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Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.

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/**
 * Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not
 * use this file except in compliance with the License. A copy of the License
 * is located at
 *
 *     http://aws.amazon.com/apache2.0/
 *
 * or in the "license" file accompanying this file. This file 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 com.amazon.deequ.anomalydetection

/**
  * Provided for backwards compatibility.
  * the old [[RateOfChangeStrategy]] actually detects absolute changes
  * so it has been migrated to [[AbsoluteChangeStrategy]]
  * use [[RelativeRateOfChangeStrategy]] if you want to
  * detect relative changes to the previous values
  */
@deprecated("use AbsoluteChangeStrategy instead which describes the strategy more accurately")
case class RateOfChangeStrategy(
  maxRateDecrease: Option[Double] = None,
  maxRateIncrease: Option[Double] = None,
  order: Int = 1) extends BaseChangeStrategy




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