Recently, I was working on an application that required reading hierarchically structured data. And I thought it might be useful to document multiple ways to store and query such hierarchical data (ex. Org. chart, File-system layout, or Set of tasks in a project) in a database. So, let’s jump right in.
Definitions first – what is hierarchical data?
Hierarchical data is a specific kind of data, characterized by a hierarchical relationship between the data sets.
Think about data sets having multiple levels: something above, something below, and a few at the same level. A typical example of such hierarchical model is an organizational chart like the one below.
Most modern-day relational database systems use SQL MERGE (also called UPSERT) statements to INSERT new records or UPDATE existing records if a matching row already exists. UPSERT is a combination of Insert and Update, driven by a “PRIMARY KEY” on the table.
Average(mean), median, mode are core statistical concepts, that are often applied in software engineering. Whether you are new to programming or have multi years of computer science experience, you’ve likely at some point in time will have used these statistical functions, say to calculate system resource utilization, or network traffic or a website latency. In my current role, my team is responsible for running a telemetry platform to help dev teams measure application performance. We do this by collecting point-in-time data points referred as metrics.
A common use case for metrics is to tell the application latency(i.e. amount of time it took between a user action and web app response to that action). For examples, amount of time it took you to click on twitter photo and till it finally showed up on your device screen. So if you have this metrics collected at regular intervals (say every 1s), you can simply average it over a period of time like an hour or a day to calculate latency. Simple right!
I don’t think there has been a better year than 2020 to read. With most of us confined to our homes at some point during the year due to pandemic, books (and Netflix!) have become more popular than ever.
In this post, I’m reviewing all the books I have read in the year. Hopefully you’ll enjoy these quick reviews, plus I’ve also added a favorite quote from each.
Wow! I can’t believe this is my 25th post and have no idea how I made it this far. During my academic years, I barely liked to read anything, let alone write. So then what got me here and why I started to blog? Here’s my Top 5 (in no specific order)
PS. I don’t want to give the illusion that this post will be full of advice for you to start a blog, still, you might find somethings relatable …
SQL injection is a code injection technique that is capable of destroying your database. It is a code injection technique, used to attack data-driven applications, in which malicious SQL statements are inserted into an entry field for execution. (e.g. to dump the database contents to the attacker)
A transaction is a unit of work that you want to treat as “a whole.” It has to either happen in full or not at all. In Go lang, a transaction is essentially an object that reserves a connection to the database. You begin a transaction with a call to db.Begin() and close it with a commit() or rollback() method on the resulting Tx variable.
A Novel about Developers, Digital Disruption, and Thriving in the Age of Data
Over a month ago, I read the book “The Phoenix Project” and published a review on my blog. The book was certainly amazing as it touched on so many important aspects of software development, DevOps and my own IT career. To my surprise, I found that the book also has a sequel “The Unicorn Project“.
In the last post Updating/Deleting rows with Go, we learned to manipulate rows in PostgreSQL database in Go project using database/sql package that ships with Go, along with github.com/lib/pq Postgres driver. In this post, we’ll learn how to query rows i.e. SELECT