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za$Nr3dBtL_%!$%T(mUW{fa?1HQRe;sI$QWZPj-^chzG|j=hMRMV-Az(fY-(Ib{36h Hp0WP}-u5yM literal 0 HcmV?d00001 diff --git a/docs/guides/migrate-from-influx.md b/docs/guides/migrate-from-influx.md new file mode 100644 index 0000000000..6bc3efa3b0 --- /dev/null +++ b/docs/guides/migrate-from-influx.md @@ -0,0 +1,270 @@ +# Migrate from InfluxDB to VictoriaMetrics + +InfluxDB is a well-known time series database built for +[IoT](https://en.wikipedia.org/wiki/Internet_of_things) monitoring, Application Performance Monitoring (APM) and +analytics. It has its query language, unique data model, and rich tooling for collecting and processing metrics. + +Nowadays, the volume of time series data grows constantly, as well as requirements for durable time series storage. And +sometimes old known solutions just can't keep up with the new expectations. + +VictoriaMetrics is a high-performance opensource time series database specifically designed to deal with huge volumes of +monitoring data while remaining cost-efficient at the same time. Many companies are choosing to migrate from InfluxDB to +VictoriaMetrics specifically for performance and scalability reasons. Along them see case studies provided by +[ARNES](https://docs.victoriametrics.com/CaseStudies.html#arnes) +and [Brandwatch](https://docs.victoriametrics.com/CaseStudies.html#brandwatch). + +This guide will cover the differences between two solutions, most commonly asked questions, and approaches for migrating +from InfluxDB to VictoriaMetrics. + +## Data model differences + +While readers are likely familiar +with [InfluxDB key concepts](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/), the data model of +VictoriaMetrics is something [new to explore](https://docs.victoriametrics.com/keyConcepts.html#data-model). Let's start +with similarities and differences: + +* both solutions are **schemaless**, which means there is no need to define metrics or their tags in advance; +* multi-dimensional data support is implemented + via [tags](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#tags) + in InfluxDB and via [labels](https://docs.victoriametrics.com/keyConcepts.html#structure-of-a-metric) in + VictoriaMetrics. However, labels in VictoriaMetrics are always `strings`, while InfluxDB supports multiple data types; +* timestamps are stored with nanosecond resolution in InfluxDB, while in VictoriaMetrics it is **milliseconds**; +* in VictoriaMetrics metric's value is always `float64`, while InfluxDB supports multiple data types. +* there are + no [measurements](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#measurement) + or [fields](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#field-key) in + VictoriaMetrics, metric name contains it all. If measurement contains more than 1 field, then for VictoriaMetrics + it will be multiple metrics; +* there are no [buckets](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#bucket) + or [organizations](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#organization), all + data in VictoriaMetrics is stored in a global namespace or within + a [tenant](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html#multitenancy). + +Let's consider the +following [sample data](https://docs.influxdata.com/influxdb/v2.2/reference/key-concepts/data-elements/#sample-data) +borrowed from InfluxDB docs as an example: + +| _measurement | _field | location | scientist | _value | _time | +|--------------|--------|----------|-------------|--------|----------------------| +| census | bees | klamath | anderson | 23 | 2019-08-18T00:00:00Z | +| census | ants | portland | mullen | 30 | 2019-08-18T00:00:00Z | +| census | bees | klamath | anderson | 28 | 2019-08-18T00:06:00Z | +| census | ants | portland | mullen | 32 | 2019-08-18T00:06:00Z | + +In VictoriaMetrics data model this sample will have the following form: + +| metric name | labels | value | time | +|-------------|:---------------------------------------------|-------|----------------------| +| census_bees | {location="klamath", scientist="anderson"} | 23 | 2019-08-18T00:00:00Z | +| census_ants | {location="portland", scientist="mullen"} | 30 | 2019-08-18T00:00:00Z | +| census_bees | {location="klamath", scientist="anderson"} | 28 | 2019-08-18T00:06:00Z | +| census_ants | {location="portland", scientist="mullen"} | 32 | 2019-08-18T00:06:00Z | + +Actually, metric name for VictoriaMetrics is also a label with static name `__name__`, and example above can be +converted to `{__name__="census_bees", location="klamath", scientist="anderson"}`. All labels are indexed by +VictoriaMetrics, so lookups by names or labels have the same query speed. + + +## Write data + +VictoriaMetrics +supports [InfluxDB line protocol](https://docs.victoriametrics.com/#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) +for data ingestion. For example, to write a measurement to VictoriaMetrics we need to send an HTTP POST request with +payload in a line protocol format: + +```bash +curl -d 'census,location=klamath,scientist=anderson bees=23 1566079200000' -X POST 'http://:8428/write' +``` + +_hint: timestamp in the example might be out of configured retention for VictoriaMetrics. Consider increasing the +retention period or changing the timestamp, if that is the case._ + +Please note, an arbitrary number of lines delimited by `\n` (aka newline char) can be sent in a single request. + +To get the written data back let's export all series matching the `location="klamath"` filter: + +```bash +curl -G 'http://:8428/api/v1/export' -d 'match={location="klamath"}' +``` + +The expected response is the following: + +```json +{ + "metric": { + "__name__": "census_bees", + "location": "klamath", + "scientist": "anderson" + }, + "values": [ + 23 + ], + "timestamps": [ + 1566079200000 + ] +} +``` + +Please note, VictoriaMetrics performed additional +[data mapping](https://docs.victoriametrics.com/#how-to-send-data-from-influxdb-compatible-agents-such-as-telegraf) +to the data ingested via InfluxDB line protocol. + +Support of InfluxDB line protocol also means VictoriaMetrics is compatible with +[Telegraf](https://github.com/influxdata/telegraf). To configure Telegraf, simply +add `http://:8428` URL to Telegraf configs: + +``` +[[outputs.influxdb]] + urls = ["http://:8428"] +``` + +In addition to InfluxDB line protocol, VictoriaMetrics supports many other ways for +[metrics collection](https://docs.victoriametrics.com/keyConcepts.html#write-data). + +## Query data + +VictoriaMetrics does not have a com\mand-line interface (CLI). Instead, it provides +an [HTTP API](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#prometheus-querying-api-usage) +for serving read queries. This API is used in various integrations such as +[Grafana](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#grafana-setup). The same API is also used +by [VMUI](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#vmui) - a graphical User Interface for +querying and visualizing metrics: + +{% include img.html href="migrate-from-influx-vmui.png" %} + +See more about [how to query data in VictoriaMetrics](https://docs.victoriametrics.com/keyConcepts.html#query-data). + +### Basic concepts + +Let's take a closer look at querying specific with the following data sample: + +```sql +foo +,instance=localhost bar=1.00 1652169600000000000 +foo,instance=localhost bar=2.00 1652169660000000000 +foo,instance=localhost bar=3.00 1652169720000000000 +foo,instance=localhost bar=5.00 1652169840000000000 +foo,instance=localhost bar=5.50 1652169960000000000 +foo,instance=localhost bar=5.50 1652170020000000000 +foo,instance=localhost bar=4.00 1652170080000000000 +foo,instance=localhost bar=3.50 1652170260000000000 +foo,instance=localhost bar=3.25 1652170320000000000 +foo,instance=localhost bar=3.00 1652170380000000000 +foo,instance=localhost bar=2.00 1652170440000000000 +foo,instance=localhost bar=1.00 1652170500000000000 +foo,instance=localhost bar=4.00 1652170560000000000 +``` + +The data sample consists data points for a measurement `foo` +and a field `bar` with additional tag `instance=localhost`. If we would like plot this data as a time series in Grafana +it might have the following look: + +{% include img.html href="migrate-from-influx-data-sample-in-influx.png" %} + +The query used for this panel is written in +[InfluxQL](https://docs.influxdata.com/influxdb/v1.8/query_language/): + +```sql +SELECT last ("bar") +FROM "foo" +WHERE ("instance" = 'localhost') + AND $timeFilter +GROUP BY time (1m) +``` + +Having this, let's import the same data sample in VictoriaMetrics and plot it in Grafana as well. To understand how the +InfluxQL query might be translated to MetricsQL let's break it into components first: + +* `SELECT last("bar") FROM "foo"` - all requests + to [instant](https://docs.victoriametrics.com/keyConcepts.html#instant-query) + or [range](https://docs.victoriametrics.com/keyConcepts.html#range-query) VictoriaMetrics APIs are reads, so no need + to specify the `SELECT` statement. There are no `measurements` or `fields` in VictoriaMetrics, so the whole expression + can be replaced with `foo_bar` in MetricsQL; +* `WHERE ("instance" = 'localhost')`- [filtering by labels](https://docs.victoriametrics.com/keyConcepts.html#filtering) + in MetricsQL requires specifying the filter in curly braces next to the metric name. So in MetricsQL filter expression + will be translated to `{instance="localhost"}`; +* `WHERE $timeFilter` - filtering by time is done via request params sent along with query, so in MetricsQL no need to + specify this filter; +* `GROUP BY time(1m)` - grouping by time is done by default + in [range](https://docs.victoriametrics.com/keyConcepts.html#range-query) API according to specified `step` param. + This param is also a part of params sent along with request. See how to perform additional + [aggregations and grouping via MetricsQL](https://docs.victoriametrics.com/keyConcepts.html#aggregation-and-grouping-functions) + . + +In result, executing the `foo_bar{instance="localhost"}` MetricsQL expression with `step=1m` for the same set of data in +Grafana will have the following form: + +{% include img.html href="migrate-from-influx-data-sample-in-vm.png" %} + +It is noticeable that visualizations from both databases are a bit different - VictoriaMetrics shows some extra points +filling the gaps in the graph. This behavior is described in more +detail [here](https://docs.victoriametrics.com/keyConcepts.html#range-query). In InfluxDB, we can achieve a similar +behavior by adding `fill(previous)` to the query. + +### Advanced usage + +The good thing is that knowing the basics and some aggregation functions is often enough for using MetricsQL or PromQL. +Let's consider one of the most popular Grafana +dashboards [Node Exporter Full](https://grafana.com/grafana/dashboards/1860). It has almost 15 million downloads and +about 230 PromQL queries in it! But a closer look at those queries shows the following: + +* ~120 queries are just selecting a metric with label filters, + e.g. `node_textfile_scrape_error{instance="$node",job="$job"}`; +* ~80 queries are using [rate](https://docs.victoriametrics.com/MetricsQL.html#rate) function for selected metric, + e.g. `rate(node_netstat_Tcp_InSegs{instance=\"$node\",job=\"$job\"})` +* and the rest + are [aggregation functions](https://docs.victoriametrics.com/keyConcepts.html#aggregation-and-grouping-functions) + like [sum](https://docs.victoriametrics.com/MetricsQL.html#sum) + or [count](https://docs.victoriametrics.com/MetricsQL.html#count). + +To get a better understanding of how MetricsQL works, see the following resources: + +* [MetricsQL concepts](https://docs.victoriametrics.com/keyConcepts.html#metricsql); +* [MetricsQL functions](https://docs.victoriametrics.com/MetricsQL.html); +* [PromQL tutorial for beginners](https://valyala.medium.com/promql-tutorial-for-beginners-9ab455142085). + +## How to migrate current data from InfluxDB to VictoriaMetrics + +Migrating data from other TSDBs to VictoriaMetrics is as simple as importing data via any of +[supported formats](https://docs.victoriametrics.com/keyConcepts.html#push-model). + +But migration from InfluxDB might get easier when using [vmctl](https://docs.victoriametrics.com/vmctl.html) - +VictoriaMetrics command-line tool. See more about +migrating [from InfluxDB v1.x versions](https://docs.victoriametrics.com/vmctl.html#migrating-data-from-influxdb-1x). +Migrating data from InfluxDB v2.x is not supported yet. But there is +useful [3rd party solution]((https://docs.victoriametrics.com/vmctl.html#migrating-data-from-influxdb-2x)) for this. + +Please note, that data migration is a backfilling process. So, please +consider [backfilling tips](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#backfilling). + +## Frequently asked questions + +* How does VictoriaMetrics compare to InfluxDB? + * _[Answer](https://docs.victoriametrics.com/FAQ.html#how-does-victoriametrics-compare-to-influxdb)_ +* Why don't VictoriaMetrics support Remote Read API, so I don't need to learn MetricsQL? + * _[Answer](https://docs.victoriametrics.com/FAQ.html#why-doesnt-victoriametrics-support-the-prometheus-remote-read-api)_ +* The PromQL and MetricsQL are often mentioned together - why is that? + * _MetricsQL - query language inspired by PromQL. MetricsQL is backward-compatible with PromQL, so Grafana + dashboards backed by Prometheus datasource should work the same after switching from Prometheus to + VictoriaMetrics. Both languages mostly share the same concepts with slight differences._ +* Query returns more data points than expected - why? + * _VictoriaMetrics may return non-existing data points if `step` param is lower than the actual data resolution. See + more about this [here](https://docs.victoriametrics.com/keyConcepts.html#range-query)._ +* How do I get the `real` last data point, not `ephemeral`? + * _[last_over_time](https://docs.victoriametrics.com/MetricsQL.html#last_over_time) function can be used for + limiting the lookbehind window for calculated data. For example, `last_over_time(metric[10s])` would return + calculated samples only if the real samples are located closer than 10 seconds to the calculated timestamps + according to + `start`, `end` and `step` query args passed + to [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query)._ +* How do I get raw data points with MetricsQL? + * _For getting raw data points specify the interval at which you want them in square brackets and send + as [instant query](https://docs.victoriametrics.com/keyConcepts.html#instant-query). For + example, `GET api/v1/query?query="my_metric[5m]"&time=