Visualization types in Elasticsearch

Introduction

Visualizations help you see your data clearly. They turn numbers into pictures that are easy to understand.

You want to see trends in your website visits over time.

You need to compare sales numbers between different products.

You want to find out which categories have the most errors.

You want to show the distribution of response times for your server.

You want to create a dashboard to monitor key metrics at a glance.

Syntax

Elasticsearch

In Elasticsearch Kibana, you create visualizations by choosing a type and configuring data sources and options.

Common visualization types include:
- Bar chart
- Line chart
- Pie chart
- Data table
- Metric
- Heat map
- Gauge

Each type has settings for fields, aggregations, and display options.

You pick the visualization type based on what you want to show.

Most visualizations use aggregations to group and summarize data.

Examples

Example: Number of sales per product category.

Elasticsearch

Bar chart: Shows data as vertical bars.
Use it to compare values across categories.

Example: Website visits per day over a month.

Elasticsearch

Line chart: Shows data points connected by lines.
Use it to show trends over time.

Example: Percentage of errors by error type.

Elasticsearch

Pie chart: Shows parts of a whole as slices.
Use it to show percentage breakdowns.

Example: List of top users with their scores.

Elasticsearch

Data table: Shows raw or aggregated data in rows and columns.
Use it to see exact numbers.

Sample Program

This Elasticsearch query groups sales by category. You can use the results to create a bar chart showing sales per category.

Elasticsearch

POST /sales/_search
{
  "size": 0,
  "aggs": {
    "sales_per_category": {
      "terms": { "field": "category.keyword" }
    }
  }
}

# This query gets sales count per category.
# In Kibana, you would use this aggregation in a bar chart visualization.

Important Notes

Choose visualization types that match your data story.

Use filters to focus on important data before visualizing.

Combine multiple visualizations in dashboards for a full picture.

Summary

Visualizations turn data into easy-to-understand pictures.

Pick the right type: bar for comparisons, line for trends, pie for parts of a whole.

Use Elasticsearch aggregations to prepare data for visualizations.