Options
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
04-07-2024 02:12 AM
Hi @Retired_mod , thank you for your time!
I tried again. I used format("memory") and format("delta"), just in case, but the results are the same.
Error traceback using `dbfs:/tmp/checkpoints/experiment_2_2` for checkpoint using format("statestore"):
2024-04-07 09:11:50,672 1956 ERROR _handle_rpc_error GRPC Error received
Traceback (most recent call last):
File "/databricks/spark/python/pyspark/sql/connect/client/core.py", line 1339, in _analyze
resp = self._stub.AnalyzePlan(req, metadata=self._builder.metadata())
File "/databricks/python/lib/python3.10/site-packages/grpc/_channel.py", line 946, in __call__
return _end_unary_response_blocking(state, call, False, None)
File "/databricks/python/lib/python3.10/site-packages/grpc/_channel.py", line 849, in _end_unary_response_blocking
raise _InactiveRpcError(state)
grpc._channel._InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
status = StatusCode.INTERNAL
details = "[STDS_FAILED_TO_READ_STATE_SCHEMA] Failed to read the state schema. Either the file does not exist, or the file is corrupted. options: StateSourceOptions(checkpointLocation=dbfs:/tmp/experiment_2_2, batchId=9, operatorId=0, storeName=default, joinSide=none).
Rerun the streaming query to construct the state schema, and report to the corresponding communities or vendors if the error persists. SQLSTATE: 42K03"
debug_error_string = "UNKNOWN:Error received from peer unix:/databricks/sparkconnect/grpc.sock {grpc_message:"[STDS_FAILED_TO_READ_STATE_SCHEMA] Failed to read the state schema. Either the file does not exist, or the file is corrupted. options: StateSourceOptions(checkpointLocation=dbfs:/tmp/experiment_2_2, batchId=9, operatorId=0, storeName=default, joinSide=none).\nRerun the streaming query to construct the state schema, and report to the corresponding communities or vendors if the error persists. SQLSTATE: 42K03", grpc_status:13, created_time:"2024-04-07T09:11:50.671796067+00:00"}"
>Error traceback using a azure storage account path for checkpoint using format("statestore"):
2024-04-07 09:06:55,381 1956 ERROR _handle_rpc_error GRPC Error received
Traceback (most recent call last):
File "/databricks/spark/python/pyspark/sql/connect/client/core.py", line 1339, in _analyze
resp = self._stub.AnalyzePlan(req, metadata=self._builder.metadata())
File "/databricks/python/lib/python3.10/site-packages/grpc/_channel.py", line 946, in __call__
return _end_unary_response_blocking(state, call, False, None)
File "/databricks/python/lib/python3.10/site-packages/grpc/_channel.py", line 849, in _end_unary_response_blocking
raise _InactiveRpcError(state)
grpc._channel._InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
status = StatusCode.INTERNAL
details = "[STDS_FAILED_TO_READ_STATE_SCHEMA] Failed to read the state schema. Either the file does not exist, or the file is corrupted. options: StateSourceOptions(checkpointLocation=abfss://unitycatalog@mastercatalogdev.dfs.core.windows.net/tutorials/checkpoints/experiment_2_2, batchId=9, operatorId=0, storeName=default, joinSide=none).
Rerun the streaming query to construct the state schema, and report to the corresponding communities or vendors if the error persists. SQLSTATE: 42K03"
debug_error_string = "UNKNOWN:Error received from peer unix:/databricks/sparkconnect/grpc.sock {grpc_message:"[STDS_FAILED_TO_READ_STATE_SCHEMA] Failed to read the state schema. Either the file does not exist, or the file is corrupted. options: StateSourceOptions(checkpointLocation=abfss://unitycatalog@mastercatalogdev.dfs.core.windows.net/tutorials/checkpoints/experiment_2_2, batchId=9, operatorId=0, storeName=default, joinSide=none).\nRerun the streaming query to construct the state schema, and report to the corresponding communities or vendors if the error persists. SQLSTATE: 42K03", grpc_status:13, created_time:"2024-04-07T09:06:55.381219715+00:00"}"
>If you need more details about the code, stream, or storage accounts just tell me.
Thank you very much!