*TimescaleDB* | TimescaleDB is a time-series database built as a PostgreSQL extension. If enabled, Grafana will use `time_bucket` in the `$__timeGroup` macro and display TimescaleDB specific aggregate functions in the query builder (only available in Grafana 5.3+).
A lower limit for the [$__interval](/reference/templating/#the-interval-variable) and [$__interval_ms](/reference/templating/#the-interval-ms-variable) variables.
Recommended to be set to write frequency, for example `1m` if your data is written every minute.
This option can also be overridden/configured in a dashboard panel under data source options. It's important to note that this value **needs** to be formatted as a
number followed by a valid time identifier, e.g. `1m` (1 minute) or `30s` (30 seconds). The following time identifiers are supported:
You find the PostgreSQL query editor in the metrics tab in Graph or Singlestat panel's edit mode. You enter edit mode by clicking the
panel title, then edit.
The query editor has a link named `Generated SQL` that shows up after a query has been executed, while in panel edit mode. Click on it and it will expand and show the raw interpolated SQL string that was executed.
### Select table, time column and metric column (FROM)
When you enter edit mode for the first time or add a new query Grafana will try to prefill the query builder with the first table that has a timestamp column and a numeric column.
In the FROM field, Grafana will suggest tables that are in the `search_path` of the database user. To select a table or view not in your `search_path`
you can manually enter a fully qualified name (schema.table) like `public.metrics`.
The Time column field refers to the name of the column holding your time values. Selecting a value for the Metric column field is optional. If a value is selected, the Metric column field will be used as the series name.
The metric column suggestions will only contain columns with a text datatype (char,varchar,text).
If you want to use a column with a different datatype as metric column you may enter the column name with a cast: `ip::text`.
You may also enter arbitrary SQL expressions in the metric column field that evaluate to a text datatype like
`hostname || ' ' || container_name`.
### Columns, Window and Aggregation functions (SELECT)
In the `SELECT` row you can specify what columns and functions you want to use.
In the column field you may write arbitrary expressions instead of a column name like `column1 * column2 / column3`.
The available functions in the query editor depend on the PostgreSQL version you selected when configuring the datasource.
If you use aggregate functions you need to group your resultset. The editor will automatically add a `GROUP BY time` if you add an aggregate function.
The editor tries to simplify and unify this part of the query. For example:<br>
<br>
The above will generate the following PostgreSQL `SELECT` clause:
```sql
avg(tx_bytes) OVER (ORDER BY "time" ROWS 5 PRECEDING) AS "tx_bytes"
```
You may add further value columns by clicking the plus button and selecting `Column` from the menu. Multiple value columns will be plotted as separate series in the graph panel.
### Filter data (WHERE)
To add a filter click the plus icon to the right of the `WHERE` condition. You can remove filters by clicking on
the filter and selecting `Remove`. A filter for the current selected timerange is automatically added to new queries.
### Group By
To group by time or any other columns click the plus icon at the end of the GROUP BY row. The suggestion dropdown will only show text columns of your currently selected table but you may manually enter any column.
You can remove the group by clicking on the item and then selecting `Remove`.
If you add any grouping, all selected columns need to have an aggregate function applied. The query builder will automatically add aggregate functions to all columns without aggregate functions when you add groupings.
Grafana can fill in missing values when you group by time. The time function accepts two arguments. The first argument is the time window that you would like to group by, and the second argument is the value you want Grafana to fill missing items with.
You can switch to the raw query editor mode by clicking the hamburger icon and selecting `Switch editor mode` or by clicking `Edit SQL` below the query.
> If you use the raw query editor, be sure your query at minimum has `ORDER BY time` and a filter on the returned time range.
*$__time(dateColumn)* | Will be replaced by an expression to rename the column to `time`. For example, *dateColumn as time*
*$__timeSec(dateColumn)* | Will be replaced by an expression to rename the column to `time` and converting the value to unix timestamp. For example, *extract(epoch from dateColumn) as time*
*$__timeFilter(dateColumn)* | Will be replaced by a time range filter using the specified column name. For example, *dateColumn BETWEEN '2017-04-21T05:01:17Z' AND '2017-04-21T05:06:17Z'*
*$__timeGroup(dateColumn,'5m')* | Will be replaced by an expression usable in a GROUP BY clause. For example, *(extract(epoch from dateColumn)/300)::bigint*300*
*$__timeGroup(dateColumn,'5m', 0)* | Same as above but with a fill parameter so missing points in that series will be added by Grafana and 0 will be used as the value.
*$__timeGroup(dateColumn,'5m', previous)* | Same as above but the previous value in that series will be used as fill value. If no value has been seen yet, NULL will be used (only available in Grafana 5.3+).
*$__timeGroupAlias(dateColumn,'5m')* | Will be replaced with an expression identical to $__timeGroup, but with an added column alias (only available in Grafana 5.3+).
*$__unixEpochFilter(dateColumn)* | Will be replaced by a time range filter using the specified column name with times represented as unix timestamps. For example, *dateColumn >= 1494410783 AND dateColumn <= 1494497183*
We plan to add many more macros. If you have suggestions for what macros you would like to see, please [open an issue](https://github.com/grafana/grafana) in our GitHub repo.
## Table queries
If the `Format as` query option is set to `Table` then you can basically do any type of SQL query. The table panel will automatically show the results of whatever columns & rows your query returns.
Query editor with example query:
The query:
```sql
SELECT
title as "Title",
"user".login as "Created By",
dashboard.created as "Created On"
FROM dashboard
INNER JOIN "user" on "user".id = dashboard.created_by
WHERE $__timeFilter(dashboard.created)
```
You can control the name of the Table panel columns by using regular `as ` SQL column selection syntax.
If you set `Format as` to `Time series`, for use in Graph panel for example, then the query must return a column named `time` that returns either a SQL datetime or any numeric datatype representing unix epoch.
Any column except `time` and `metric` are treated as a value column.
You may return a column named `metric` that is used as metric name for the value column.
If you return multiple value columns and a column named `metric` then this column is used as prefix for the series name (only available in Grafana 5.3+).
Instead of hard-coding things like server, application and sensor name in you metric queries you can use variables in their place. Variables are shown as dropdown select boxes at the top of the dashboard. These dropdowns makes it easy to change the data being displayed in your dashboard.
Checkout the [Templating]({{< relref "reference/templating.md" >}}) documentation for an introduction to the templating feature and the different types of template variables.
### Query Variable
If you add a template variable of the type `Query`, you can write a PostgreSQL query that can
return things like measurement names, key names or key values that are shown as a dropdown select box.
For example, you can have a variable that contains all values for the `hostname` column in a table if you specify a query like this in the templating variable *Query* setting.
```sql
SELECT hostname FROM host
```
A query can return multiple columns and Grafana will automatically create a list from them. For example, the query below will return a list with values from `hostname` and `hostname2`.
```sql
SELECT host.hostname, other_host.hostname2 FROM host JOIN other_host ON host.city = other_host.city
To use time range dependent macros like `$__timeFilter(column)` in your query the refresh mode of the template variable needs to be set to *On Time Range Change*.
```sql
SELECT event_name FROM event_log WHERE $__timeFilter(time_column)
Another option is a query that can create a key/value variable. The query should return two columns that are named `__text` and `__value`. The `__text` column value should be unique (if it is not unique then the first value is used). The options in the dropdown will have a text and value that allows you to have a friendly name as text and an id as the value. An example query with `hostname` as the text and `id` as the value:
```sql
SELECT hostname AS __text, id AS __value FROM host
the hosts variable only show hosts from the current selected region with a query like this (if `region` is a multi-value variable then use the `IN` comparison operator rather than `=` to match against multiple values):
```sql
SELECT hostname FROM host WHERE region IN($region)
From Grafana 4.3.0 to 4.6.0, template variables are always quoted automatically. If your template variables are strings, do not wrap them in quotes in where clauses.
Grafana automatically creates a quoted, comma-separated string for multi-value variables. For example: if `server01` and `server02` are selected then it will be formatted as: `'server01', 'server02'`. To disable quoting, use the csv formatting option for variables:
[Annotations]({{< relref "reference/annotations.md" >}}) allow you to overlay rich event information on top of graphs. You add annotation queries via the Dashboard menu / Annotations view.
It's now possible to configure datasources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for datasources on the [provisioning docs page](/administration/provisioning/#datasources)
