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Tree: 690754acb7

add-admin-and-worker-to-helm-charts

add-ec-vacuum

add-foundation-db

add_fasthttp_client

add_remote_storage

adding-message-queue-integration-tests

avoid_releasing_temp_file_on_write

changing-to-zap

collect-public-metrics

create-table-snapshot-api-design

data_query_pushdown

dependabot/maven/other/java/client/com.google.protobuf-protobuf-java-3.25.5

dependabot/maven/other/java/examples/org.apache.hadoop-hadoop-common-3.4.0

detect-and-plan-ec-tasks

do-not-retry-if-error-is-NotFound

fasthttp

filer1_maintenance_branch

fix-GetObjectLockConfigurationHandler

fix-versioning-listing-only

ftp

gh-pages

improve-fuse-mount

improve-fuse-mount2

logrus

master

message_send

mount2

mq-subscribe

mq2

original_weed_mount

random_access_file

refactor-needle-read-operations

refactor-volume-write

remote_overlay

revert-5134-patch-1

revert-5819-patch-1

revert-6434-bugfix-missing-s3-audit

s3-select

sub

tcp_read

test-reverting-lock-table

test_udp

testing

testing-sdx-generation

tikv

track-mount-e2e

volume_buffered_writes

worker-execute-ec-tasks

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dev

helm-3.65.1

v0.69

v0.70beta

v3.33

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seaweedfs/weed/static/javascript/jquery-sparklines/2.1.2

History

chrislu 690754acb7 fix: Increase fetch batch sizes to utilize available maxBytes capacity PROBLEM: Consumer throughput only 36.80 msgs/sec vs producer 50.21 msgs/sec. Test shows messages consumed at 73% of production rate. ROOT CAUSE: FetchMultipleBatches was hardcoded to fetch only: - 10 records per batch (5.1 KB per batch with 512-byte messages) - 10 batches max per fetch (~51 KB total per fetch) But clients request 10 MB per fetch! - Utilization: 0.5% of requested capacity - Massive inefficiency causing slow consumer throughput Analysis: - Client requests: 10 MB per fetch (FetchSize: 10e6) - Server returns: ~51 KB per fetch (200x less!) - Batches: 10 records each (way too small) - Result: Consumer falls behind producer by 26% FIX: Calculate optimal batch size based on maxBytes: - recordsPerBatch = (maxBytes - overhead) / estimatedMsgSize - Start with 9.8MB / 1024 bytes = ~9,600 records per fetch - Min 100 records, max 10,000 records per batch - Scale max batches based on available space - Adaptive sizing for remaining bytes EXPECTED IMPACT: - Consumer throughput: 36.80 → ~48+ msgs/sec (match producer) - Fetch efficiency: 0.5% → ~98% of maxBytes - Message loss: 45% → near 0% This is critical for matching Kafka semantics where clients specify fetch sizes and the broker should honor them.		1 week ago
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jquery.sparkline.min.js	embed static resources via statik	7 years ago