You can read the file entirely in an in-memory data structure (a tree model), which allows for easy random access to all the data. Using SQL to Parse a Large JSON Array in Snowflake - Medium Parabolic, suborbital and ballistic trajectories all follow elliptic paths. Anyway, if you have to parse a big JSON file and the structure of the data is too complex, it can be very expensive in terms of time and memory. How to manage a large JSON file efficiently and quickly If you have certain memory constraints, you can try to apply all the tricks seen above. To get a familiar interface that aims to be a Pandas equivalent while taking advantage of PySpark with minimal effort, you can take a look at Koalas, Like Dask, it is multi-threaded and can make use of all cores of your machine. She loves applying Data Mining and Machine Learnings techniques, strongly believing in the power of Big Data and Digital Transformation. JSON data is written as name/value pairs, just like JavaScript object Are there any canonical examples of the Prime Directive being broken that aren't shown on screen? How much RAM/CPU do you have in your machine? JavaScript names do not. Bank Marketing, Low to no-code CDPs for developing better customer experience, How to generate engagement with compelling messages, Getting value out of a CDP: How to pick the right one. You should definitely check different approaches and libraries. document.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() ); This site uses Akismet to reduce spam. If youre working in the .NET stack, Json.NET is a great tool for parsing large files. Refresh the page, check Medium s site status, or find Split huge Json objects for saving into database, Extract and copy values from JSONObject to HashMap. Here is the reference to understand the orient options and find the right one for your case [4]. There are some excellent libraries for parsing large JSON files with minimal resources. One is the popular GSON library . It gets at the same effe In the past I would do Why in the Sierpiski Triangle is this set being used as the example for the OSC and not a more "natural"? It gets at the same effect of parsing the file as both stream and object. Using Node.JS, how do I read a JSON file into (server) memory? Hire Us. A strong emphasis on engagement-based tracking and reporting, coupled with a range of scalable out-of-the-box solutions gives immediate and rewarding results. Required fields are marked *. Is there any way to avoid loading the whole file and just get the relevant values that I need?