v0.5.6 Stand-alone(RocksDB)

Note:
The current performance metrics are based on an earlier version. The latest version has significant improvements in both performance and functionality. We encourage you to refer to the most recent release featuring autonomous distributed storage and enhanced computational push down capabilities. Alternatively, you may wait for the community to update the data with these enhancements.

1 Test environment

Compressed machine information:

CPU	Memory	网卡	磁盘
48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz	128G	10000Mbps	750GB SSD,2.7T HDD

Information about the machine used to generate loads: configured the same as the machine that is being tested under load.
Testing tool: Apache JMeter 2.5.1

Note: The load-generating machine and the machine under test are located in the same local network.

2 Test description

2.1 Definition of terms (the unit of time is ms)

Samples: The total number of threads completed in the current scenario.
Average: The average response time.
Median: The statistical median of the response time.
90% Line: The response time below which 90% of all threads fall.
Min: The minimum response time.
Max: The maximum response time.
Error: The error rate.
Throughput: The number of requests processed per unit of time.
KB/sec: Throughput measured in terms of data transferred per second.

2.2 Underlying storage

RocksDB is used for backend storage, HugeGraph and RocksDB are both started on the same machine, and the configuration files related to the server remain as default except for the modification of the host and port.

3 Summary of performance results

The speed of inserting a single vertex and edge in HugeGraph is about 1w per second
The batch insertion speed of vertices and edges is much faster than the single insertion speed
The concurrency of querying vertices and edges by id can reach more than 13000, and the average delay of requests is less than 50ms

4 Test results and analysis

4.1 batch insertion

4.1.1 Upper limit stress testing

Test methods

The upper limit of stress testing is to continuously increase the concurrency and test whether the server can still provide services normally.

Stress Parameters

Duration: 5 minutes

Maximum insertion speed for vertices:

in conclusion:

With a concurrency of 2200, the throughput for vertices is 2026.8. This means that the system can process data at a rate of 405360 per second (2026.8 * 200).

Maximum insertion speed for edges

Conclusion:

With a concurrency of 900, the throughput for edges is 776.9. This means that the system can process data at a rate of 388450 per second (776.9 * 500).

4.2 Single insertion

4.2.1 Stress limit testing

Test Methods

Stress limit testing is a process of continuously increasing the concurrency level to test the upper limit of the server’s ability to provide normal service.

Stress parameters

Duration: 5 minutes.
Service exception indicator: Error rate greater than 0.00%.

Single vertex insertion

Conclusion:

With a concurrency of 11500, the throughput is 10730. This means that the system can handle a single concurrent insertion of vertices at a concurrency level of 11500.

Single edge insertion

Conclusion:

With a concurrency of 9000, the throughput is 8418. This means that the system can handle a single concurrent insertion of edges at a concurrency level of 9000.