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Tree: d4d6836139

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

add-ec-vacuum

add_fasthttp_client

add_remote_storage

adding-message-queue-integration-tests

also-delete-parent-directory-if-empty

avoid_releasing_temp_file_on_write

changing-to-zap

collect-public-metrics

copilot/fix-helm-chart-installation

copilot/fix-s3-object-tagging-issue

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

ec-disk-type-support

enhance-erasure-coding

fasthttp

feature/tus-protocol

filer1_maintenance_branch

fix-GetObjectLockConfigurationHandler

fix-mount-http-parallelism

fix-s3-object-tagging-issue-7589

fix-versioning-listing-only

ftp

gh-pages

improve-fuse-mount

improve-fuse-mount2

logrus

master

message_send

mount2

mq-subscribe

mq2

original_weed_mount

pr-7412

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

upgrade-versions-to-4.00

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/other

History

chrislu 1d78409440 test: prove Parquet works perfectly when written directly (not via Spark) Created ParquetMemoryComparisonTest that writes identical Parquet data to: 1. Local filesystem 2. SeaweedFS RESULTS: ✅ Both files are 643 bytes ✅ Files are byte-for-byte IDENTICAL ✅ Both files read successfully with ParquetFileReader ✅ NO EOF errors! CONCLUSION: The 78-byte EOF error ONLY occurs when Spark writes Parquet files. Direct Parquet writes work perfectly on SeaweedFS. This proves: - SeaweedFS file storage is correct - Parquet library works fine with SeaweedFS - The issue is in SPARK's Parquet writing logic The problem is likely in how Spark's ParquetOutputFormat or ParquetFileWriter interacts with our getPos() implementation during the multi-stage write/commit process.		1 week ago
..
java	test: prove Parquet works perfectly when written directly (not via Spark)	1 week ago
metrics	Add bucket's traffic metrics (#6444)	11 months ago
mq_client_example	Accumulated changes for message queue (#6600)	9 months ago