---
title: "Write a LogQL query | Grafana Labs"
description: "Learn how to use the Grafana query builder to write a LogQL query"
---

# Write a LogQL query

Now that you’ve defined the requirements for your visualization, it’s time to write the query. A query is an expression that specifies the dataset used in the visualization.

LogQL generates two types of queries:

- **Log queries**: Select and return log lines
- **Metric queries**: Wrap a log query in a function to extract and return metrics

## Elements of a LogQL query

A LogQL query consists of the following basic elements, as shown in the query `count_over_time({namespace="game-2048"} |= "error" [$__auto])`, which selects logs from the `game-app` namespace, filters for lines containing “error”, and counts them over 5-minute intervals.

### Log stream selector

A log stream selector determines which log streams to include in a query’s results. A log stream is a unique source of log entries, defined by a combination of labels and their values. The selector is written by wrapping the label matchers in curly braces.

For example, `{namespace = game-app}` is a log stream selector that uses a filter expression. This selector returns all logs associated with a game app that’s being monitored.

Other common examples of selectors include:

- `service_name`: Identifies the application or service generating the logs
- `pod`: Specifies the name of the pod where the log originated
- `filename`: Denotes the source file of the logs

### Log pipeline (optional)

A log pipeline can be appended to a log stream selector to further process and filter log streams. It is composed of a set of expressions. Each expression is executed in left to right sequence for each log line. If an expression filters out a log line, the pipeline will stop processing the current log line and start processing the next log line.

For example, `|= "error"` is the log pipeline, which uses a line filter expression to retrieve only those log lines that contain the word `error`. You can also use other expressions, such as parser expressions or line format expressions.

### Operation (optional)

An operation creates a metric query. Metric queries extend log queries by applying a function to log query results. This powerful feature creates metrics from logs.

For example, the `count_over_time` operation calculates the number of error logs received for each time interval.

To write a LogQL query, complete the following steps:

1. Select a key-value pair from the **Label filter** drop-down list.
   
   For example, select `namespace`, `=`, and `game-app`.
   
   If you are unsure of the label name, you can click **Label browser** and search for the label.
2. Click **Label browser** to explore available labels and values.
3. Click **Refresh** located in the top-right corner of the dashboard.
   
   The visualization should populate with data.

At this stage, you can save the dashboard and share it with others. The current dashboard includes a Logs panel displaying all logs within the selected namespace. However, this view offers limited utility for troubleshooting.

In the next steps, you’ll learn how to apply a filter expression and aggregation to the log data to monitor the count of error logs per time interval.

1. To define a log pipeline expression, select a line filter operator.
   
   For example, select **Line contains** and enter `error`. The system returns all error logs. All other log types (warning, info) aren’t included in the Logs panel.
2. Click **+ Operations** and select a function.
   
   For example, click **Range function > Count over time**.
3. From the **Visualization** drop-down list located in the upper-right of the page, select **Time series**.
   
   When you apply an operation to log data, you are creating a metrics LogQL query.
4. Click **Refresh** located in the top-right corner of the dashboard.
   
   The visualization updates to show a time series graph.

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### More to explore (optional)

At this point in your journey, you can explore the following paths:

- [Understand labels](/docs/loki/latest/get-started/labels/)
- [Log queries](/docs/loki/latest/query/log_queries/)
- [Log label filters](/docs/grafana/latest/datasources/loki/query-editor/#label-filters)
- [Metric queries](/docs/loki/latest/query/metric_queries/)
- [Log operations](/docs/grafana/latest/datasources/loki/query-editor/#operations)