Overview

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Spring Batch RS provides a rich set of item readers and writers for various data sources and formats. All readers and writers use the builder pattern for easy, type-safe configuration.

Available Features

Enable only the features you need to keep your dependencies minimal:

Feature	Description	Status
`csv`	CSV file reading and writing	✅ Stable
`json`	JSON file reading and writing	✅ Stable
`xml`	XML file reading and writing	✅ Stable
`mongodb`	MongoDB database integration	✅ Stable
`rdbc-postgres`	PostgreSQL via RDBC	✅ Stable
`rdbc-mysql`	MySQL/MariaDB via RDBC	✅ Stable
`rdbc-sqlite`	SQLite via RDBC	✅ Stable
`orm`	SeaORM integration	✅ Stable
`fake`	Mock data generation	✅ Stable
`logger`	Debug logging writer	✅ Stable

File-Based Readers & Writers

CSV

Read and write CSV files with configurable delimiters, headers, and quoting

Learn More →

JSON

Handle JSON arrays and objects with pretty printing support

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XML

Process XML documents with custom root and item elements

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Database Readers & Writers

RDBC (Generic SQL)

Direct database access for PostgreSQL, MySQL, and SQLite using SQLx

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SeaORM

Type-safe ORM with pagination and filtering

Learn More →

MongoDB

Native MongoDB document operations

Learn More →

Utility Readers & Writers

Fake Data Generator

Generate realistic mock data for testing

Learn More →

Logger Writer

Debug output for development

Learn More →

Quick Examples

CSV Reader

use spring_batch_rs::item::csv::CsvItemReaderBuilder;
use serde::Deserialize;

#[derive(Deserialize)]
struct Product {
    id: u32,
    name: String,
    price: f64,
}

let reader = CsvItemReaderBuilder::<Product>::new()
    .has_headers(true)
    .delimiter(b',')
    .from_path("products.csv")?;

JSON Writer

use spring_batch_rs::item::json::JsonItemWriterBuilder;

let writer = JsonItemWriterBuilder::<MyType>::new()
    .pretty_formatter(true)
    .from_path("output.json")?;

Database Reader (RDBC)

use spring_batch_rs::item::rdbc::rdbc_reader::{RdbcItemReaderBuilder, RdbcRowMapper};
use sqlx::{AnyPool, Row};

struct ProductRowMapper;

impl RdbcRowMapper<Product> for ProductRowMapper {
    fn map_row(&self, row: &sqlx::any::AnyRow) -> Product {
        Product {
            id: row.get("id"),
            name: row.get("name"),
            price: row.get("price"),
        }
    }
}

let pool = AnyPool::connect("postgresql://user:pass@localhost/db").await?;

let reader = RdbcItemReaderBuilder::new()
    .pool(&pool)
    .query("SELECT id, name, price FROM products")
    .page_size(1000)
    .row_mapper(&ProductRowMapper)
    .build();

Custom Readers & Writers

You can create custom implementations by implementing the respective traits:

Custom Reader
Custom Writer

use spring_batch_rs::core::item::ItemReader;
use spring_batch_rs::BatchError;

struct MyCustomReader {
    data: Vec<String>,
    index: usize,
}

impl ItemReader<String> for MyCustomReader {
    fn read(&mut self) -> Result<Option<String>, BatchError> {
        if self.index < self.data.len() {
            let item = self.data[self.index].clone();
            self.index += 1;
            Ok(Some(item))
        } else {
            Ok(None)  // No more items
        }
    }
}

use spring_batch_rs::core::item::ItemWriter;
use spring_batch_rs::BatchError;

struct MyCustomWriter {
    output: Vec<String>,
}

impl ItemWriter<String> for MyCustomWriter {
    fn write(&mut self, items: &[String]) -> Result<(), BatchError> {
        for item in items {
            self.output.push(item.clone());
            // Custom write logic here
        }
        Ok(())
    }
}

Performance Considerations

Chunk Size

Choose appropriate chunk sizes based on your data and memory:

// Small chunks (10-50): Memory-constrained environments
.chunk(25)

// Medium chunks (100-500): Balanced performance
.chunk(250)

// Large chunks (1000+): High-throughput scenarios
.chunk(1000)

Database Pagination

For database readers, configure page sizes to optimize memory:

let reader = RdbcItemReaderBuilder::new()
    .page_size(500)  // Fetch 500 records at a time
    .build();

Buffered I/O

File-based readers and writers use buffered I/O by default for optimal performance.

Next Steps

Explore detailed documentation for each reader and writer type: