kylebrandt

{
  "__inputs": [
    {
      "name": "DS_MOCK",
      "label": "Mock",
      "description": "",
      "type": "datasource",
      "pluginId": "grafana-mock-datasource",
      "pluginName": "Mock"
    },

kylebrandt

Dataplane FAQ

How does dataplane relate to Dataframes?

Dataplane adds a data typing layer on top of data frames. By analogy Dataplane Types are to dataframes as typescript is to javascript.

Specifically, a property is added to the dataframe to indicate its type with is made up of a kind and a format, for example "Timeseries Wide".

There are two properties attached to each data frame for this, frame.meta.type and frame.meta.typeversion.

kylebrandt

HTTP/1.1 200 OK
Audit-Id: 5b82aaf1-4ba7-48bc-bb7b-94a7b89c6c5e
Cache-Control: no-store
Content-Type: application/json
X-Content-Type-Options: nosniff
X-Frame-Options: deny
X-Xss-Protection: 1; mode=block
Date: Fri, 19 Sep 2025 14:51:41 GMT
Content-Length: 902
Connection: close

kylebrandt

The queries

Panel: Main Sheet

SQL:

SELECT title, author, copyright, href, image, rating, series
FROM main

kylebrandt

/* Long 
WITH movie_genre AS (
  SELECT
    A.title,
    A.year,
    B.Genre AS genre
  FROM A
  JOIN B ON A.imdb_id = B.imdb_id
),
genre_totals AS (

kylebrandt

Smooth Time Series (PromQL DS)

Trend line over Time Series (PromQL DS)

Aggregation and Math across Different Queries (Azure Metrics)

Calculate percentage of syn packages against total packets, per direction

kylebrandt

package sql

import (
	"context"
	"time"

	mysql "github.com/dolthub/go-mysql-server/sql"
	"github.com/dolthub/go-mysql-server/sql/types"
)

kylebrandt

📘 Basic Usage of SQL Expressions in Grafana

SQL expressions in Grafana let you perform lightweight SQL-like transformations on the results of other queries — directly within the panel. This is great for reshaping, renaming, filtering, and aggregating data without modifying the original datasource query.

---

🔧 How SQL Expressions Work

SQL expressions operate on the output of another query in the same panel, referenced by its query letter (e.g., A, B). These expressions are parsed and executed by Grafana — not sent to an external database.

kylebrandt

Why *_full_long Formats Are Essential for Handling Label Sparsity

Overview

In Grafana, data coming from many sources includes sparse labels — meaning some series have label keys that others do not.
This is common in systems like Prometheus, OpenTelemetry, or SQL queries with GROUP BY.

However, traditional long formats (like time_series_long or numeric_long) do not preserve label sparsity correctly, leading to broken behaviors in visualization, alerts, and expressions.

---

kylebrandt

package sql

import (
	"fmt"

	mysql "github.com/dolthub/go-mysql-server/sql"
	"github.com/dolthub/go-mysql-server/sql/types"
)

type SlothFunction struct{}