Github user rxin commented on a diff in the pull request: https://github.com/apache/spark/pull/5799#discussion_r29406968 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala --- @@ -0,0 +1,127 @@ +/* +* 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.sql.execution.stat + +import org.apache.spark.Logging +import org.apache.spark.sql.{Column, DataFrame, Row} +import org.apache.spark.sql.catalyst.plans.logical.LocalRelation +import org.apache.spark.sql.types.{ArrayType, StructField, StructType} + +import scala.collection.mutable.{Map => MutableMap} + +private[sql] object FrequentItems extends Logging { + + /** A helper class wrapping `MutableMap[Any, Long]` for simplicity. */ + private class FreqItemCounter(size: Int) extends Serializable { + val baseMap: MutableMap[Any, Long] = MutableMap.empty[Any, Long] + + /** + * Add a new example to the counts if it exists, otherwise deduct the count + * from existing items. + */ + def add(key: Any, count: Long): this.type = { + if (baseMap.contains(key)) { + baseMap(key) += count + } else { + if (baseMap.size < size) { + baseMap += key -> count + } else { + // TODO: Make this more efficient... A flatMap? + baseMap.retain((k, v) => v > count) + baseMap.transform((k, v) => v - count) + } + } + this + } + + /** + * Merge two maps of counts. + * @param other The map containing the counts for that partition + */ + def merge(other: FreqItemCounter): this.type = { + other.toSeq.foreach { case (k, v) => + add(k, v) + } + this + } + + def toSeq: Seq[(Any, Long)] = baseMap.toSeq + + def foldLeft[A, B](start: A)(f: (A, (Any, Long)) => A): A = baseMap.foldLeft(start)(f) + + def freqItems: Seq[Any] = baseMap.keys.toSeq + } + + /** + * Finding frequent items for columns, possibly with false positives. Using the + * frequent element count algorithm described in + * [[http://dx.doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou]]. + * For Internal use only. + * + * @param df The input DataFrame + * @param cols the names of the columns to search frequent items in + * @param support The minimum frequency for an item to be considered `frequent` + * @return A Local DataFrame with the Array of frequent items for each column. + */ + private[sql] def singlePassFreqItems( + df: DataFrame, + cols: Seq[String], + support: Double): DataFrame = { + if (support < 1e-6) { --- End diff -- ```scala require(support >= 1e-6, s"support ($support) must be greater than 1e-6.") ```
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