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app/vminsert: add -replicationFactor command-line flag for enabling data replication among available -storageNode instances

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This commit is contained in:
Aliaksandr Valialkin 2020-05-27 17:29:37 +03:00
parent b4e3bffe4b
commit 77e5165e7b
3 changed files with 60 additions and 23 deletions
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17
README.md
View File

@ -16,8 +16,9 @@ Join [our Slack](http://slack.victoriametrics.com/) or [contact us](mailto:info@
## Prominent features
- Supports all the features of [single-node version](https://github.com/VictoriaMetrics/VictoriaMetrics).
- Performance and capacity scales horizontally.
- Supports multiple independent namespaces for time series data (aka multi-tenancy).
- Performance and capacity scales horizontally. See [these docs for details](#cluster-resizing-and-scalability).
- Supports multiple independent namespaces for time series data (aka multi-tenancy). See [these docs for details](#multitenancy).
- Supports replication. See [these docs for details](#replication-and-data-safety).
## Architecture overview
@ -203,7 +204,7 @@ or [an alternative dashboard for VictoriaMetrics cluster](https://grafana.com/gr
across `vmstorage` nodes.
### Cluster resizing and scalability.
### Cluster resizing and scalability
Cluster performance and capacity scales with adding new nodes.
@ -283,7 +284,7 @@ Upgrade follows `Cluster resizing procedure` under the hood.
### Replication and data safety
VictoriaMetrics offloads replication to the underlying storage pointed by `-storageDataPath`.
By default VictoriaMetrics offloads replication to the underlying storage pointed by `-storageDataPath`.
It is recommended storing data on [Google Compute Engine persistent disks](https://cloud.google.com/compute/docs/disks/#pdspecs),
since they are protected from data loss and data corruption. They also provide consistently high performance
and [may be resized](https://cloud.google.com/compute/docs/disks/add-persistent-disk) without downtime.
@ -291,7 +292,13 @@ HDD-based persistent disks should be enough for the majority of use cases.
It is recommended using durable replicated persistent volumes in Kubernetes.
Note that [replication doesn't save from disaster](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883).
If `-replicationFactor=N` command-line flag is passed to `vminsert`, then `vminsert` puts `N` copies of the ingested data to distinct `vmstorage` nodes.
This guarantees that all the data remains available for querying if up to `N-1` `vmstorage` nodes are unavailable. Note that `-dedup.minScrapeInterval=1ms` command-line
flag must be passed to `vmselect` if `-replicationFactor` exceeds 1 in order to de-duplicate replicated data during queries.
It is OK if `-dedup.minScrapeInterval` exceeds 1ms.
Note that [replication doesn't save from disaster](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883),
so it is recommended performing regular backups. See [these docs](#backups) for details.
### Backups

27
app/vminsert/netstorage/insert_ctx.go
View File

@ -1,6 +1,7 @@
package netstorage
import (
"flag"
"fmt"
"net/http"
@ -14,6 +15,10 @@ import (
jump "github.com/lithammer/go-jump-consistent-hash"
)
var replicationFactor = flag.Int("replicationFactor", 1, "Replication factor for the ingested data, i.e. how many copies to make among distinct -storageNode instances. "+
"Note that vmselect must run with -dedup.minScrapeInterval=1ms for data de-duplication when replicationFactor is greater than 1. "+
"Higher values for -dedup.minScrapeInterval at vmselect is OK")
// InsertCtx is a generic context for inserting data.
//
// InsertCtx.Reset must be called before the first usage.
@ -115,8 +120,17 @@ func (ctx *InsertCtx) WriteDataPoint(at *auth.Token, labels []prompb.Label, time
// WriteDataPointExt writes the given metricNameRaw with (timestmap, value) to ctx buffer with the given storageNodeIdx.
func (ctx *InsertCtx) WriteDataPointExt(at *auth.Token, storageNodeIdx int, metricNameRaw []byte, timestamp int64, value float64) error {
br := &ctx.bufRowss[storageNodeIdx]
sn := storageNodes[storageNodeIdx]
idx := storageNodeIdx
replicas := *replicationFactor
if replicas <= 0 {
replicas = 1
}
if replicas > len(storageNodes) {
replicas = len(storageNodes)
}
for {
br := &ctx.bufRowss[idx]
sn := storageNodes[idx]
bufNew := storage.MarshalMetricRow(br.buf, metricNameRaw, timestamp, value)
if len(bufNew) >= maxBufSizePerStorageNode {
// Send buf to storageNode, since it is too big.
@ -128,8 +142,17 @@ func (ctx *InsertCtx) WriteDataPointExt(at *auth.Token, storageNodeIdx int, metr
br.buf = bufNew
}
br.rows++
replicas--
if replicas == 0 {
return nil
}
idx++
if idx >= len(storageNodes) {
idx = 0
}
}
}
// FlushBufs flushes ctx bufs to remote storage nodes.
func (ctx *InsertCtx) FlushBufs() error {

17
docs/Cluster-VictoriaMetrics.md
View File

@ -16,8 +16,9 @@ Join [our Slack](http://slack.victoriametrics.com/) or [contact us](mailto:info@
## Prominent features
- Supports all the features of [single-node version](https://github.com/VictoriaMetrics/VictoriaMetrics).
- Performance and capacity scales horizontally.
- Supports multiple independent namespaces for time series data (aka multi-tenancy).
- Performance and capacity scales horizontally. See [these docs for details](#cluster-resizing-and-scalability).
- Supports multiple independent namespaces for time series data (aka multi-tenancy). See [these docs for details](#multitenancy).
- Supports replication. See [these docs for details](#replication-and-data-safety).
## Architecture overview
@ -203,7 +204,7 @@ or [an alternative dashboard for VictoriaMetrics cluster](https://grafana.com/gr
across `vmstorage` nodes.
### Cluster resizing and scalability.
### Cluster resizing and scalability
Cluster performance and capacity scales with adding new nodes.
@ -283,7 +284,7 @@ Upgrade follows `Cluster resizing procedure` under the hood.
### Replication and data safety
VictoriaMetrics offloads replication to the underlying storage pointed by `-storageDataPath`.
By default VictoriaMetrics offloads replication to the underlying storage pointed by `-storageDataPath`.
It is recommended storing data on [Google Compute Engine persistent disks](https://cloud.google.com/compute/docs/disks/#pdspecs),
since they are protected from data loss and data corruption. They also provide consistently high performance
and [may be resized](https://cloud.google.com/compute/docs/disks/add-persistent-disk) without downtime.
@ -291,7 +292,13 @@ HDD-based persistent disks should be enough for the majority of use cases.
It is recommended using durable replicated persistent volumes in Kubernetes.
Note that [replication doesn't save from disaster](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883).
If `-replicationFactor=N` command-line flag is passed to `vminsert`, then `vminsert` puts `N` copies of the ingested data to distinct `vmstorage` nodes.
This guarantees that all the data remains available for querying if up to `N-1` `vmstorage` nodes are unavailable. Note that `-dedup.minScrapeInterval=1ms` command-line
flag must be passed to `vmselect` if `-replicationFactor` exceeds 1 in order to de-duplicate replicated data during queries.
It is OK if `-dedup.minScrapeInterval` exceeds 1ms.
Note that [replication doesn't save from disaster](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883),
so it is recommended performing regular backups. See [these docs](#backups) for details.
### Backups