org.apache.spark.SparkException: Currently, LogisticRegression with ElasticNet in ML package only supports binary classification. Found 5 in the input dataset.

Stack Overflow | krishna Prasad | 7 months ago
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  1. 0

    Logistic Regression as multiclass classification using PySpark and issues

    Stack Overflow | 7 months ago | krishna Prasad
    org.apache.spark.SparkException: Currently, LogisticRegression with ElasticNet in ML package only supports binary classification. Found 5 in the input dataset.
  2. 0

    Issues with Logistic Regression for multiclass classification using PySpark

    Stack Overflow | 7 months ago | krishna Prasad
    org.apache.spark.SparkException: Currently, LogisticRegression with ElasticNet in ML package only supports binary classification. Found 5 in the input dataset.
  3. 0

    Logistic Regression as multiclass classification using PySpark and issues

    Data Science | 7 months ago | krishna Prasad
    org.apache.spark.SparkException: Currently, LogisticRegression with ElasticNet in ML package only supports binary classification. Found 5 in the input dataset.
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  5. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 1 year ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
  6. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 1 year ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)

Root Cause Analysis

  1. org.apache.spark.SparkException

    Currently, LogisticRegression with ElasticNet in ML package only supports binary classification. Found 5 in the input dataset.

    at org.apache.spark.ml.classification.LogisticRegression.train()
  2. Spark Project ML Library
    Predictor.fit
    1. org.apache.spark.ml.classification.LogisticRegression.train(LogisticRegression.scala:290)
    2. org.apache.spark.ml.classification.LogisticRegression.train(LogisticRegression.scala:159)
    3. org.apache.spark.ml.Predictor.fit(Predictor.scala:90)
    4. org.apache.spark.ml.Predictor.fit(Predictor.scala:71)
    4 frames
  3. Java RT
    Method.invoke
    1. sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    2. sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    3. sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    4. java.lang.reflect.Method.invoke(Method.java:498)
    4 frames
  4. Py4J
    GatewayConnection.run
    1. py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    2. py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    3. py4j.Gateway.invoke(Gateway.java:259)
    4. py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    5. py4j.commands.CallCommand.execute(CallCommand.java:79)
    6. py4j.GatewayConnection.run(GatewayConnection.java:209)
    6 frames
  5. Java RT
    Thread.run
    1. java.lang.Thread.run(Thread.java:745)
    1 frame