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add data synchronization test to verification Suite. (#526)
* add data synchronization test to verification suite * review comments * update test and doc strings
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src/main/scala/com/amazon/deequ/analyzers/DataSynchronizationAnalyzer.scala
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/** | ||
* Copyright 2024 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. | ||
* | ||
*/ | ||
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package com.amazon.deequ.analyzers | ||
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import com.amazon.deequ.analyzers.Analyzers.metricFromFailure | ||
import com.amazon.deequ.comparison.DataSynchronization | ||
import com.amazon.deequ.comparison.DataSynchronizationFailed | ||
import com.amazon.deequ.comparison.DataSynchronizationSucceeded | ||
import com.amazon.deequ.metrics.DoubleMetric | ||
import com.amazon.deequ.metrics.Entity | ||
import org.apache.spark.sql.DataFrame | ||
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import scala.util.Failure | ||
import scala.util.Try | ||
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/** | ||
* An Analyzer for Deequ that performs a data synchronization check between two DataFrames. | ||
* It evaluates the degree of synchronization based on specified column mappings and an assertion function. | ||
* | ||
* The analyzer computes a ratio of synchronized data points to the total data points, represented as a DoubleMetric. | ||
* Refer to [[com.amazon.deequ.comparison.DataSynchronization.columnMatch]] for DataSynchronization implementation | ||
* | ||
* @param dfToCompare The DataFrame to compare with the primary DataFrame that is setup | ||
* during [[com.amazon.deequ.VerificationSuite.onData]] setup. | ||
* @param columnMappings A map where each key-value pair represents a column in the primary DataFrame | ||
* and its corresponding column in dfToCompare. | ||
* @param assertion A function that takes a Double (the match ratio) and returns a Boolean. | ||
* It defines the condition for successful synchronization. | ||
* | ||
* Usage: | ||
* This analyzer is used in Deequ's VerificationSuite based if `isDataSynchronized` check is defined or could be used | ||
* manually as well. | ||
* | ||
* Example: | ||
* val analyzer = DataSynchronizationAnalyzer(dfToCompare, Map("col1" -> "col2"), _ > 0.8) | ||
* val verificationResult = VerificationSuite().onData(df).addAnalyzer(analyzer).run() | ||
* | ||
* // or could do something like below | ||
* val verificationResult = VerificationSuite().onData(df).isDataSynchronized(dfToCompare, Map("col1" -> "col2"), | ||
* _ > 0.8).run() | ||
* | ||
* | ||
* The computeStateFrom method calculates the synchronization state by comparing the specified columns of the two | ||
* DataFrames. | ||
* The computeMetricFrom method then converts this state into a DoubleMetric representing the synchronization ratio. | ||
* | ||
*/ | ||
case class DataSynchronizationAnalyzer(dfToCompare: DataFrame, | ||
columnMappings: Map[String, String], | ||
assertion: Double => Boolean) | ||
extends Analyzer[DataSynchronizationState, DoubleMetric] { | ||
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override def computeStateFrom(data: DataFrame): Option[DataSynchronizationState] = { | ||
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val result = DataSynchronization.columnMatch(data, dfToCompare, columnMappings, assertion) | ||
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result match { | ||
case succeeded: DataSynchronizationSucceeded => | ||
Some(DataSynchronizationState(succeeded.passedCount, succeeded.totalCount)) | ||
case failed: DataSynchronizationFailed => | ||
Some(DataSynchronizationState(failed.passedCount.getOrElse(0), failed.totalCount.getOrElse(0))) | ||
case _ => None | ||
} | ||
} | ||
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override def computeMetricFrom(state: Option[DataSynchronizationState]): DoubleMetric = { | ||
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val metric = state match { | ||
case Some(s) => Try(s.synchronizedDataCount.toDouble / s.totalDataCount.toDouble) | ||
case _ => Failure(new IllegalStateException("No state available for DataSynchronizationAnalyzer")) | ||
} | ||
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DoubleMetric(Entity.Dataset, "DataSynchronization", "", metric, None) | ||
} | ||
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override private[deequ] def toFailureMetric(failure: Exception) = | ||
metricFromFailure(failure, "DataSynchronization", "", Entity.Dataset) | ||
} | ||
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src/main/scala/com/amazon/deequ/analyzers/DataSynchronizationState.scala
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/** | ||
* Copyright 2023 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. | ||
* | ||
*/ | ||
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package com.amazon.deequ.analyzers | ||
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/** | ||
* Represents the state of data synchronization between two DataFrames in Deequ. | ||
* This state keeps track of the count of synchronized record count and the total record count. | ||
* It is used to calculate a ratio of synchronization, which is a measure of how well the data | ||
* in the two DataFrames are synchronized. | ||
* | ||
* @param synchronizedDataCount The count of records that are considered synchronized between the two DataFrames. | ||
* @param totalDataCount The total count of records for check. | ||
* | ||
* The `sum` method allows for aggregation of this state with another, combining the counts from both states. | ||
* This is useful in distributed computations where states from different partitions need to be aggregated. | ||
* | ||
* The `metricValue` method computes the synchronization ratio. It is the ratio of `synchronizedDataCount` | ||
* to `dataCount`. | ||
* If `dataCount` is zero, which means no data points were examined, the method returns `Double.NaN` | ||
* to indicate the undefined state. | ||
* | ||
*/ | ||
case class DataSynchronizationState(synchronizedDataCount: Long, totalDataCount: Long) | ||
extends DoubleValuedState[DataSynchronizationState] { | ||
override def sum(other: DataSynchronizationState): DataSynchronizationState = { | ||
DataSynchronizationState(synchronizedDataCount + other.synchronizedDataCount, totalDataCount + other.totalDataCount) | ||
} | ||
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override def metricValue(): Double = { | ||
if (totalDataCount == 0L) Double.NaN else synchronizedDataCount.toDouble / totalDataCount.toDouble | ||
} | ||
} | ||
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object DataSynchronizationState |
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