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uniVocity-parsers: A powerful CSV/TSV/Fixed-width file parser library for Java

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uniVocity-parsers: A powerful CSV/TSV/Fixed-width file parser library for Java

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uniVocity-parsers is an open-source project CSV/TSV/Fixed-width file parser library in Java, providing many capabilities to read/write files with simplified API, and powerful features as shown below.

Unlike other libraries out there, uniVocity-parsers built its own architecture for parsing text files, which
focuses on maximum performance and flexibility while making it easy to extend and build new parsers.


Overview Installation Features Overview Reading CSV/TSV/Fixed-width Files Writing CSV/TSV/Fixed-width Files Performance and Flexibility Design and Implementations

1. Overview

I'm a Java developer working on a web-based system to evaluate telecommunication carriers' network and work out reports. In the system, the CSV format was heavily involved for the network-related data, such as real-time network status (online/offline) for the broadband subscribers, and real-time traffic for each subscriber. Generally the size of a single CSV file would exceed 1GB, with millions of rows included. And we were using the library JavaCSV as the CSV file parser. As growth in the capacity of carriers' network and the time duration our system monitors, the size of data in CSV increased so much. My team and I have to work out a solution to achieve better performance (even in seconds) in CSV files processing, and better extendability to provide much more customized functionality. We came across this library uniVocity-parsers  as a final solution after a lot of testing and analysis, and we found it great. In addition of better performance and extendability, the library provides developers with simplified APIs, detailed documents & tutorials and commercial support for highly customized functionality. This project is hosted at Github  with 62 stars & 8 forks (at the time of writing). Tremendous documents & tutorials are provided at here  and here. You can find more examples and news here as well. In addition, the well-known open-source project Apache Camel integrates uniVocity-parsers for reading and writing CSV/TSV/Fixed-width files. Find more details here.

2. Installation

I'm using version 1.5.1 , but refer to the official download page to see if there's a more recent version available. The project is also available in the maven central repository, so you can add this to your pom.xml:

3. Features Overview

uniVocity-parsers provides a list of powerful features, which can fulfill all requirements you might have for processing tabular presentations of data. Check the following overview chart for the features:

4. Reading Tabular Presentations Data

Read all rows of a csv
CsvParser parser = new CsvParser(new CsvParserSettings());
List<String[]> allRows = parser.parseAll(getReader("/examples/example.csv"));
For full list of demos in reading features, refer to: https://github.com/uniVocity/univocity-parsers#reading-csv 

5. Writing Tabular Presentations Data

Write data in CSV format with just 2 lines of code:
List<String[]> rows = someMethodToCreateRows();

CsvWriter writer = new CsvWriter(outputWriter, new CsvWriterSettings());
For full list of demos in writing features, refer to: https://github.com/uniVocity/univocity-parsers/blob/master/README.md#writing 

6. Performance and Flexibility

Here is the performance comparison we tested for uniVocity-parsers and JavaCSV in our system:
File size Duration for JavaCSV parsing
Duration for uniVocity-parsers parsing
10MB, 145453 rows
100MB, 809008 rows
434MB, 4499959 rows
1GB, 23803502 rows
Here are some performance comparison tables for almost all CSV parsers libraries in existence. And you can find that uniVocity-parsers got significantly ahead of other libraries in performance. uniVocity-parsers achieved its purpose in performance and flexibility with the following mechanisms:
  • Read input on separate thread (enable by invoking CsvParserSettings.setReadInputOnSeparateThread())
  • Concurrent row processor (refer to ConcurrentRowProcessor which implements RowProcessor)
  • Extend ColumnProcessor to process columns with your own business logic
  • Extend RowProcessor to read rows with your own business logic

7. Design and Implementations

A bunch of processors in uniVocity-parsers are core modules, which are responsible for reading/writing data in rows and columns, and execute data conversions. Here is the diagram of processors: You can create your own processors easily by implementing the RowProcessor interface or extending the provided implementations. In the following example I simply used an anonymous class:
CsvParserSettings settings = new CsvParserSettings();

settings.setRowProcessor(new RowProcessor() {

    * initialize whatever you need before processing the first row, with your own business logic
    public void processStarted(ParsingContext context) {
        System.out.println("Started to process rows of data.");

    * process the row with your own business logic
    StringBuilder stringBuilder = new StringBuilder();
    public void rowProcessed(String[] row, ParsingContext context) {
        System.out.println("The row in line #" + context.currentLine() + ": ");
        for (String col : row) {

    * After all rows were processed, perform any cleanup you need
    public void processEnded(ParsingContext context) {
        System.out.println("Finished processing rows of data.");

CsvParser parser = new CsvParser(settings);
List<String[]> allRows = parser.parseAll(new FileReader("/myFile.csv"));
The library offers a whole lot more features. I recommend you to have a look as it really made a difference in our project.

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