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The major change is adding `sort` directive to docs. For those docs which are copied from internal packages `sort` is added via makefile command. For the rest it is added manually since they're updated manually as well. The rest of changes is connected with markdown formatting. For example, changing headers in some files (`##` => `#`) makes navigation on .github.io to look better. This especially useful for `changelog` docs. Table of contents for `vmctl` is dropped, since we already have it autogenerated on .github.io. No link changes expected. The corresponding PR to `cluster` branch will be made in follow-up PR.
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sort: 7
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---
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# vmctl
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Victoria metrics command-line tool
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Features:
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- [x] Prometheus: migrate data from Prometheus to VictoriaMetrics using snapshot API
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- [x] Thanos: migrate data from Thanos to VictoriaMetrics
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- [ ] ~~Prometheus: migrate data from Prometheus to VictoriaMetrics by query~~(discarded)
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- [x] InfluxDB: migrate data from InfluxDB to VictoriaMetrics
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- [ ] Storage Management: data re-balancing between nodes
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## Articles
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* [How to migrate data from Prometheus](https://medium.com/@romanhavronenko/victoriametrics-how-to-migrate-data-from-prometheus-d44a6728f043)
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* [How to migrate data from Prometheus. Filtering and modifying time series](https://medium.com/@romanhavronenko/victoriametrics-how-to-migrate-data-from-prometheus-filtering-and-modifying-time-series-6d40cea4bf21)
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## How to build
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It is recommended using [binary releases](https://github.com/VictoriaMetrics/VictoriaMetrics/releases) - `vmctl` is located in `vmutils-*` archives there.
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### Development build
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1. [Install Go](https://golang.org/doc/install). The minimum supported version is Go 1.15.
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2. Run `make vmctl` from the root folder of [the repository](https://github.com/VictoriaMetrics/VictoriaMetrics).
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It builds `vmctl` binary and puts it into the `bin` folder.
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### Production build
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1. [Install docker](https://docs.docker.com/install/).
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2. Run `make vmctl-prod` from the root folder of [the repository](https://github.com/VictoriaMetrics/VictoriaMetrics).
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It builds `vmctl-prod` binary and puts it into the `bin` folder.
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### Building docker images
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Run `make package-vmctl`. It builds `victoriametrics/vmctl:<PKG_TAG>` docker image locally.
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`<PKG_TAG>` is auto-generated image tag, which depends on source code in the repository.
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The `<PKG_TAG>` may be manually set via `PKG_TAG=foobar make package-vmctl`.
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The base docker image is [alpine](https://hub.docker.com/_/alpine) but it is possible to use any other base image
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by setting it via `<ROOT_IMAGE>` environment variable. For example, the following command builds the image on top of [scratch](https://hub.docker.com/_/scratch) image:
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```bash
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ROOT_IMAGE=scratch make package-vmctl
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```
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### ARM build
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ARM build may run on Raspberry Pi or on [energy-efficient ARM servers](https://blog.cloudflare.com/arm-takes-wing/).
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#### Development ARM build
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1. [Install Go](https://golang.org/doc/install). The minimum supported version is Go 1.15.
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2. Run `make vmctl-arm` or `make vmctl-arm64` from the root folder of [the repository](https://github.com/VictoriaMetrics/VictoriaMetrics).
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It builds `vmctl-arm` or `vmctl-arm64` binary respectively and puts it into the `bin` folder.
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#### Production ARM build
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1. [Install docker](https://docs.docker.com/install/).
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2. Run `make vmctl-arm-prod` or `make vmctl-arm64-prod` from the root folder of [the repository](https://github.com/VictoriaMetrics/VictoriaMetrics).
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It builds `vmctl-arm-prod` or `vmctl-arm64-prod` binary respectively and puts it into the `bin` folder.
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## Migrating data from InfluxDB (1.x)
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`vmctl` supports the `influx` mode to migrate data from InfluxDB to VictoriaMetrics time-series database.
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See `./vmctl influx --help` for details and full list of flags.
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To use migration tool please specify the InfluxDB address `--influx-addr`, the database `--influx-database` and VictoriaMetrics address `--vm-addr`.
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Flag `--vm-addr` for single-node VM is usually equal to `--httpListenAddr`, and for cluster version
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is equal to `--httpListenAddr` flag of VMInsert component. Please note, that vmctl performs initial readiness check for the given address
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by checking `/health` endpoint. For cluster version it is additionally required to specify the `--vm-account-id` flag.
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See more details for cluster version [here](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster).
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As soon as required flags are provided and all endpoints are accessible, `vmctl` will start the InfluxDB scheme exploration.
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Basically, it just fetches all fields and timeseries from the provided database and builds up registry of all available timeseries.
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Then `vmctl` sends fetch requests for each timeseries to InfluxDB one by one and pass results to VM importer.
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VM importer then accumulates received samples in batches and sends import requests to VM.
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The importing process example for local installation of InfluxDB(`http://localhost:8086`)
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and single-node VictoriaMetrics(`http://localhost:8428`):
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```
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./vmctl influx --influx-database benchmark
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InfluxDB import mode
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2020/01/18 20:47:11 Exploring scheme for database "benchmark"
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2020/01/18 20:47:11 fetching fields: command: "show field keys"; database: "benchmark"; retention: "autogen"
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2020/01/18 20:47:11 found 10 fields
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2020/01/18 20:47:11 fetching series: command: "show series "; database: "benchmark"; retention: "autogen"
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Found 40000 timeseries to import. Continue? [Y/n] y
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40000 / 40000 [-----------------------------------------------------------------------------------------------------------------------------------------------] 100.00% 21 p/s
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2020/01/18 21:19:00 Import finished!
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2020/01/18 21:19:00 VictoriaMetrics importer stats:
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idle duration: 13m51.461434876s;
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time spent while importing: 17m56.923899847s;
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total samples: 345600000;
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samples/s: 320914.04;
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total bytes: 5.9 GB;
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bytes/s: 5.4 MB;
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import requests: 40001;
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2020/01/18 21:19:00 Total time: 31m48.467044016s
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```
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### Data mapping
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Vmctl maps Influx data the same way as VictoriaMetrics does by using the following rules:
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* `influx-database` arg is mapped into `db` label value unless `db` tag exists in the Influx line.
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* Field names are mapped to time series names prefixed with {measurement}{separator} value,
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where {separator} equals to _ by default.
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It can be changed with `--influx-measurement-field-separator` command-line flag.
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* Field values are mapped to time series values.
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* Tags are mapped to Prometheus labels format as-is.
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For example, the following Influx line:
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```
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foo,tag1=value1,tag2=value2 field1=12,field2=40
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```
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is converted into the following Prometheus format data points:
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```
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foo_field1{tag1="value1", tag2="value2"} 12
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foo_field2{tag1="value1", tag2="value2"} 40
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```
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### Configuration
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The configuration flags should contain self-explanatory descriptions.
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### Filtering
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The filtering consists of two parts: timeseries and time.
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The first step of application is to select all available timeseries
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for given database and retention. User may specify additional filtering
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condition via `--influx-filter-series` flag. For example:
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```
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./vmctl influx --influx-database benchmark \
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--influx-filter-series "on benchmark from cpu where hostname='host_1703'"
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InfluxDB import mode
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2020/01/26 14:23:29 Exploring scheme for database "benchmark"
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2020/01/26 14:23:29 fetching fields: command: "show field keys"; database: "benchmark"; retention: "autogen"
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2020/01/26 14:23:29 found 12 fields
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2020/01/26 14:23:29 fetching series: command: "show series on benchmark from cpu where hostname='host_1703'"; database: "benchmark"; retention: "autogen"
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Found 10 timeseries to import. Continue? [Y/n]
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```
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The timeseries select query would be following:
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`fetching series: command: "show series on benchmark from cpu where hostname='host_1703'"; database: "benchmark"; retention: "autogen"`
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The second step of filtering is a time filter and it applies when fetching the datapoints from Influx.
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Time filtering may be configured with two flags:
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* --influx-filter-time-start
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* --influx-filter-time-end
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Here's an example of importing timeseries for one day only:
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`./vmctl influx --influx-database benchmark --influx-filter-series "where hostname='host_1703'" --influx-filter-time-start "2020-01-01T10:07:00Z" --influx-filter-time-end "2020-01-01T15:07:00Z"`
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Please see more about time filtering [here](https://docs.influxdata.com/influxdb/v1.7/query_language/schema_exploration#filter-meta-queries-by-time).
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## Migrating data from InfluxDB (2.x)
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Migrating data from InfluxDB v2.x is not supported yet ([#32](https://github.com/VictoriaMetrics/vmctl/issues/32)).
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You may find useful a 3rd party solution for this - https://github.com/jonppe/influx_to_victoriametrics.
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## Migrating data from Prometheus
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`vmctl` supports the `prometheus` mode for migrating data from Prometheus to VictoriaMetrics time-series database.
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Migration is based on reading Prometheus snapshot, which is basically a hard-link to Prometheus data files.
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See `./vmctl prometheus --help` for details and full list of flags.
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To use migration tool please specify the path to Prometheus snapshot `--prom-snapshot` and VictoriaMetrics address `--vm-addr`.
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More about Prometheus snapshots may be found [here](https://www.robustperception.io/taking-snapshots-of-prometheus-data).
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Flag `--vm-addr` for single-node VM is usually equal to `--httpListenAddr`, and for cluster version
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is equal to `--httpListenAddr` flag of VMInsert component. Please note, that vmctl performs initial readiness check for the given address
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by checking `/health` endpoint. For cluster version it is additionally required to specify the `--vm-account-id` flag.
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See more details for cluster version [here](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster).
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As soon as required flags are provided and all endpoints are accessible, `vmctl` will start the Prometheus snapshot exploration.
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Basically, it just fetches all available blocks in provided snapshot and read the metadata. It also does initial filtering by time
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if flags `--prom-filter-time-start` or `--prom-filter-time-end` were set. The exploration procedure prints some stats from read blocks.
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Please note that stats are not taking into account timeseries or samples filtering. This will be done during importing process.
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The importing process takes the snapshot blocks revealed from Explore procedure and processes them one by one
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accumulating timeseries and samples. Please note, that `vmctl` relies on responses from Influx on this stage,
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so ensure that Explore queries are executed without errors or limits. Please see this
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[issue](https://github.com/VictoriaMetrics/vmctl/issues/30) for details.
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The data processed in chunks and then sent to VM.
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The importing process example for local installation of Prometheus
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and single-node VictoriaMetrics(`http://localhost:8428`):
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```
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./vmctl prometheus --prom-snapshot=/path/to/snapshot \
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--vm-concurrency=1 \
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--vm-batch-size=200000 \
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--prom-concurrency=3
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Prometheus import mode
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Prometheus snapshot stats:
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blocks found: 14;
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blocks skipped: 0;
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min time: 1581288163058 (2020-02-09T22:42:43Z);
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max time: 1582409128139 (2020-02-22T22:05:28Z);
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samples: 32549106;
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series: 27289.
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Found 14 blocks to import. Continue? [Y/n] y
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14 / 14 [-------------------------------------------------------------------------------------------] 100.00% 0 p/s
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2020/02/23 15:50:03 Import finished!
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2020/02/23 15:50:03 VictoriaMetrics importer stats:
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idle duration: 6.152953029s;
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time spent while importing: 44.908522491s;
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total samples: 32549106;
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samples/s: 724786.84;
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total bytes: 669.1 MB;
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bytes/s: 14.9 MB;
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import requests: 323;
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import requests retries: 0;
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2020/02/23 15:50:03 Total time: 51.077451066s
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```
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### Data mapping
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VictoriaMetrics has very similar data model to Prometheus and supports [RemoteWrite integration](https://prometheus.io/docs/operating/integrations/#remote-endpoints-and-storage).
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So no data changes will be applied.
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### Configuration
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The configuration flags should contain self-explanatory descriptions.
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### Filtering
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The filtering consists of three parts: by timeseries and time.
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Filtering by time may be configured via flags `--prom-filter-time-start` and `--prom-filter-time-end`
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in in RFC3339 format. This filter applied twice: to drop blocks out of range and to filter timeseries in blocks with
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overlapping time range.
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Example of applying time filter:
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```
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./vmctl prometheus --prom-snapshot=/path/to/snapshot \
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--prom-filter-time-start=2020-02-07T00:07:01Z \
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--prom-filter-time-end=2020-02-11T00:07:01Z
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Prometheus import mode
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Prometheus snapshot stats:
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blocks found: 2;
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blocks skipped: 12;
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min time: 1581288163058 (2020-02-09T22:42:43Z);
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max time: 1581328800000 (2020-02-10T10:00:00Z);
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samples: 1657698;
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series: 3930.
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Found 2 blocks to import. Continue? [Y/n] y
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```
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Please notice, that total amount of blocks in provided snapshot is 14, but only 2 of them were in provided
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time range. So other 12 blocks were marked as `skipped`. The amount of samples and series is not taken into account,
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since this is heavy operation and will be done during import process.
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Filtering by timeseries is configured with following flags:
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* `--prom-filter-label` - the label name, e.g. `__name__` or `instance`;
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* `--prom-filter-label-value` - the regular expression to filter the label value. By default matches all `.*`
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For example:
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```
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./vmctl prometheus --prom-snapshot=/path/to/snapshot \
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--prom-filter-label="__name__" \
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--prom-filter-label-value="promhttp.*" \
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--prom-filter-time-start=2020-02-07T00:07:01Z \
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--prom-filter-time-end=2020-02-11T00:07:01Z
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Prometheus import mode
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Prometheus snapshot stats:
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blocks found: 2;
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blocks skipped: 12;
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min time: 1581288163058 (2020-02-09T22:42:43Z);
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max time: 1581328800000 (2020-02-10T10:00:00Z);
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samples: 1657698;
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series: 3930.
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Found 2 blocks to import. Continue? [Y/n] y
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14 / 14 [------------------------------------------------------------------------------------------------------------------------------------------------------] 100.00% ? p/s
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2020/02/23 15:51:07 Import finished!
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2020/02/23 15:51:07 VictoriaMetrics importer stats:
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idle duration: 0s;
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time spent while importing: 37.415461ms;
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total samples: 10128;
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samples/s: 270690.24;
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total bytes: 195.2 kB;
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bytes/s: 5.2 MB;
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import requests: 2;
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import requests retries: 0;
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2020/02/23 15:51:07 Total time: 7.153158218s
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```
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## Migrating data from Thanos
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Thanos uses the same storage engine as Prometheus and the data layout on-disk should be the same. That means
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`vmctl` in mode `prometheus` may be used for Thanos historical data migration as well.
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These instructions may vary based on the details of your Thanos configuration.
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Please read carefully and verify as you go. We assume you're using Thanos Sidecar on your Prometheus pods,
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and that you have a separate Thanos Store installation.
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### Current data
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1. For now, keep your Thanos Sidecar and Thanos-related Prometheus configuration, but add this to also stream
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metrics to VictoriaMetrics:
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```
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remote_write:
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- url: http://victoria-metrics:8428/api/v1/write
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```
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2. Make sure VM is running, of course. Now check the logs to make sure that Prometheus is sending and VM is receiving.
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In Prometheus, make sure there are no errors. On the VM side, you should see messages like this:
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```
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2020-04-27T18:38:46.474Z info VictoriaMetrics/lib/storage/partition.go:207 creating a partition "2020_04" with smallPartsPath="/victoria-metrics-data/data/small/2020_04", bigPartsPath="/victoria-metrics-data/data/big/2020_04"
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2020-04-27T18:38:46.506Z info VictoriaMetrics/lib/storage/partition.go:222 partition "2020_04" has been created
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```
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3. Now just wait. Within two hours, Prometheus should finish its current data file and hand it off to Thanos Store for long term
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storage.
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### Historical data
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Let's assume your data is stored on S3 served by minio. You first need to copy that out to a local filesystem,
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then import it into VM using `vmctl` in `prometheus` mode.
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1. Copy data from minio.
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1. Run the `minio/mc` Docker container.
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1. `mc config host add minio http://minio:9000 accessKey secretKey`, substituting appropriate values for the last 3 items.
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1. `mc cp -r minio/prometheus thanos-data`
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1. Import using `vmctl`.
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1. Follow the [instructions](#how-to-build) to compile `vmctl` on your machine.
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1. Use [prometheus](#migrating-data-from-prometheus) mode to import data:
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```
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vmctl prometheus --prom-snapshot thanos-data --vm-addr http://victoria-metrics:8428
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```
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## Migrating data from VictoriaMetrics
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### Native protocol
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The [native binary protocol](https://victoriametrics.github.io/#how-to-export-data-in-native-format)
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was introduced in [1.42.0 release](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.42.0)
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and provides the most efficient way to migrate data between VM instances: single to single, cluster to cluster,
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single to cluster and vice versa. Please note that both instances (source and destination) should be of v1.42.0
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or higher.
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See `./vmctl vm-native --help` for details and full list of flags.
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In this mode `vmctl` acts as a proxy between two VM instances, where time series filtering is done by "source" (`src`)
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and processing is done by "destination" (`dst`). Because of that, `vmctl` doesn't actually know how much data will be
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processed and can't show the progress bar. It will show the current processing speed and total number of processed bytes:
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```
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./vmctl vm-native --vm-native-src-addr=http://localhost:8528 \
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--vm-native-dst-addr=http://localhost:8428 \
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--vm-native-filter-match='{job="vmagent"}' \
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--vm-native-filter-time-start='2020-01-01T20:07:00Z'
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VictoriaMetrics Native import mode
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Initing export pipe from "http://localhost:8528" with filters:
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filter: match[]={job="vmagent"}
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Initing import process to "http://localhost:8428":
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Total: 336.75 KiB ↖ Speed: 454.46 KiB p/s
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2020/10/13 17:04:59 Total time: 952.143376ms
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```
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Importing tips:
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1. Migrating all the metrics from one VM to another may collide with existing application metrics
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(prefixed with `vm_`) at destination and lead to confusion when using
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[official Grafana dashboards](https://grafana.com/orgs/victoriametrics/dashboards).
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To avoid such situation try to filter out VM process metrics via `--vm-native-filter-match` flag.
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2. Migration is a backfilling process, so it is recommended to read
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[Backfilling tips](https://github.com/VictoriaMetrics/VictoriaMetrics#backfilling) section.
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3. `vmctl` doesn't provide relabeling or other types of labels management in this mode.
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Instead, use [relabeling in VictoriaMetrics](https://github.com/VictoriaMetrics/vmctl/issues/4#issuecomment-683424375).
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## Tuning
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### Influx mode
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The flag `--influx-concurrency` controls how many concurrent requests may be sent to InfluxDB while fetching
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timeseries. Please set it wisely to avoid InfluxDB overwhelming.
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The flag `--influx-chunk-size` controls the max amount of datapoints to return in single chunk from fetch requests.
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Please see more details [here](https://docs.influxdata.com/influxdb/v1.7/guides/querying_data/#chunking).
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The chunk size is used to control InfluxDB memory usage, so it won't OOM on processing large timeseries with
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billions of datapoints.
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### Prometheus mode
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The flag `--prom-concurrency` controls how many concurrent readers will be reading the blocks in snapshot.
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Since snapshots are just files on disk it would be hard to overwhelm the system. Please go with value equal
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to number of free CPU cores.
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### VictoriaMetrics importer
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The flag `--vm-concurrency` controls the number of concurrent workers that process the input from InfluxDB query results.
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Please note that each import request can load up to a single vCPU core on VictoriaMetrics. So try to set it according
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to allocated CPU resources of your VictoriMetrics installation.
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The flag `--vm-batch-size` controls max amount of samples collected before sending the import request.
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For example, if `--influx-chunk-size=500` and `--vm-batch-size=2000` then importer will process not more
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than 4 chunks before sending the request.
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### Importer stats
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After successful import `vmctl` prints some statistics for details.
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The important numbers to watch are following:
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- `idle duration` - shows time that importer spent while waiting for data from InfluxDB/Prometheus
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to fill up `--vm-batch-size` batch size. Value shows total duration across all workers configured
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|
via `--vm-concurrency`. High value may be a sign of too slow InfluxDB/Prometheus fetches or too
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high `--vm-concurrency` value. Try to improve it by increasing `--<mode>-concurrency` value or
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decreasing `--vm-concurrency` value.
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- `import requests` - shows how many import requests were issued to VM server.
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The import request is issued once the batch size(`--vm-batch-size`) is full and ready to be sent.
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Please prefer big batch sizes (50k-500k) to improve performance.
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- `import requests retries` - shows number of unsuccessful import requests. Non-zero value may be
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a sign of network issues or VM being overloaded. See the logs during import for error messages.
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### Silent mode
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|
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By default `vmctl` waits confirmation from user before starting the import. If this is unwanted
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behavior and no user interaction required - pass `-s` flag to enable "silence" mode:
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|
```
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|
-s Whether to run in silent mode. If set to true no confirmation prompts will appear. (default: false)
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|
```
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### Significant figures
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`vmctl` allows to limit the number of [significant figures](https://en.wikipedia.org/wiki/Significant_figures)
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before importing. For example, the average value for response size is `102.342305` bytes and it has 9 significant figures.
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If you ask a human to pronounce this value then with high probability value will be rounded to first 4 or 5 figures
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because the rest aren't really that important to mention. In most cases, such a high precision is too much.
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Moreover, such values may be just a result of [floating point arithmetic](https://en.wikipedia.org/wiki/Floating-point_arithmetic),
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create a [false precision](https://en.wikipedia.org/wiki/False_precision) and result into bad compression ratio
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|
according to [information theory](https://en.wikipedia.org/wiki/Information_theory).
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|
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`vmctl` provides the following flags for improving data compression:
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* `--vm-round-digits` flag for rounding processed values to the given number of decimal digits after the point.
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For example, `--vm-round-digits=2` would round `1.2345` to `1.23`. By default the rounding is disabled.
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* `--vm-significant-figures` flag for limiting the number of significant figures in processed values. It takes no effect if set
|
|
to 0 (by default), but set `--vm-significant-figures=5` and `102.342305` will be rounded to `102.34`.
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The most common case for using these flags is to improve data compression for time series storing aggregation
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|
results such as `average`, `rate`, etc.
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### Adding extra labels
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`vmctl` allows to add extra labels to all imported series. It can be achived with flag `--vm-extra-label label=value`.
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If multiple labels needs to be added, set flag for each label, for example, `--vm-extra-label label1=value1 --vm-extra-label label2=value2`.
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If timeseries already have label, that must be added with `--vm-extra-label` flag, flag has priority and will override label value from timeseries.
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|