#Rails postgres json query code

It’s doing in 22 seconds what used to take 3 minutes. This algorithm performs just fine in plain Ruby now that it’s inherently efficient. Keep those computer science fundamentals in mind, especially as the data gets bigger! There’s no point in trying to optimize a poor algorithm by writing faster code. Here’s what that difference looks like in a graph of time and memory vs data size:

We were able to rewrite this algorithm as O(n). We discovered that one of our AppMap post-processing algorithms had an O(n²) running time. But as the data grows to dozens of MB and beyond, algorithm design becomes very important. With a few hundred KB of data, most simple algorithms will perform about the same.

#Rails postgres json query code

Here’s an example of our Go client code sending multipart/mixed 2. The JSON data is loaded efficiently into PostgreSQL, without having to sacrifice all the benefits provided by the Rails framework. In this way, we minimize the amount of request processing that’s performed in the application tier. So, we disable Rails JSON parsing behavior by sending content type multipart/mixed instead of application/json. Since all we want to do is insert the data into PostgreSQL, and PostgreSQL can parse the JSON itself, we don’t need Rails to do any parsing. When Rails receives an HTTP request with content type application/json, it parses the request JSON into Ruby objects and then passes this data, as params, to the controller. When AppMap data is received by the AppMap server, we want to get it into PostgreSQL as fast as possible. So, without further ado, here are four ways to accelerate JSON processing with Rails and PostgreSQL. In this post, I’m describing some of the ways that we scaled up our architecture to handle these large JSON files. As hundreds, and then thousands of JSON files were generated from these large repos and pushed into the AppMap server, our server became stressed and we had to dig in and optimize. But before long, AppMap server users started to record some very large apps, including monolithic Java and Ruby repos with up to 1 million lines of code. In the initial development period of the AppMap server, AppMap files typically ranged from a few KB up to a few hundred KB. Naturally, we use the powerful JSONB data type to store the JSON data in the database. Our stack is vanilla Rails and PostgreSQL. The AppMap server is built to ingest and process large AppMap JSON files. Users can view and analyze AppMaps locally using the AppMap extension for VS Code, and also push AppMaps to AppMap Cloud for analytics, sharing, discussion etc. The framework provides client agents for Ruby, Java and Python (early access) that record running code and generate JSON files called AppMaps. SELECT 'transactions'.* FROM 'transactions' WHERE ('transactions'.'payload' -> 'invoice_number' ILIKE '%123%')īasically performing a search for records in transactions table that have a key called invoice_number with value containing a string 123, within a JSON column payload.AppMap is an open source framework that developers can use to record, analyze, and optimize end-to-end code and data flows. Now with our search set on link_type_cont (cont being just one of Ransack available search predicates), if the user entered for example 123 in the search filed, it would generate a query like this: To achieve this we added the following ransacker to our Transaction modelĪrel::Nodes::InfixOperation.new('->', parent.table, 'invoice_number') In our case we needed to perform a search within transactions table and payload JSON column, looking for records containing a key called invoice_number. You can find more information on Arel here.

The premise behind Ransack is to provide access to Arel predicate methods. We were alredy using Ransack for building search forms within the application, so we needed a way of telling Ransack to perform a search by given key in our JSON column. While working on a Ruby on Rails application that used PostgreSQL database to store data, we came a across an issue where we needed to implement a search by key within a JSON column. Starting with v9.2, PostgreSQL added native JSON support which enabled us to take advantage of some benefits that come with NoSQL database within a traditional relational database such as PostgreSQL.

Using Ransack to search for a key in PostgreSQL JSON column