zeotuan commented on code in PR #46151:
URL: https://github.com/apache/spark/pull/46151#discussion_r1574581536
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mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala:
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@@ -192,12 +193,13 @@ class CrossValidator @Since("1.2.0") (@Since("1.4.0")
override val uid: String)
foldMetrics
}.transpose.map(_.sum / $(numFolds)) // Calculate average metric over all
splits
- instr.logInfo(s"Average cross-validation metrics:
${metrics.toImmutableArraySeq}")
+ instr.logInfo(log"Average cross-validation metrics: ${MDC(
+ CROSS_VALIDATION_METRICS, metrics.mkString("[", ", ", "]"))}")
val (bestMetric, bestIndex) =
if (eval.isLargerBetter) metrics.zipWithIndex.maxBy(_._1)
else metrics.zipWithIndex.minBy(_._1)
- instr.logInfo(s"Best set of parameters:\n${epm(bestIndex)}")
- instr.logInfo(s"Best cross-validation metric: $bestMetric.")
+ instr.logInfo(log"Best set of parameters:\n${MDC(ESTIMATOR_PARAMETER_MAP,
epm(bestIndex))}")
Review Comment:
Wonder if there is a guideline on how to deal with more complex data
structures? ex. HashMap, Seq of case class ?
The only example I saw is `logWarning(log"BatchedWriteAheadLog Writer failed
to write ${MDC(RECORDS, buffer)}", e)`
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