Query throughput
We have done many performance optimizations between the 2.2.1 and 2.3.0 releases of WiredTiger. This page details a simple benchmark that measures the performance improvements.
| Version | Load time (seconds) | Query (million operations per second) |
|---|---|---|
| 2.2.1 | 7.85 | 1.75 million |
| 2.3.0 | 7.42 | 2.10 million |
That is a 20% improvement in a highly optimized code path in a single release. These performance optimizations should improve throughput for almost all in-memory workloads.
The benchmark tool used is wtperf included with the WiredTiger package. The configuration file used is:
conn_config="cache_size=5G"
table_config="internal_page_max=1MB,leaf_page_max=1MB"
icount=5000000
report_interval=10
run_time=200
populate_threads=1
threads=((count=8,reads=1))
value_sz=10
A summary of the workload:
- Small keys and values
- In cache workload
- Running 8 concurrent threads doing random point queries
Tested on an AWS h1.4xlarge instance type, which has 60GB RAM, 2x1024GB SSD drives (configured as RAID 0 with xfs), 16 vCPUs.