
During December 2025, qindongliang addressed a critical bug in the apache/spark repository by correcting the Spark SQL ROUND function’s handling of decimal precision. The work involved modifying the RoundBase logic to use the target type’s precision rather than the input decimal’s, which previously caused NULL results for certain values. This fix, implemented in Scala and leveraging Spark’s data processing capabilities, improved the reliability of analytics and financial computations by ensuring accurate decimal rounding. The solution was validated through regression tests and continuous integration checks, demonstrating a strong grasp of big data, SQL, and robust testing practices in a production environment.
December 2025: Delivered a critical correctness fix for the Spark SQL ROUND function in decimals, eliminating NULL results caused by precision handling, and backed by regression tests. The patch targets a bug in RoundBase that used the input Decimal precision instead of the target type precision, improving accuracy for decimal rounding and percentile-based calculations. Business value includes more reliable analytics, dashboards, and financial computations. The effort closes SPARK-54750 (closes #53529), lead-authored by qindongliang, with co-authorship from Kent Yao, and was validated via regression tests and CI checks.
December 2025: Delivered a critical correctness fix for the Spark SQL ROUND function in decimals, eliminating NULL results caused by precision handling, and backed by regression tests. The patch targets a bug in RoundBase that used the input Decimal precision instead of the target type precision, improving accuracy for decimal rounding and percentile-based calculations. Business value includes more reliable analytics, dashboards, and financial computations. The effort closes SPARK-54750 (closes #53529), lead-authored by qindongliang, with co-authorship from Kent Yao, and was validated via regression tests and CI checks.

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