Skip to content

Latest commit

 

History

History
130 lines (112 loc) · 3.78 KB

README.md

File metadata and controls

130 lines (112 loc) · 3.78 KB
Raw

JSON to XML Statistics Converter

This Java application provides a command-line interface for processing JSON files and generating XML statistics files based on specified attributes.

Features

  • Processes JSON files in a specified directory.
  • Extracts specified attributes from JSON files.
  • Generates XML statistics files for each attribute based on attribute value counts.
  • Utilizes multi-threading for efficient processing.

Usage

Prerequisites

  • Java 17 or higher
  • Maven

Installation

  1. Clone this repository to your local machine:

    git clone https://github.com/vr242kj/JsonToXml.git

  2. Go to the project directory

  3. Build the project using Maven:

    mvn clean install

  4. Run the application using Maven with the following command:

    mvn compile exec:java "-Dexec.args=<directory_path> <attribute_names>"

    Replace <directory_path> with the path to the directory containing your JSON files and <attribute_names> with a comma-separated list of attribute names without any spaces.
    Example:

    mvn compile exec:java "-Dexec.args=/path/to/json/files attribute1,attribute2"

Additional Information

These are simple examples of JSON schemas that the application operates with.

- [ { key: [value1, value2, value3] } ] array of values
- [ { key: [{},{},{}] } ]               array of objects
- [ { key: {} } ]                       object
- [ { key: value } ]                    value

The data in JSON files must be in an array (start with an array). For example:

[
  {
    "title": "1984",
    "author": "George Orwell",
    "year_published": 1949,
    "genre": "Dystopian, Political Fiction"
  },
  {
    "title": "Pride and Prejudice",
    "author": "Jane Austen",
    "year_published": 1813,
    "genre": "Romance, Satire"
  },
  {
    "title": "Romeo and Juliet",
    "author": "William Shakespeare",
    "year_published": 1597,
    "genre": "Romance, Tragedy"
  }
]

The result of the program is an XML file with the name statistics_by_attribute.xml
In this case, the attribute is genre

<statistics>
  <item>
   <value>Romance</value>
   <count>2</count>
  </item>
  <item>
   <value>Dystopian</value>
   <count>1</count>
  </item>
  <item>
   <value>Satire</value>
   <count>1</count>
  </item>
  <item>
   <value>Political Fiction</value>
   <count>1</count>
  </item>
  <item>
   <value>Tragedy</value>
   <count>1</count>
  </item>
</statistics>

Performance

For testing, eight JSON files were created with a total size of 35 MB.
Processor - Intel(R) Core(TM) i5-8265U CPU @ 1.60GHz, 1800MHz, 4 cores, 8 logic processors

Performance test results with different numbers of threads:
Test 1

  • Execution time with thread pool size 1: 69 ms
  • Execution time with thread pool size 2: 22 ms
  • Execution time with thread pool size 4: 17 ms
  • Execution time with thread pool size 8: 14 ms

Test 2

  • Execution time with thread pool size 1: 58 ms
  • Execution time with thread pool size 2: 21 ms
  • Execution time with thread pool size 4: 20 ms
  • Execution time with thread pool size 8: 27 ms

Test 3

  • Execution time with thread pool size 1: 56 ms
  • Execution time with thread pool size 2: 17 ms
  • Execution time with thread pool size 4: 15 ms
  • Execution time with thread pool size 8: 18 ms

Test 4

  • Execution time with thread pool size 1: 61 ms
  • Execution time with thread pool size 2: 18 ms
  • Execution time with thread pool size 4: 17 ms
  • Execution time with thread pool size 8: 17 ms

Conclusions: According to the results of the tests we can observe performance improvement when using 2 threads, weak improvement when using 4 threads, but increasing up to 8 threads may not always be advantageous. It may depend on the amount of test data or technical characteristics of the computer on which the tests were conducted.