Skip to content

fix(dbconnect-run): surface Databricks Connect import failures #2121

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
rugpanov wants to merge 2 commits into
base: main
Choose a base branch
from
Open

fix(dbconnect-run): surface Databricks Connect import failures #2121

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
6feb9d1
fix(dbconnect-run): surface Databricks Connect import failures
rugpanov Aug 14, 2026
2024d1b
fix(dbconnect-run): make the pyspark remediation conditional on the c…
rugpanov Aug 14, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 25 additions & 7 deletions packages/databricks-vscode/resources/python/dbconnect-bootstrap.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,17 +45,35 @@ def load_env_from_leaf(path: str) -> bool:
from databricks.sdk.runtime import dbutils # noqa: E402
db_globals['dbutils'] = dbutils

# "table", "sc", "sqlContext" are missing
# "table", "sc", "sqlContext" are missing.
#
# The import and the session build are handled separately on purpose. A failure to
# import Databricks Connect (or pyspark) means the Python environment itself is
# broken and the user's own script will hit the same error, so it is surfaced. The
# most common cause is a standalone "pyspark" package installed alongside
# databricks-connect: the two share the pyspark namespace and overwrite each other,
# and the resulting Java/protobuf error otherwise gives no hint at the cause. A
# failure to *build* the session (no configured compute, auth) is left quiet — many
# scripts create their own session and never touch the injected one.
try:
from pyspark.sql import functions as udf, SparkSession
from databricks.connect import DatabricksSession
spark: SparkSession = DatabricksSession.builder.getOrCreate()
sql = spark.sql
db_globals['spark'] = spark
db_globals['sql'] = sql
db_globals['udf'] = udf
except Exception as e:
logging.debug(f"Failed to create DatabricksSession: {e}")
logging.error(
"Failed to import Databricks Connect: %s. This usually means the Python "
"environment is misconfigured. A common cause is a standalone 'pyspark' "
"package installed alongside databricks-connect: they share the pyspark "
"package and overwrite each other, so if your project depends on a "
"standalone pyspark, remove it and re-run 'Set up Python environment'.", e)
else:
try:
spark: SparkSession = DatabricksSession.builder.getOrCreate()
sql = spark.sql
db_globals['spark'] = spark
db_globals['sql'] = sql
db_globals['udf'] = udf
except Exception as e:
logging.debug(f"Failed to create DatabricksSession: {e}")

# We do this to prevent importing widgets implementation prematurely
# The widget import should prompt users to use the implementation
Expand Down
Loading