CsvJdbc is an open-source, read-only JDBC driver that treats a directory containing CSV files as a database and the individual CSV files as database tables. This library allows you to use standard SQL SELECT statements to query, filter, and sort your tabular text data directly within a Java application without needing a database management system (DBMS). Prerequisites & Dependency
To use CsvJdbc, you must include its dependency in your project. If you are using Maven, add the following snippet to your pom.xml:
Reading a CSV file using CsvJdbc mirrors the standard Java Database Connectivity (JDBC) workflow:
Load the Driver Class: Register org.relique.jdbc.csv.CsvDriver.
Define Connection Properties: Configure the column separator, file extension, and header properties.
Establish a Connection: Use a JDBC URL pointing to the folder containing your CSV files, not the file itself.
Execute SQL Queries: Write a standard SELECT query where the filename (without extension) acts as the table name. Code Example: Reading a CSV File
Suppose you have a directory located at /path/to/csv/folder containing a file named users.csv with columns like id, name, and email.
import java.sql.Connection; import java.sql.DriverManager; import java.sql.ResultSet; import java.sql.Statement; import java.util.Properties; public class CsvReaderExample { public static void main(String[] args) { // Path to the directory where CSV files are saved String csvDirectory = “/path/to/csv/folder”; // Step 1: Set driver properties Properties props = new Properties(); props.put(“separator”, “,”); // Define the delimiter props.put(“fileExtension”, “.csv”); // Identify targeted file types props.put(“suppressHeaders”, “false”); // First line contains column names // Step 2: Establish connection using the prefix ‘jdbc:relique:csv:’ String url = “jdbc:relique:csv:” + csvDirectory; try { // Load the driver explicitly Class.forName(“org.relique.jdbc.csv.CsvDriver”); try (Connection conn = DriverManager.getConnection(url, props); Statement stmt = conn.createStatement()) { // Step 3: Execute query (table name matches the filename) String sql = “SELECT id, name, email FROM users WHERE id > 10 ORDER BY name ASC”; try (ResultSet results = stmt.executeQuery(sql)) { // Step 4: Iterate over data grid rows while (results.next()) { String String name = results.getString(“name”); String email = results.getString(“email”); System.out.println(id + “ | ” + name + “ | ” + email); } } } } catch (Exception e) { e.printStackTrace(); } } } Use code with caution. Important Features and Driver Constraints
While CsvJdbc simplifies parsing tabular records, it operates with structural limits:
SQL Support: It strictly supports SELECT commands; mutations like INSERT, UPDATE, or DELETE are disallowed.
No Table Joins: Standard SQL queries are restricted to single-table interactions; multi-table joins are unsupported.
Alternative Storage: Beyond raw local folders, it provides built-in syntax to query CSVs packed inside .zip archives or loaded over the application classpath.
Memory Constraints: Filtering with WHERE processes records sequentially streaming one-at-a-time, but incorporating ORDER BY or GROUP BY prompts the driver to load all matching file data into memory to compute sorting adjustments.
If you would like to proceed with setting up your project, please let me know:
Your build automation tool (e.g., Maven, Gradle, or manual JAR configuration).
Whether your CSV files contain headers, or use alternate markers like semicolons or tabs.
If you need to perform complex operations like aggregations or memory-intensive sorting. Reading CSV file without header with CSV-JDBC driver
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