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Description

Error 1709 indicates that an attempt to create an index failed because the specified column or combination of columns exceeds the maximum permissible byte length for an index. This limitation is typically imposed by the underlying storage engine, such as InnoDB, to ensure data integrity and efficient indexing.

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Error Message

Index column size too large. The maximum column size is %lu bytes.

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Known Causes

4 known causes

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Indexing Long String Columns

Attempting to index a VARCHAR, TEXT, or BLOB column with a length that exceeds the storage engine's maximum indexable size without specifying a prefix length.

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Excessive Composite Index Length

When creating a multi-column index, the sum of the byte lengths of all indexed columns can surpass the maximum allowed size for a single index entry.

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Multi-byte Character Set Usage

Using character sets like `utf8mb4`, where characters can consume multiple bytes, can cause a column's byte length to exceed the index limit even if the character count is low.

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Storage Engine Limitations

The specific storage engine in use (e.g., InnoDB) has a hard limit on the total byte length of an index entry, which can be exceeded by large columns.

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Solutions

4 solutions available

1. Reduce Index Column Size with Data Type Adjustment medium

Change the data type of the indexed column to a smaller one if possible.

1

Identify the table and column causing the error. The error message might not directly state it, so you may need to examine your `CREATE TABLE` statements or query the information schema.

SELECT TABLE_NAME, COLUMN_NAME, DATA_TYPE, CHARACTER_MAXIMUM_LENGTH FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_SCHEMA = 'your_database_name' AND COLUMN_TYPE LIKE '%TEXT%' OR COLUMN_TYPE LIKE '%BLOB%';

2

Analyze the data stored in the column. Determine if the current data type (e.g., `LONGTEXT`, `BLOB`) is truly necessary. For example, if the column stores short strings, `VARCHAR(255)` might suffice.

3

If a smaller data type is appropriate, create a new column with the desired smaller data type, copy the data from the old column to the new one, drop the old column, and rename the new column.

ALTER TABLE your_table_name ADD COLUMN new_column_name VARCHAR(255);
UPDATE your_table_name SET new_column_name = your_column_name;
ALTER TABLE your_table_name DROP COLUMN your_column_name;
ALTER TABLE your_table_name CHANGE COLUMN new_column_name your_column_name VARCHAR(255);
-- Recreate any indexes on the modified column.

4

Alternatively, if the column is not the primary source of large data and is part of a composite index, consider removing it from the index if it's not critical for performance.

ALTER TABLE your_table_name DROP INDEX index_name;
-- Then recreate the index without the problematic column.

2. Create a Partial Index (Prefix Index) medium

Index only a prefix of the column data to reduce the index size.

1

Identify the table and column that is too large to be indexed.

2

Determine a reasonable prefix length for the index. This depends on the data and how you query it. For example, if you frequently search for the beginning of a string, a prefix of 20-50 characters might be sufficient.

3

Drop the existing index on the column (if any) and create a new one using a prefix.

ALTER TABLE your_table_name DROP INDEX index_name; -- If an index already exists
CREATE INDEX index_name ON your_table_name (your_column_name(prefix_length));

4

Test your queries to ensure that the partial index is still effective for your use cases.

3. Use a Full-Text Index for Textual Data medium

Leverage MariaDB's full-text indexing for large text fields instead of a standard B-tree index.

1

Ensure your table engine supports full-text indexes (e.g., `InnoDB` and `MyISAM`).

2

Identify the large text column you want to index.

3

Drop any existing index on that column that is causing the error.

ALTER TABLE your_table_name DROP INDEX index_name;

4

Add a full-text index to the column. You can specify multiple columns if needed.

ALTER TABLE your_table_name ADD FULLTEXT (your_text_column);

5

Update your `SELECT` queries to use `MATCH() AGAINST()` syntax for searching within the full-text indexed column.

SELECT * FROM your_table_name WHERE MATCH(your_text_column) AGAINST('search term');

4. Normalize Data or Use a Separate Table for Large Data advanced

Refactor your schema to store large data in a separate, related table.

1

Analyze the schema and identify if the large column contains data that could be considered a separate entity or has a one-to-many relationship.

2

Create a new table to store the large data, including a foreign key referencing the original table.

CREATE TABLE your_large_data_table (
  id INT AUTO_INCREMENT PRIMARY KEY,
  your_original_table_id INT,
  large_data_column LONGTEXT,
  FOREIGN KEY (your_original_table_id) REFERENCES your_table_name(id)
);

3

Migrate the large data from the original table to the new table.

INSERT INTO your_large_data_table (your_original_table_id, large_data_column)
SELECT id, your_column_name FROM your_table_name WHERE your_column_name IS NOT NULL;

4

Remove the large column from the original table.

ALTER TABLE your_table_name DROP COLUMN your_column_name;

5

Modify your queries to join the original table with the new table when the large data is needed.

SELECT t1.*, t2.large_data_column FROM your_table_name t1 JOIN your_large_data_table t2 ON t1.id = t2.your_original_table_id;

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Related Errors

5 related errors

MariaDB Error 1709: Index Column Size Exceeded