我尝试设置Databricks Connect，以便能够与Azure上的Workspace上已运行的远程Databricks群集一起工作。当我尝试运行命令时：'databricks-connect test'永远不会结束。
我遵循官方文件。
我已经安装了最新的Anaconda 3.7版本。我已经创建了本地环境：conda create --name dbconnect python=3.5
我已经在5.1版中安装了'databricks-connect'，它与Azure Databricks上的群集配置相匹配。

pip install -U databricks-connect==5.1.*

我已经设置了'databricks-connect configure如下：

(base) C:\>databricks-connect configure
    The current configuration is:
    * Databricks Host: ******.azuredatabricks.net
    * Databricks Token: ************************************
    * Cluster ID: ****-******-*******
    * Org ID: ****************
    * Port: 8787

经过上述步骤后，我尝试运行“test”命令进行数据块连接：

databricks-connect test

因此，程序在发出有关MetricsSystem的警告后启动和停止，如下所示：

(dbconnect) C:\>databricks-connect test
    * PySpark is installed at c:\users\miltad\appdata\local\continuum\anaconda3\envs\dbconnect\lib\site-packages\pyspark
    * Checking java version
    java version "1.8.0_181"
    Java(TM) SE Runtime Environment (build 1.8.0_181-b13)
    Java HotSpot(TM) 64-Bit Server VM (build 25.181-b13, mixed mode)
    * Testing scala command
    19/05/31 08:14:26 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
    Setting default log level to "WARN".
    To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
    19/05/31 08:14:34 WARN MetricsSystem: Using default name SparkStatusTracker for source because neither spark.metrics.namespace nor spark.app.id is set.

我希望这个过程应该像官方文档中那样进入下一步：

* Testing scala command
    18/12/10 16:38:44 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
    Setting default log level to "WARN".
    To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
    18/12/10 16:38:50 WARN MetricsSystem: Using default name SparkStatusTracker for source because neither spark.metrics.namespace nor spark.app.id is set.
    18/12/10 16:39:53 WARN SparkServiceRPCClient: Now tracking server state for 5abb7c7e-df8e-4290-947c-c9a38601024e, invalidating prev state
    18/12/10 16:39:59 WARN SparkServiceRPCClient: Syncing 129 files (176036 bytes) took 3003 ms
    Welcome to
          ____              __
         / __/__  ___ _____/ /__
        _\ \/ _ \/ _ `/ __/  '_/
       /___/ .__/\_,_/_/ /_/\_\   version 2.4.0-SNAPSHOT
          /_/

    Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_152)
    Type in expressions to have them evaluated.
    Type :help for more information.

所以我的进程在'WARN MetricsSystem：使用默认名称“Spark状态跟踪器”。
我做错了什么？我应该配置更多的东西吗？