Guoqiang Li created SPARK-4902:
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Summary: gap-sampling performance optimization
Key: SPARK-4902
URL: https://issues.apache.org/jira/browse/SPARK-4902
Project: Spark
Issue Type: Improvement
Components: Spark Core
Affects Versions: 1.2.0
Reporter: Guoqiang Li
{{CacheManager.getOrCompute}} returns an instance of InterruptibleIterator that
contains an array or a iterator(when the memory is not enough).
The GapSamplingIterator implementation is as follows
{code}
private val iterDrop: Int => Unit = {
val arrayClass = Array.empty[T].iterator.getClass
val arrayBufferClass = ArrayBuffer.empty[T].iterator.getClass
data.getClass match {
case `arrayClass` => ((n: Int) => { data = data.drop(n) })
case `arrayBufferClass` => ((n: Int) => { data = data.drop(n) })
case _ => ((n: Int) => {
var j = 0
while (j < n && data.hasNext) {
data.next()
j += 1
}
})
}
}
{code}
The code does not deal with InterruptibleIterator.
This leads to the following code can't use the {{Iterator.drop}} method
{code}
rdd.cache()
data.sample(false,0.1)
{code}
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