[
https://issues.apache.org/jira/browse/SPARK-21690?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-21690:
------------------------------------
Assignee: Apache Spark (was: zhengruifeng)
> one-pass imputer
> ----------------
>
> Key: SPARK-21690
> URL: https://issues.apache.org/jira/browse/SPARK-21690
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.2.1
> Reporter: zhengruifeng
> Assignee: Apache Spark
>
> {code}
> val surrogates = $(inputCols).map { inputCol =>
> val ic = col(inputCol)
> val filtered = dataset.select(ic.cast(DoubleType))
> .filter(ic.isNotNull && ic =!= $(missingValue) && !ic.isNaN)
> if(filtered.take(1).length == 0) {
> throw new SparkException(s"surrogate cannot be computed. " +
> s"All the values in $inputCol are Null, Nan or
> missingValue(${$(missingValue)})")
> }
> val surrogate = $(strategy) match {
> case Imputer.mean => filtered.select(avg(inputCol)).as[Double].first()
> case Imputer.median => filtered.stat.approxQuantile(inputCol,
> Array(0.5), 0.001).head
> }
> surrogate
> }
> {code}
> Current impl of {{Imputer}} process one column after after another. In this
> place, we should parallelize the processing in a more efficient way.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
