Share via

py4j.security.Py4JSecurityException

Ahuja, Rachit 0 Reputation points
2024-05-06T12:48:28.3166667+00:00

Hello I am trying to run spark XGBoostRegression model on Databricks cluster with Databricks runtime: 14.3 LTS.

I am getting the following error:

Py4JError: An error occurred while calling o547.resourceProfileManager. Trace: py4j.security.Py4JSecurityException: Method public org.apache.spark.resource.ResourceProfileManager org.apache.spark.SparkContext.resourceProfileManager() is not whitelisted on class class org.apache.spark.SparkContext at py4j.security.WhitelistingPy4JSecurityManager.checkCall(WhitelistingPy4JSecurityManager.java:473) at py4j.Gateway.invoke(Gateway.java:305) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:199) at py4j.ClientServerConnection.run(ClientServerConnection.java:119) at java.lang.Thread.run(Thread.java:750)

Here is my cluster configuration JSON: { "cluster_id": "0412-193940-roa64zgt", "creator_user_name": "b90f2c51-c49c-4f97-95a9-d58c6c1e8fc8", "spark_context_id": 5504105953918341000, "driver_healthy": true, "cluster_name": "DsShared", "spark_version": "14.3.x-cpu-ml-scala2.12", "spark_conf": { "spark.databricks.delta.preview.enabled": "true" }, "azure_attributes": { "first_on_demand": 1, "availability": "ON_DEMAND_AZURE", "spot_bid_max_price": -1 }, "node_type_id": "Standard_D4s_v5", "driver_node_type_id": "Standard_D4s_v5", "spark_env_vars": { "PYSPARK_PYTHON": "/databricks/python3/bin/python3" }, "autotermination_minutes": 20, "enable_elastic_disk": true, "disk_spec": {}, "cluster_source": "UI", "enable_local_disk_encryption": false, "instance_source": { "node_type_id": "Standard_D4s_v5" }, "driver_instance_source": { "node_type_id": "Standard_D4s_v5" }, "data_security_mode": "LEGACY_PASSTHROUGH", "runtime_engine": "STANDARD", "effective_spark_version": "14.3.x-cpu-ml-scala2.12", "autoscale": { "min_workers": 1, "max_workers": 3, "target_workers": 1 }, "default_tags": { "Vendor": "Databricks", "Creator": "b90f2c51-c49c-4f97-95a9-d58c6c1e8fc8", "ClusterName": "DsShared", "ClusterId": "0412-193940-roa64zgt", }, "termination_reason": { "code": "INACTIVITY", "type": "SUCCESS", "parameters": { "inactivity_duration_min": "20" } }, "pinned_by_user_name": "4460559388477034", "init_scripts_safe_mode": false, "spec": { "cluster_name": "DsShared", "spark_version": "14.3.x-cpu-ml-scala2.12", "spark_conf": { "spark.databricks.delta.preview.enabled": "true" }, "azure_attributes": { "first_on_demand": 1, "availability": "ON_DEMAND_AZURE", "spot_bid_max_price": -1 }, "node_type_id": "Standard_D4s_v5", "driver_node_type_id": "Standard_D4s_v5", "spark_env_vars": { "PYSPARK_PYTHON": "/databricks/python3/bin/python3" }, "autotermination_minutes": 20, "enable_elastic_disk": true, "cluster_source": "UI", "data_security_mode": "LEGACY_PASSTHROUGH", "runtime_engine": "STANDARD", "autoscale": { "min_workers": 1, "max_workers": 3 } } }

Any help would be highly appreciated.

Azure Databricks
Azure Databricks

An Apache Spark-based analytics platform optimized for Azure.


Your answer

Answers can be marked as 'Accepted' by the question author and 'Recommended' by moderators, which helps users know the answer solved the author's problem.