Github user thunterdb commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19439#discussion_r150250118
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/image/HadoopUtils.scala 
---
    @@ -0,0 +1,109 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.ml.image
    +
    +import scala.language.existentials
    +import scala.util.Random
    +
    +import org.apache.commons.io.FilenameUtils
    +import org.apache.hadoop.conf.{Configuration, Configured}
    +import org.apache.hadoop.fs.{Path, PathFilter}
    +import org.apache.hadoop.mapreduce.lib.input.FileInputFormat
    +
    +import org.apache.spark.sql.SparkSession
    +
    +private object RecursiveFlag {
    +  /**
    +   * Sets the spark recursive flag and then restores it.
    +   *
    +   * @param value Value to set
    +   * @param spark Existing spark session
    +   * @param f The function to evaluate after setting the flag
    +   * @return Returns the evaluation result T of the function
    +   */
    +  def withRecursiveFlag[T](value: Boolean, spark: SparkSession)(f: => T): 
T = {
    +    val flagName = FileInputFormat.INPUT_DIR_RECURSIVE
    +    val hadoopConf = spark.sparkContext.hadoopConfiguration
    +    val old = Option(hadoopConf.get(flagName))
    +    hadoopConf.set(flagName, value.toString)
    +    try f finally {
    +      old match {
    +        case Some(v) => hadoopConf.set(flagName, v)
    +        case None => hadoopConf.unset(flagName)
    +      }
    +    }
    +  }
    +}
    +
    +/**
    + * Filter that allows loading a fraction of HDFS files.
    + */
    +private class SamplePathFilter extends Configured with PathFilter {
    --- End diff --
    
    Actually, I take this comment back, since it would break on some 
pathological cases such as all the names being the same. When users want some 
samples, they most probably want a result that is a fraction of the original, 
whatever it may contain.
    
    @jkbradley do you prefer a something that may not be deterministic (using 
random numbers) or deterministic but not respecting the sampling ratio in 
pathological cases? The only way to do both that I can think of is 
deduplicating, which requires a shuffle.


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