#Login to parallels access mac#
#Login to parallels access windows#

It will reduce the time for calculation step to get completed which will reduce the execution time of initial load of table from source to target central finance S/ 4HANA system through SLT.Ī) Table to be loaded from Source System is Transparent or Pool Table.ī) Record count in source table to be loaded is more than 50,000 based on LTRS filter values. Hence, we should execute access plan calculation jobs in parallel to bring records from source table to SLT. Single Access Plan Calculation job takes high amount of time depending upon the volume of records extracted from source table. By default, a single access plan calculation job copies the data from the original table to the queue in the source system. While starting the initial load of these tables, relevant data is extracted and temporarily stored in a compressed format in a queue in source system. AUFK and COBK they have huge amount of source data and it takes time to bring those data from source system to SLT system during calculation phase. If we consider central finance table i.e. Access Plan Calculation is the major activity during initial load of tables from source system to target Central Finance S/4 system via SLT. This answer might help with that.The Purpose of this document is to detail the set of activities which must be done to achieve parallelization of Access Plan Calculation Jobs.

Then check that you can access the SQL Server's port (the default is 1433), using nc -v YOUR_VM_IP_ADDRESS 1433Įnsure that you can connect using sqlcmd (note that Windows authentication won't work when connecting from the macOS machine, you have to use login/password): sqlcmd -S YOUR_VM_IP_ADDRESS -U username -P passwordĪfter the above tests succeed, you have a chance of coming up with the correct connection string and establishing the SQLAlchemy connection. Once you ensure the guest VM uses 'Shared networking' and find its public IP address (referred to as YOUR_VM_IP_ADDRESS from now on), check that you can ping it with ping YOUR_VM_IP_ADDRESS I'm guessing that while you try to use SERVER=local, you don't actually have local mapped to the guest VM.

Access Parallels Windows localhost from Mac might be helpful with that. I assume you're trying to connect to MS SQL Server, though your question has contradictory information - parts of it refer to MSSQL, while other parts mention MySQL.įirst you need to establish network connectivity with the guest. I've turned off the firewall from windows, but still nothing.Ĭonnection = (host='10.211.55.3',Īnd now I find myself with the following error: ProgrammingError: 1045 (28000): Access denied for user (using password: NO) I have also tried the following in terms of adjusting the connection string: SERVER=10.211.55.3 OperationalError: (pyodbc.OperationalError) ('HYT00', ' Login timeout expired (0) (SQLDriverConnect)') New_race_data = pd.read_sql_query(sql_get_data, db)

Params = 'DRIVER= ' 'SERVER=local ' 'DATABASE=Totepro 'ĭb = create_engine('mssql+pyodbc:///?odbc_connect=%s' % params) I've tried the following code: import pyodbc I'm writing a python script on Jupyter notebook on my Mac OS, and I'm trying to connect to a local DB that is located on my Parallels Windows operating system that is running from my external hard drive.

#Login to parallels access windows#

#Login to parallels access mac#