Trait

org.apache.spark.internal

Logging

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trait Logging extends AnyRef

Utility trait for classes that want to log data. Creates a SLF4J logger for the class and allows logging messages at different levels using methods that only evaluate parameters lazily if the log level is enabled.

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AnyRef, Any
Known Subclasses
AFTSurvivalRegression, AFTSurvivalRegressionModel, ALS, ALS, ALS, ALSModel, AssociationRules, AsyncRDDActions, BasicBlockReplicationPolicy, Binarizer, BinaryClassificationMetrics, BisectingKMeans, BisectingKMeans, BisectingKMeansModel, BisectingKMeansModel, BlockMatrix, Broadcast, Bucketizer, Builder, ChiSqSelector, ChiSqSelectorModel, ClassificationModel, Classifier, CoGroupedRDD, Column, ColumnName, ConstantInputDStream, CountVectorizer, CountVectorizerModel, CrossValidator, CrossValidatorModel, CrossValidatorModelWriter, DCT, DStream, DataFrameReader, DataStreamReader, DataValidators, DecisionTree, DecisionTree, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeModel, DecisionTreeRegressionModel, DecisionTreeRegressor, DefaultTopologyMapper, DistributedLDAModel, DoubleRDDFunctions, EdgeRDD, EdgeRDDImpl, ElementwiseProduct, Estimator, ExecutionListenerManager, FPGrowth, FPGrowth, FPGrowthModel, FeatureHasher, FileBasedTopologyMapper, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GaussianMixture, GaussianMixtureModel, GeneralizedLinearAlgorithm, GeneralizedLinearRegression, GeneralizedLinearRegressionModel, GradientBoostedTrees, GradientBoostedTrees, GradientDescent, GradientDescent, GraphGenerators, GraphLoader, HadoopMapRedCommitProtocol, HadoopMapReduceCommitProtocol, HadoopRDD, HashingTF, HiveContext, HiveFileFormat, IDF, IDFModel, Imputer, ImputerModel, IndexToString, InputDStream, InputFormatInfo, Interaction, IsotonicRegression, IsotonicRegressionModel, JdbcRDD, KMeans, KMeans, KMeansModel, KryoSerializer, LBFGS, LBFGS, LDA, LDA, LDAModel, LassoWithSGD, LinearRegression, LinearRegressionModel, LinearRegressionWithSGD, LinearSVC, LinearSVCModel, LocalLDAModel, LogisticRegression, LogisticRegressionModel, LogisticRegressionWithLBFGS, LogisticRegressionWithSGD, MLUtils, MLWriter, MapWithStateDStream, MatrixFactorizationModel, MaxAbsScaler, MaxAbsScalerModel, MinMaxScaler, MinMaxScalerModel, Model, MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier, NGram, NaiveBayes, NaiveBayes, NaiveBayesModel, NewHadoopRDD, Node, Normalizer, OneHotEncoder, OneVsRest, OneVsRestModel, OnlineLDAOptimizer, OrderedRDDFunctions, PCA, PCAModel, PageRank, PairRDDFunctions, PartitionPruningRDD, Pipeline, PipelineModel, PipelineStage, PolynomialExpansion, PowerIterationClustering, PredictionModel, Predictor, PrefixSpan, PrefixSpan, Pregel, ProbabilisticClassificationModel, ProbabilisticClassifier, QuantileDiscretizer, QuantileDiscretizer, RDD, RFormula, RFormulaModel, RandomBlockReplicationPolicy, RandomForest, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RankingMetrics, ReceiverInputDStream, RegexTokenizer, RegressionMetrics, RegressionModel, RidgeRegressionWithSGD, RowMatrix, SQLContext, SQLTransformer, SVMWithSGD, SequenceFileRDDFunctions, ShuffledRDD, SizeEstimator, SparkConf, SparkContext, SparkContext, SparkEnv, SparkEnv, SparkHadoopMapRedUtil, SparkSession, StandardScaler, StandardScaler, StandardScalerModel, StatsReportListener, StopWordsRemover, StreamingContext, StreamingContext, StreamingKMeans, StreamingKMeansModel, StreamingLinearAlgorithm, StreamingLinearRegressionWithSGD, StreamingLogisticRegressionWithSGD, StreamingQueryManager, StreamingTest, StringIndexer, StringIndexerModel, Summarizer, Tokenizer, TrainValidationSplit, TrainValidationSplitModel, TrainValidationSplitModelWriter, Transformer, TypedColumn, UDFRegistration, UnaryTransformer, UnionRDD, VectorAssembler, VectorIndexer, VectorIndexerModel, VectorSlicer, VertexRDD, VertexRDDImpl, Word2Vec, Word2Vec, Word2VecModel
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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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  12. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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  13. final def isInstanceOf[T0]: Boolean

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  14. def isTraceEnabled(): Boolean

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  15. def log: Logger

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  16. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  17. def logDebug(msg: ⇒ String): Unit

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  18. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  19. def logError(msg: ⇒ String): Unit

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  20. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  21. def logInfo(msg: ⇒ String): Unit

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  22. def logName: String

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  23. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  24. def logTrace(msg: ⇒ String): Unit

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  25. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  26. def logWarning(msg: ⇒ String): Unit

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  27. final def ne(arg0: AnyRef): Boolean

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  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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  30. final def synchronized[T0](arg0: ⇒ T0): T0

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  31. def toString(): String

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  32. final def wait(): Unit

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  33. final def wait(arg0: Long, arg1: Int): Unit

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  34. final def wait(arg0: Long): Unit

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