org.apache.spark.internal

Interface Logging

All Known Implementing Classes:

AFTSurvivalRegression, AFTSurvivalRegressionModel, ALS, ALS, ALSModel, AssociationRules, AsyncRDDActions, BaseRRDD, BasicBlockReplicationPolicy, Binarizer, BinaryClassificationMetrics, BisectingKMeans, BisectingKMeans, BisectingKMeansModel, BisectingKMeansModel, BlockMatrix, Broadcast, BucketedRandomProjectionLSH, BucketedRandomProjectionLSHModel, Bucketizer, ChiSqSelector, ChiSqSelectorModel, ClassificationModel, Classifier, CoGroupedRDD, Column, ColumnName, ColumnPruner, ConstantInputDStream, CountVectorizer, CountVectorizerModel, CreateHiveTableAsSelectCommand, CrossValidator, CrossValidatorModel, DataFrameReader, DataStreamReader, DCT, DecisionTree, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeRegressionModel, DecisionTreeRegressor, DefaultTopologyMapper, DetermineTableStats, DistributedLDAModel, DoubleRDDFunctions, DStream, EdgeRDD, EdgeRDDImpl, ElementwiseProduct, Estimator, ExecutionListenerManager, FileBasedTopologyMapper, FPGrowth, FPGrowth, FPGrowthModel, GaussianMixture, GaussianMixtureModel, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GeneralizedLinearAlgorithm, GeneralizedLinearRegression, GeneralizedLinearRegressionModel, GradientBoostedTrees, GradientDescent, HadoopMapReduceCommitProtocol, HadoopRDD, HashingTF, HiveContext, HiveFileFormat, IDF, IDFModel, Imputer, ImputerModel, IndexToString, InputDStream, InputFormatInfo, InsertIntoHiveTable, Interaction, IsotonicRegression, IsotonicRegressionModel, JdbcRDD, JobProgressListener, KMeans, KMeans, KMeansModel, KryoSerializer, LassoWithSGD, LBFGS, LDA, LDA, LDAModel, org.apache.spark.sql.catalyst.plans.logical.LeafNode, LinearRegression, LinearRegressionModel, LinearRegressionWithSGD, LinearSVC, LinearSVCModel, LocalLDAModel, org.apache.spark.sql.catalyst.plans.logical.LogicalPlan, LogisticAggregator, LogisticRegression, LogisticRegressionModel, LogisticRegressionWithLBFGS, LogisticRegressionWithSGD, MapWithStateDStream, MatrixFactorizationModel, MaxAbsScaler, MaxAbsScalerModel, MinHashLSH, MinHashLSHModel, MinMaxScaler, MinMaxScalerModel, MLWriter, Model, MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier, NaiveBayes, NaiveBayes, NaiveBayesModel, NewHadoopRDD, NGram, Node, Normalizer, OneHotEncoder, OneVsRest, OneVsRestModel, OrderedRDDFunctions, PairRDDFunctions, PairwiseRRDD, PartitionPruningRDD, PCA, PCAModel, Pipeline, PipelineModel, PipelineStage, PolynomialExpansion, PredictionModel, Predictor, PrefixSpan, ProbabilisticClassificationModel, ProbabilisticClassifier, QuantileDiscretizer, RandomBlockReplicationPolicy, RandomForest, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RankingMetrics, RBackendAuthHandler, RDD, ReceiverInputDStream, RegexTokenizer, RegressionMetrics, RegressionModel, RelationConversions, ResolveHiveSerdeTable, RFormula, RFormulaModel, RidgeRegressionWithSGD, RowMatrix, RRDD, org.apache.spark.sql.catalyst.rules.Rule, ScriptTransformationExec, ScriptTransformationWriterThread, SequenceFileRDDFunctions, ShuffledRDD, SparkConf, SparkContext, SparkEnv, org.apache.spark.sql.execution.SparkPlan, SparkSession, SparkSession.Builder, SQLContext, SQLTransformer, StandardScaler, StandardScaler, StandardScalerModel, StatsReportListener, StopWordsRemover, StreamingContext, StreamingKMeans, StreamingKMeansModel, StreamingLinearAlgorithm, StreamingLinearRegressionWithSGD, StreamingLogisticRegressionWithSGD, StreamingQueryManager, StreamingTest, StringIndexer, StringIndexerModel, StringRRDD, SVMWithSGD, Tokenizer, TrainValidationSplit, TrainValidationSplitModel, Transformer, TypedColumn, UDFRegistration, UnaryTransformer, UnionRDD, VectorAssembler, VectorAttributeRewriter, VectorIndexer, VectorIndexerModel, VectorSlicer, VertexRDD, VertexRDDImpl, Word2Vec, Word2Vec, Word2VecModel

public interface Logging

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.

Method Summary

Modifier and Type	Method and Description
void	initializeLogging(boolean isInterpreter)
void	initializeLogIfNecessary(boolean isInterpreter)
boolean	isTraceEnabled()
org.slf4j.Logger	log_()
org.slf4j.Logger	log()
void	logDebug(scala.Function0<String> msg)
void	logDebug(scala.Function0<String> msg, Throwable throwable)
void	logError(scala.Function0<String> msg)
void	logError(scala.Function0<String> msg, Throwable throwable)
void	logInfo(scala.Function0<String> msg)
void	logInfo(scala.Function0<String> msg, Throwable throwable)
String	logName()
void	logTrace(scala.Function0<String> msg)
void	logTrace(scala.Function0<String> msg, Throwable throwable)
void	logWarning(scala.Function0<String> msg)
void	logWarning(scala.Function0<String> msg, Throwable throwable)

Method Detail

log_

org.slf4j.Logger log_()

logName

String logName()

log

org.slf4j.Logger log()

logInfo

void logInfo(scala.Function0<String> msg)

logDebug

void logDebug(scala.Function0<String> msg)

logTrace

void logTrace(scala.Function0<String> msg)

logWarning

void logWarning(scala.Function0<String> msg)

logError

void logError(scala.Function0<String> msg)

logInfo

void logInfo(scala.Function0<String> msg,
             Throwable throwable)

logDebug

void logDebug(scala.Function0<String> msg,
              Throwable throwable)

logTrace

void logTrace(scala.Function0<String> msg,
              Throwable throwable)

logWarning

void logWarning(scala.Function0<String> msg,
                Throwable throwable)

logError

void logError(scala.Function0<String> msg,
              Throwable throwable)

isTraceEnabled

boolean isTraceEnabled()

initializeLogIfNecessary

void initializeLogIfNecessary(boolean isInterpreter)

initializeLogging

void initializeLogging(boolean isInterpreter)