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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
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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 @@ -212,40 +212,8 @@ 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 =>
KryoSerializer.loadableSparkClasses.foreach { clazz =>
try {
val clazz = Utils.classForName(name)
kryo.register(clazz)
} catch {
case NonFatal(_) => // do nothing
Expand Down Expand Up @@ -516,6 +484,50 @@ private[serializer] object KryoSerializer {
}
}
)

// 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 loadableSparkClasses: Seq[Class[_]] = {
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.
}
}
}
}

/**
Expand Down