batch-processing-jobs
About
This skill provides patterns for implementing robust batch processing systems using job queues, schedulers, and distributed workers. It's designed for handling large datasets, scheduled tasks, resource-intensive computations, and asynchronous operations. Key capabilities include scalable background task processing and efficient management of long-running jobs like ETL pipelines and bulk data updates.
Documentation
Batch Processing Jobs
Overview
Implement scalable batch processing systems for handling large-scale data processing, scheduled tasks, and async operations efficiently.
When to Use
- Processing large datasets
- Scheduled report generation
- Email/notification campaigns
- Data imports and exports
- Image/video processing
- ETL pipelines
- Cleanup and maintenance tasks
- Long-running computations
- Bulk data updates
Architecture Patterns
┌─────────────┐ ┌─────────────┐ ┌──────────┐
│ Producer │─────▶│ Queue │─────▶│ Worker │
└─────────────┘ └─────────────┘ └──────────┘
│ │
│ ▼
│ ┌──────────┐
└─────────────▶│ Result │
│ Storage │
└──────────┘
Implementation Examples
1. Bull Queue (Node.js)
import Queue from 'bull';
import { v4 as uuidv4 } from 'uuid';
interface JobData {
id: string;
type: string;
payload: any;
userId?: string;
metadata?: Record<string, any>;
}
interface JobResult {
success: boolean;
data?: any;
error?: string;
processedAt: number;
duration: number;
}
class BatchProcessor {
private queue: Queue.Queue<JobData>;
private resultQueue: Queue.Queue<JobResult>;
constructor(redisUrl: string) {
// Main processing queue
this.queue = new Queue('batch-jobs', redisUrl, {
defaultJobOptions: {
attempts: 3,
backoff: {
type: 'exponential',
delay: 2000
},
removeOnComplete: 1000,
removeOnFail: 5000,
timeout: 300000 // 5 minutes
},
settings: {
maxStalledCount: 2,
stalledInterval: 30000
}
});
// Results queue
this.resultQueue = new Queue('batch-results', redisUrl);
this.setupProcessors();
this.setupEvents();
}
private setupProcessors(): void {
// Data processing job
this.queue.process('process-data', 10, async (job) => {
const startTime = Date.now();
const { payload } = job.data;
job.log(`Processing ${payload.items?.length || 0} items`);
try {
// Update progress
await job.progress(0);
const results = await this.processDataBatch(
payload.items,
(progress) => job.progress(progress)
);
const duration = Date.now() - startTime;
return {
success: true,
data: results,
processedAt: Date.now(),
duration
};
} catch (error: any) {
const duration = Date.now() - startTime;
throw new Error(`Processing failed: ${error.message}`);
}
});
// Report generation job
this.queue.process('generate-report', 2, async (job) => {
const { payload } = job.data;
const report = await this.generateReport(
payload.type,
payload.filters,
payload.format
);
return {
success: true,
data: {
reportId: uuidv4(),
url: report.url,
size: report.size
},
processedAt: Date.now(),
duration: 0
};
});
// Email batch job
this.queue.process('send-emails', 5, async (job) => {
const { payload } = job.data;
const { recipients, template, data } = payload;
const results = await this.sendEmailBatch(
recipients,
template,
data
);
return {
success: true,
data: {
sent: results.successful,
failed: results.failed
},
processedAt: Date.now(),
duration: 0
};
});
}
private setupEvents(): void {
this.queue.on('completed', (job, result) => {
console.log(`Job ${job.id} completed:`, result);
// Store result
this.resultQueue.add({
jobId: job.id,
...result
});
});
this.queue.on('failed', (job, error) => {
console.error(`Job ${job?.id} failed:`, error.message);
// Store failure
this.resultQueue.add({
jobId: job?.id,
success: false,
error: error.message,
processedAt: Date.now(),
duration: 0
});
});
this.queue.on('progress', (job, progress) => {
console.log(`Job ${job.id} progress: ${progress}%`);
});
this.queue.on('stalled', (job) => {
console.warn(`Job ${job.id} stalled`);
});
}
async addJob(
type: string,
payload: any,
options?: Queue.JobOptions
): Promise<Queue.Job<JobData>> {
const jobData: JobData = {
id: uuidv4(),
type,
payload,
metadata: {
createdAt: Date.now()
}
};
return this.queue.add(type, jobData, options);
}
async addBulkJobs(
jobs: Array<{ type: string; payload: any; options?: Queue.JobOptions }>
): Promise<Queue.Job<JobData>[]> {
const bulkData = jobs.map(({ type, payload, options }) => ({
name: type,
data: {
id: uuidv4(),
type,
payload,
metadata: { createdAt: Date.now() }
},
opts: options || {}
}));
return this.queue.addBulk(bulkData);
}
async scheduleJob(
type: string,
payload: any,
cronExpression: string
): Promise<Queue.Job<JobData>> {
return this.addJob(type, payload, {
repeat: {
cron: cronExpression
}
});
}
private async processDataBatch(
items: any[],
onProgress: (progress: number) => Promise<void>
): Promise<any[]> {
const results = [];
const total = items.length;
for (let i = 0; i < total; i++) {
const result = await this.processItem(items[i]);
results.push(result);
// Update progress
const progress = Math.round(((i + 1) / total) * 100);
await onProgress(progress);
}
return results;
}
private async processItem(item: any): Promise<any> {
// Simulate processing
await new Promise(resolve => setTimeout(resolve, 100));
return { ...item, processed: true };
}
private async generateReport(
type: string,
filters: any,
format: string
): Promise<any> {
// Simulate report generation
return {
url: `https://cdn.example.com/reports/${uuidv4()}.${format}`,
size: 1024 * 1024
};
}
private async sendEmailBatch(
recipients: string[],
template: string,
data: any
): Promise<{ successful: number; failed: number }> {
// Simulate email sending
return {
successful: recipients.length,
failed: 0
};
}
async getJobStatus(jobId: string): Promise<any> {
const job = await this.queue.getJob(jobId);
if (!job) return null;
const state = await job.getState();
const logs = await this.queue.getJobLogs(jobId);
return {
id: job.id,
name: job.name,
data: job.data,
state,
progress: job.progress(),
attempts: job.attemptsMade,
failedReason: job.failedReason,
finishedOn: job.finishedOn,
processedOn: job.processedOn,
logs: logs.logs
};
}
async getQueueStats(): Promise<any> {
const [
waiting,
active,
completed,
failed,
delayed,
paused
] = await Promise.all([
this.queue.getWaitingCount(),
this.queue.getActiveCount(),
this.queue.getCompletedCount(),
this.queue.getFailedCount(),
this.queue.getDelayedCount(),
this.queue.getPausedCount()
]);
return {
waiting,
active,
completed,
failed,
delayed,
paused
};
}
async pause(): Promise<void> {
await this.queue.pause();
}
async resume(): Promise<void> {
await this.queue.resume();
}
async clean(grace: number = 0): Promise<void> {
await this.queue.clean(grace, 'completed');
await this.queue.clean(grace, 'failed');
}
async close(): Promise<void> {
await this.queue.close();
await this.resultQueue.close();
}
}
// Usage
const processor = new BatchProcessor('redis://localhost:6379');
// Add single job
const job = await processor.addJob('process-data', {
items: [{ id: 1 }, { id: 2 }, { id: 3 }]
});
// Add bulk jobs
await processor.addBulkJobs([
{
type: 'process-data',
payload: { items: [/* ... */] }
},
{
type: 'generate-report',
payload: { type: 'sales', format: 'pdf' }
}
]);
// Schedule recurring job
await processor.scheduleJob(
'generate-report',
{ type: 'daily-summary' },
'0 0 * * *' // Daily at midnight
);
// Check status
const status = await processor.getJobStatus(job.id!);
console.log('Job status:', status);
// Get queue stats
const stats = await processor.getQueueStats();
console.log('Queue stats:', stats);
2. Celery-Style Worker (Python)
from celery import Celery, Task
from celery.schedules import crontab
from typing import List, Any, Dict
import time
import logging
# Initialize Celery
app = Celery(
'batch_processor',
broker='redis://localhost:6379/0',
backend='redis://localhost:6379/1'
)
# Configure Celery
app.conf.update(
task_serializer='json',
accept_content=['json'],
result_serializer='json',
timezone='UTC',
enable_utc=True,
task_track_started=True,
task_time_limit=300, # 5 minutes
task_soft_time_limit=270, # 4.5 minutes
worker_prefetch_multiplier=4,
worker_max_tasks_per_child=1000,
)
# Periodic tasks
app.conf.beat_schedule = {
'daily-report': {
'task': 'tasks.generate_daily_report',
'schedule': crontab(hour=0, minute=0),
},
'cleanup-old-data': {
'task': 'tasks.cleanup_old_data',
'schedule': crontab(hour=2, minute=0),
},
}
logger = logging.getLogger(__name__)
class CallbackTask(Task):
"""Base task with callback support."""
def on_success(self, retval, task_id, args, kwargs):
logger.info(f"Task {task_id} succeeded: {retval}")
def on_failure(self, exc, task_id, args, kwargs, einfo):
logger.error(f"Task {task_id} failed: {exc}")
def on_retry(self, exc, task_id, args, kwargs, einfo):
logger.warning(f"Task {task_id} retrying: {exc}")
@app.task(base=CallbackTask, bind=True, max_retries=3)
def process_batch_data(self, items: List[Dict[str, Any]]) -> Dict[str, Any]:
"""Process batch of data items."""
try:
results = []
total = len(items)
for i, item in enumerate(items):
# Process item
result = process_single_item(item)
results.append(result)
# Update progress
progress = int((i + 1) / total * 100)
self.update_state(
state='PROGRESS',
meta={'current': i + 1, 'total': total, 'percent': progress}
)
return {
'processed': len(results),
'success': True,
'results': results
}
except Exception as exc:
logger.error(f"Batch processing failed: {exc}")
raise self.retry(exc=exc, countdown=60) # Retry after 1 minute
@app.task
def process_single_item(item: Dict[str, Any]) -> Dict[str, Any]:
"""Process single item."""
# Simulate processing
time.sleep(0.1)
return {
'id': item.get('id'),
'processed': True,
'timestamp': time.time()
}
@app.task(bind=True)
def generate_report(
self,
report_type: str,
filters: Dict[str, Any],
format: str = 'pdf'
) -> Dict[str, str]:
"""Generate report."""
logger.info(f"Generating {report_type} report in {format} format")
self.update_state(state='PROGRESS', meta={'step': 'gathering_data'})
# Gather data
time.sleep(2)
self.update_state(state='PROGRESS', meta={'step': 'processing'})
# Process data
time.sleep(2)
self.update_state(state='PROGRESS', meta={'step': 'generating'})
# Generate report
time.sleep(2)
return {
'report_id': f"report-{int(time.time())}",
'url': f"https://cdn.example.com/reports/report.{format}",
'format': format
}
@app.task
def send_email_batch(
recipients: List[str],
template: str,
context: Dict[str, Any]
) -> Dict[str, int]:
"""Send batch of emails."""
successful = 0
failed = 0
for recipient in recipients:
try:
send_email(recipient, template, context)
successful += 1
except Exception as e:
logger.error(f"Failed to send email to {recipient}: {e}")
failed += 1
return {
'successful': successful,
'failed': failed,
'total': len(recipients)
}
@app.task
def generate_daily_report():
"""Scheduled task: Generate daily report."""
logger.info("Generating daily report")
generate_report.delay('daily', {}, 'pdf')
@app.task
def cleanup_old_data():
"""Scheduled task: Clean up old data."""
logger.info("Cleaning up old data")
# Cleanup logic here
def send_email(recipient: str, template: str, context: Dict[str, Any]):
"""Send single email."""
logger.info(f"Sending email to {recipient}")
# Email sending logic
# Task chaining and grouping
from celery import chain, group, chord
def process_in_chunks(items: List[Any], chunk_size: int = 100):
"""Process items in parallel chunks."""
chunks = [items[i:i + chunk_size] for i in range(0, len(items), chunk_size)]
# Process chunks in parallel
job = group(process_batch_data.s(chunk) for chunk in chunks)
result = job.apply_async()
return result
def process_with_callback(items: List[Any]):
"""Process items and call callback when done."""
callback = send_notification.s()
header = group(process_batch_data.s(chunk) for chunk in [items])
# Use chord to call callback after all tasks complete
job = chord(header)(callback)
return job
@app.task
def send_notification(results):
"""Callback task after batch processing."""
logger.info(f"All tasks completed: {len(results)} results")
# Usage examples
if __name__ == '__main__':
# Enqueue task
result = process_batch_data.delay([
{'id': 1, 'value': 'a'},
{'id': 2, 'value': 'b'}
])
# Check task status
print(f"Task ID: {result.id}")
print(f"Status: {result.status}")
# Wait for result (blocking)
final_result = result.get(timeout=10)
print(f"Result: {final_result}")
# Process in chunks
items = [{'id': i} for i in range(1000)]
chunk_result = process_in_chunks(items, chunk_size=100)
# Check group result
print(f"Chunks: {len(chunk_result)}")
3. Cron Job Scheduler
import cron from 'node-cron';
interface ScheduledJob {
name: string;
schedule: string;
handler: () => Promise<void>;
enabled: boolean;
lastRun?: Date;
nextRun?: Date;
}
class JobScheduler {
private jobs: Map<string, cron.ScheduledTask> = new Map();
private jobConfigs: Map<string, ScheduledJob> = new Map();
register(job: ScheduledJob): void {
if (this.jobs.has(job.name)) {
throw new Error(`Job ${job.name} already registered`);
}
// Validate cron expression
if (!cron.validate(job.schedule)) {
throw new Error(`Invalid cron expression: ${job.schedule}`);
}
const task = cron.schedule(job.schedule, async () => {
if (!job.enabled) return;
console.log(`Running job: ${job.name}`);
const startTime = Date.now();
try {
await job.handler();
const duration = Date.now() - startTime;
console.log(`Job ${job.name} completed in ${duration}ms`);
job.lastRun = new Date();
} catch (error) {
console.error(`Job ${job.name} failed:`, error);
}
});
this.jobs.set(job.name, task);
this.jobConfigs.set(job.name, job);
if (job.enabled) {
task.start();
}
}
start(name: string): void {
const task = this.jobs.get(name);
if (!task) {
throw new Error(`Job ${name} not found`);
}
task.start();
const config = this.jobConfigs.get(name)!;
config.enabled = true;
}
stop(name: string): void {
const task = this.jobs.get(name);
if (!task) {
throw new Error(`Job ${name} not found`);
}
task.stop();
const config = this.jobConfigs.get(name)!;
config.enabled = false;
}
remove(name: string): void {
const task = this.jobs.get(name);
if (task) {
task.destroy();
this.jobs.delete(name);
this.jobConfigs.delete(name);
}
}
getJobs(): ScheduledJob[] {
return Array.from(this.jobConfigs.values());
}
}
// Usage
const scheduler = new JobScheduler();
// Register jobs
scheduler.register({
name: 'daily-backup',
schedule: '0 2 * * *', // 2 AM daily
enabled: true,
handler: async () => {
console.log('Running daily backup...');
// Backup logic
}
});
scheduler.register({
name: 'hourly-cleanup',
schedule: '0 * * * *', // Every hour
enabled: true,
handler: async () => {
console.log('Running cleanup...');
// Cleanup logic
}
});
scheduler.register({
name: 'weekly-report',
schedule: '0 9 * * 1', // Monday 9 AM
enabled: true,
handler: async () => {
console.log('Generating weekly report...');
// Report generation
}
});
Best Practices
✅ DO
- Implement idempotency for all jobs
- Use job queues for distributed processing
- Monitor job success/failure rates
- Implement retry logic with exponential backoff
- Set appropriate timeouts
- Log job execution details
- Use dead letter queues for failed jobs
- Implement job priority levels
- Batch similar operations together
- Use connection pooling
- Implement graceful shutdown
- Monitor queue depth and processing time
❌ DON'T
- Process jobs synchronously in request handlers
- Ignore failed jobs
- Set unlimited retries
- Skip monitoring and alerting
- Process jobs without timeouts
- Store large payloads in queue
- Forget to clean up completed jobs
Resources
Quick Install
/plugin add https://github.com/aj-geddes/useful-ai-prompts/tree/main/batch-processing-jobsCopy and paste this command in Claude Code to install this skill
GitHub 仓库
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