

I won’t summarize the entire thing, it’s a laundry list of complaints, but this resonated with me:

Notice that it is just table-names that appear in the FROM clause. Completeness suggests that it should be table-expressions (as Gray puts it, “anything in computer science that is not recursive is no good”).

…a simple table-reference (i.e. a table-name) ought to be just a special case of a general table-expression

To give a (trivial) example, say we want to union 2 tables and extract a column. We’d write that like this in SQL:

SELECT EMPLOYEE_ID FROM EMPLOYEES
UNION
SELECT EMPLOYEE_ID FROM CONTRACTORS

But if table names were just special cases of table expressions, we could write it like this instead:

SELECT EMPLOYEE_ID FROM (EMPLOYEES UNION CONTRACTORS)

SQL gets the job done, and it could be a lot worse - but it is a little sad that many of the issues academics have known about for 35+ years still exist today. It’s a reminder of how entrenched something that’s only “good enough” can become.

I recently rewrote most of this website (more on that soon!) and it’s now much easier to work on. Last week, I shipped a feature that I really like: dark mode using the new prefers-color-scheme media query. If you have dark mode enabled in your OS and a reasonably new browser, reillywood.com now shows you a dark UI using the Solarized colour scheme:

I’m taking a self-funded sabbatical after 8 years of working full-time. It feels like the right thing to do at this stage of my career.

I’ve had an unusually stable career for a software developer. When I graduated from university in 2011 I interviewed at a few places, including a mid-sized investment firm. I didn’t know anything about finance and the… rustic state of their website was a little concerning, but the people seemed great. So I took the job, and told myself I’d stick around for 2 or 3 years.

8 years later I was still at the same company. Orbis offers a lot of different opportunities; I wrangled big financial data systems, ran a small team, got my hands dirty building a modern web stack, and worked in London and Cape Town. It was a blast, and I’d highly recommend Orbis as an employer.

Still, after 8 years, it’s time to try something new. I miss the open-ended learning that’s so common in school, and I want to explore my technical interests with no regard for immediate relevance to my day job. Gianfranco Chicco’s description of a “serendipity break” really resonated with me:

In the note I sent out to my friends and network I mentioned that I’d be undertaking a Serendipity Break, which wasn’t a nice way to say that I wasn’t going to work for a few months but that I wanted to actively explore different possible paths.

In the book The Craftsman, sociologist Richard Sennett describes how “skill builds by moving irregularly, and sometimes by taking detours”, which is akin to keeping the Serendipity Engine in perpetual motion to encourage the strengthening of current skills and allowing the development of new ones.

Leaving a great job at a great company was a little scary, but I think it’s necessary for my long-term growth. Reading about Joel Spolsky’s sabbaticals helped a lot; it’s reassuring to see successful developers following similar paths.

My last day at Orbis was July 27th, and since then I’ve been trying all kinds of things. I’ve been diving into database internals, rewriting this website, and even learning Lisp/Scheme. I’m not exactly sure where my interests will take me next, but I’m looking forward to finding out.

Here’s something I’ve found useful in SQL Server, but it should apply in any DBMS with checksum functions. Next time you’re refactoring some database objects and you want to do some regression testing, give the CHECKSUM (MSDN) and CHECKSUM_AGG (MSDN) functions a try.

CHECKSUM and CHECKSUM_AGG

They behave pretty much as you would expect; CHECKSUM returns 1 checksum given 1 row, and CHECKSUM_AGG is an aggregate function that returns 1 checksum given multiple checksum rows. Between the two of them, you can get a checksum for any arbitrary collection of data:

-- Returns 2 rows with 2 columns
SELECT Field1, Field2
FROM (VALUES ('foo','bar'),('baz','foo')) TempTable(Field1,Field2)

-- Returns 2 rows with 1 checksum column
SELECT CHECKSUM(Field1,Field2)
FROM (VALUES ('foo','bar'),('baz','foo')) TempTable(Field1,Field2)
 
-- Returns 1 row with 1 checksum column
SELECT CHECKSUM_AGG(CHECKSUM(Field1,Field2))
FROM (VALUES ('foo','bar'),('baz','foo')) TempTable(Field1,Field2)

Regression testing

These help with a common problem: when you’re refactoring a database object, how can you be sure that you haven’t changed the existing functionality? Sometimes it’s enough to spot check a few inputs, but often the logic is complex enough that this does not provide a high level of confidence. With CHECKSUM and CHECKSUM_AGG, you can quickly check large numbers of test cases.

For example, say we have a TVF called MyDateTVF that takes in a date parameter and returns columns Column1 and Column2. I want to refactor this function and then test that the functionality is unchanged for every date in 2018. If we have a table called DateList which contains every date (more useful than you might expect in a DB with a lot of temporal aspects), I can simply run the following before and after my change:

SELECT CHECKSUM_AGG(CHECKSUM(MDT.Column1, MDT.Column2))
FROM DateList DL
CROSS APPLY (
    SELECT Column1, Column2 from dbo.MyDateTVF(DL.Date)
) MDT
WHERE DL.Date BETWEEN '2018-01-01' AND '2018-12-31'

If that query returns the same checksum before and after my change, we can rule out any regressions for those inputs. Nice and easy!