| Interface and Description | 
|---|
| org.apache.spark.AccumulableParam use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam use AccumulatorV2. Since 2.0.0. | 
| Class and Description | 
|---|
| org.apache.spark.Accumulable use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.Accumulator use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$ use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam.FloatAccumulatorParam$ use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam.IntAccumulatorParam$ use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam.LongAccumulatorParam$ use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.AccumulatorParam.StringAccumulatorParam$ use AccumulatorV2. Since 2.0.0. | 
| org.apache.spark.sql.hive.HiveContext Use SparkSession.builder.enableHiveSupport instead. Since 2.0.0. | 
| 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. | 
| org.apache.spark.mllib.regression.LinearRegressionWithSGD Use ml.regression.LinearRegression or LBFGS. Since 2.0.0. | 
| org.apache.spark.mllib.classification.LogisticRegressionWithSGD Use ml.classification.LogisticRegression or LogisticRegressionWithLBFGS. Since 2.0.0. | 
| 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. |