---
title: Monitor states
description: Flux provides several functions to help monitor states and state changes in your data.
url: https://docs.influxdata.com/enterprise_influxdb/v1/flux/guides/monitor-states/
estimated_tokens: 3681
product: InfluxDB Enterprise v1
version: v1
---

# Monitor states

Flux helps you monitor states in your metrics and events:

-   [Find how long a state persists](#find-how-long-a-state-persists)
-   [Count the number of consecutive states](#count-the-number-of-consecutive-states)
-   [Detect state changes](#example-query-to-count-machine-state)

If you’re just getting started with Flux queries, check out the following:

-   [Get started with Flux](/enterprise_influxdb/v1/flux/get-started/) for a conceptual overview of Flux.
-   [Execute queries](/enterprise_influxdb/v1/flux/guides/executing-queries/) to discover a variety of ways to run your queries.

## Find how long a state persists

1. Use the [`stateDuration()`](/flux/v0/stdlib/universe/stateduration/) function to calculate how long a column value has remained the same value (or state). Include the following information:
    
    -   **Column to search:** any tag key, tag value, field key, field value, or measurement.
    -   **Value:** the value (or state) to search for in the specified column.
    -   **State duration column:** a new column to store the state duration─the length of time that the specified value persists.
    -   **Unit:** the unit of time (`1s` (by default), `1m`, `1h`) used to increment the state duration.
    
    ```js
    data
        |> stateDuration(
            fn: (r) => r._column_to_search == "value_to_search_for",
            column: "state_duration",
            unit: 1s,
        )
    ```
    
2. Use `stateDuration()` to search each point for the specified value:
    
    -   For the first point that evaluates `true`, the state duration is set to `0`. For each consecutive point that evaluates `true`, the state duration increases by the time interval between each consecutive point (in specified units).
    -   If the state is `false`, the state duration is reset to `-1`.

### Example query with stateDuration()

The following query searches the `doors` bucket over the past 5 minutes to find how many seconds a door has been `closed`.

```js
from(bucket: "doors")
    |> range(start: -5m)
    |> stateDuration(
        fn: (r) => r._value == "closed",
        column: "door_closed",
        unit: 1s,
    )
```

In this example, `door_closed` is the **State duration** column. If you write data to the `doors` bucket every minute, the state duration increases by `60s` for each consecutive point where `_value` is `closed`. If `_value` is not `closed`, the state duration is reset to `0`.

#### Query results

Results for the example query above may look like this (for simplicity, we’ve omitted the measurement, tag, and field columns):

```bash
_time                   _value        door_closed
2019-10-26T17:39:16Z    closed        0
2019-10-26T17:40:16Z    closed        60
2019-10-26T17:41:16Z    closed        120
2019-10-26T17:42:16Z    open          -1
2019-10-26T17:43:16Z    closed        0
2019-10-26T17:44:27Z    closed        60
```

## Count the number of consecutive states

1. Use the `stateCount()` function and include the following information:
    
    -   **Column to search:** any tag key, tag value, field key, field value, or measurement.
    -   **Value:** to search for in the specified column.
    -   **State count column:** a new column to store the state count─the number of consecutive records in which the specified value exists.
    
    ```js
    data
        |> stateCount(
            fn: (r) => r._column_to_search == "value_to_search_for",
            column: "state_count"
        )
    ```
    
2. Use `stateCount()` to search each point for the specified value:
    
    -   For the first point that evaluates `true`, the state count is set to `1`. For each consecutive point that evaluates `true`, the state count increases by 1.
    -   If the state is `false`, the state count is reset to `-1`.

### Example query with stateCount()

The following query searches the `doors` bucket over the past 5 minutes and calculates how many points have `closed` as their `_value`.

```js
from(bucket: "doors")
    |> range(start: -5m)
    |> stateDuration(fn: (r) => r._value == "closed", column: "door_closed")
```

This example stores the **state count** in the `door_closed` column. If you write data to the `doors` bucket every minute, the state count increases by `1` for each consecutive point where `_value` is `closed`. If `_value` is not `closed`, the state count is reset to `-1`.

#### Query results

Results for the example query above may look like this (for simplicity, we’ve omitted the measurement, tag, and field columns):

```bash
_time                   _value        door_closed
2019-10-26T17:39:16Z    closed        1
2019-10-26T17:40:16Z    closed        2
2019-10-26T17:41:16Z    closed        3
2019-10-26T17:42:16Z    open          -1
2019-10-26T17:43:16Z    closed        1
2019-10-26T17:44:27Z    closed        2
```

#### Example query to count machine state

The following query checks the machine state every minute (idle, assigned, or busy). InfluxDB searches the `servers` bucket over the past hour and counts records with a machine state of `idle`, `assigned` or `busy`.

```js
from(bucket: "servers")
    |> range(start: -1h)
    |> filter(fn: (r) => r.machine_state == "idle" or r.machine_state == "assigned" or r.machine_state == "busy")
    |> stateCount(fn: (r) => r.machine_state == "busy", column: "_count")
    |> stateCount(fn: (r) => r.machine_state == "assigned", column: "_count")
    |> stateCount(fn: (r) => r.machine_state == "idle", column: "_count")
```