Github user rdblue commented on a diff in the pull request:
https://github.com/apache/spark/pull/21977#discussion_r209992878
--- Diff:
core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala ---
@@ -60,14 +61,20 @@ private[spark] object PythonEvalType {
*/
private[spark] abstract class BasePythonRunner[IN, OUT](
funcs: Seq[ChainedPythonFunctions],
- bufferSize: Int,
- reuseWorker: Boolean,
evalType: Int,
- argOffsets: Array[Array[Int]])
+ argOffsets: Array[Array[Int]],
+ conf: SparkConf)
extends Logging {
require(funcs.length == argOffsets.length, "argOffsets should have the
same length as funcs")
+ private val bufferSize = conf.getInt("spark.buffer.size", 65536)
+ private val reuseWorker = conf.getBoolean("spark.python.worker.reuse",
true)
+ // each python worker gets an equal part of the allocation. the worker
pool will grow to the
+ // number of concurrent tasks, which is determined by the number of
cores in this executor.
+ private val memoryMb = conf.get(PYSPARK_EXECUTOR_MEMORY)
+ .map(_ / conf.getInt("spark.executor.cores", 1))
--- End diff --
The Spark docs say to use 2 spaces for an indent, which this does. This
also uses 2 indents for continuation lines. Continuation lines aren't covered
in the Spark docs other than for lines with function parameters -- where 2
indents are required -- but it is fairly common to do this. I've seen both in
Spark code.
I don't think that the DataBricks style guide applies to Apache projects.
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