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chore(sql-lab): catch PyArrow deserialization error (#11201)
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@ -93,3 +93,7 @@ class QueryObjectValidationError(SupersetException):
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class DashboardImportException(SupersetException):
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pass
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class SerializationError(SupersetException):
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pass
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@ -72,6 +72,7 @@ from superset.databases.filters import DatabaseFilter
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from superset.exceptions import (
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CertificateException,
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DatabaseNotFound,
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SerializationError,
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SupersetException,
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SupersetSecurityException,
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SupersetTimeoutException,
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@ -1961,7 +1962,9 @@ class Superset(BaseSupersetView): # pylint: disable=too-many-public-methods
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return self.results_exec(key)
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@staticmethod
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def results_exec(key: str) -> FlaskResponse:
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def results_exec( # pylint: disable=too-many-return-statements
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key: str,
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) -> FlaskResponse:
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"""Serves a key off of the results backend
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It is possible to pass the `rows` query argument to limit the number
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@ -1995,9 +1998,15 @@ class Superset(BaseSupersetView): # pylint: disable=too-many-public-methods
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return json_errors_response([ex.error], status=403)
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payload = utils.zlib_decompress(blob, decode=not results_backend_use_msgpack)
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try:
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obj = _deserialize_results_payload(
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payload, query, cast(bool, results_backend_use_msgpack)
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)
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except SerializationError:
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return json_error_response(
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__("Data could not be deserialized. You may want to re-run the query."),
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status=404,
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)
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if "rows" in request.args:
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try:
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@ -33,7 +33,11 @@ import superset.models.core as models
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from superset import app, dataframe, db, is_feature_enabled, result_set
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from superset.connectors.connector_registry import ConnectorRegistry
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from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
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from superset.exceptions import SupersetException, SupersetSecurityException
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from superset.exceptions import (
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SerializationError,
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SupersetException,
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SupersetSecurityException,
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)
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from superset.legacy import update_time_range
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from superset.models.core import Database
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from superset.models.dashboard import Dashboard
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@ -521,7 +525,10 @@ def _deserialize_results_payload(
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ds_payload = msgpack.loads(payload, raw=False)
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with stats_timing("sqllab.query.results_backend_pa_deserialize", stats_logger):
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try:
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pa_table = pa.deserialize(ds_payload["data"])
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except pa.ArrowSerializationError:
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raise SerializationError("Unable to deserialize table")
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df = result_set.SupersetResultSet.convert_table_to_df(pa_table)
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ds_payload["data"] = dataframe.df_to_records(df) or []
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