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Column Count Analyzer and Check (#555)
* Fix flaky KLL test * Move CustomSql state to CustomSql analyzer * Implement new Analyzer to count columns * Improve documentation, remove unused parameter, replace if/else with map --------- Co-authored-by: Yannis Mentekidis <[email protected]>
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src/main/scala/com/amazon/deequ/analyzers/ColumnCount.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.metrics.DoubleMetric | ||
import com.amazon.deequ.metrics.Entity | ||
import org.apache.spark.sql.DataFrame | ||
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case class ColumnCount() extends Analyzer[NumMatches, DoubleMetric] { | ||
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val name = "ColumnCount" | ||
val instance = "*" | ||
val entity = Entity.Dataset | ||
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/** | ||
* Compute the state (sufficient statistics) from the data | ||
* | ||
* @param data the input dataframe | ||
* @return the number of columns in the input | ||
*/ | ||
override def computeStateFrom(data: DataFrame, filterCondition: Option[String]): Option[NumMatches] = { | ||
if (filterCondition.isDefined) { | ||
throw new IllegalArgumentException("ColumnCount does not accept a filter condition") | ||
} else { | ||
val numColumns = data.columns.size | ||
Some(NumMatches(numColumns)) | ||
} | ||
} | ||
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/** | ||
* Compute the metric from the state (sufficient statistics) | ||
* | ||
* @param state the computed state from [[computeStateFrom]] | ||
* @return a double metric indicating the number of columns for this analyzer | ||
*/ | ||
override def computeMetricFrom(state: Option[NumMatches]): DoubleMetric = { | ||
state | ||
.map(v => Analyzers.metricFromValue(v.metricValue(), name, instance, entity)) | ||
.getOrElse(Analyzers.metricFromEmpty(this, name, instance, entity)) | ||
} | ||
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/** | ||
* Compute the metric from a failure - reports the exception thrown while trying to count columns | ||
*/ | ||
override private[deequ] def toFailureMetric(failure: Exception): DoubleMetric = { | ||
Analyzers.metricFromFailure(failure, name, instance, entity) | ||
} | ||
} |
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src/test/scala/com/amazon/deequ/analyzers/ColumnCountTest.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.SparkContextSpec | ||
import com.amazon.deequ.utils.FixtureSupport | ||
import org.apache.spark.sql.Row | ||
import org.apache.spark.sql.types.StructType | ||
import org.scalatest.matchers.should.Matchers | ||
import org.scalatest.wordspec.AnyWordSpec | ||
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import scala.util.Failure | ||
import scala.util.Success | ||
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class ColumnCountTest extends AnyWordSpec with Matchers with SparkContextSpec with FixtureSupport { | ||
"ColumnCount" should { | ||
"return column count for a dataset" in withSparkSession { session => | ||
val data = getDfWithStringColumns(session) | ||
val colCount = ColumnCount() | ||
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val state = colCount.computeStateFrom(data) | ||
state.isDefined shouldBe true | ||
state.get.metricValue() shouldBe 5.0 | ||
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val metric = colCount.computeMetricFrom(state) | ||
metric.fullColumn shouldBe None | ||
metric.value shouldBe Success(5.0) | ||
} | ||
} | ||
} |