Home > Workload Solutions > Oracle > Guides > Implementation Guide—Oracle Database 19c Best Practices on PowerStore > HammerDB test database configuration
We used HammerDB to generate an OLTP workload that simulates enterprise applications. We generated a significant load on the Oracle infrastructure to determine the performance difference between baseline configuration and best practices configuration.
We began the test database environment configuration by creating a test database. We performed the dbca command as the Oracle user to create an Oracle database using the following disk groups:
We used the following main performance related database settings or database limit settings for this HammerDB test in the baseline configuration.
SGA_target | 64GB |
PGA_target | 10GB |
DB_BLOCK_SIZE | 8k |
Processes, sessions, transactions | 640 |
Sessions | 984 |
Transactions | 1082 |
Undo_management, | Auto |
Undo tablespace | UNDOTBS1 |
filesystem_io_options | SETALL |
disk_async_io | TRUE |
db_file_multiblock_read_count | 128 |
db_writer_process | 1 |
Redo log file size | 200 MB each |
Redo log file block size | 512 |
LOG_CHECKPOINT_INTERVAL | 0 |
LOG_CHECKPOINT_TIMEOUT | 1800 |
log_buffer | 115200 K |
Redo/temp files | coarse |
In addition to these database parameters, we maintained the ASM disk group parameter AU Size to the default value of 4 MB in the baseline configuration.
The Hammer DB workload configuration is shown in the following table:
Setting Name | Value |
Total transactions per user | 1,000,000 |
Number of warehouses | 5,000 |
Number of virtual users | 80 |
Minutes of ramp up time | 10 |
Minutes of test duration | 50 |
Use all warehouses | Yes |
User delay (ms) | 100 |
Repeat delay (ms) | 100 |
Iterations | 1 |
In reviewing the configuration parameters, the overall profile can be labeled as an entry-level database. An entry-level database configuration provides a foundation to build upon best practices. Over the course of validating best practices the database configuration will change to optimize performance. This approach of starting with a minimal configuration and adding best practices has the benefit of enabling customers to address database growth challenges using these validated recommendations.