我是 Databricks 新手，正在尝试从我的通用计算集群连接到 Rstudio Server。
以下是集群配置：
政策：个人计算
访问模式：单用户
Databricks 运行时版本：
13.2 ML（包括 Apache Spark 3.4.0、Scala 2.12）
我们的工作区中还配置了统一目录。
按照此处的说明，我尝试使用 sparlyr 和 SparkR 运行代码。
sparklyr
> library(sparklyr)
> sc <- spark_connect(method = "databricks")
但是，我收到以下错误：
Error in value[[3L]](cond) :
Failed to start sparklyr backend: java.util.concurrent.ExecutionException: org.apache.spark.SparkException: There is no Credential Scope.
at com.google.common.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:299)
at com.google.common.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:286)
at com.google.common.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
at com.google.common.util.concurrent.Uninterruptibles.getUninterruptibly(Uninterruptibles.java:135)
at com.google.common.cache.LocalCache$Segment.getAndRecordStats(LocalCache.java:2344)
at com.google.common.cache.LocalCache$Segment.loadSync(LocalCache.java:2316)
at com.google.common.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2278)
at com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2193)
at com.google.common.cache.LocalCache.get(LocalCache.java:3932)
at com.google.common.cache.LocalCache.getOrLoad(LocalCache.java:3936)
at com.google.common.cache.LocIn addition: Warning messages:1: In file.create(to[okay]) : cannot create file '/usr/local/lib/R/site-library/sparklyr/java//sparklyr-2.2-2.11.jar', reason 'Permission denied'2: In file.create(to[okay]) : cannot create file '/usr/local/lib/R/site-library/sparklyr/java//sparklyr-2.1-2.11.jar', reason 'Permission denied'
火花
> library(SparkR)
> sparkR.session()
Java ref type org.apache.spark.sql.SparkSession id 1 > df <- SparkR::sql("SELECT * FROM default.diamonds LIMIT 2")
错误回溯：
Error in handleErrors(returnStatus, conn) :
org.apache.spark.sql.AnalysisException: There is no Credential Scope. ; line 1 pos 14
at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:69)
at org.apache.spark.sql.execution.datasources.ResolveSQLOnFile$$anonfun$apply$1.applyOrElse(rules.scala:172)
at org.apache.spark.sql.execution.datasources.ResolveSQLOnFile$$anonfun$apply$1.applyOrElse(rules.scala:94)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDownWithPruning$2(AnalysisHelper.scala:219)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:106)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDownWithPruning$1(AnalysisHelper.scala:219)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:372)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDownWithPruning(AnalysisHelper.scal
我不是 R 开发人员，因此无法真正尝试不同的配置。我尝试设置个人身份验证令牌，但没有成功。如有任何帮助，我们将不胜感激，并提前致谢:)