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How to Efficiently Remove Duplicate Rows in Netezza Without a Unique Identifier?

Linda Hamilton
Release: 2025-01-12 11:36:41
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How to Efficiently Remove Duplicate Rows in Netezza Without a Unique Identifier?

Eliminating Duplicate Rows in Netezza Without Unique Keys

Duplicate data in large tables impacts storage and data quality. Removing these duplicates without a unique identifier presents a challenge. While techniques like using row numbers (common in standard SQL) aren't directly applicable in Netezza, a highly effective alternative exists.

The Netezza Approach: Leveraging the DELETE Command

Netezza offers a powerful solution using the USING keyword within the DELETE statement. Consider this example:

<code class="language-sql">DELETE FROM table_with_dups T1
USING table_with_dups T2
WHERE T1.ctid < T2.ctid
AND T1.column1 = T2.column1
AND T1.column2 = T2.column2
-- ... add more columns as needed ...</code>
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This query compares each row (T1) against all other rows (T2) in table_with_dups. It identifies and deletes older duplicate rows based on their ctid (row ID) values. The AND conditions ensure that only rows with identical values in specified columns are considered duplicates.

Previewing Before Deletion

To review the rows slated for deletion before executing the DELETE command, replace DELETE with SELECT * and the USING keyword with a comma:

<code class="language-sql">SELECT * FROM table_with_dups T1, table_with_dups T2
WHERE T1.ctid < T2.ctid
AND T1.column1 = T2.column1
AND T1.column2 = T2.column2
-- ... add more columns as needed ...</code>
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Performance Optimization

For optimal performance, avoid NOT IN clauses, which can significantly slow down the process due to subquery overhead. The USING method demonstrated here provides superior speed in most scenarios.

Handling NULL Values

If any key columns contain NULL values, use the COALESCE() function within the WHERE clause to ensure accurate comparison:

<code class="language-sql">
AND COALESCE(T1.col_with_nulls, '[NULL]') = COALESCE(T2.col_with_nulls, '[NULL]')
```  This treats `NULL` values consistently.  Replace `col_with_nulls` with the actual column name.  Remember to adjust the column list in the `WHERE` clause to include all relevant columns for duplicate identification.</code>
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