What Factors Affect the Throughput Rates?

The following factors directly or indirectly affect the throughput rate of Oracle Data Loader On Demand:

• Type of object (record type). When a record in Oracle CRM On Demand is processed, many records might have to be created or updated. Depending on the complexity of the record type, the number of underlying database records might differ substantially. As a result, the throughput rates differ. The difference is based on the record type that is selected.

• Type of operation (Insert, Update, or Upsert). Throughput rates vary by operation. Update operations are usually faster than Insert operations, because Insert operations might have to write many records and update indexes. Upsert operations are a combination of Insert operations and Update operations and as a result you must include both factors in your estimate.

• Type of fields (picklist, date, description). Some fields require more processing time for validation than others. Picklists, description fields, and dates might process more slowly than Boolean and text fields.

• The number of fields mapped. The more fields you map, the slower the processing of the records. For best results, remove the unnecessary fields.

• Data quality. The more errors in the data file, the more data validation must occur, and more log messages must be written to the log file.

• Log Level. The higher the level of the log file, the more processing time is required, which slows the throughput rate.

• Submission time. Data loads performed during peak hours when other users are also using the server’s resources are slower than loads submitted during off-peak hours.

• Associations. When a record is associated with other records, additional processing and validation might be required.

• Background processes. Many background processes are not visible and might affect the throughput rate. These background processes include: log file generation, email notification, and other processes.