Why Deleting and closing indexes in Elasticsearch? - Purpose & Use Cases

The Big Idea

What if you could instantly hide or remove huge data sets without risking mistakes or downtime?

The Scenario

Imagine you have a huge library of books (data) organized on shelves (indexes). Over time, some shelves become outdated or unused. You try to manually remove or hide these shelves by physically moving books around or covering them with cloth.

The Problem

This manual approach is slow and risky. You might accidentally remove important books or lose track of which shelves are still needed. It's hard to keep the library organized and efficient without a clear system.

The Solution

Deleting and closing indexes in Elasticsearch lets you quickly remove or temporarily disable data collections without losing control. Deleting removes the data permanently, while closing keeps it safe but hidden, freeing resources.

Before vs After

✗ Before

curl -XDELETE 'http://localhost:9200/old_index'
curl -XPOST 'http://localhost:9200/old_index/_close'

✓ After

DELETE /old_index
POST /old_index/_close

What It Enables

This concept enables efficient management of data storage, improving search speed and saving system resources effortlessly.

Real Life Example

A company archives last year's sales data by closing its index to save memory but can reopen it anytime for audits. Old marketing campaigns' data can be deleted permanently to keep the system clean.

Key Takeaways

Manual data cleanup is slow and error-prone.

Deleting and closing indexes provide safe, fast ways to manage data.

They help keep Elasticsearch fast and organized.