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<@ULVA73B9P> set up pool process work pool in linu...
# ask-marvin
w
@Marvin set up pool process work pool in linux server where proxy is required. i wan to daemonized the process so i create /etc/systemd/system/prefect-worker.service i can specify environment variable in the file. can i also specify environment variable in browser in worker edit page?
m
✅ thought for 74.5 seconds
Yes, you can set environment variables both in your systemd service file and through the Prefect UI for your work pool. Let me explain both approaches: 1. Systemd Service File Configuration
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ini
[Unit]
Description=Prefect Worker Service
After=network.target

[Service]
Type=simple
User=your_user
Environment="HTTP_PROXY=<http://your.proxy:port>"
Environment="HTTPS_PROXY=<http://your.proxy:port>"
Environment="NO_PROXY=localhost,127.0.0.1"
# Add any other environment variables you need
ExecStart=/path/to/prefect worker start -p "your-pool-name"
Restart=always

[Install]
WantedBy=multi-user.target
2. Prefect UI Configuration Yes, you can set environment variables through the UI: 1. Go to your work pools in the Prefect UI 2. Click on your process work pool 3. Click the "Edit" button 4. Look for the "Base Job Template" section 5. Under the configuration, you can add environment variables that will be applied to all workers in this pool The environment variables set in the UI will be merged with those set in your systemd service file, with the systemd variables taking precedence if there are conflicts. A few important notes: - Environment variables set through the UI will apply to all workers using that work pool - Sensitive information (like proxy credentials) might be better set through the systemd service file for security reasons - Make sure to restart your systemd service after making changes to the service file:
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bash
sudo systemctl daemon-reload
sudo systemctl restart prefect-worker.service
For proxy settings specifically, remember to include these common variables if needed: - HTTP_PROXY - HTTPS_PROXY - NO_PROXY You can verify your worker is running with the correct environment variables by checking:
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bash
sudo systemctl status prefect-worker.service
For more details on managing work pools and their configuration, you can refer to the Prefect documentation on managing work pools.
w
File "/home/daservice/projects/prefect-da/flows/etl_typeform_responses.py", line 116, in upsert_to_databricks spark_df = spark.createDataFrame(df) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/daservice/projects/prefect-da/.venv/lib/python3.12/site-packages/pyspark/sql/connect/session.py", line 376, in createDataFrame timezone, safecheck = self._client.get_configs( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/daservice/projects/prefect-da/.venv/lib/python3.12/site-packages/pyspark/sql/connect/client/core.py", line 1207, in get_configs configs = dict(self.config(op).pairs) ^^^^^^^^^^^^^^^ File "/home/daservice/projects/prefect-da/.venv/lib/python3.12/site-packages/pyspark/sql/connect/client/core.py", line 1250, in config self._handle_error(error) File "/home/daservice/projects/prefect-da/.venv/lib/python3.12/site-packages/pyspark/sql/connect/client/core.py", line 1308, in _handle_error self._handle_rpc_error(error) File "/home/daservice/projects/prefect-da/.venv/lib/python3.12/site-packages/pyspark/sql/connect/client/core.py", line 1348, in _handle_rpc_error raise SparkConnectGrpcException(str(rpc_error)) from None pyspark.errors.exceptions.connect.SparkConnectGrpcException: <_InactiveRpcError of RPC that terminated with: status = StatusCode.UNAVAILABLE details = "failed to connect to all addresses; last error: UNKNOWN: ipv420.247.134.0443: Failed to connect to remote host: Timeout occurred: FD Shutdown" debug_error_string = "UNKNOWN:Error received from peer {grpc_status:14, grpc_message:"failed to connect to all addresses; last error: UNKNOWN: ipv420.247.134.0443: Failed to connect to remote host: Timeout occurred: FD Shutdown"}" @Marvin why i got this error, when trying to use spark session (databricks cluster). i am sure that I set up proxy correctly because the task before also use http request. i check that cluster is running.
m
✅ thought for 72.0 seconds
The error you're seeing is a gRPC connection issue where Spark Connect is unable to establish a connection to your Databricks cluster through the proxy. While your HTTP requests work, gRPC connections (which Spark Connect uses) might need additional configuration. Here's how to resolve this: 1. First, ensure you have all the necessary proxy environment variables set:
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bash
HTTP_PROXY=<http://your.proxy:port>
HTTPS_PROXY=<http://your.proxy:port>
GRPC_PROXY=<http://your.proxy:port>  # Important for gRPC connections
NO_PROXY=localhost,127.0.0.1
2. For Spark Connect specifically, you need to set additional environment variables:
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python
import os

os.environ['SPARK_REMOTE'] = f"<sc://your-databricks-instance.cloud.databricks.com:443/default>"
os.environ['DATABRICKS_TOKEN'] = 'your-token'
os.environ['DATABRICKS_CLUSTER_ID'] = 'your-cluster-id'
3. When creating your Spark session, make sure to include the proper configurations:
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python
from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .remote(f"<sc://your-databricks-instance.cloud.databricks.com:443/default>") \
    .config("spark.databricks.service.token", os.environ.get('DATABRICKS_TOKEN')) \
    .config("spark.driver.extraJavaOptions", "-Dhttps.proxyHost=your-proxy-host -Dhttps.proxyPort=your-proxy-port") \
    .config("spark.executor.extraJavaOptions", "-Dhttps.proxyHost=your-proxy-host -Dhttps.proxyPort=your-proxy-port") \
    .getOrCreate()
4. Verify your connection settings: - Ensure your Databricks cluster is actually running and accepting connections - Check that your proxy allows gRPC traffic (port 443) - Verify that your Databricks token has the necessary permissions - Make sure your cluster's network settings allow incoming connections 5. If you're running this in a Prefect flow, you can set these environment variables in your work pool configuration:
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python
@flow
def your_flow():
    # Set environment variables at the start of your flow if needed
    os.environ.update({
        'SPARK_REMOTE': "<sc://your-databricks-instance.cloud.databricks.com:443/default>",
        'GRPC_PROXY': "<http://your.proxy:port>",
        # other necessary variables
    })
    
    # Your spark session creation and operations
    spark = SparkSession.builder.remote(...).getOrCreate()
6. Common troubleshooting steps: - Try increasing the connection timeout:
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python
spark = SparkSession.builder \
    .config("spark.connect.timeout", "120s") \
    .remote(...) \
    .getOrCreate()
- Verify proxy connectivity:
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python
import requests
response = requests.get('<https://your-databricks-instance.cloud.databricks.com>')
print(response.status_code)
If these steps don't resolve the issue, you might need to: 1. Check your Databricks cluster logs for any connection rejection messages 2. Verify that your proxy administrator hasn't blocked gRPC traffic 3. Ensure all necessary Databricks endpoints are whitelisted in your proxy configuration For more detailed information about configuring Prefect with Databricks, you can refer to the Prefect-Databricks integration documentation.
w
@Marvin my code work okay (running spark command to databricks cluster), when i run process work pool using prefect worker start --pool "process-work-pool" . but i will get error i describe when i deamonized process work pool with ini [Unit] Description=Prefect Worker Service After=network.target [Service] Type=simple User=daservice Environment="PREFECT_API_URL=http://127.0.0.1:4200/api" WorkingDirectory=/home ExecStart=/home/daservice/projects/prefect-da/.venv/bin/prefect worker start -p 'process-work-pool' Restart=always RestartSec=3 [Install] WantedBy=multi-user.target
m
✅ thought for 12.3 seconds
I understand the issue better now - the proxy environment variables are not being passed through when running as a systemd service, even though they work when running the worker manually. Let's fix your systemd service configuration. You need to add all the proxy environment variables to your systemd service file. Here's the corrected version:
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ini
[Unit]
Description=Prefect Worker Service
After=network.target

[Service]
Type=simple
User=daservice
# Add your proxy settings
Environment="HTTP_PROXY=<http://your.proxy:port>"
Environment="HTTPS_PROXY=<http://your.proxy:port>"
Environment="GRPC_PROXY=<http://your.proxy:port>"
Environment="NO_PROXY=localhost,127.0.0.1"
Environment="PREFECT_API_URL=<http://127.0.0.1:4200/api>"
# If you have any Databricks-specific environment variables, add them here
Environment="DATABRICKS_HOST=your-databricks-host"
Environment="DATABRICKS_TOKEN=your-token"
Environment="DATABRICKS_CLUSTER_ID=your-cluster-id"

WorkingDirectory=/home/daservice/projects/prefect-da  # Changed to your project directory
ExecStart=/home/daservice/projects/prefect-da/.venv/bin/prefect worker start -p 'process-work-pool'
Restart=always
RestartSec=3

[Install]
WantedBy=multi-user.target
Key changes and notes: 1. Added proxy environment variables that were previously available in your shell environment 2. Changed the WorkingDirectory to your actual project directory (this is important for relative paths) 3. Added Databricks-specific environment variables if you're using them After making these changes: 1. Reload the systemd daemon and restart the service:
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bash
sudo systemctl daemon-reload
sudo systemctl restart prefect-worker.service
2. Check the status and logs:
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bash
sudo systemctl status prefect-worker.service
sudo journalctl -u prefect-worker.service -f
Additional troubleshooting tips: 1. Make sure the 
daservice
user has all necessary permissions 2. You can verify the environment variables are being set correctly by modifying your flow to print them:
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python
@flow
def debug_flow():
    import os
    print("Proxy settings:", {
        'HTTP_PROXY': os.getenv('HTTP_PROXY'),
        'HTTPS_PROXY': os.getenv('HTTPS_PROXY'),
        'GRPC_PROXY': os.getenv('GRPC_PROXY')
    })
3. If you're using any virtual environment dependencies, make sure they're all accessible to the systemd service Remember to replace the proxy URLs, Databricks host, and other placeholder values with your actual configuration values.
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