Ranking with ts_rank in PostgreSQL

Introduction

Ranking with ts_rank helps you find and order text search results by how well they match your search words.

You want to search a list of articles and show the most relevant ones first.

You have a product catalog and want to rank products by how closely their descriptions match a search term.

You want to highlight the best matching rows in a large text database.

You need to sort search results by relevance instead of just showing all matches equally.

Syntax

PostgreSQL

ts_rank(vector, query [, weights])

vector is a special text search vector made from your text data.

query is the search phrase turned into a text search query.

Examples

This ranks how well the word 'PostgreSQL' matches the text 'PostgreSQL tutorial'.

PostgreSQL

SELECT ts_rank(to_tsvector('english', 'PostgreSQL tutorial'), to_tsquery('english', 'PostgreSQL')) AS rank;

This ranks the phrase 'SQL & databases' against the text 'Learn SQL and databases'.

PostgreSQL

SELECT ts_rank(to_tsvector('english', 'Learn SQL and databases'), to_tsquery('english', 'SQL & databases')) AS rank;

Sample Program

This example creates a table of articles, inserts some sample data, and then searches the body text for 'SQL' and 'database'. It ranks the articles by how well they match and shows the best matches first.

PostgreSQL

CREATE TABLE articles (id SERIAL PRIMARY KEY, title TEXT, body TEXT);

INSERT INTO articles (title, body) VALUES
('PostgreSQL Basics', 'Learn the basics of PostgreSQL database.'),
('Advanced SQL', 'Deep dive into SQL queries and optimization.'),
('Database Tutorial', 'Tutorial on databases and SQL.');

SELECT id, title, ts_rank(to_tsvector('english', body), to_tsquery('english', 'SQL & database')) AS rank
FROM articles
WHERE to_tsvector('english', body) @@ to_tsquery('english', 'SQL & database')
ORDER BY rank DESC;

Important Notes

The ts_rank function returns a number showing match quality; it is not limited to between 0 and 1.

Higher rank means better match.

You can use weights to give more importance to some words.

Summary

ts_rank helps order search results by relevance.

Use to_tsvector to prepare text and to_tsquery for search terms.

Sort results by ts_rank to show best matches first.

Practice

1. What does the ts_rank function do in PostgreSQL full-text search?

easy

A. It creates a search query from a string.

B. It converts text into a searchable vector format.

C. It calculates the relevance ranking of a document for a search query.

D. It sorts rows alphabetically by a text column.

Solution

1. Step 1: Understand the purpose of ts_rank

   The ts_rank function scores how well a document matches a search query in full-text search.

2. Step 2: Differentiate from related functions

   to_tsvector prepares text, to_tsquery creates queries, but ts_rank ranks results.

3. Final Answer:

   It calculates the relevance ranking of a document for a search query. -> Option C

4. Quick Check:

   ts_rank = relevance score [OK]

Hint: Remember ts_rank ranks relevance, not text conversion [OK]

Common Mistakes:

• Confusing ts_rank with to_tsvector
• Thinking ts_rank creates search queries
• Assuming ts_rank sorts alphabetically

2. Which of the following is the correct syntax to rank search results using ts_rank in PostgreSQL?

easy

A. SELECT *, ts_rank(to_tsvector(text_column), to_tsquery('search')) AS rank FROM table ORDER BY rank DESC;

B. SELECT *, ts_rank(text_column, 'search') AS rank FROM table ORDER BY rank ASC;

C. SELECT *, ts_rank(to_tsquery(text_column), to_tsvector('search')) AS rank FROM table;

D. SELECT *, ts_rank('search', text_column) AS rank FROM table ORDER BY rank DESC;

Solution

1. Step 1: Check correct function arguments

   ts_rank requires a tsvector and a tsquery, so to_tsvector(text_column) and to_tsquery('search') are correct.

2. Step 2: Verify ordering and syntax

   Ordering by rank descending shows best matches first, matching SELECT *, ts_rank(to_tsvector(text_column), to_tsquery('search')) AS rank FROM table ORDER BY rank DESC;.

3. Final Answer:

   SELECT *, ts_rank(to_tsvector(text_column), to_tsquery('search')) AS rank FROM table ORDER BY rank DESC; -> Option A

4. Quick Check:

   Correct ts_rank syntax = SELECT *, ts_rank(to_tsvector(text_column), to_tsquery('search')) AS rank FROM table ORDER BY rank DESC; [OK]

Hint: ts_rank needs to_tsvector first, then to_tsquery second [OK]

Common Mistakes:

• Swapping to_tsvector and to_tsquery arguments
• Ordering results ascending instead of descending
• Passing plain text instead of tsvector or tsquery

3. Given the table documents with column content, what will this query return?

SELECT content, ts_rank(to_tsvector(content), to_tsquery('cat & dog')) AS rank FROM documents ORDER BY rank DESC LIMIT 2;

medium

A. The two documents containing either 'cat' or 'dog', sorted alphabetically.

B. The two documents with the highest relevance to both 'cat' and 'dog'.

C. All documents containing 'cat' or 'dog' without ranking.

D. An error because ts_rank cannot be used with LIMIT.

Solution

1. Step 1: Understand the query components

   The query uses to_tsquery('cat & dog') which searches for documents containing both 'cat' and 'dog'.

2. Step 2: Analyze ordering and limit

   Results are ordered by ts_rank descending, so highest relevance first, limited to 2 rows.

3. Final Answer:

   The two documents with the highest relevance to both 'cat' and 'dog'. -> Option B

4. Quick Check:

   ts_rank orders best matches first [OK]

Hint: AND in tsquery means both terms must appear [OK]

Common Mistakes:

• Thinking it returns documents with either word
• Assuming alphabetical order instead of rank
• Believing LIMIT causes an error with ts_rank

4. Identify the error in this query:

SELECT content, ts_rank(to_tsquery(content), to_tsvector('search')) AS rank FROM documents ORDER BY rank DESC;

medium

A. Arguments to ts_rank are reversed; tsvector should be first, tsquery second.

B. to_tsquery cannot be used on a column; it only accepts strings.

C. ORDER BY rank DESC is invalid syntax here.

D. The query is correct and will run without errors.

Solution

1. Step 1: Check ts_rank argument order

   ts_rank expects tsvector first, then tsquery. Here, they are reversed.

2. Step 2: Confirm argument types

   to_tsquery(content) is incorrect because content is text, not a query string; also to_tsvector('search') is a vector, but arguments are swapped.

3. Final Answer:

   Arguments to ts_rank are reversed; tsvector should be first, tsquery second. -> Option A

4. Quick Check:

   ts_rank(tsvector, tsquery) order matters [OK]

Hint: ts_rank always: tsvector first, tsquery second [OK]

Common Mistakes:

• Swapping ts_rank arguments
• Using to_tsquery on text column
• Ignoring argument types for ts_rank

5. You want to find the top 3 most relevant documents containing either 'apple' or 'orange' using high weights to boost relevance. Which query correctly uses ts_rank with weights to achieve this?

hard

A. SELECT content, ts_rank(setweight(to_tsvector(content), 'D'), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank ASC LIMIT 3;

B. SELECT content, ts_rank(to_tsvector(content), to_tsquery('apple & orange')) AS rank FROM documents ORDER BY rank DESC LIMIT 3;

C. SELECT content, ts_rank(to_tsvector(content), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank ASC LIMIT 3;

D. SELECT content, ts_rank(setweight(to_tsvector(content), 'A'), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank DESC LIMIT 3;

Solution

1. Step 1: Understand weighting with setweight

   Using setweight with 'A' assigns highest weight to terms in to_tsvector, boosting the relevance of matching terms.

2. Step 2: Analyze the query logic

   to_tsquery('apple | orange') searches for either word, and ordering by rank descending with LIMIT 3 returns top 3 relevant documents.

3. Step 3: Compare options

   SELECT content, ts_rank(to_tsvector(content), to_tsquery('apple & orange')) AS rank FROM documents ORDER BY rank DESC LIMIT 3; uses AND (&) which requires both words, not either. SELECT content, ts_rank(to_tsvector(content), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank ASC LIMIT 3; orders ascending, showing least relevant first. SELECT content, ts_rank(setweight(to_tsvector(content), 'D'), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank ASC LIMIT 3; uses weight 'D' which is lowest, so it does not boost relevance as much.

4. Final Answer:

   SELECT content, ts_rank(setweight(to_tsvector(content), 'A'), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank DESC LIMIT 3; -> Option D

5. Quick Check:

   Weighted ts_rank with OR query = SELECT content, ts_rank(setweight(to_tsvector(content), 'A'), to_tsquery('apple | orange')) AS rank FROM documents ORDER BY rank DESC LIMIT 3; [OK]

Hint: Use setweight with 'A' to boost preferred terms [OK]

Common Mistakes:

• Using AND instead of OR in tsquery
• Ordering by rank ascending instead of descending
• Assigning lowest weight to preferred terms