与此同时，降本增效已成为企业核心诉求。企业通过数据湖技术消除冗余数据拷贝、提升引擎执行效率以节约计算资源（如 CPU 利用率优化）及人力维护成本，进而缩短任务处理周期。在此背景下，DataWorks 结合 Serverless Spark 通过智能化调度与高性能计算能力，助力企业实现降本增效。
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The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:
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公式： f(x)=λ⋅ELU(α,x)