---
type: concept
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  pageDirectory: concepts
  sources:
    - delta_duplicate_columns_found-error-condition-databricks-on-aws.md
  confidence: 1
  provenanceState: extracted
  freshnessStatus: unverified
  aliases:
    - duplicate-column-scenarios-in-delta-lake
    - DCSIDL
    - duplicate-column-error-scenarios-in-delta-lake
    - DCESIDL
  citations:
    - file: delta_duplicate_columns_found-error-condition-databricks-on-aws.md
title: Duplicate column scenarios in Delta Lake
description: The specific operational contexts in which the DELTA_DUPLICATE_COLUMNS_FOUND error can be triggered, including adding columns, partitioning, schema operations, data reads/writes, and table conversions.
tags:
  - delta-lake
  - error-handling
  - schema-management
timestamp: "2026-06-18T15:18:57.995Z"
---

---
title: Duplicate Column Scenarios in Delta Lake
summary: An overview of the DELTA_DUPLICATE_COLUMNS_FOUND error condition and the specific Delta Lake operations that can trigger it.
sources:
  - delta_duplicate_columns_found-error-condition-databricks-on-aws.md
kind: concept
createdAt: "2026-06-18T14:33:25.717Z"
updatedAt: "2026-06-18T14:33:25.717Z"
tags:
  - delta-lake
  - error-conditions
  - schema-evolution
aliases:
  - duplicate-column-scenarios-in-delta-lake
  - DCSIDL
confidence: 0.95
provenanceState: extracted
inferredParagraphs: 0
---

# Duplicate Column Scenarios in Delta Lake

The **DELTA_DUPLICATE_COLUMNS_FOUND** error condition occurs when Delta Lake detects one or more duplicate column identifiers in a schema operation. The associated SQLSTATE is `42711`, which falls under SQL class 42 (syntax error or access rule violation). At runtime, the error message lists the duplicate column(s) found. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md]

## Scenarios That Trigger the Error

Duplicate columns can appear in several distinct Delta Lake operations. The error reason is classified by a sub‑type that indicates where the duplicate was detected.

| Sub‑type | Scenario |
|----------|----------|
| `ADDING_COLUMNS` | Found during an `ALTER TABLE ADD COLUMNS` or equivalent schema‑evolution operation. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `CLUSTER_BY` | Found in the columns specified by a `CLUSTER BY` clause. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `CONVERT_TO_DELTA` | Found during conversion of a non‑Delta table to Delta format. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `DATA` | Found in the data being saved (for example, in a `DataFrame` that is being written). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `EXISTING_SCHEMA` | Found in the schema of the existing Delta table (the table itself has duplicate columns). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `METADATA_UPDATE` | Found during a metadata update operation (e.g., setting table properties). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `PARTITION_COLUMNS` | Found in the partition columns specified for the table. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `PARTITION_SCHEMA` | Found in the partition schema (the schema inferred from partition values). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `READ_SCHEMA` | Found in the schema of the data being read (e.g., a file being loaded). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `REPLACING_COLUMNS` | Found while replacing columns (e.g., `ALTER TABLE REPLACE COLUMNS`). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `SPECIFIED_COLUMNS` | Found in the columns explicitly specified in a command. ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |
| `TABLE_SCHEMA` | Found in the table schema (the final schema after the operation). ^[delta_duplicate_columns_found-error-condition-databricks-on-aws.md] |

## How to Resolve

Resolution depends on the sub‑type. In general, ensure that no column names are repeated in the input schema, the partition specification, or the data being written. Duplicate columns in the existing table schema can be corrected by using `ALTER TABLE REPLACE COLUMNS` or by creating a new table with a deduplicated schema. For operations like `CLUSTER BY` or `PARTITION COLUMNS`, remove the repeated column from the list.

## Related Concepts

- Delta Lake Schema Enforcement and Evolution – How Delta Lake manages schema changes.
- [Delta Lake Error Conditions](/concepts/delta-error-sub-conditions.md) – Reference for other Delta Lake errors.
- [SQLSTATE 42711](/concepts/sqlstate-42711.md) – The SQL standard state for duplicate column errors.
- ALTER TABLE – DDL statements that can trigger schema‑related duplicate errors.
- CLUSTER BY – Liquid clustering clause that must not contain duplicate columns.

## 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)
