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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)|
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.