我无法切换node.js版本

Question

我正在尝试切换我的node.js版本。

我所做的是：

sudo npm cache clean -f
sudo npm install -g n
sudo n 10.10.0

但是我使用

检查了当前版本后

node -v

它始终显示

v6.14.3

我不确定我做错了什么。有什么建议吗？

Answer 1

如Intervalia所述，try using using NVM (node version manager)

使用nvm，您可以非常轻松地执行以下操作：

py4j.protocol.Py4JJavaError: An error occurred while calling o1040.collectToPython. : org.apache.spark.SparkException: Failed to execute user defined function($anonfun$4: (string) => double) at org.apache.spark.sql.catalyst.expressions.ScalaUDF.eval(ScalaUDF.scala:1072) at org.apache.spark.sql.catalyst.expressions.BinaryExpression.eval(Expression.scala:409) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$.org$apache$spark$sql$catalyst$optimizer$EliminateOuterJoin$$canFilterOutNull(joins.scala:116) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$$anonfun$7.apply(joins.scala:125) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$$anonfun$7.apply(joins.scala:125) at scala.collection.LinearSeqOptimized$class.exists(LinearSeqOptimized.scala:93) at scala.collection.immutable.List.exists(List.scala:84) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$.org$apache$spark$sql$catalyst$optimizer$EliminateOuterJoin$$buildNewJoinType(joins.scala:125) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$$anonfun$apply$2.applyOrElse(joins.scala:140) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$$anonfun$apply$2.applyOrElse(joins.scala:138) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:287) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:277) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$.apply(joins.scala:138) at org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin$.apply(joins.scala:105) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82) at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57) at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66) at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:35) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74) at scala.collection.immutable.List.foreach(List.scala:381) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:73) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:73) at org.apache.spark.sql.execution.QueryExecution$$anonfun$toString$2.apply(QueryExecution.scala:230) at org.apache.spark.sql.execution.QueryExecution$$anonfun$toString$2.apply(QueryExecution.scala:230) at org.apache.spark.sql.execution.QueryExecution.stringOrError(QueryExecution.scala:107) at org.apache.spark.sql.execution.QueryExecution.toString(QueryExecution.scala:230) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:54) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765) at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2742) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:280) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:214) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Unseen label: null. at org.apache.spark.ml.feature.StringIndexerModel$$anonfun$4.apply(StringIndexer.scala:170) at org.apache.spark.ml.feature.StringIndexerModel$$anonfun$4.apply(StringIndexer.scala:166) at org.apache.spark.sql.catalyst.expressions.ScalaUDF$$anonfun$2.apply(ScalaUDF.scala:89) at org.apache.spark.sql.catalyst.expressions.ScalaUDF$$anonfun$2.apply(ScalaUDF.scala:88) at org.apache.spark.sql.catalyst.expressions.ScalaUDF.eval(ScalaUDF.scala:1069) ... 75 more ，它将下载该版本的节点。然后执行nvm install 10.10.0，然后执行nvm use 10.10.0将返回node -v。

  

这是我运行10.10.0

时发生的情况