* initial design
* added simulation as tests
* reorganized the codebase to move the simulation framework and tests into their own dedicated package
* integration test. ec worker task
* remove "enhanced" reference
* start master, volume servers, filer
Current Status
✅ Master: Healthy and running (port 9333)
✅ Filer: Healthy and running (port 8888)
✅ Volume Servers: All 6 servers running (ports 8080-8085)
🔄 Admin/Workers: Will start when dependencies are ready
* generate write load
* tasks are assigned
* admin start wtih grpc port. worker has its own working directory
* Update .gitignore
* working worker and admin. Task detection is not working yet.
* compiles, detection uses volumeSizeLimitMB from master
* compiles
* worker retries connecting to admin
* build and restart
* rendering pending tasks
* skip task ID column
* sticky worker id
* test canScheduleTaskNow
* worker reconnect to admin
* clean up logs
* worker register itself first
* worker can run ec work and report status
but:
1. one volume should not be repeatedly worked on.
2. ec shards needs to be distributed and source data should be deleted.
* move ec task logic
* listing ec shards
* local copy, ec. Need to distribute.
* ec is mostly working now
* distribution of ec shards needs improvement
* need configuration to enable ec
* show ec volumes
* interval field UI component
* rename
* integration test with vauuming
* garbage percentage threshold
* fix warning
* display ec shard sizes
* fix ec volumes list
* Update ui.go
* show default values
* ensure correct default value
* MaintenanceConfig use ConfigField
* use schema defined defaults
* config
* reduce duplication
* refactor to use BaseUIProvider
* each task register its schema
* checkECEncodingCandidate use ecDetector
* use vacuumDetector
* use volumeSizeLimitMB
* remove
remove
* remove unused
* refactor
* use new framework
* remove v2 reference
* refactor
* left menu can scroll now
* The maintenance manager was not being initialized when no data directory was configured for persistent storage.
* saving config
* Update task_config_schema_templ.go
* enable/disable tasks
* protobuf encoded task configurations
* fix system settings
* use ui component
* remove logs
* interface{} Reduction
* reduce interface{}
* reduce interface{}
* avoid from/to map
* reduce interface{}
* refactor
* keep it DRY
* added logging
* debug messages
* debug level
* debug
* show the log caller line
* use configured task policy
* log level
* handle admin heartbeat response
* Update worker.go
* fix EC rack and dc count
* Report task status to admin server
* fix task logging, simplify interface checking, use erasure_coding constants
* factor in empty volume server during task planning
* volume.list adds disk id
* track disk id also
* fix locking scheduled and manual scanning
* add active topology
* simplify task detector
* ec task completed, but shards are not showing up
* implement ec in ec_typed.go
* adjust log level
* dedup
* implementing ec copying shards and only ecx files
* use disk id when distributing ec shards
🎯 Planning: ActiveTopology creates DestinationPlan with specific TargetDisk
📦 Task Creation: maintenance_integration.go creates ECDestination with DiskId
🚀 Task Execution: EC task passes DiskId in VolumeEcShardsCopyRequest
💾 Volume Server: Receives disk_id and stores shards on specific disk (vs.store.Locations[req.DiskId])
📂 File System: EC shards and metadata land in the exact disk directory planned
* Delete original volume from all locations
* clean up existing shard locations
* local encoding and distributing
* Update docker/admin_integration/EC-TESTING-README.md
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* check volume id range
* simplify
* fix tests
* fix types
* clean up logs and tests
---------
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
boltdb is fairly slow to write, about 6 minutes for recreating index
for 1553934 files. Boltdb loads 1,553,934 x 16 = 24,862,944bytes from
disk, and generate the boltdb as large as 134,217,728 bytes in 6
minutes.
To compare, for leveldb, it recreates index in leveldb as large as
27,188,148 bytes in 8 seconds.
For in memory version, it loads the index in
To test the memory consumption, the leveldb or boltdb index are
created. And the server is restarted. Using the benchmark tool to read
lots of files. There are 7 volumes in benchmark collection, each with
about 1553K files.
For leveldb, the memory starts at 142,884KB, and stays at 179,340KB.
For boltdb, the memory starts at 73,756KB, and stays at 144,564KB.
For in-memory, the memory starts at 368,152KB, and stays at 448,032KB.
This supposedly should reduce memory consumption. However, for tests
with millions of, this shows consuming more memories. Need to see
whether this will work out. If not, later boltdb will be tested.
The volume TTL and file TTL are not necessarily the same. as long as
file TTL is smaller than volume TTL, it'll be fine.
volume TTL is used when assigning file id, e.g.
http://.../dir/assign?ttl=3h
file TTL is used when uploading
Chris Lu
chrislu
Konstantin Lebedev
LazyDBA247-Anyvision
j.laycock
brstgt
Stuart P. Bentley
Brian McQueen
wyy