Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/18140
Simple example to illustrate:
```
> df <- createDataFrame(as.data.frame(Titanic, stringsAsFactors = FALSE))
> rModel <- stats::glm(Freq ~ Sex + Age, family = "gaussian", data =
as.data.frame(df))
> summary(rModel)$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 91.34375 35.99417 2.537737 0.016790098
SexMale 78.81250 41.56249 1.896241 0.067931094
AgeChild -123.93750 41.56249 -2.981956 0.005752153
> model <- spark.glm(df, Freq ~ Sex + Age, family = "gaussian")
> summary(model)$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -32.59375 35.99417 -0.9055286 0.372647658
Sex_Male 78.81250 41.56249 1.8962412 0.067931094
Age_Adult 123.93750 41.56249 2.9819558 0.005752153
> model2 <- spark.glm(df, Freq ~ Sex + Age, family = "gaussian",
+ stringIndexerOrderType = "alphabetDesc")
> summary(model2)$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 91.34375 35.99417 2.537737 0.016790098
Sex_Male 78.81250 41.56249 1.896241 0.067931094
Age_Child -123.93750 41.56249 -2.981956 0.005752153
```
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