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// CSV Transform - Parallel CSV Processing Demo (Parallel File Read Version)
//
// Demonstrates parallel CSV processing using loom.
// Uses loom to read file chunks in parallel, then processes with parallel iterators.
//
// Usage: zig build samples-loom -Doptimize=ReleaseFast
//
// Input: src/loom/docs/datas/inputs/sample_01.csv (auto-generated if missing)
// Output: Aggregation results and statistics
const std = @import("std");
const loom = @import("loom");
const par_iter = loom.par_iter;
const par_range = loom.par_range;
const ThreadPool = loom.ThreadPool;
const input_file = "src/loom/docs/datas/inputs/sample_01.csv";
// Default row count for generated CSV (100K for quick demos, increase for stress testing)
const DEFAULT_ROW_COUNT: usize = 100_000;
// CSV generation categories and descriptions (matches random_csv_gen.py)
const categories = [_][]const u8{ "Apple", "Banana", "Cherry", "Date", "Elderberry", "Fig", "Grape", "Honeydew" };
const descriptions = [_][]const u8{
"lorem ipsum dolor",
"sit amet consectetur",
"adipiscing elit",
"sed do eiusmod",
"tempor incididunt",
"ut labore et dolore",
"magna aliqua",
"ut enim ad minim",
};
/// Generates sample CSV file if it doesn't exist.
/// Mirrors the behavior of src/loom/docs/datas/random_csv_gen.py
fn ensureSampleCsvExists(allocator: std.mem.Allocator, total_rows: usize) !void {
// Check if file already exists
std.fs.cwd().access(input_file, .{}) catch {
// File doesn't exist, generate it
std.debug.print("Sample CSV not found, generating {d} rows...\n", .{total_rows});
try generateSampleCsv(allocator, total_rows);
return;
};
std.debug.print("Sample CSV exists: {s}\n", .{input_file});
}
/// Generates a sample CSV file with random data
fn generateSampleCsv(allocator: std.mem.Allocator, total_rows: usize) !void {
var timer = try std.time.Timer.start();
// Ensure parent directory exists
const dir_path = std.fs.path.dirname(input_file) orelse ".";
std.fs.cwd().makePath(dir_path) catch {};
const file = try std.fs.cwd().createFile(input_file, .{});
defer file.close();
// Write header
try file.writeAll("id,measurement,category,description,is_active\n");
// Initialize PRNG
var prng = std.Random.DefaultPrng.init(@bitCast(std.time.timestamp()));
const random = prng.random();
// Generate rows in chunks, building each chunk in memory before writing
var rows_written: usize = 0;
const chunk_size: usize = 10_000;
// Buffer for building chunks
var chunk_buf: std.ArrayListUnmanaged(u8) = .empty;
defer chunk_buf.deinit(allocator);
while (rows_written < total_rows) {
const chunk_end = @min(rows_written + chunk_size, total_rows);
// Clear buffer for new chunk
chunk_buf.shrinkRetainingCapacity(0);
for (rows_written..chunk_end) |id| {
// Random measurement 0.0-1000.0 with 4 decimal places
const measurement = random.float(f64) * 1000.0;
// Random category and description
const category = categories[random.intRangeAtMost(usize, 0, categories.len - 1)];
const description = descriptions[random.intRangeAtMost(usize, 0, descriptions.len - 1)];
// Random is_active (0 or 1)
const is_active: u8 = random.intRangeAtMost(u8, 0, 1);
// Build row string
const row = try std.fmt.allocPrint(allocator, "{d},{d:.4},{s},{s},{d}\n", .{ id, measurement, category, description, is_active });
defer allocator.free(row);
try chunk_buf.appendSlice(allocator, row);
}
// Write entire chunk at once
try file.writeAll(chunk_buf.items);
rows_written = chunk_end;
// Progress update
const elapsed_ns = timer.read();
const elapsed_s = @as(f64, @floatFromInt(elapsed_ns)) / 1_000_000_000.0;
std.debug.print(" Written {d} rows... ({d:.2}s elapsed)\n", .{ rows_written, elapsed_s });
}
const total_elapsed = timer.read();
const file_stat = try file.stat();
std.debug.print("Generated {s}\n", .{input_file});
std.debug.print(" Rows: {d}, Size: {d:.2} MB, Time: {d:.2}s\n\n", .{
total_rows,
@as(f64, @floatFromInt(file_stat.size)) / (1024.0 * 1024.0),
@as(f64, @floatFromInt(total_elapsed)) / 1_000_000_000.0,
});
}
// Chunk size for parallel file reading (256MB per chunk - larger = fewer syscalls)
const READ_CHUNK_SIZE: usize = 256 * 1024 * 1024;
pub fn main() !void {
const allocator = std.heap.page_allocator;
std.debug.print("\n", .{});
std.debug.print("================================================\n", .{});
std.debug.print(" CSV Transform - Parallel File Read with Loom\n", .{});
std.debug.print("================================================\n\n", .{});
// Ensure sample CSV exists (generates if missing)
try ensureSampleCsvExists(allocator, DEFAULT_ROW_COUNT);
// Initialize thread pool FIRST (before file operations)
const pool = try ThreadPool.init(allocator, .{});
defer pool.deinit();
std.debug.print("Thread pool: {d} workers\n\n", .{pool.numWorkers()});
// ========================================================================
// PARALLEL FILE READING using loom
// ========================================================================
std.debug.print("--- Parallel File Reading (using loom) ---\n\n", .{});
std.debug.print("Opening: {s}\n", .{input_file});
var read_timer = try std.time.Timer.start();
const file = std.fs.cwd().openFile(input_file, .{}) catch |err| {
std.debug.print("Failed to open file: {any}\n", .{err});
return err;
};
defer file.close();
// Get file size
const file_stat = try file.stat();
const file_size = file_stat.size;
std.debug.print("File size: {d:.2} GB ({d} bytes)\n", .{
@as(f64, @floatFromInt(file_size)) / (1024.0 * 1024.0 * 1024.0),
file_size,
});
// Allocate buffer for entire file
const file_data = try allocator.alloc(u8, file_size);
defer allocator.free(file_data);
// Calculate number of chunks for parallel reading
const num_chunks = (file_size + READ_CHUNK_SIZE - 1) / READ_CHUNK_SIZE;
std.debug.print("Reading in {d} parallel chunks of {d}MB each...\n", .{ num_chunks, READ_CHUNK_SIZE / (1024 * 1024) });
// Context for parallel file reading - shared across all workers
const ReadContext = struct {
file_handle: std.fs.File.Handle,
buffer: []u8,
chunk_size: usize,
total_size: usize,
};
const read_ctx = ReadContext{
.file_handle = file.handle,
.buffer = file_data,
.chunk_size = READ_CHUNK_SIZE,
.total_size = file_size,
};
// Use par_range with context - clean API, no allocations needed!
par_range(@as(usize, 0), num_chunks)
.withPool(pool)
.withContext(&read_ctx)
.forEach(struct {
fn readChunk(ctx: *const ReadContext, chunk_idx: usize) void {
const start = chunk_idx * ctx.chunk_size;
const end = @min(start + ctx.chunk_size, ctx.total_size);
if (start >= end) return;
// Use pread for positional read (thread-safe, doesn't move file cursor)
_ = std.posix.pread(ctx.file_handle, ctx.buffer[start..end], start) catch {};
}
}.readChunk);
const total_bytes_read = file_size;
const read_elapsed = read_timer.read();
const read_throughput = @as(f64, @floatFromInt(file_size)) / (@as(f64, @floatFromInt(read_elapsed)) / 1_000_000_000.0) / (1024.0 * 1024.0 * 1024.0);
std.debug.print("Parallel read: {d:.2}s ({d:.2} GB/s)\n", .{
@as(f64, @floatFromInt(read_elapsed)) / 1_000_000_000.0,
read_throughput,
});
std.debug.print("Total bytes: {d}\n\n", .{total_bytes_read});
// ========================================================================
// PARALLEL FILE ANALYSIS - Process in-memory data with loom
// ========================================================================
std.debug.print("--- Parallel File Analysis (using loom) ---\n\n", .{});
var total_timer = try std.time.Timer.start();
// Count newlines in parallel
const newline_count = par_iter(file_data).withPool(pool).count(struct {
fn isNewline(byte: u8) bool {
return byte == '\n';
}
}.isNewline);
var elapsed = total_timer.read();
const throughput_1 = @as(f64, @floatFromInt(file_size)) / (@as(f64, @floatFromInt(elapsed)) / 1_000_000_000.0) / (1024.0 * 1024.0 * 1024.0);
std.debug.print("Newline count (parallel): {d:.2}ms ({d:.2} GB/s) -> {d} lines\n", .{
@as(f64, @floatFromInt(elapsed)) / 1_000_000.0,
throughput_1,
newline_count,
});
// Count commas in parallel
total_timer.reset();
const comma_count = par_iter(file_data).withPool(pool).count(struct {
fn isComma(byte: u8) bool {
return byte == ',';
}
}.isComma);
elapsed = total_timer.read();
const throughput_2 = @as(f64, @floatFromInt(file_size)) / (@as(f64, @floatFromInt(elapsed)) / 1_000_000_000.0) / (1024.0 * 1024.0 * 1024.0);
const avg_fields = @as(f64, @floatFromInt(comma_count)) / @as(f64, @floatFromInt(newline_count));
std.debug.print("Comma count (parallel): {d:.2}ms ({d:.2} GB/s) -> {d} commas ({d:.1} fields/row)\n", .{
@as(f64, @floatFromInt(elapsed)) / 1_000_000.0,
throughput_2,
comma_count,
avg_fields + 1,
});
// Count digit characters in parallel
total_timer.reset();
const digit_count = par_iter(file_data).withPool(pool).count(struct {
fn isDigit(byte: u8) bool {
return byte >= '0' and byte <= '9';
}
}.isDigit);
elapsed = total_timer.read();
const throughput_3 = @as(f64, @floatFromInt(file_size)) / (@as(f64, @floatFromInt(elapsed)) / 1_000_000_000.0) / (1024.0 * 1024.0 * 1024.0);
const digit_pct = @as(f64, @floatFromInt(digit_count)) * 100.0 / @as(f64, @floatFromInt(file_size));
std.debug.print("Digit count (parallel): {d:.2}ms ({d:.2} GB/s) -> {d} ({d:.1}%% of file)\n\n", .{
@as(f64, @floatFromInt(elapsed)) / 1_000_000.0,
throughput_3,
digit_count,
digit_pct,
});
// ========================================================================
// Parallel Line Indexing
// ========================================================================
std.debug.print("--- Parallel Line Indexing ---\n\n", .{});
total_timer.reset();
var lines = std.ArrayListUnmanaged([]const u8){};
defer lines.deinit(allocator);
try lines.ensureTotalCapacity(allocator, newline_count);
var line_iter = std.mem.splitScalar(u8, file_data, '\n');
_ = line_iter.next(); // Skip header
while (line_iter.next()) |line| {
if (line.len > 0) {
lines.appendAssumeCapacity(line);
}
}
const split_elapsed = total_timer.read();
const row_count = lines.items.len;
std.debug.print("Lines indexed: {d:.2}s ({d} rows)\n\n", .{
@as(f64, @floatFromInt(split_elapsed)) / 1_000_000_000.0,
row_count,
});
// ========================================================================
// Parallel Aggregations
// ========================================================================
std.debug.print("--- Parallel Row Aggregations ---\n\n", .{});
// 1. Count active rows
total_timer.reset();
const active_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
if (line.len == 0) return false;
return line[line.len - 1] == '1';
}
}.check);
elapsed = total_timer.read();
const active_pct = @as(f64, @floatFromInt(active_count)) * 100.0 / @as(f64, @floatFromInt(row_count));
std.debug.print("1. Active count: {d:.2}ms\n", .{@as(f64, @floatFromInt(elapsed)) / 1_000_000.0});
std.debug.print(" Result: {d} / {d} ({d:.1}%)\n\n", .{ active_count, row_count, active_pct });
// 2. Count by category
total_timer.reset();
const apple_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Apple,") != null;
}
}.check);
const banana_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Banana,") != null;
}
}.check);
const cherry_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Cherry,") != null;
}
}.check);
const date_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Date,") != null;
}
}.check);
const fig_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Fig,") != null;
}
}.check);
const grape_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Grape,") != null;
}
}.check);
const honeydew_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, ",Honeydew,") != null;
}
}.check);
elapsed = total_timer.read();
std.debug.print("2. Category counts: {d:.2}ms\n", .{@as(f64, @floatFromInt(elapsed)) / 1_000_000.0});
std.debug.print(" Apple: {d:>12}\n", .{apple_count});
std.debug.print(" Banana: {d:>12}\n", .{banana_count});
std.debug.print(" Cherry: {d:>12}\n", .{cherry_count});
std.debug.print(" Date: {d:>12}\n", .{date_count});
std.debug.print(" Fig: {d:>12}\n", .{fig_count});
std.debug.print(" Grape: {d:>12}\n", .{grape_count});
std.debug.print(" Honeydew: {d:>12}\n\n", .{honeydew_count});
// 3. Count high measurements (>900)
total_timer.reset();
const high_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
var field_iter = std.mem.splitScalar(u8, line, ',');
_ = field_iter.next();
const measurement_str = field_iter.next() orelse return false;
const value = std.fmt.parseFloat(f64, measurement_str) catch return false;
return value > 900.0;
}
}.check);
elapsed = total_timer.read();
const high_pct = @as(f64, @floatFromInt(high_count)) * 100.0 / @as(f64, @floatFromInt(row_count));
std.debug.print("3. High values (>900): {d:.2}ms\n", .{@as(f64, @floatFromInt(elapsed)) / 1_000_000.0});
std.debug.print(" Result: {d} ({d:.2}%)\n\n", .{ high_count, high_pct });
// 4. Count low measurements (<100)
total_timer.reset();
const low_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
var field_iter = std.mem.splitScalar(u8, line, ',');
_ = field_iter.next();
const measurement_str = field_iter.next() orelse return false;
const value = std.fmt.parseFloat(f64, measurement_str) catch return false;
return value < 100.0;
}
}.check);
elapsed = total_timer.read();
const low_pct = @as(f64, @floatFromInt(low_count)) * 100.0 / @as(f64, @floatFromInt(row_count));
std.debug.print("4. Low values (<100): {d:.2}ms\n", .{@as(f64, @floatFromInt(elapsed)) / 1_000_000.0});
std.debug.print(" Result: {d} ({d:.2}%)\n\n", .{ low_count, low_pct });
// 5. Count lorem ipsum
total_timer.reset();
const lorem_count = par_iter(lines.items).withPool(pool).count(struct {
fn check(line: []const u8) bool {
return std.mem.indexOf(u8, line, "lorem ipsum") != null;
}
}.check);
elapsed = total_timer.read();
const lorem_pct = @as(f64, @floatFromInt(lorem_count)) * 100.0 / @as(f64, @floatFromInt(row_count));
std.debug.print("5. Contains 'lorem ipsum': {d:.2}ms\n", .{@as(f64, @floatFromInt(elapsed)) / 1_000_000.0});
std.debug.print(" Result: {d} ({d:.2}%)\n\n", .{ lorem_count, lorem_pct });
// ========================================================================
// Summary
// ========================================================================
const avg_throughput = (throughput_1 + throughput_2 + throughput_3) / 3.0;
std.debug.print("================================================\n", .{});
std.debug.print(" Processing Complete!\n", .{});
std.debug.print("================================================\n\n", .{});
std.debug.print("Processed {d} rows with {d} workers\n", .{ row_count, pool.numWorkers() });
std.debug.print("File size: {d:.2} GB\n", .{@as(f64, @floatFromInt(file_size)) / (1024.0 * 1024.0 * 1024.0)});
std.debug.print("Parallel file read: {d:.2} GB/s\n", .{read_throughput});
std.debug.print("Processing throughput: {d:.2} GB/s\n\n", .{avg_throughput});
}