scirs2-io 0.4.2

Input/Output utilities module for SciRS2 (scirs2-io)
Documentation
//! Bulk operations for databases

use crate::database::{DatabaseConnection, QueryBuilder};
use crate::error::Result;
use scirs2_core::ndarray::ArrayView2;

/// Bulk insert configuration
#[derive(Debug, Clone)]
pub struct BulkInsertConfig {
    pub batch_size: usize,
    pub commit_interval: Option<usize>,
    pub on_conflict: ConflictStrategy,
}

#[derive(Debug, Clone, Copy)]
pub enum ConflictStrategy {
    Ignore,
    Replace,
    Error,
}

impl Default for BulkInsertConfig {
    fn default() -> Self {
        Self {
            batch_size: 1000,
            commit_interval: Some(10000),
            on_conflict: ConflictStrategy::Error,
        }
    }
}

/// Perform bulk insert with batching
pub fn bulk_insert(
    conn: &dyn DatabaseConnection,
    table: &str,
    data: ArrayView2<f64>,
    columns: &[&str],
    config: &BulkInsertConfig,
) -> Result<usize> {
    let mut total_inserted = 0;
    let row_count = data.nrows();

    for chunk_start in (0..row_count).step_by(config.batch_size) {
        let chunk_end = (chunk_start + config.batch_size).min(row_count);
        let chunk = data.slice(scirs2_core::ndarray::s![chunk_start..chunk_end, ..]);

        total_inserted += conn.insert_array(table, chunk, columns)?;

        if let Some(interval) = config.commit_interval {
            if total_inserted % interval == 0 {
                // In a real implementation, we'd commit the transaction here
            }
        }
    }

    Ok(total_inserted)
}

/// Bulk update using a temporary table strategy
pub fn bulk_update(
    conn: &dyn DatabaseConnection,
    table: &str,
    data: ArrayView2<f64>,
    key_columns: &[&str],
    value_columns: &[&str],
) -> Result<usize> {
    // This is a stub implementation
    // In production, this would:
    // 1. Create a temporary table
    // 2. Bulk insert into temp table
    // 3. Perform UPDATE...FROM or MERGE
    // 4. Drop temp table
    conn.insert_array(table, data, &[key_columns, value_columns].concat())
}