嘿 StackOverflowers！
我遇到了一个问题。
我已将 PyCharm 设置为通过 SSH 连接与（天蓝色）VM 连接。
所以首先我为 ssh 连接进行配置
我设置了映射
我通过在 vm 中启动一个终端来创建一个 conda 环境，然后我下载并连接到 databricks-connect。我在终端上测试它，它工作正常。
我在 pycharm 配置上设置了控制台
但是当我尝试运行 spark 会话 (spark = SparkSession.builder.getOrCreate()) 时，databricks-connect 会在错误的文件夹中搜索 .databricks-connect 文件并给我以下错误：
Caused by: java.lang.RuntimeException: Config file /root/.databricks-connect not found. Please run 数据块连接配置 to accept the end user license agreement and configure Databricks Connect. A copy of the EULA is provided below: Copyright (2018) Databricks, Inc.
以及完整的错误+一些警告。
20/07/10 17:23:05 WARN Utils: Your hostname, george resolves to a loopback address: 127.0.0.1; using 10.0.0.4 instead (on interface eth0)
20/07/10 17:23:05 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
20/07/10 17:23:05 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).
Traceback (most recent call last):
File "/anaconda/envs/py37/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-23fe18298795>", line 1, in <module>
runfile('/home/azureuser/code/model/check_vm.py')
File "/home/azureuser/.pycharm_helpers/pydev/_pydev_bundle/pydev_umd.py", line 197, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "/home/azureuser/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/azureuser/code/model/check_vm.py", line 13, in <module>
spark = SparkSession.builder.getOrCreate()
File "/anaconda/envs/py37/lib/python3.7/site-packages/pyspark/sql/session.py", line 185, in getOrCreate
sc = SparkContext.getOrCreate(sparkConf)
File "/anaconda/envs/py37/lib/python3.7/site-packages/pyspark/context.py", line 373, in getOrCreate
SparkContext(conf=conf or SparkConf())
File "/anaconda/envs/py37/lib/python3.7/site-packages/pyspark/context.py", line 137, in __init__
conf, jsc, profiler_cls)
File "/anaconda/envs/py37/lib/python3.7/site-packages/pyspark/context.py", line 199, in _do_init
self._jsc = jsc or self._initialize_context(self._conf._jconf)
File "/anaconda/envs/py37/lib/python3.7/site-packages/pyspark/context.py", line 312, in _initialize_context
return self._jvm.JavaSparkContext(jconf)
File "/anaconda/envs/py37/lib/python3.7/site-packages/py4j/java_gateway.py", line 1525, in __call__
answer, self._gateway_client, None, self._fqn)
File "/anaconda/envs/py37/lib/python3.7/site-packages/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.lang.ExceptionInInitializerError
at org.apache.spark.SparkContext.<init>(SparkContext.scala:99)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:61)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:250)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.RuntimeException: Config file /root/.databricks-connect not found. Please run `databricks-connect configure` to accept the end user license agreement and configure Databricks Connect. A copy of the EULA is provided below: Copyright (2018) Databricks, Inc.
This library (the "Software") may not be used except in connection with the Licensee's use of the Databricks Platform Services pursuant to an Agreement (defined below) between Licensee (defined below) and Databricks, Inc. ("Databricks"). This Software shall be deemed part of the “Subscription Services” under the Agreement, or if the Agreement does not define Subscription Services, then the term in such Agreement that refers to the applicable Databricks Platform Services (as defined below) shall be substituted herein for “Subscription Services.” Licensee's use of the Software must comply at all times with any restrictions applicable to the Subscription Services, generally, and must be used in accordance with any applicable documentation. If you have not agreed to an Agreement or otherwise do not agree to these terms, you may not use the Software. This license terminates automatically upon the termination of the Agreement or Licensee's breach of these terms.
Agreement: the agreement between Databricks and Licensee governing the use of the Databricks Platform Services, which shall be, with respect to Databricks, the Databricks Terms of Service located at www.databricks.com/termsofservice, and with respect to Databricks Community Edition, the Community Edition Terms of Service located at www.databricks.com/ce-termsofuse, in each case unless Licensee has entered into a separate written agreement with Databricks governing the use of the applicable Databricks Platform Services. Databricks Platform Services: the Databricks services or the Databricks Community Edition services, according to where the Software is used.
Licensee: the user of the Software, or, if the Software is being used on behalf of a company, the company.
To accept this agreement and start using Databricks Connect, run `databricks-connect configure` in a shell.
at com.databricks.spark.util.DatabricksConnectConf$.checkEula(DatabricksConnectConf.scala:41)
at org.apache.spark.SparkContext$.<init>(SparkContext.scala:2679)
at org.apache.spark.SparkContext$.<clinit>(SparkContext.scala)
... 13 more
但是，我没有对该文件夹的访问权限，因此我无法将 databricks 连接文件放在那里。
同样奇怪的是，如果我运行： Pycharm -> ssh terminal -> activate conda env -> python 以下
这是一种方法吗：
1. Point out to java where the databricks-connect file is
2. Configure databricks-connect in another way throughout the script or enviromental variables inside pycharm
3. Other way?
or do I miss something?