JSONSki 0.0.28

Python binding port for JSONSki

JSONSki

JSONSki is a streaming JSONPath processor with fast-forward functionality. During the streaming, it can automatically fast-forward over certain JSON substructures that are irrelavent to the query evaluation, without parsing them in detail. To make the fast-forward efficient, JSONSki features a highly bit-parallel solution that intensively utilizes bitwise and SIMD operations that are prevelent on modern CPUs to implement the fast-forward APIs.

Installation

pip install JSONSki

Quick Start

import jsonski as jski
print(jski.loadSingleRecord("$.features[150].actor.login", "datasets/test.json"))

import jsonski as jski
print(jski.loadRecords("$.features[150].actor.login", "datasets/test.json"))

• We interface the following method:

jski.loadSingleRecord(args1, args2)    //args1 - String(query) and args2 - String(file_location)

jski.loadRecords(args1, args2)    //args1 - String(query) and args2 - String(file_location)

Requirements

Hardware requirements

• CPUs: 64-bit ALU instructions, 256-bit SIMD instruction set, and the carry-less multiplication instruction (pclmulqdq)
• Operating System: Linux, MacOs (Intel Chips only)
• C++ Compiler: g++ (7.4.0 or higher)

Software requirements

Before starting to use JSONSki-API you need to assure you have the following prerequisites:

• Python (v3.7) see: Installing Python

• C++ : g++ (v7.4.0 and above) see: Installing C++

Getting Started with Querying using JSONSki

JSONPath

JSONPath is the basic query language of JSON data. It refers to substructures of JSON data in a similar way as XPath queries are used for XML data. For the details of JSONPath syntax, please refer to Stefan Goessner's article.

JSONSki Queries Operators

Operator	Description
$	root object
.	child object
[]	child array
*	wildcard, all objects or array members
[index]	array index
[start:end]	array slice operator

Path Examples

Consider a piece of geo-referenced tweet in JSON

{
    "coordinates": [
        40.74118764, -73.9998279
    ],
    "user": {
        "id": 6253282
    },
    "place": {
        "name": "Manhattan",
        "bounding_box": {
            "type": "Ploygon",
            "pos": [
                [-74.026675, 40.683935],
                ......
            ]
        }
    }
}

JsonPath	Result
$.coordinates[*]	all coordinates
$.place.name	place name
$.place.bounding_box.pos[0]	first position of the bounding box in place
$.place.bounding_box.pos[0:2]	first two positions of the bounding box in place

Performance Comparison with Javascript Parsing

Below is an example usage of Jsonski npm package.

#JSONSki
import jsonski as jski
import time

start_time = time.time()
print(jski.loadSingleRecord("$[*].entities.urls[*].url","./JSONSki/dataset/twitter_sample_large_record.json"))
end_time = time.time()
elapsed_time = end_time - start_time
print("Elapsed jsonski time:", elapsed_time, "seconds")


#Python`s inbuilt JSON parser
import json as j

start_time = time.time()
def parse_json_file(file_path):
    with open(file_path, 'r') as file:
        json_data = j.load(file)
        return json_data
json_file_path = './JSONSki/dataset/twitter_sample_large_record.json'
print(parse_json_file(json_file_path))
end_time = time.time()
elapsed_time = end_time - start_time
print("Elapsed default_python_json time:", elapsed_time, "seconds")

• Note: The code snippet above benchmarks performance for Python parsing VS JSONSki parsing.

Publication

[1] Lin Jiang and Zhijia Zhao. JSONSki: Streaming Semi-structured Data with Bit-Parallel Fast-Forwarding. In Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2022.

@inproceedings{jsonski,
  title={JSONSki: Streaming Semi-structured Data with Bit-Parallel Fast-Forwarding},
  author={Lin Jiang and Zhijia Zhao},
  booktitle={Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)},
  year={2022}
}

Performance

Benchmarking

Performance of JSONSki_nodejs is compared with simdjson_nodejs and Javascript Parsing - https://github.com/AutomataLab/NPM-JSON-Parser-Benchmarking