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upstream-seaweedfs/test/kafka/loadtest/resume_million_test.go
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208 lines
5.8 KiB
Go

package integration
import (
"fmt"
"sync"
"sync/atomic"
"testing"
"time"
"github.com/seaweedfs/seaweedfs/weed/glog"
)
// TestResumeMillionRecords_Fixed - Fixed version with better concurrency handling
func TestResumeMillionRecords_Fixed(t *testing.T) {
const (
totalRecords = 1000000
numPartitions = int32(8)
numProducers = 4
brokerAddr = "localhost:17777"
batchSize = 100 // Process in smaller batches to avoid overwhelming
)
// Create direct broker client
client, err := NewDirectBrokerClient(brokerAddr)
if err != nil {
t.Fatalf("Failed to create direct broker client: %v", err)
}
defer client.Close()
topicName := fmt.Sprintf("resume-million-test-%d", time.Now().Unix())
// Create topic
glog.Infof("Creating topic %s with %d partitions for RESUMED test", topicName, numPartitions)
err = client.ConfigureTopic(topicName, numPartitions)
if err != nil {
t.Fatalf("Failed to configure topic: %v", err)
}
// Performance tracking
var totalProduced int64
var totalErrors int64
startTime := time.Now()
// Progress tracking
ticker := time.NewTicker(5 * time.Second) // More frequent updates
defer ticker.Stop()
go func() {
for range ticker.C {
produced := atomic.LoadInt64(&totalProduced)
errors := atomic.LoadInt64(&totalErrors)
elapsed := time.Since(startTime)
rate := float64(produced) / elapsed.Seconds()
progressPercent := float64(produced) / float64(totalRecords) * 100
glog.Infof("PROGRESS: %d/%d records (%.1f%%), rate: %.0f records/sec, errors: %d",
produced, totalRecords, progressPercent, rate, errors)
if produced >= totalRecords {
return
}
}
}()
// Fixed producer function with better error handling
producer := func(producerID int, recordsPerProducer int) error {
defer glog.Infof("Producer %d FINISHED", producerID)
// Create dedicated clients per producer to avoid contention
producerClient, err := NewDirectBrokerClient(brokerAddr)
if err != nil {
return fmt.Errorf("producer %d failed to create client: %v", producerID, err)
}
defer producerClient.Close()
successCount := 0
for i := 0; i < recordsPerProducer; i++ {
recordID := producerID*recordsPerProducer + i
// Generate test record
testRecord := GenerateMockTestRecord(recordID)
key, value := SerializeMockTestRecord(testRecord)
partition := int32(testRecord.UserID % int64(numPartitions))
// Produce with retry logic
maxRetries := 3
var lastErr error
success := false
for retry := 0; retry < maxRetries; retry++ {
err := producerClient.PublishRecord(topicName, partition, key, value)
if err == nil {
success = true
break
}
lastErr = err
time.Sleep(time.Duration(retry+1) * 100 * time.Millisecond) // Exponential backoff
}
if success {
atomic.AddInt64(&totalProduced, 1)
successCount++
} else {
atomic.AddInt64(&totalErrors, 1)
if atomic.LoadInt64(&totalErrors) < 10 {
glog.Errorf("Producer %d failed record %d after retries: %v", producerID, recordID, lastErr)
}
}
// Batch progress logging
if successCount > 0 && successCount%10000 == 0 {
glog.Infof("Producer %d: %d/%d records completed", producerID, successCount, recordsPerProducer)
}
// Small delay to prevent overwhelming the broker
if i > 0 && i%batchSize == 0 {
time.Sleep(10 * time.Millisecond)
}
}
glog.Infof("Producer %d completed: %d successful, %d errors",
producerID, successCount, recordsPerProducer-successCount)
return nil
}
// Start concurrent producers
glog.Infof("Starting FIXED %d producers for %d records total", numProducers, totalRecords)
var wg sync.WaitGroup
recordsPerProducer := totalRecords / numProducers
for i := 0; i < numProducers; i++ {
wg.Add(1)
go func(producerID int) {
defer wg.Done()
if err := producer(producerID, recordsPerProducer); err != nil {
glog.Errorf("Producer %d FAILED: %v", producerID, err)
}
}(i)
}
// Wait for completion with timeout
done := make(chan bool)
go func() {
wg.Wait()
done <- true
}()
select {
case <-done:
glog.Infof("All producers completed normally")
case <-time.After(30 * time.Minute): // 30-minute timeout
glog.Errorf("Test timed out after 30 minutes")
t.Errorf("Test timed out")
return
}
produceTime := time.Since(startTime)
finalProduced := atomic.LoadInt64(&totalProduced)
finalErrors := atomic.LoadInt64(&totalErrors)
// Performance results
throughputPerSec := float64(finalProduced) / produceTime.Seconds()
dataVolumeMB := float64(finalProduced) * 300 / (1024 * 1024)
throughputMBPerSec := dataVolumeMB / produceTime.Seconds()
successRate := float64(finalProduced) / float64(totalRecords) * 100
glog.Infof("\n"+
"=== FINAL MILLION RECORD TEST RESULTS ===\n"+
"==========================================\n"+
"Records produced: %d / %d\n"+
"Production time: %v\n"+
"Average throughput: %.0f records/sec\n"+
"Data volume: %.1f MB\n"+
"Bandwidth: %.1f MB/sec\n"+
"Errors: %d (%.2f%%)\n"+
"Success rate: %.1f%%\n"+
"Partitions used: %d\n"+
"Concurrent producers: %d\n",
finalProduced, totalRecords,
produceTime,
throughputPerSec,
dataVolumeMB,
throughputMBPerSec,
finalErrors,
float64(finalErrors)/float64(totalRecords)*100,
successRate,
numPartitions,
numProducers,
)
// Test assertions
if finalProduced < int64(totalRecords*0.95) { // Allow 5% tolerance
t.Errorf("Too few records produced: %d < %d (95%% of target)", finalProduced, int64(float64(totalRecords)*0.95))
}
if finalErrors > int64(totalRecords*0.05) { // Error rate should be < 5%
t.Errorf("Too many errors: %d > %d (5%% of target)", finalErrors, int64(float64(totalRecords)*0.05))
}
if throughputPerSec < 100 {
t.Errorf("Throughput too low: %.0f records/sec (expected > 100)", throughputPerSec)
}
glog.Infof("🏆 MILLION RECORD KAFKA INTEGRATION TEST COMPLETED SUCCESSFULLY!")
}