zhengruifeng edited a comment on pull request #29255:
URL: https://github.com/apache/spark/pull/29255#issuecomment-664216405
test code:
```
import org.apache.spark.ml.linalg._
import org.apache.spark.ml.classification._
import org.apache.spark.storage.StorageLevel
val df =
spark.read.format("libsvm").load("/data1/Datasets/a9a/a9a").withColumn("label",
(col("label")+1)/2)
df.persist(StorageLevel.MEMORY_AND_DISK)
df.count
val lr = new LogisticRegression().setMaxIter(10)
val model = lr.fit(df)
val vecs = df.select("features").rdd.map(row => row.getAs[Vector](0)).collect
model.setThreshold(0.2)
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predict(vec)}}; val end = System.currentTimeMillis;
end - start
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predictRaw(vec)}}; val end =
System.currentTimeMillis; end - start
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predictProbability(vec)}}; val end =
System.currentTimeMillis; end - start
val start = System.currentTimeMillis; Seq.range(0, 100).foreach{i =>
model.transform(df).count}; val end = System.currentTimeMillis; end - start
model.setThresholds(Array(1, 10))
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predict(vec)}}; val end = System.currentTimeMillis;
end - start
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predictRaw(vec)}}; val end =
System.currentTimeMillis; end - start
val start = System.currentTimeMillis; Seq.range(0, 1000).foreach{i =>
vecs.foreach{vec => model.predictProbability(vec)}}; val end =
System.currentTimeMillis; end - start
val start = System.currentTimeMillis; Seq.range(0, 100).foreach{i =>
model.transform(df).count}; val end = System.currentTimeMillis; end - start
```
Results:
`model.setThreshold(0.2)`
|Durations| model.predict | model.predictRaw | model.predictProbability |
model.transform(df).count |
|------|----------|------------|----------|------------|
|This PR|3895|5740|7502|3791|
|Master|28139|5878|9121|4049|
`model.setThresholds(Array(1, 10))`
|Durations| model.predict | model.predictRaw | model.predictProbability |
model.transform(df).count |
|------|----------|------------|----------|------------|
|This PR|3693|5886|7523|3687|
|Master|21052|5828|9086|3857|
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