jsonparser VS zed

In this article, I will introduce you to a new package called astjson that I have been working on for the last couple of weeks. It is a Go package that allows you to transform and merge JSON objects with unmatched speed. It is based on the jsonparser package by buger aka Leonid Bugaev and extends it with the ability to transform and merge JSON objects at unparalleled performance.

Use this to extract the data value, and handle/unmarshal it accordingly.

jsonparser can decode, but can't encode

Best I've found is this: https://github.com/buger/jsonparser

I was actually just trying to get it into a []byte to use this package which claims it works well for unknown data structures.

`jj` is a little tool I wrote that uses https://github.com/buger/jsonparser

If you don't know the schema or you only need to access one or two fields in a much larger JSON object, I would recommend https://github.com/buger/jsonparser as it provides an easy API to access specific values without fully unmarshaling. This is an unusual use case though, 9 times out of 10 I would tend to use easyjson.

Reading and navigating arbitrary JSON: I've used https://github.com/tidwall/gjson, many others like https://github.com/buger/jsonparser are also out there.

VAST is an open-source SecDataOps project for working with data from open-source security tools. Version 3.0 adds a pipeline syntax similar to splunk, Kusto, PRQL, and Zed.

Cool, I didn't realize you used sqlite-utils for your performance demo!

It's not particularly designed for speed - it should be fast as far as Python code goes (I use some generator tricks to stream data and avoid having to load everything into memory at once) but I wouldn't expect "sqlite-utils insert" to win any performance competitions with tools written in other languages.

Those benchmarks against sqlite itself are definitely interesting. I'm looking forward to playing with the "native ZNG support for Python" mentioned on https://github.com/brimdata/zed/blob/main/docs/libraries/pyt... when that becomes available.

Hi, all. Author here. Thanks for all the great feedback.

I've learned a lot from your comments and pointers.

The Zed project is broader than "a jq alternative" and my bad for trying out this initial positioning. I do know there are a lot of people out there who find jq really confusing, but it's clear if you become an expert, my arguments don't hold water.

We've had great feedback from many of our users who are really productive with the blend of search, analytics, and data discovery in the Zed language, and who find manipulating eclectic data in the ZNG format to be really easy.

Anyway, we'll write more about these other aspects of the Zed project in the coming weeks and months, and in the meantime, if you find any of this intriguing and want to kick the tires, feel free to hop on our slack with questions/feedback or file GitHub issues if you have ideas for improvements or find bugs.

Thanks a million!

https://github.com/brimdata/zed

In my observation, mock data has tended to be used in a rather loose, slipshod, careless manner. Unlike documentation, it is treated as the garbage of software material. (Sometimes even referred to as "garbage data"). People will try to avoid writing it by using elaborate "generators" such as jFairy or zed.

There are a few examples in the ZSON spec...

https://github.com/brimdata/zed/blob/main/docs/formats/zson....

And you can easily see whatever data you'd like formatted as ZSON using the "zq" CLI tool, but I just made this gist (with some data from the brimdata/zed-sample-data report) so you can have a quick look (the bstring stuff is a little noisy and an artifact of the data source being Zeek)... https://gist.github.com/mccanne/94865d557ca3de8abfd3eb09e8ac...