Passing arrays of parameter values for bulk insert operations, for example, with SQLPrepare/SQLExecute and SQLExecDirect can reduce the ODBC call load and network traffic. To use arrays of parameters, the application calls SQLSetStmtAttr with the following attribute arguments:
• SQL_ATTR_PARAMSET_SIZE sets the array size of the parameter.
• SQL_ATTR_PARAMS_PROCESSED_PTR assigns a variable filled by SQLExecute, which contains the number of rows that are actually inserted.
• SQL_ATTR_PARAM_STATUS_PTR points to an array in which status information for each row of parameter values is returned.
Note: With ODBC 3.x, calls to SQLSetStmtAttr with the SQL_ATTR_PARAMSET_SIZE, SQL_ATTR_PARAMS_PROCESSED_ARRAY, and SQL_ATTR_PARAM_STATUS_PTR arguments replace the ODBC 2.x call to SQLParamOptions.
Before executing the statement, the application sets the value of each data element in the bound array. When the statement is executed, the driver tries to process the entire array contents using one network round trip. For example, let us compare the following examples, Case 1 and Case 2.
Case 1: Executing Prepared Statement Multiple Times
rc = SQLPrepare (hstmt, "INSERT INTO DailyLedger (...)
VALUES (?,?,...)", SQL_NTS);
// bind parameters
...
do {
// read ledger values into bound parameter buffers
...
rc = SQLExecute (hstmt);
// insert row
} while ! (eof);
Case 2: Using Arrays of Parameters
SQLPrepare (hstmt, " INSERT INTO DailyLedger (...) VALUES
// Specify an array in which to return the status of
// each set of parameters.
SQLSetStmtAttr(hstmt, SQL_ATTR_PARAM_STATUS_PTR,
ParamStatusArray, SQL_IS_POINTER);
// pass 100 parameters per execute
// bind parameters
...
do {
// read up to 100 ledger values into
// bound parameter buffers
...
rc = SQLExecute (hstmt);
// insert a group of 100 rows
} while ! (eof);
In Case 1, if there are 100 rows to insert, 101 network round trips are required to the server, one to prepare the statement with SQLPrepare and 100 additional round-trips for each time SQLExecute is called.
In Case 2, the call load has been reduced from 100 SQLExecute calls to only 1 SQLExecute call. Furthermore, network traffic is reduced considerably.
