- 1 year ago
Painfully slow insertion times into Azure SQL database from Python script via ODBC
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If you're experiencing painfully slow insertion times into an Azure SQL database from a Python script via ODBC, there are a few things you can try to improve the performance:
- Use a parameterized query: Instead of building the SQL query as a string with values inserted directly into the query, use a parameterized query. This can significantly reduce the amount of time the database takes to parse and compile the query. Here's an example of how to use a parameterized query with pyodbc:
scsscursor.execute("INSERT INTO mytable (column1, column2) VALUES (?, ?)", value1, value2)
In this example, the values value1
and value2
are inserted into the query as parameters rather than directly in the query string.
- Use the
executemany
method: If you need to insert multiple rows into the database, use theexecutemany
method instead of executing each insertion query individually. This can reduce the overhead of repeatedly preparing and executing queries. Here's an example of how to useexecutemany
with pyodbc:
scssvalues = [('value1', 'value2'), ('value3', 'value4')]
cursor.executemany("INSERT INTO mytable (column1, column2) VALUES (?, ?)", values)
In this example, the values are specified as a list of tuples, and the executemany
method inserts them all into the database at once.
- Use the correct
autocommit
mode: Ensure that the connection is set to the correctautocommit
mode. If theautocommit
mode is disabled, each insertion will require an additional commit operation, which can slow down the performance. Here's an example of how to enableautocommit
mode with pyodbc:
graphqlconn.autocommit = True
In this example, conn
is the connection object.
- Optimize the table schema and indexes: If the table has a large number of columns or indexes, it may be slowing down the insertion performance. Consider optimizing the table schema and indexes to reduce the overhead of inserting rows.
By following these steps, you can improve the insertion performance into an Azure SQL database from a Python script via ODBC.