QL charts: Overview

QL charts are charts created from a connection if the connection source is a database, Prometheus, or Monitoring. To create such charts, one uses direct queries to the source. Depending on the chart type, the query can be run in the source database's SQL dialect, as well as the Prometheus or Monitoring query languages. This helps you to expand visualization capabilities by using language-specific transactions.

Running a query does not create a separate dataset object: a chart is generated on the fly and displayed in the preview panel.

Unlike dataset-based charts, the logic of a visualization area in QL charts favors queries against the source, i.e., the visualization area only displays the data from the query. You can also save QL charts and add them to dashboards as widgets.

The following types of QL charts are supported:

• SQL. These allow you to build visualizations with flexible dataset management based on parameterization of an SQL query to the source DB.

  SQL charts:

  • Reduce database workload by using direct queries.

  • Are only suitable for SELECT queries.

  • Enable the use of JOIN, GROUP BY, and SORT BY queries and aggregation functions in SQL queries.

  • Enable the parameterization of any part of a SQL query.

  • Support a limited set of visualizations types.

  • Do not support RLS and calculable fields.

    Example database query ClickHouse®

    SELECT Category, Month, ROUND(SUM(Sales))
    FROM samples.SampleLite
    WHERE Category in {{category}}: A variable used in the selector
    GROUP BY Category, Month: Grouping by category and month
    ORDER BY Category, Month: Sorting by category and month
    

• Prometheus. These allow you to create a chart based on Prometheus. You cannot build a dataset on top of this source. You can only work with it using QL charts.

  Example query for Prometheus

  sum by (name) (rate(container_cpu_user_seconds_total{container_label_org_label_schema_group="monitoring"}[1m]) * 100  / scalar(count(node_cpu_seconds_total{mode="user"})))
  

• Monitoring. These allow you to create a chart based on Yandex Monitoring. You cannot build a dataset on top of this source. You can only work with it using QL charts.

  Example query for Monitoring

  {project="monitoring", sensor="nodejs.heap_space.size.bytes"}
  

To create a QL chart, follow this guide.

See alsoSee also

• Creating a QL chart
• Chart
• Creating a chart

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