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[SPARK-28112] [TEST] Fix Kryo exception perf. bottleneck in tests due to absence of ML/MLlib classes #24916

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[SPARK-28112] [TEST] Fix Kryo exception perf. bottleneck in tests due to absence of ML/MLlib classes #24916

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ae1b642
fix
gatorsmile Jun 19, 2019
c8680f9
Move to companion
JoshRosen Jun 19, 2019
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78 changes: 45 additions & 33 deletions core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -88,6 +88,50 @@ class KryoSerializer(conf: SparkConf)
private val useUnsafe = conf.get(KRYO_USE_UNSAFE)
private val usePool = conf.get(KRYO_USE_POOL)

// classForName() is expensive in case the class is not found, so we filter the list of
// SQL / ML / MLlib classes once and then re-use that filtered list in newInstance() calls.
private lazy val loadableClasses: Seq[Class[_]] = {
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@JoshRosen JoshRosen Jun 19, 2019 •
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Could this be moved into a private[serializer] field in a object KryoSerializer companion? Now that I look at this again, I'm worried that it'll be serialized as part of KryoSerializer itself, since I think the serializer itself is serialized as part of ShuffleDependency. I don't think that's a huge deal but we could probably shave off some additional work with that extra step.

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@JoshRosen JoshRosen Jun 19, 2019

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Here's a commit with that change: JoshRosen@c8680f9

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@JoshRosen JoshRosen Jun 19, 2019

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Actually, I just pushed directly to your branch using GitHub's new "allow edits from maintainers" feature. Hope you don't mind 😄!

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@gatorsmile gatorsmile Jun 20, 2019

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Sure. Feel free to push it.

Seq(
"org.apache.spark.sql.catalyst.expressions.UnsafeRow",
"org.apache.spark.sql.catalyst.expressions.UnsafeArrayData",
"org.apache.spark.sql.catalyst.expressions.UnsafeMapData",

"org.apache.spark.ml.attribute.Attribute",
"org.apache.spark.ml.attribute.AttributeGroup",
"org.apache.spark.ml.attribute.BinaryAttribute",
"org.apache.spark.ml.attribute.NominalAttribute",
"org.apache.spark.ml.attribute.NumericAttribute",

"org.apache.spark.ml.feature.Instance",
"org.apache.spark.ml.feature.LabeledPoint",
"org.apache.spark.ml.feature.OffsetInstance",
"org.apache.spark.ml.linalg.DenseMatrix",
"org.apache.spark.ml.linalg.DenseVector",
"org.apache.spark.ml.linalg.Matrix",
"org.apache.spark.ml.linalg.SparseMatrix",
"org.apache.spark.ml.linalg.SparseVector",
"org.apache.spark.ml.linalg.Vector",
"org.apache.spark.ml.stat.distribution.MultivariateGaussian",
"org.apache.spark.ml.tree.impl.TreePoint",
"org.apache.spark.mllib.clustering.VectorWithNorm",
"org.apache.spark.mllib.linalg.DenseMatrix",
"org.apache.spark.mllib.linalg.DenseVector",
"org.apache.spark.mllib.linalg.Matrix",
"org.apache.spark.mllib.linalg.SparseMatrix",
"org.apache.spark.mllib.linalg.SparseVector",
"org.apache.spark.mllib.linalg.Vector",
"org.apache.spark.mllib.regression.LabeledPoint",
"org.apache.spark.mllib.stat.distribution.MultivariateGaussian"
).flatMap { name =>
try {
Some[Class[_]](Utils.classForName(name))
} catch {
case NonFatal(_) => None // do nothing
case _: NoClassDefFoundError if Utils.isTesting => None // See SPARK-23422.
}
}
}

def newKryoOutput(): KryoOutput =
if (useUnsafe) {
new KryoUnsafeOutput(bufferSize, math.max(bufferSize, maxBufferSize))
Expand Down Expand Up @@ -212,40 +256,8 @@ class KryoSerializer(conf: SparkConf)

// We can't load those class directly in order to avoid unnecessary jar dependencies.
// We load them safely, ignore it if the class not found.
Seq(
"org.apache.spark.sql.catalyst.expressions.UnsafeRow",
"org.apache.spark.sql.catalyst.expressions.UnsafeArrayData",
"org.apache.spark.sql.catalyst.expressions.UnsafeMapData",

"org.apache.spark.ml.attribute.Attribute",
"org.apache.spark.ml.attribute.AttributeGroup",
"org.apache.spark.ml.attribute.BinaryAttribute",
"org.apache.spark.ml.attribute.NominalAttribute",
"org.apache.spark.ml.attribute.NumericAttribute",

"org.apache.spark.ml.feature.Instance",
"org.apache.spark.ml.feature.LabeledPoint",
"org.apache.spark.ml.feature.OffsetInstance",
"org.apache.spark.ml.linalg.DenseMatrix",
"org.apache.spark.ml.linalg.DenseVector",
"org.apache.spark.ml.linalg.Matrix",
"org.apache.spark.ml.linalg.SparseMatrix",
"org.apache.spark.ml.linalg.SparseVector",
"org.apache.spark.ml.linalg.Vector",
"org.apache.spark.ml.stat.distribution.MultivariateGaussian",
"org.apache.spark.ml.tree.impl.TreePoint",
"org.apache.spark.mllib.clustering.VectorWithNorm",
"org.apache.spark.mllib.linalg.DenseMatrix",
"org.apache.spark.mllib.linalg.DenseVector",
"org.apache.spark.mllib.linalg.Matrix",
"org.apache.spark.mllib.linalg.SparseMatrix",
"org.apache.spark.mllib.linalg.SparseVector",
"org.apache.spark.mllib.linalg.Vector",
"org.apache.spark.mllib.regression.LabeledPoint",
"org.apache.spark.mllib.stat.distribution.MultivariateGaussian"
).foreach { name =>
loadableClasses.foreach { clazz =>
try {
val clazz = Utils.classForName(name)
kryo.register(clazz)
} catch {
case NonFatal(_) => // do nothing
Expand Down