---
type: concept
x-llmwiki:
  schemaVersion: "0.1"
  contentHash: 4f1f255be82130f8aadc751f74c2bb7dafaae7fcd327d2db41573d200ce96478
  pageDirectory: concepts
  sources:
    - delta_duplicate_columns_found-error-condition-databricks-on-aws.md
  confidence: 0.9
  provenanceState: extracted
  freshnessStatus: unverified
  aliases:
    - convert_to_delta-duplicate-column-validation
    - CDCV
  citations:
    - file: delta_duplicate_columns_found-error-condition-databricks-on-aws.md
title: CONVERT_TO_DELTA Duplicate Column Validation
description: The validation that occurs when converting an existing data source to Delta format, which checks for duplicate columns and raises DELTA_DUPLICATE_COLUMNS_FOUND if found.
tags:
  - delta-lake
  - table-conversion
  - data-validation
timestamp: "2026-06-19T15:04:38.614Z"
---

# CONVERT_TO_DELTA Duplicate Column Validation

**CONVERT_TO_DELTA Duplicate Column Validation** is a specific error scenario within the DELTA_DUPLICATE_COLUMNS_FOUND error class that occurs when duplicate column names are detected during the process of converting an existing data source to the [Delta Lake](/concepts/delta-lake.md) format. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md]

## Overview

The `CONVERT_TO_DELTA` sub‑condition is one of many sub‑conditions under the `DELTA_DUPLICATE_COLUMNS_FOUND` error class (SQLSTATE 42711, Class 42 – Syntax Error or Access Rule Violation). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] It is raised specifically when the [CONVERT TO DELTA](/concepts/convert-to-delta.md) operation encounters a table or dataset that has duplicate column names. Because Delta Lake requires a strict one‑to‑one mapping of column names to schema entries, any duplicates in the source data or schema will cause the conversion to fail.

## When It Occurs

The error occurs when a user or automated process attempts to convert a table to Delta Lake (via `CONVERT TO DELTA` or equivalent), but the underlying source data contains duplicate column names. This can happen in several scenarios:

- The source data itself has columns with identical names (e.g., a CSV file with two headers named `user_id`).
- The source schema defines duplicate columns.
- The metadata of the source contains duplicate column entries.

## Error Message

The full error message reads:

```
Found duplicate column(s): <column_names>
```

with the sub‑condition qualifier `CONVERT_TO_DELTA`, indicating that the duplicate was found specifically during the conversion to Delta. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md]

## Resolution

To resolve the `CONVERT_TO_DELTA` duplicate column validation error:

1. **Identify the duplicate columns** – Examine the source data or schema to find which columns are duplicated.
2. **Remove or rename duplicates** – Ensure that every column name in the source data is unique. This may involve:
   - Renaming one of the duplicate columns using a transform or SELECT statement.
   - Dropping the duplicate column if it is not needed.
   - Correcting the source file format (e.g., fixing a malheader in a CSV).
3. **Retry the conversion** – Once the duplicates are resolved, run `CONVERT TO DELTA` again.

## Related Concepts

- [Delta Lake Schema Enforcement](/concepts/delta-table-schema-requirements.md) – The mechanism that enforces unique column names in Delta tables.
- DELTA_DUPLICATE_COLUMNS_FOUND – The parent error class covering all duplicate column scenarios.
- Schema Evolution – How Delta Lake handles schema changes over time (but not duplicates).
- [Data Quality Validation](/concepts/data-quality-monitoring.md) – Broader practices for ensuring data integrity before conversion.
- [CONVERT TO DELTA](/concepts/convert-to-delta.md) – The command that triggers this validation.

## Sources

- delta_duplicate_columns_found-error-condition-databricks-on-aws.md

# Citations

1. [delta_duplicate_columns_found-error-condition-databricks-on-aws.md](/references/delta_duplicate_columns_found-error-condition-databricks-on-aws-42950ac1.md)
