chore: Adding telemetry for the dataset metadata. This one is specially for …

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/CognitiveServiceBase.scala

@@ -494,8 +494,7 @@ abstract class CognitiveServicesBaseNoHandler(val uid: String) extends Transform
   }
 
   override def transform(dataset: Dataset[_]): DataFrame = {
-    logTransform[DataFrame](
-      getInternalTransformer(dataset.schema).transform(dataset)
+    logTransform[DataFrame](getInternalTransformer(dataset.schema).transform(dataset), dataset.columns.length
     )
   }
 

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/anomaly/AnomalyDetection.scala

@@ -265,7 +265,7 @@ class SimpleDetectAnomalies(override val uid: String) extends AnomalyDetectorBas
         getErrorCol,
         s"$getOutputCol.1"
       ).withColumnRenamed("1", getOutputCol)
-    })
+    }, dataset.columns.length)
 
   }
 

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/anomaly/MultivariateAnomalyDetection.scala

@@ -526,7 +526,7 @@ class SimpleFitMultivariateAnomaly(override val uid: String) extends Estimator[S
         .setModelId(modelId)
         .setIntermediateSaveDir(getIntermediateSaveDir)
         .setDiagnosticsInfo(modelInfo("diagnosticsInfo").convertTo[DiagnosticsInfo])
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): SimpleFitMultivariateAnomaly = defaultCopy(extra)
@@ -589,7 +589,7 @@ class SimpleDetectMultivariateAnomaly(override val uid: String) extends Model[Si
 
   //scalastyle:off method.length
   override def transform(dataset: Dataset[_]): DataFrame =
-    logTransform[DataFrame] {
+    logTransform[DataFrame] ({
 
       // check model status first
       MADUtils.checkModelStatus(getUrl, getModelId, getSubscriptionKey)
@@ -635,7 +635,7 @@ class SimpleDetectMultivariateAnomaly(override val uid: String) extends Model[Si
       df.join(finalDF, df(getTimestampCol) === finalDF("resultTimestamp"), "left")
         .drop("resultTimestamp")
         .sort(col(getTimestampCol).asc)
-    }
+    }, dataset.columns.length)
   //scalastyle:on method.length
 
   override def copy(extra: ParamMap): SimpleDetectMultivariateAnomaly = defaultCopy(extra)

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/form/FormOntologyLearner.scala

@@ -73,7 +73,7 @@ class FormOntologyLearner(override val uid: String) extends Estimator[FormOntolo
         .setInputCol(getInputCol)
         .setOutputCol(getOutputCol)
         .setOntology(mergedSchema)
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): Estimator[FormOntologyTransformer] = defaultCopy(extra)
@@ -121,7 +121,7 @@ class FormOntologyTransformer(override val uid: String) extends Model[FormOntolo
 
       dataset.toDF()
         .withColumn(getOutputCol, convertToOntologyUDF(col(getInputCol)))
-    })
+    }, dataset.columns.length)
   }
 
   override def transformSchema(schema: StructType): StructType = {

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/openai/OpenAIPrompt.scala

@@ -108,7 +108,7 @@ class OpenAIPrompt(override val uid: String) extends Transformer
       } else {
         results
       }
-    })
+    }, dataset.columns.length)
   }
 
   private def openAICompletion: OpenAICompletion = {

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/search/AzureSearch.scala

@@ -133,7 +133,7 @@ class AddDocuments(override val uid: String) extends CognitiveServicesBase(uid)
           s"/indexes/$getIndexName/docs/index?api-version=${AzureSearchAPIConstants.DefaultAPIVersion}")
       }
       super.transform(dataset)
-    })
+    }, dataset.columns.length)
   }
 
   override def prepareEntity: Row => Option[AbstractHttpEntity] = row =>

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/speech/SpeechToTextSDK.scala

@@ -418,7 +418,7 @@ abstract class SpeechSDKBase extends Transformer
         isUriAudio
       ))(enc)
         .drop(dynamicParamColName)
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): this.type = defaultCopy(extra)

cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/translate/DocumentTranslator.scala

@@ -164,7 +164,7 @@ class DocumentTranslator(override val uid: String) extends CognitiveServicesBase
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame]({
       getInternalTransformer(dataset.schema).transform(dataset)
-    })
+    }, dataset.columns.length)
   }
 
   override def responseDataType: DataType = TranslationStatusResponse.schema

core/src/main/scala/com/microsoft/azure/synapse/ml/automl/FindBestModel.scala

@@ -114,7 +114,7 @@ class FindBestModel(override val uid: String) extends Estimator[BestModel]
         .setBestModelMetrics(evaluator.transform(bestScoredDf))
         .setRocCurve(evaluator.rocCurve)
         .setAllModelMetrics(allModelMetrics)
-    })
+    }, dataset.columns.length)
   }
 
   // Choose a random model as we don't know which one will be chosen yet - all will transform schema in same way
@@ -189,7 +189,7 @@ class BestModel(val uid: String) extends Model[BestModel]
 
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame](
-      getBestModel.transform(dataset)
+      getBestModel.transform(dataset), dataset.columns.length
     )
   }
 

core/src/main/scala/com/microsoft/azure/synapse/ml/automl/TuneHyperparameters.scala

@@ -215,7 +215,7 @@ class TuneHyperparameters(override val uid: String) extends Estimator[TuneHyperp
       // Compute best model fit on dataset
       val bestModel = getModels(bestIndex % numModels).fit(dataset, paramsPerRun(bestIndex)).asInstanceOf[Model[_]]
       new TuneHyperparametersModel(uid).setBestModel(bestModel).setBestMetric(bestMetric)
-    })
+    }, dataset.columns.length)
   }
   //scalastyle:on method.length
 
@@ -247,7 +247,7 @@ class TuneHyperparametersModel(val uid: String)
 
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame](
-      getBestModel.transform(dataset)
+      getBestModel.transform(dataset), dataset.columns.length
     )
   }
 

core/src/main/scala/com/microsoft/azure/synapse/ml/causal/DoubleMLEstimator.scala

@@ -133,7 +133,7 @@ class DoubleMLEstimator(override val uid: String)
       }
       val dmlModel = this.copyValues(new DoubleMLModel(uid)).setRawTreatmentEffects(ates.toArray)
       dmlModel
-    })
+    }, dataset.columns.length)
   }
 
   //scalastyle:off method.length
@@ -358,7 +358,7 @@ class DoubleMLModel(val uid: String)
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame]({
       dataset.toDF()
-    })
+    }, dataset.columns.length)
   }
 
   @DeveloperApi

core/src/main/scala/com/microsoft/azure/synapse/ml/causal/ResidualTransformer.scala

@@ -87,7 +87,7 @@ class ResidualTransformer(override val uid: String) extends Transformer
             s"Prediction column $getPredictedCol must be of type Vector or NumericType, but is $predictedColDataType" +
               s", please use 'setPredictedCol' to set the correct prediction column")
       }
-    })
+    }, dataset.columns.length)
   }
 }
 

core/src/main/scala/com/microsoft/azure/synapse/ml/explainers/ICEExplainer.scala

@@ -209,7 +209,7 @@ class ICETransformer(override val uid: String) extends Transformer
 
 
   def transform(ds: Dataset[_]): DataFrame = {
-    logTransform {
+    logTransform ({
       transformSchema(ds.schema)
       val df = ds.toDF
       val idCol = DatasetExtensions.findUnusedColumnName("idCol", df)
@@ -250,7 +250,7 @@ class ICETransformer(override val uid: String) extends Transformer
         case `featureKind` =>
           dependenceDfs.reduce(_ union _).orderBy(desc(getDependenceNameCol))
       }
-    }
+    }, ds.columns.length)
   }
 
   private def collectCategoricalValues[_](df: DataFrame, feature: ICECategoricalFeature): Array[_] = {

core/src/main/scala/com/microsoft/azure/synapse/ml/explainers/KernelSHAPBase.scala

@@ -40,7 +40,7 @@ abstract class KernelSHAPBase(override val uid: String)
     with Wrappable
     with SynapseMLLogging {
 
-  override def transform(instances: Dataset[_]): DataFrame = logTransform {
+  override def transform(instances: Dataset[_]): DataFrame = logTransform ({
     import instances.sparkSession.implicits._
     this.validateSchema(instances.schema)
 
@@ -91,7 +91,7 @@ abstract class KernelSHAPBase(override val uid: String)
     }.toDF(idCol, this.getOutputCol, this.getMetricsCol)
 
     preprocessed.join(fitted, Seq(idCol), "inner").drop(idCol)
-  }
+  }, instances.columns.length)
 
   override def copy(extra: ParamMap): Transformer = defaultCopy(extra)
 

core/src/main/scala/com/microsoft/azure/synapse/ml/explainers/LIMEBase.scala

@@ -152,7 +152,7 @@ abstract class LIMEBase(override val uid: String)
     weightUdf
   }
 
-  final override def transform(instances: Dataset[_]): DataFrame = logTransform {
+  final override def transform(instances: Dataset[_]): DataFrame = logTransform ({
     import instances.sparkSession.implicits._
     this.validateSchema(instances.schema)
     val regularization = this.getRegularization
@@ -200,7 +200,7 @@ abstract class LIMEBase(override val uid: String)
     }.toDF(idCol, this.getOutputCol, this.getMetricsCol)
 
     preprocessed.join(fitted, Seq(idCol), "inner").drop(idCol)
-  }
+  }, instances.columns.length)
 
   override def copy(extra: ParamMap): Transformer = this.defaultCopy(extra)
 

core/src/main/scala/com/microsoft/azure/synapse/ml/exploratory/AggregateBalanceMeasure.scala

@@ -87,7 +87,7 @@ class AggregateBalanceMeasure(override val uid: String)
 
       df.unpersist
       calculateAggregateMeasures(featureStats, featureProbCol)
-    })
+    }, dataset.columns.length)
   }
 
   private def calculateAggregateMeasures(featureStats: DataFrame, featureProbCol: String): DataFrame = {

core/src/main/scala/com/microsoft/azure/synapse/ml/exploratory/DistributionBalanceMeasure.scala

@@ -124,7 +124,7 @@ class DistributionBalanceMeasure(override val uid: String)
 
       df.unpersist
       calculateDistributionMeasures(featureStats, featureProbCol, featureCountCol, numRows)
-    })
+    }, dataset.columns.length)
   }
 
   private def calculateDistributionMeasures(featureStats: DataFrame,

core/src/main/scala/com/microsoft/azure/synapse/ml/exploratory/FeatureBalanceMeasure.scala

@@ -128,7 +128,7 @@ class FeatureBalanceMeasure(override val uid: String)
 
       df.unpersist
       calculateParity(associationMetricsDf, featureValueCol)
-    })
+    }, dataset.columns.length)
   }
 
   private def calculateParity(associationMetricsDf: DataFrame, featureValueCol: String): DataFrame = {

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/CleanMissingData.scala

@@ -84,7 +84,7 @@ class CleanMissingData(override val uid: String) extends Estimator[CleanMissingD
         .setFillValues(fillValues.toArray)
         .setInputCols(getInputCols)
         .setOutputCols(getOutputCols)
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): Estimator[CleanMissingDataModel] = defaultCopy(extra)
@@ -179,7 +179,7 @@ class CleanMissingDataModel(val uid: String)
           }).toList
       val addedCols = dataset.select(datasetCols ::: datasetInputCols: _*)
       addedCols.na.fill(getColsToFill.zip(getFillValues).toMap)
-    })
+    }, dataset.columns.length)
   }
 
   override def transformSchema(schema: StructType): StructType =

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/CountSelector.scala

@@ -41,7 +41,7 @@ class CountSelector(override val uid: String) extends Estimator[CountSelectorMod
         .setIndices(slotsToKeep)
         .setInputCol(getInputCol)
         .setOutputCol(getOutputCol)
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): this.type = defaultCopy(extra)
@@ -77,7 +77,8 @@ class CountSelectorModel(val uid: String) extends Model[CountSelectorModel]
 
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame](
-      getModel.transform(dataset)
+      getModel.transform(dataset),
+      dataset.columns.length
     )
   }
 

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/DataConversion.scala

@@ -101,7 +101,7 @@ class DataConversion(override val uid: String) extends Transformer
         df
       }
       res
-    })
+    }, dataset.columns.length)
   }
   //scalastyle:on cyclomatic.complexity
 

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/Featurize.scala

@@ -225,7 +225,7 @@ class Featurize(override val uid: String) extends Estimator[PipelineModel]
       )
 
       new Pipeline().setStages(Seq(encoders, casters, imputers, featurizers, va).flatten.toArray).fit(dataset)
-    })
+    }, dataset.columns.length)
   }
   //scalastyle:on cyclomatic.complexity
   //scalastyle:on method.length

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/IndexToValue.scala

@@ -50,7 +50,7 @@ class IndexToValue(val uid: String) extends Transformer
           case _ => throw new Exception("Unsupported type " + dataType.toString)
         }
       dataset.withColumn(getOutputCol, getLevel(dataset(getInputCol)).as(getOutputCol))
-    })
+    }, dataset.columns.length)
   }
 
   private class Default[T] {var value: T = _ }

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/ValueIndexer.scala

@@ -86,7 +86,7 @@ class ValueIndexer(override val uid: String) extends Estimator[ValueIndexerModel
         .setOutputCol(getOutputCol)
         .setLevels(castSortLevels)
         .setDataType(dataType)
-    })
+    }, dataset.columns.length)
   }
 
   private def sortLevels[T: TypeTag](levels: Array[_])
@@ -198,7 +198,7 @@ class ValueIndexerModel(val uid: String)
         mmlStyle = false)
       val inputColIndex = getIndex(dataset(getInputCol))
       dataset.withColumn(getOutputCol, inputColIndex.as(getOutputCol, metadata))
-    })
+    }, dataset.columns.length)
   }
   //scalastyle:on cyclomatic.complexity
 

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/text/MultiNGram.scala

@@ -58,7 +58,7 @@ class MultiNGram(override val uid: String)
         Row.fromSeq(row.toSeq :+ mergedNGrams)
       }(RowEncoder(intermediateDF.schema.add(getOutputCol, ArrayType(StringType))))
         .drop(intermediateOutputCols: _*)
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): MultiNGram =

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/text/PageSplitter.scala

@@ -94,7 +94,8 @@ class PageSplitter(override val uid: String)
 
   override def transform(dataset: Dataset[_]): DataFrame = {
     logTransform[DataFrame](
-      dataset.toDF().withColumn(getOutputCol, UDFUtils.oldUdf(split _, ArrayType(StringType))(col(getInputCol)))
+      dataset.toDF().withColumn(getOutputCol, UDFUtils.oldUdf(split _, ArrayType(StringType))(col(getInputCol))),
+      dataset.columns.length
     )
   }
 

core/src/main/scala/com/microsoft/azure/synapse/ml/featurize/text/TextFeaturizer.scala

@@ -342,7 +342,7 @@ class TextFeaturizer(override val uid: String)
 
       val stages = chainedModels ++ Seq(new DropColumns().setCols(colsToDrop.toArray))
       new Pipeline().setStages(stages.toArray).fit(dataset).setParent(this)
-    })
+    }, dataset.columns.length)
   }
   //scalastyle:on method.length
 

core/src/main/scala/com/microsoft/azure/synapse/ml/image/SuperpixelTransformer.scala

@@ -49,7 +49,7 @@ class SuperpixelTransformer(val uid: String) extends Transformer
         dataset.schema(getInputCol).dataType, getCellSize, getModifier)
 
       dataset.toDF().withColumn(getOutputCol, getSuperPixels(col(getInputCol)))
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): Transformer = defaultCopy(extra)

core/src/main/scala/com/microsoft/azure/synapse/ml/image/UnrollImage.scala

@@ -182,7 +182,7 @@ class UnrollImage(val uid: String) extends Transformer
       assert(ImageSchemaUtils.isImage(df.schema(getInputCol)), "input column should have Image type")
       val unrollUDF = udf(unroll _)
       df.withColumn(getOutputCol, unrollUDF(df(getInputCol)))
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): Transformer = defaultCopy(extra)
@@ -238,7 +238,7 @@ class UnrollBinaryImage(val uid: String) extends Transformer
       }, VectorType)
 
       df.withColumn($(outputCol), unrollUDF(df($(inputCol))))
-    })
+    }, dataset.columns.length)
   }
 
   override def copy(extra: ParamMap): Transformer = defaultCopy(extra)

core/src/main/scala/com/microsoft/azure/synapse/ml/io/http/HTTPTransformer.scala

@@ -137,7 +137,7 @@ class HTTPTransformer(val uid: String)
           }
         }
       }(enc)
-    })
+    }, dataset.columns.length)
   }
 
   def copy(extra: ParamMap): HTTPTransformer = defaultCopy(extra)