mirror of
https://github.com/seaweedfs/seaweedfs.git
synced 2026-07-06 00:04:02 +00:00
Chris Lu
a9c0ed91b5
* fix(topology): keep physical disk 0 distinct in SplitByPhysicalDisk DiskId 0 doubles as the first physical disk (Locations[0]) and the protobuf "unset" default. SplitByPhysicalDisk folded every DiskId-0 record onto the aggregate DiskId whenever that was non-zero, so on a multi-disk node the first disk's volumes merged into whichever disk held volumes[0]: the node reported one fewer disk, the sibling showed ~2x volumes, and per-disk max was smeared across the survivors. This surfaced as cluster.status and volume.list undercounting disks. Only treat 0 as unset when no record carries a non-zero DiskId; with a mix, 0 is a real disk and keeps its own entry. * fix(admin): resolve physical disk 0 in active-topology indexes rebuildIndexes re-derived each volume/EC record's physical disk id with the same "DiskId 0 means unset" heuristic SplitByPhysicalDisk used, so the two agreed only by sharing the bug. Now that SplitByPhysicalDisk keeps disk 0 distinct, the duplicated heuristic would fold disk-0 records onto a sibling while at.disks kept them on disk 0; GetVolumeLocations and GetECShardLocations then matched no record and silently dropped every volume and EC shard on the first disk, starving balance and EC tasks. Build the indexes from the same SplitByPhysicalDisk reconstruction that builds at.disks, so the keys always resolve. One source of truth instead of a parallel normalize. * fix(ec): allow physical disk 0 as preferred EC shard target pickBestDiskOnNode gated its result on bestDiskId != 0, but 0 is both a valid physical disk and the uint32 zero value, so a best-scoring disk 0 was discarded and the non-matching fallback returned instead. Gate on bestScore. * test(admin): cover EC-shard index resolution for physical disk 0 rebuildIndexes builds ecShardIndex the same way as volumeIndex; pin the EC path too so a shard on disk 0 keeps resolving via GetECShardLocations.
461 lines
20 KiB
Go
461 lines
20 KiB
Go
package shell
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import (
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"testing"
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"github.com/seaweedfs/seaweedfs/weed/pb/master_pb"
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"github.com/seaweedfs/seaweedfs/weed/storage/erasure_coding"
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"github.com/seaweedfs/seaweedfs/weed/storage/needle"
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"github.com/seaweedfs/seaweedfs/weed/storage/types"
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)
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// TestPickBestDiskOnNodeSelectsPhysicalDiskZero verifies physical disk 0 can be
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// chosen as the preferred shard target. Gating on bestDiskId != 0 discarded a
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// best-scoring disk 0 (0 is also the zero value) and returned the fallback.
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func TestPickBestDiskOnNodeSelectsPhysicalDiskZero(t *testing.T) {
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ecNode := &EcNode{
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disks: map[uint32]*EcDisk{
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0: {diskId: 0, diskType: string(types.SsdType), freeEcSlots: 10, ecShards: map[needle.VolumeId]*erasure_coding.ShardsInfo{}},
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5: {diskId: 5, diskType: string(types.HardDriveType), freeEcSlots: 10, ecShards: map[needle.VolumeId]*erasure_coding.ShardsInfo{}},
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},
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}
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// Disk 0 matches the requested type; it must win over the non-matching
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// fallback on disk 5 instead of being treated as "no match".
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if got := pickBestDiskOnNode(ecNode, needle.VolumeId(42), types.SsdType, false, 0, 0); got != 0 {
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t.Fatalf("want physical disk 0 (matching type), got %d", got)
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}
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}
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func TestCommandEcBalanceSmall(t *testing.T) {
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn1", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}),
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newEcNode("dc1", "rack2", "dn2", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}),
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},
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applyBalancing: false,
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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}
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func TestCommandEcBalanceNothingToMove(t *testing.T) {
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn1", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}),
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newEcNode("dc1", "rack1", "dn2", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}),
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},
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applyBalancing: false,
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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}
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func TestCommandEcBalanceAddNewServers(t *testing.T) {
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn1", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}),
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newEcNode("dc1", "rack1", "dn2", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}),
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newEcNode("dc1", "rack1", "dn3", 100),
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newEcNode("dc1", "rack1", "dn4", 100),
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},
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applyBalancing: false,
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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}
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func TestCommandEcBalanceAddNewRacks(t *testing.T) {
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn1", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}),
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newEcNode("dc1", "rack1", "dn2", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{7, 8, 9, 10, 11, 12, 13}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6}),
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newEcNode("dc1", "rack2", "dn3", 100),
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newEcNode("dc1", "rack2", "dn4", 100),
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},
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applyBalancing: false,
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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}
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func TestCommandEcBalanceVolumeEvenButRackUneven(t *testing.T) {
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ecb := ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn_shared", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0}),
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newEcNode("dc1", "rack1", "dn_a1", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{1}),
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newEcNode("dc1", "rack1", "dn_a2", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{2}),
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newEcNode("dc1", "rack1", "dn_a3", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{3}),
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newEcNode("dc1", "rack1", "dn_a4", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{4}),
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newEcNode("dc1", "rack1", "dn_a5", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{5}),
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newEcNode("dc1", "rack1", "dn_a6", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{6}),
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newEcNode("dc1", "rack1", "dn_a7", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{7}),
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newEcNode("dc1", "rack1", "dn_a8", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{8}),
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newEcNode("dc1", "rack1", "dn_a9", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{9}),
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newEcNode("dc1", "rack1", "dn_a10", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{10}),
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newEcNode("dc1", "rack1", "dn_a11", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{11}),
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newEcNode("dc1", "rack1", "dn_a12", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{12}),
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newEcNode("dc1", "rack1", "dn_a13", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{13}),
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newEcNode("dc1", "rack1", "dn_b1", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{1}),
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newEcNode("dc1", "rack1", "dn_b2", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{2}),
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newEcNode("dc1", "rack1", "dn_b3", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{3}),
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newEcNode("dc1", "rack1", "dn_b4", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{4}),
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newEcNode("dc1", "rack1", "dn_b5", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{5}),
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newEcNode("dc1", "rack1", "dn_b6", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{6}),
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newEcNode("dc1", "rack1", "dn_b7", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{7}),
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newEcNode("dc1", "rack1", "dn_b8", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{8}),
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newEcNode("dc1", "rack1", "dn_b9", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{9}),
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newEcNode("dc1", "rack1", "dn_b10", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{10}),
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newEcNode("dc1", "rack1", "dn_b11", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{11}),
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newEcNode("dc1", "rack1", "dn_b12", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{12}),
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newEcNode("dc1", "rack1", "dn_b13", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{13}),
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newEcNode("dc1", "rack1", "dn3", 100),
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},
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applyBalancing: false,
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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}
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func newEcNode(dc string, rack string, dataNodeId string, freeEcSlot int) *EcNode {
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return &EcNode{
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info: &master_pb.DataNodeInfo{
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Id: dataNodeId,
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DiskInfos: make(map[string]*master_pb.DiskInfo),
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},
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dc: DataCenterId(dc),
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rack: RackId(rack),
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freeEcSlot: freeEcSlot,
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}
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}
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func (ecNode *EcNode) addEcVolumeAndShardsForTest(vid uint32, collection string, shardIds []erasure_coding.ShardId) *EcNode {
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return ecNode.addEcVolumeShards(needle.VolumeId(vid), collection, shardIds, types.HardDriveType)
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}
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// TestCommandEcBalanceEvenDataAndParityDistribution verifies that after balancing:
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// 1. Data shards (0-9) are evenly distributed across racks (max 2 per rack for 6 racks)
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// 2. Parity shards (10-13) are evenly distributed across racks (max 1 per rack for 6 racks)
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func TestCommandEcBalanceEvenDataAndParityDistribution(t *testing.T) {
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// Setup: All 14 shards start on rack1 (simulating fresh EC encode)
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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// All shards initially on rack1/dn1
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newEcNode("dc1", "rack1", "dn1", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}),
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// Empty nodes on other racks
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newEcNode("dc1", "rack2", "dn2", 100),
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newEcNode("dc1", "rack3", "dn3", 100),
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newEcNode("dc1", "rack4", "dn4", 100),
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newEcNode("dc1", "rack5", "dn5", 100),
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newEcNode("dc1", "rack6", "dn6", 100),
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},
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applyBalancing: false, // Dry-run mode (simulates moves by updating internal state)
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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// After balancing (dry-run), verify the PLANNED distribution by checking what moves were proposed
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// The ecb.ecNodes state is updated during dry-run to track planned moves
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vid := needle.VolumeId(1)
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dataShardCount := erasure_coding.DataShardsCount // 10
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parityShardCount := erasure_coding.ParityShardsCount // 4
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// Count data and parity shards per rack based on current (updated) state
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dataPerRack, parityPerRack := countDataAndParityShardsPerRack(ecb.ecNodes, vid, dataShardCount)
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// With 6 racks:
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// - Data shards (10): max 2 per rack (ceil(10/6) = 2)
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// - Parity shards (4): max 1 per rack (ceil(4/6) = 1)
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maxDataPerRack := ceilDivide(dataShardCount, 6) // 2
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maxParityPerRack := ceilDivide(parityShardCount, 6) // 1
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// Verify no rack has more than max data shards
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for rackId, count := range dataPerRack {
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if count > maxDataPerRack {
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t.Errorf("rack %s has %d data shards, expected max %d", rackId, count, maxDataPerRack)
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}
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}
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// Verify no rack has more than max parity shards
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for rackId, count := range parityPerRack {
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if count > maxParityPerRack {
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t.Errorf("rack %s has %d parity shards, expected max %d", rackId, count, maxParityPerRack)
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}
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}
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// Verify all shards are distributed (total counts)
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totalData := 0
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totalParity := 0
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for _, count := range dataPerRack {
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totalData += count
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}
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for _, count := range parityPerRack {
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totalParity += count
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}
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if totalData != dataShardCount {
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t.Errorf("total data shards = %d, expected %d", totalData, dataShardCount)
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}
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if totalParity != parityShardCount {
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t.Errorf("total parity shards = %d, expected %d", totalParity, parityShardCount)
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}
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// Verify data shards are spread across at least 5 racks (10 shards / 2 max per rack)
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racksWithData := len(dataPerRack)
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minRacksForData := dataShardCount / maxDataPerRack // At least 5 racks needed for 10 data shards
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if racksWithData < minRacksForData {
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t.Errorf("data shards spread across only %d racks, expected at least %d", racksWithData, minRacksForData)
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}
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// Verify parity shards are spread across at least 4 racks (4 shards / 1 max per rack)
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racksWithParity := len(parityPerRack)
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if racksWithParity < parityShardCount {
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t.Errorf("parity shards spread across only %d racks, expected at least %d", racksWithParity, parityShardCount)
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}
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t.Logf("Distribution after balancing:")
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t.Logf(" Data shards per rack: %v (max allowed: %d)", dataPerRack, maxDataPerRack)
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t.Logf(" Parity shards per rack: %v (max allowed: %d)", parityPerRack, maxParityPerRack)
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}
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// countDataAndParityShardsPerRack counts data and parity shards per rack
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func countDataAndParityShardsPerRack(ecNodes []*EcNode, vid needle.VolumeId, dataShardCount int) (dataPerRack, parityPerRack map[string]int) {
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dataPerRack = make(map[string]int)
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parityPerRack = make(map[string]int)
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for _, ecNode := range ecNodes {
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si := findEcVolumeShardsInfo(ecNode, vid, types.HardDriveType)
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for _, shardId := range si.Ids() {
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rackId := string(ecNode.rack)
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if int(shardId) < dataShardCount {
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dataPerRack[rackId]++
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} else {
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parityPerRack[rackId]++
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}
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}
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}
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return
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}
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// TestCommandEcBalanceMultipleVolumesEvenDistribution tests that multiple volumes
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// each get their data and parity shards evenly distributed
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func TestCommandEcBalanceMultipleVolumesEvenDistribution(t *testing.T) {
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// Setup: Two volumes, each with all 14 shards on different starting racks
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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// Volume 1: all shards on rack1
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newEcNode("dc1", "rack1", "dn1", 100).addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}),
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// Volume 2: all shards on rack2
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newEcNode("dc1", "rack2", "dn2", 100).addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}),
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// Empty nodes on other racks
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newEcNode("dc1", "rack3", "dn3", 100),
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newEcNode("dc1", "rack4", "dn4", 100),
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newEcNode("dc1", "rack5", "dn5", 100),
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newEcNode("dc1", "rack6", "dn6", 100),
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},
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applyBalancing: false, // Dry-run mode
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diskType: types.HardDriveType,
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}
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ecb.balance([]string{"c1"})
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// Check both volumes
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for _, vid := range []needle.VolumeId{1, 2} {
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dataPerRack, parityPerRack := countDataAndParityShardsPerRack(ecb.ecNodes, vid, erasure_coding.DataShardsCount)
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maxDataPerRack := ceilDivide(erasure_coding.DataShardsCount, 6)
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maxParityPerRack := ceilDivide(erasure_coding.ParityShardsCount, 6)
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for rackId, count := range dataPerRack {
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if count > maxDataPerRack {
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t.Errorf("volume %d: rack %s has %d data shards, expected max %d", vid, rackId, count, maxDataPerRack)
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}
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}
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for rackId, count := range parityPerRack {
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if count > maxParityPerRack {
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t.Errorf("volume %d: rack %s has %d parity shards, expected max %d", vid, rackId, count, maxParityPerRack)
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}
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}
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t.Logf("Volume %d - Data: %v, Parity: %v", vid, dataPerRack, parityPerRack)
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}
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}
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// TestCommandEcBalanceAllNodesShareAllVolumes reproduces the scenario from issue #8793:
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// When every node has a shard of every volume, ec.balance was unable to move any shards
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// because it skipped volumes that already existed on the target node at the volume level.
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func TestCommandEcBalanceAllNodesShareAllVolumes(t *testing.T) {
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// 4 nodes, all in same rack, 2 volumes with 14 shards each.
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// Distribute shards so every node has shards of both volumes, but unevenly:
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// dn1: vol1 shards 0-4, vol2 shards 0-4 => 10 shards
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// dn2: vol1 shards 5-9, vol2 shards 5-9 => 10 shards
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// dn3: vol1 shards 10-12, vol2 shards 10-12 => 6 shards
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// dn4: vol1 shard 13, vol2 shard 13 => 2 shards
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// Total: 28 shards, average = 7 per node
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ecb := &ecBalancer{
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ecNodes: []*EcNode{
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newEcNode("dc1", "rack1", "dn1", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{0, 1, 2, 3, 4}),
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newEcNode("dc1", "rack1", "dn2", 100).
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addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{5, 6, 7, 8, 9}).
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addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{5, 6, 7, 8, 9}),
|
|
newEcNode("dc1", "rack1", "dn3", 100).
|
|
addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{10, 11, 12}).
|
|
addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{10, 11, 12}),
|
|
newEcNode("dc1", "rack1", "dn4", 100).
|
|
addEcVolumeAndShardsForTest(1, "c1", []erasure_coding.ShardId{13}).
|
|
addEcVolumeAndShardsForTest(2, "c1", []erasure_coding.ShardId{13}),
|
|
},
|
|
applyBalancing: false,
|
|
diskType: types.HardDriveType,
|
|
}
|
|
|
|
ecb.balance([]string{"c1"})
|
|
|
|
// Count total shards per node after balancing
|
|
for _, node := range ecb.ecNodes {
|
|
count := 0
|
|
if diskInfo, found := node.info.DiskInfos[string(types.HardDriveType)]; found {
|
|
for _, ecsi := range diskInfo.EcShardInfos {
|
|
count += erasure_coding.GetShardCount(ecsi)
|
|
}
|
|
}
|
|
// Average is 7, so all nodes should be at 7 (ceil(28/4) = 7)
|
|
if count > 7 {
|
|
t.Errorf("node %s has %d shards after balancing, expected at most 7", node.info.Id, count)
|
|
}
|
|
t.Logf("node %s: %d shards", node.info.Id, count)
|
|
}
|
|
}
|
|
|
|
// TestCommandEcBalanceIssue8793Topology simulates the real cluster from issue #8793:
|
|
// 14 nodes (9 with max=80, 5 with max=33), all in one rack, with mixed capacities.
|
|
// Each EC volume has 1 shard per node. Nodes have uneven totals (some have extra volumes).
|
|
func TestCommandEcBalanceIssue8793Topology(t *testing.T) {
|
|
// Simulate 22 EC volumes across 14 nodes (each volume has 14 shards, 1 per node).
|
|
// Give nodes 0-3 an extra volume each (vol 23-26, all 14 shards) to create imbalance.
|
|
// Before balancing: nodes 0-3 have 22+14=36 shards each, nodes 4-13 have 22 shards each.
|
|
// Total = 4*36 + 10*22 = 144+220 = 364. Capacities are heterogeneous (max 80 vs
|
|
// 33), so the utilization-based global phase balances by fullness, not count:
|
|
// 364 shards over 9*80+5*33=885 slots is ~41% full, so large nodes settle near
|
|
// 33 shards and small nodes near 14 (all ~41% full) rather than ~26 each, which
|
|
// would drive the small nodes to ~79%.
|
|
|
|
type nodeSpec struct {
|
|
id string
|
|
maxSlot int
|
|
}
|
|
nodes := []nodeSpec{
|
|
{"192.168.0.12:8332", 80}, {"192.168.0.12:8333", 80}, {"192.168.0.12:8334", 80},
|
|
{"192.168.0.12:8335", 80}, {"192.168.0.12:8336", 80}, {"192.168.0.12:8337", 80},
|
|
{"192.168.0.12:8338", 80}, {"192.168.0.12:8339", 80}, {"192.168.0.12:8340", 80},
|
|
{"192.168.0.12:8341", 33}, {"192.168.0.12:8342", 33}, {"192.168.0.12:8343", 33},
|
|
{"192.168.0.25:8350", 33}, {"192.168.0.25:8351", 33},
|
|
}
|
|
|
|
ecNodes := make([]*EcNode, len(nodes))
|
|
for i, ns := range nodes {
|
|
ecNodes[i] = newEcNode("home", "center", ns.id, ns.maxSlot)
|
|
}
|
|
|
|
// 22 shared volumes: each node gets exactly 1 shard (shard i for node i)
|
|
for vid := uint32(1); vid <= 22; vid++ {
|
|
for i := range ecNodes {
|
|
ecNodes[i].addEcVolumeAndShardsForTest(vid, "cldata", []erasure_coding.ShardId{erasure_coding.ShardId(i)})
|
|
}
|
|
}
|
|
|
|
// 4 extra volumes only on first 4 nodes (all 14 shards each) to create imbalance
|
|
for extra := uint32(0); extra < 4; extra++ {
|
|
vid := 23 + extra
|
|
nodeIdx := int(extra)
|
|
allShards := make([]erasure_coding.ShardId, 14)
|
|
for s := 0; s < 14; s++ {
|
|
allShards[s] = erasure_coding.ShardId(s)
|
|
}
|
|
ecNodes[nodeIdx].addEcVolumeAndShardsForTest(vid, "cldata", allShards)
|
|
}
|
|
|
|
ecb := &ecBalancer{
|
|
ecNodes: ecNodes,
|
|
applyBalancing: false,
|
|
diskType: types.HardDriveType,
|
|
}
|
|
|
|
// Log initial state
|
|
for _, node := range ecb.ecNodes {
|
|
count := 0
|
|
if diskInfo, found := node.info.DiskInfos[string(types.HardDriveType)]; found {
|
|
for _, ecsi := range diskInfo.EcShardInfos {
|
|
count += erasure_coding.GetShardCount(ecsi)
|
|
}
|
|
}
|
|
t.Logf("BEFORE node %s (max %d): %d shards", node.info.Id, node.freeEcSlot+count, count)
|
|
}
|
|
|
|
ecb.balance([]string{"cldata"})
|
|
|
|
// Verify even FULLNESS (shards/capacity), not even count: with heterogeneous
|
|
// capacities the utilization-based global phase fills nodes proportionally, so
|
|
// large nodes hold more shards than small ones while every node ends near the
|
|
// overall fullness. (An even-count result would over-fill the small nodes.)
|
|
capacityByID := make(map[string]int, len(nodes))
|
|
for _, ns := range nodes {
|
|
capacityByID[ns.id] = ns.maxSlot
|
|
}
|
|
|
|
totalShards := 0
|
|
totalCapacity := 0
|
|
shardCounts := make(map[string]int)
|
|
for _, node := range ecb.ecNodes {
|
|
count := 0
|
|
if diskInfo, found := node.info.DiskInfos[string(types.HardDriveType)]; found {
|
|
for _, ecsi := range diskInfo.EcShardInfos {
|
|
count += erasure_coding.GetShardCount(ecsi)
|
|
}
|
|
}
|
|
shardCounts[node.info.Id] = count
|
|
totalShards += count
|
|
totalCapacity += capacityByID[node.info.Id]
|
|
}
|
|
overallFullness := float64(totalShards) / float64(totalCapacity)
|
|
|
|
// Tolerance well below the gap a count-even result would show (small nodes
|
|
// would sit ~38 points above overall), but above integer-rounding skew.
|
|
const tolerance = 0.05
|
|
for _, node := range ecb.ecNodes {
|
|
count := shardCounts[node.info.Id]
|
|
capacity := capacityByID[node.info.Id]
|
|
fullness := float64(count) / float64(capacity)
|
|
t.Logf("AFTER node %s: %d/%d shards (%.0f%% full, overall %.0f%%)",
|
|
node.info.Id, count, capacity, fullness*100, overallFullness*100)
|
|
if diff := fullness - overallFullness; diff > tolerance || diff < -tolerance {
|
|
t.Errorf("node %s fullness %.1f%% deviates from overall %.1f%% by more than %.0f points",
|
|
node.info.Id, fullness*100, overallFullness*100, tolerance*100)
|
|
}
|
|
}
|
|
}
|