Sometimes you might want to access Apache Kafka that’s running on your local machine from another device not on the same network. I’m not sure I can think of a production use-case, but there are a dozen examples for sandbox, demo, and playground environments.
In this post we’ll see how you can use ngrok to, in their words, Put localhost on the internet. And specifically, your local Kafka broker on the internet.
When I started my journey learning Apache Flink one of the things that several people expressed an interest in hearing more about was PyFlink. This appeals to me too, because whilst Java is just something I don’t know and feels beyond me to try and learn, Python is something that I know enough of to at least hack my way around it. I’ve previously had fun with PySpark, and whilst Flink SQL will probably be one of my main focusses, I also want to get a feel for PyFlink.
The first step to using PyFlink is installing it - which should be simple, right?
So far I’ve plotted out a bit of a map for my exploration of Apache Flink, looked at what Flink is, and run my first Flink application. Being an absolutely abysmal coder—but knowing a thing or two about SQL—I figure that Flink SQL is where my focus is going to lie (I’m also intrigued by PyFlink, but that’s for another day…).
🎉 I just ran my first Apache Flink cluster and application on it 🎉
A brief diversion from my journey learning Apache Flink to document an interesting zsh oddity that briefly tripped me up:
cd: string not in pwd: flink-1.17.1
My journey with Apache Flink begins with an overview of what Flink actually is.
What better place to start than the Apache Flink website itself:
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.
Like a fortunate child on Christmas Day, I’ve got a brand new toy! A brand new—to me—open-source technology to unwrap, learn, and perhaps even aspire to master elements of within.
I joined Decodable two weeks ago, and since Decodable is built on top of Apache Flink it seems like a great time to learn it. After six years learning Apache Kafka and hearing about this “Flink” thing but—for better or worse—never investigating it, I now have the perfect opportunity to do so.
Writing is one of the most powerful forms of communication, and it’s useful in a multitude of roles and contexts. As a blog-writing, documentation-authoring, twitter-shitposting DevEx engineer I spend a lot of my time writing. Recently, someone paid me a very nice compliment about a blog I’d written and asked how they could learn to write like me and what resources I’d recommend.
Never one to miss a chance to write and share something, here’s my response to this :)
This was originally titled more broadly “What Does A DevEx Engineer Do”, but that made it into a far too tedious and long-winding etymological exploration of the discipline. Instead, I’m going to tell you what this particular instantiation of the entity does 😄
Wordpress still, to an extent, rules the blogging world. Its longevity is testament to…something about it ;) However, it’s not my favourite platform in which to write a blog by a long way. It doesn’t support Markdown to the extent that I want. Yes, I’ve tried the plugins; no, they didn’t do what I needed.
I like to write all my content in a structured format - ideally Asciidoc, but I’ll settle for Markdown too. Here’s how I stayed [almost] sane whilst composing a blog in Markdown, reviewing it in Google Docs, and then publishing it in Wordpress in a non-lossy way.
One of the most important ways that a project can help its developers is providing them good documentation. Actually, scratch that. Great documentation.
java.lang.ClassNotFoundException: delta.DefaultSourceNo great insights in this post, just something for folk who Google this error after me and don’t want to waste three hours chasing their tails… 😄
Here’s a neat little trick you can use with DuckDB to convert a CSV file into a Parquet file:
COPY (SELECT *
FROM read_csv('~/data/source.csv',AUTO_DETECT=TRUE))
TO '~/data/target.parquet' (FORMAT 'PARQUET', CODEC 'ZSTD');
It all started with a tweet.
What do you do when you want to query over multiple parquet files but the schemas don’t quite line up? Let’s find out 👇🏻
As we enter December and 2022 draws to a close, so does a significant chapter in my working career—later this month I’ll be leaving Confluent and onto pastures new.
It’s nearly six years since I wrote a 'moving on' blog entry, and as well as sharing what I’ll be working on next (and why), I also want to reflect on how much I’ve benefited from my time at Confluent and particularly the people with whom I worked.
In my quest to bring myself up to date with where the data & analytics engineering world is at nowadays, I’m going to build on my exploration of the storage and access technologies and look at the tools we use for loading and transforming data.
I started my dbt journey by poking and pulling at the pre-built jaffle_shop demo running with DuckDB as its data store. Now I want to see if I can put it to use myself to wrangle the session feedback data that came in from Current 2022. I’ve analysed this already, but it struck me that a particular part of it would benefit from some tidying up - and be a good excuse to see what it’s like using dbt to do so.
I’ve been wanting to try out dbt for some time now, and a recent long-haul flight seemed like the obvious opportunity to do so. Except many of the tutorials with dbt that I found were based on using Cloud, and airplane WiFi is generally sucky or non-existant. Then I found the DuckDB-based demo of dbt, which seemed to fit the bill (🦆 geddit?!) perfectly, since DuckDB runs locally. In addition, DuckDB had appeared on my radar recently and I was keen to check it out.
