mirror of
https://github.com/ClusterCockpit/cc-metric-store.git
synced 2025-04-06 13:55:54 +02:00
Compare commits
No commits in common. "main" and "v0.1.0" have entirely different histories.
6
.gitignore
vendored
6
.gitignore
vendored
@ -4,6 +4,7 @@
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*.dll
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*.so
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*.dylib
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/cc-metric-store
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# Test binary, built with `go test -c`
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*.test
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@ -15,16 +16,15 @@
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# vendor/
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# Project specific ignores
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/cc-metric-store
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/var
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aditya.creds
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test.creds
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/config.json
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./config.json
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migrateTimestamps.pl
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test_ccms_api.sh
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test_ccms_free_api.sh
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test_ccms_write_api.sh
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sample_alex.txt
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sample_fritz.txt
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sample_fritz.txt
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2
Makefile
2
Makefile
@ -1,6 +1,6 @@
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TARGET = ./cc-metric-store
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VAR = ./var/checkpoints/
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VERSION = 0.1.1
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VERSION = 0.1.0
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GIT_HASH := $(shell git rev-parse --short HEAD || echo 'development')
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CURRENT_TIME = $(shell date +"%Y-%m-%d:T%H:%M:%S")
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LD_FLAGS = '-s -X main.date=${CURRENT_TIME} -X main.version=${VERSION} -X main.commit=${GIT_HASH}'
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@ -1,10 +1,10 @@
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# `cc-metric-store` version 0.1.1
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# `cc-metric-store` version 0.1.0
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This is a bugfix release of `cc-metric-store`, the metric timeseries cache
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This is a minor release of `cc-metric-store`, the metric timeseries cache
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implementation of ClusterCockpit.
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For release specific notes visit the [ClusterCockpit Documentation](https://clusterockpit.org/docs/release/).
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Notable changes in version 0.1.0:
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Notable changes:
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- Cleanup of code and restructuring
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- Document REST API with Swagger
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@ -14,6 +14,7 @@ Notable changes in version 0.1.0:
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- Support also ms, ns in line protocol
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- Support NATS credentials
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## Breaking changes
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None
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@ -1,196 +0,0 @@
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{
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"metrics": {
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"debug_metric": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"clock": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_idle": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_iowait": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_irq": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_system": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_user": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"nv_mem_util": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"nv_temp": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"nv_sm_clock": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"acc_utilization": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"acc_mem_used": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"acc_power": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"flops_any": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"flops_dp": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"flops_sp": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"ib_recv": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"ib_xmit": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"ib_recv_pkts": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"ib_xmit_pkts": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"cpu_power": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"core_power": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"mem_power": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"ipc": {
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"frequency": 60,
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"aggregation": "avg"
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},
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"cpu_load": {
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"frequency": 60,
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"aggregation": null
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},
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"lustre_close": {
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"frequency": 60,
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"aggregation": null
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},
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"lustre_open": {
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"frequency": 60,
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"aggregation": null
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},
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"lustre_statfs": {
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"frequency": 60,
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"aggregation": null
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},
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"lustre_read_bytes": {
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"frequency": 60,
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"aggregation": null
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},
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"lustre_write_bytes": {
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"frequency": 60,
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"aggregation": null
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},
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"net_bw": {
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"frequency": 60,
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"aggregation": null
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},
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"file_bw": {
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"frequency": 60,
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"aggregation": null
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},
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"mem_bw": {
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"frequency": 60,
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"aggregation": "sum"
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},
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"mem_cached": {
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"frequency": 60,
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"aggregation": null
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},
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"mem_used": {
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"frequency": 60,
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"aggregation": null
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},
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"net_bytes_in": {
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"frequency": 60,
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"aggregation": null
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},
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"net_bytes_out": {
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"frequency": 60,
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"aggregation": null
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},
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"nfs4_read": {
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"frequency": 60,
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"aggregation": null
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},
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"nfs4_total": {
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"frequency": 60,
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"aggregation": null
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},
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"nfs4_write": {
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"frequency": 60,
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"aggregation": null
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},
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"vectorization_ratio": {
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"frequency": 60,
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"aggregation": "avg"
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}
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},
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"checkpoints": {
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"interval": "12h",
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"directory": "./var/checkpoints",
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"restore": "48h"
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},
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"archive": {
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"interval": "50h",
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"directory": "./var/archive"
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},
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"http-api": {
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"address": "localhost:8082",
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"https-cert-file": null,
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"https-key-file": null
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},
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"retention-in-memory": "48h",
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"nats": [
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{
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"address": "nats://localhost:4222",
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"creds-file-path": "test.creds",
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"subscriptions": [
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{
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"subscribe-to": "ee-hpc-nats",
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"cluster-tag": "fritz2"
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}
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]
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}
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],
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"jwt-public-key": "kzfYrYy+TzpanWZHJ5qSdMj5uKUWgq74BWhQG6copP0="
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}
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@ -180,6 +180,17 @@
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"https-key-file": null
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},
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"retention-in-memory": "48h",
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"nats": null,
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"nats": [
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{
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"address": "nats://localhost:4222",
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"creds-file-path": "test.creds",
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"subscriptions": [
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{
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"subscribe-to": "ee-hpc-nats",
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"cluster-tag": "fritz2"
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}
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]
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}
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],
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"jwt-public-key": "kzfYrYy+TzpanWZHJ5qSdMj5uKUWgq74BWhQG6copP0="
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}
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@ -8,20 +8,20 @@ import (
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"github.com/ClusterCockpit/cc-metric-store/internal/util"
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)
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func SimpleResampler(data []util.Float, old_frequency int64, new_frequency int64) ([]util.Float, int64, error) {
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if old_frequency == 0 || new_frequency == 0 || new_frequency <= old_frequency {
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return data, old_frequency, nil
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func SimpleResampler(data []util.Float, old_frequency int64, new_frequency int64) ([]util.Float, error) {
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if old_frequency == 0 || new_frequency == 0 {
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return nil, errors.New("either old or new frequency is set to 0")
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}
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if new_frequency%old_frequency != 0 {
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return nil, 0, errors.New("new sampling frequency should be multiple of the old frequency")
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return nil, errors.New("new sampling frequency should be multiple of the old frequency")
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}
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var step int = int(new_frequency / old_frequency)
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var new_data_length = len(data) / step
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if new_data_length == 0 || len(data) < 100 || new_data_length >= len(data) {
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return data, old_frequency, nil
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return data, nil
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}
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new_data := make([]util.Float, new_data_length)
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@ -30,14 +30,14 @@ func SimpleResampler(data []util.Float, old_frequency int64, new_frequency int64
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new_data[i] = data[i*step]
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}
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return new_data, new_frequency, nil
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return new_data, nil
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}
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// Inspired by one of the algorithms from https://skemman.is/bitstream/1946/15343/3/SS_MSthesis.pdf
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// Adapted from https://github.com/haoel/downsampling/blob/master/core/lttb.go
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func LargestTriangleThreeBucket(data []util.Float, old_frequency int64, new_frequency int64) ([]util.Float, int64, error) {
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if old_frequency == 0 || new_frequency == 0 || new_frequency <= old_frequency {
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if old_frequency == 0 || new_frequency == 0 {
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return data, old_frequency, nil
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}
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