Recently, we were faced with a very trivial yet challenging issue in Sidekiq. One of our models gets updated frequently which results in triggering a bunch of after_update callbacks that sends a reindex signal to our Elasticsearch engine.
Recently we faced a situation where we have to retain a pretty big form data if the user got redirected back to our site from payment gateway in case of payment failure. We chose local storage to resolve this issue. Let’s see how we implemented local storage using Vuex.
We often develop our DL models without many difficulties but training them with a huge amount of dataset is always a painful task when you have limited computing resources.
When it comes to Full-Text text search Elasticsearch does an amazing job and has a plethora of ways to search for data to your heart’s content. Most of the times, it matters how you index the data. With Lucene’s powerful Inverted Index fueling ES, we will look into how to make use of one of its elementary search techniques for Full-Text Search - simple_query_string
The most valuable asset for any organization is their employees. The abilities to source, engage, and retain qualified talents are some of the main catalysts in driving the long-term success of an organization. With heavy competition for talents across all industries, the ability to hire the best talents is a high priority for organizations. Especially, for a startup, it is very much necessary to have the right resources in place because it could make or break the company in the early stages.
There is a common misconception among Software Engineers to have a lot of code inside a model and that it is perfectly fine backed by the theory of having “Fat” Models and Skinny Controllers. Is it correct? Absolutely. However, when you inspect the code in detail, what they’ve written or designed are not “fat”, but “bloated” models.
We as Rails developers would have come across the need to execute a query and get results as an array of hashes.