org.apache.spark
Interface Logging
- All Known Subinterfaces:
- ActorHelper
- All Known Implementing Classes:
- ALS, ALS, ALSModel, AsyncRDDActions, BaseRRDD, Binarizer, BinaryClassificationMetrics, BlockMatrix, Broadcast, Bucketizer, ClassificationModel, Classifier, CoGroupedRDD, Column, ColumnName, ConstantInputDStream, CrossValidator, CrossValidatorModel, DataValidators, DecisionTree, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeRegressionModel, DecisionTreeRegressor, DoubleRDDFunctions, DStream, EdgeRDD, EdgeRDDImpl, ElementwiseProduct, Estimator, FPGrowth, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GeneralizedLinearAlgorithm, GradientBoostedTrees, GradientDescent, GraphLoader, HadoopRDD, HashingTF, HiveContext, IDF, IDFModel, InputDStream, InputFormatInfo, JdbcRDD, JobLogger, JobProgressListener, KafkaTestUtils, KinesisWordCountASL, KMeans, KryoSerializer, LassoWithSGD, LBFGS, LDA, LinearRegression, LinearRegressionModel, LinearRegressionWithSGD, LocalSQLContext, LogisticRegression, LogisticRegressionModel, LogisticRegressionWithLBFGS, LogisticRegressionWithSGD, MatrixFactorizationModel, Model, NaiveBayes, NewHadoopRDD, Node, Normalizer, OneHotEncoder, OneVsRest, OneVsRestModel, OrderedRDDFunctions, PageRank, PairRDDFunctions, PairwiseRRDD, PartitionPruningRDD, Pipeline, PipelineModel, PipelineStage, PolynomialExpansion, PredictionModel, Predictor, Pregel, RandomForest, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RankingMetrics, RDD, ReceiverInputDStream, RegexTokenizer, RegressionMetrics, RegressionModel, RidgeRegressionWithSGD, RowMatrix, RRDD, SequenceFileRDDFunctions, ShuffledRDD, SizeEstimator, SparkConf, SparkContext, SparkEnv, SQLContext, StandardScaler, StandardScaler, StandardScalerModel, StatsReportListener, StreamingContext, StreamingKMeans, StreamingKMeansModel, StreamingLinearAlgorithm, StreamingLinearRegressionWithSGD, StreamingLogisticRegressionWithSGD, StringIndexer, StringIndexerModel, StringRRDD, SVMWithSGD, TestSQLContext, Tokenizer, Transformer, UDFRegistration, UnaryTransformer, UnionRDD, VectorAssembler, VectorIndexer, VectorIndexerModel, VertexRDD, VertexRDDImpl, Word2Vec, Word2Vec, Word2VecModel
public interface Logging
:: DeveloperApi ::
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.
NOTE: DO NOT USE this class outside of Spark. It is intended as an internal utility.
This will likely be changed or removed in future releases.
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()
initializeIfNecessary
void initializeIfNecessary()
initializeLogging
void initializeLogging()