@magmacomputing/tempo-plugin-batch

This is a Community plugin for the Tempo library that parallelizes massive epoch mutation tasks across worker threads utilizing lock-free SharedArrayBuffer shared memory architecture for extreme throughput.

Perfect For

Heavy data ETL pipelines, massive IoT telemetry ingestion, financial ledger backtesting, and parallel bulk date-processing workloads.

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🚀 Installation & Quickstart

npm install @magmacomputing/tempo-plugin-batch

Interactive Demo (@magmacomputing/tempo-plugin-batch)

Open in Full REPL↗

// ⚡ Parallel Bulk Mutation Demo (@magmacomputing/tempo-plugin-batch)
// Note: @magmacomputing/tempo-plugin-batch uses Node.js worker_threads for multi-threaded processing.
const timestamps = [1700000000000, 1700086400000, 1700172800000];
console.log('Original timestamps count:', timestamps.length);

let mutated;
const isNode = typeof process !== 'undefined' && Boolean(process.versions?.node);

if (isNode) {
  const { BatchPlugin } = await import('@magmacomputing/tempo-plugin-batch');
  Tempo.use(BatchPlugin);
  mutated = await Tempo.batch(timestamps, '+1w');
} else {
  console.info('Running browser fallback (BatchPlugin worker_threads requires Node.js).');
  mutated = timestamps.map(ts => new Tempo(ts).add({ weeks: 1 }).epoch.ms);
}

console.log('Mutated +1 week timestamps:', mutated);
return `Batch processed ${mutated.length} timestamps successfully!`;

Executes 100% in browser via native ESM sandbox

import { Tempo } from '@magmacomputing/tempo';
import { BatchPlugin } from '@magmacomputing/tempo-plugin-batch';

Tempo.use(BatchPlugin);

// Assume `epochs` is a massive array of integers representing timestamps
const epochs = [1700000000000, 1700000001000, /* ... millions more ... */];

// Mutate millions of dates concurrently using the background worker pool!
// The engine automatically splits the payload and offloads to workers
const batchResult = await Tempo.batch(epochs, '+1w', { threads: 4 });

console.log(batchResult); // Returns an array of mutated timestamp integers

Zero-Boilerplate Auto-Installation (Side-Effect Import)

import { Tempo } from '@magmacomputing/tempo';
import '@magmacomputing/tempo-plugin-batch/install';

const epochs = [1700000000000, 1700000001000];
const batchResult = await Tempo.batch(epochs, '+1w');

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📚 API Surface Catalog

The Batch plugin mounts the static Tempo.batch() method and exports the underlying BatchOrchestrator:

Export / Method	Signature	Returns	Description
Tempo.batch()	(epochs: number[], operation: string, options?: BatchOptions)	Promise<number[] | Tempo[]>	Splits the input array across worker threads and applies duration mutation.
BatchOrchestrator	Static class	BatchOrchestrator	Low-level orchestration engine with transform() and sanitizeExecArgv() tools.

Configuration Options (BatchOptions)

Option	Type	Default	Description
threads	number	os.cpus().length	Number of worker threads to allocate for the pool.
rehydrate	boolean	false	When false, returns raw numeric timestamps (number[]) for peak throughput. When true, rehydrates output numbers into Tempo[] instances.

Supported Mutation Operations

The operation parameter accepts either standard duration strings or shorthand intervals:

• Days: '+1d', '+2 days', '-5d'
• Weeks: '+1w', '+4 weeks'
• Hours: '+1h', '+8 hours'
• Minutes: '+30m', '-15 mins'
• Months / Years: '+1mo', '+1y'

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📖 Architecture & Specialized Guides

• Parallel Worker Pool & SharedArrayBuffer Architecture: Zero-copy SharedArrayBuffer vs postMessage structural cloning fallback, browser Cross-Origin Isolation (COOP/COEP), and worker isolate CLI flag allowlisting.
• Production Use Cases & Architectural Patterns: Industrial IoT telemetry clock skew correction, financial tick backtesting pipelines, and large-scale CSV payroll processing.

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📄 Licensing

This is a Community plugin. It is completely free and open-source for personal and commercial use under the MIT license. No license token is required.