Interface and Description |
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org.apache.spark.AccumulableParam
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam
use AccumulatorV2. Since 2.0.0.
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Class and Description |
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org.apache.spark.Accumulable
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.Accumulator
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam.IntAccumulatorParam$
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam.LongAccumulatorParam$
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.AccumulatorParam.StringAccumulatorParam$
use AccumulatorV2. Since 2.0.0.
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org.apache.spark.sql.hive.HiveContext
Use SparkSession.builder.enableHiveSupport instead. Since 2.0.0.
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org.apache.spark.mllib.regression.LassoWithSGD
Use ml.regression.LinearRegression with elasticNetParam = 1.0. Note the default regParam is 0.01 for LassoWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
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org.apache.spark.mllib.regression.LinearRegressionWithSGD
Use ml.regression.LinearRegression or LBFGS. Since 2.0.0.
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org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Use ml.classification.LogisticRegression or LogisticRegressionWithLBFGS. Since 2.0.0.
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org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Use ml.regression.LinearRegression with elasticNetParam = 0.0. Note the default regParam is 0.01 for RidgeRegressionWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
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