What is a full-text index and when would you use it?

Understanding Full-Text Indexes in MySQL

A full-text index is a special type of index used for fast text-based searching in large text fields. It allows MySQL to perform advanced searches on textual data such as natural language search, boolean search, and phrase matching.

Where Full-Text Indexes Can Be Used

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Supported in InnoDB and MyISAM tables.
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Can be created on CHAR, VARCHAR, and TEXT columns.
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Optimized for large bodies of text—articles, descriptions, comments, logs, etc.

When to Use a Full-Text Index

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When searching for keywords in text columns (e.g., blog posts, product descriptions).
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When you need natural-language ranking of results.
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When performing boolean-mode searches (AND, OR, NOT).
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When simple LIKE '%keyword%' searches are too slow or inefficient.

Creating a Full-Text Index

Example Query

Full-text indexes provide high-performance text search capabilities that go far beyond simple pattern matching and are essential for search functionality in applications.

Difficulty: 5/10

Topics: full-text search, indexing, MySQL

Scenario Questions

0-2 years experience

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We have a MySQL table storing blog posts with a 'content' column. How would you enable keyword search on that column using a full‑text index?
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If you run a SELECT with MATCH...AGAINST on a column that doesn't have a full‑text index, what will happen and why?
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What storage‑engine considerations are there when creating a full‑text index in MySQL?

2-5 years experience

1
Our product added a feature to filter user reviews by relevance. We created a full‑text index on the 'review_text' column, but the results seem unrelated. What could be causing this and how would you troubleshoot?
2
Explain the trade‑offs between using a full‑text index versus LIKE '%term%' for searching product descriptions in a catalog of 2 million rows.
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We need to support phrase searches and boolean operators. How would you configure MATCH...AGAINST to meet these requirements, and what limitations should we be aware of?

5-8 years experience

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Design a solution for a multi‑tenant SaaS platform where each tenant's data lives in the same MySQL database, and you need fast full‑text search across tenant‑specific documents while ensuring data isolation. What indexing strategy would you choose and why?
2
Our MySQL cluster experiences high write load on a table with a full‑text index, causing index rebuilds to become a bottleneck. How would you mitigate the performance impact?
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We are planning to migrate from MySQL's built‑in full‑text search to an external search engine like Elasticsearch. What factors would influence the decision, and how would you orchestrate a phased migration while keeping search functionality available?

8+ years experience

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At the company level, we have legacy applications using MySQL full‑text indexes and newer services using a dedicated search service. How would you define a long‑term architecture that balances consistency, operational overhead, and query capabilities across teams?
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Regulatory compliance requires audit logs of all search queries and results. How would you extend MySQL's full‑text search to capture this information without degrading performance?
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If you need to support multilingual full‑text search (e.g., English, Japanese, Arabic) in a single MySQL instance, what architectural changes or configurations would you propose to ensure relevance and maintainability?

Follow-up Questions

❓Can you compare the storage requirements of a full‑text index to a regular B‑Tree index?
❓What are the limitations of MySQL’s built‑in full‑text search regarding language support?
❓How would you monitor the health of a full‑text index in production?