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Merge pull request #5476 from gyuho/latency_dodc 

Documentation: add average latency numbers
release-3.0
Gyu-Ho Lee 2016-05-27 15:47:26 -07:00
parent f7fbcf8209 79fac9ee6f
commit 0313484f17
1 changed files with 23 additions and 12 deletions
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35
Documentation/op-guide/performance.md
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@ -20,44 +20,55 @@ For some baseline performance numbers, we consider a three member etcd cluster w
- Ubuntu 15.10
- etcd v3 master branch (commit SHA d8f325d), Go 1.6.2
With this configuration, etcd can approximately write::
With this configuration, etcd can approximately write:
| Number of keys | Key size in bytes | Value size in bytes | Number of connections | Number of clients | Target etcd server | Average write QPS | Memory |
|----------------|-------------------|---------------------|-----------------------|-------------------|--------------------|-------------------|--------|
| 100,000 | 8 | 256 | 100 | 1000 | leader only | 25,000 | 35 MB |
| 100,000 | 8 | 256 | 100 | 1000 | all members | 33,000 | 35 MB |
| Number of keys | Key size in bytes | Value size in bytes | Number of connections | Number of clients | Target etcd server | Average write QPS | Average latency per request | Memory |
|----------------|-------------------|---------------------|-----------------------|-------------------|--------------------|-------------------|-----------------------------|--------|
| 10,000 | 8 | 256 | 1 | 1 | leader only | 525 | 2ms | 35 MB |
| 100,000 | 8 | 256 | 100 | 1000 | leader only | 25,000 | 30ms | 35 MB |
| 100,000 | 8 | 256 | 100 | 1000 | all members | 33,000 | 25ms | 35 MB |
Sample commands are:
```
# assuming IP_1 is leader, write requests to the leader
benchmark --endpoints={IP_1} --conns=100 --clients=1000 \
benchmark --endpoints={IP_1} --conns=1 --clients=1 \
put --key-size=8 --sequential-keys --total=10000 --val-size=256
benchmark --endpoints={IP_1} --conns=100 --clients=1000 \
put --key-size=8 --sequential-keys --total=100000 --val-size=256
# write to all members
benchmark --endpoints={IP_1},{IP_2},{IP_3} --conns=100 --clients=1000 \
put --key-size=8 --sequential-keys --total=10000 --val-size=256
put --key-size=8 --sequential-keys --total=100000 --val-size=256
```
Linearizable read requests go through a quorum of cluster members for consensus to fetch the most recent data. Serializable read requests are cheaper than linearizable reads since they are served by any single etcd member, instead of a quorum of members, in exchange for possibly serving stale data. etcd can read:
| Number of requests | Key size in bytes | Value size in bytes | Number of connections | Number of clients | Consistency | Average read QPS |
|--------------------|-------------------|---------------------|-----------------------|-------------------|-------------|------------------|
| 100,000 | 8 | 256 | 100 | 1000 | Linearizable | 43,000 |
| 100,000 | 8 | 256 | 100 | 1000 | Serializable | 93,000 |
| Number of requests | Key size in bytes | Value size in bytes | Number of connections | Number of clients | Consistency | Average latency per request | Average read QPS |
|--------------------|-------------------|---------------------|-----------------------|-------------------|-------------|-----------------------------|------------------|
| 10,000 | 8 | 256 | 1 | 1 | Linearizable | 2ms | 560 |
| 10,000 | 8 | 256 | 1 | 1 | Serializable | 0.4ms | 7,500 |
| 100,000 | 8 | 256 | 100 | 1000 | Linearizable | 15ms | 43,000 |
| 100,000 | 8 | 256 | 100 | 1000 | Serializable | 9ms | 93,000 |
Sample commands are:
```
# Linearizable read requests
benchmark --endpoints={IP_1},{IP_2},{IP_3} --conns=1 --clients=1 \
range YOUR_KEY --consistency=l --total=10000
benchmark --endpoints={IP_1},{IP_2},{IP_3} --conns=100 --clients=1000 \
range YOUR_KEY --consistency=l --total=100000
# Serializable read requests for each member and sum up the numbers
for endpoint in {IP_1} {IP_2} {IP_3}; do
benchmark --endpoints=$endpoint --conns=1 --clients=1 \
range YOUR_KEY --consistency=s --total=10000
done
for endpoint in {IP_1} {IP_2} {IP_3}; do
benchmark --endpoints=$endpoint --conns=100 --clients=1000 \
range YOUR_KEY --consistency=s --total=100000
done
```
We encourage running the benchmark test when setting up an etcd cluster for the first time in a new environment to ensure the cluster achieves adequate performance; cluster latency and throughput can be sensitive to minor environment differences.
We encourage running the benchmark test when setting up an etcd cluster for the first time in a new environment to ensure the cluster achieves adequate performance; cluster latency and throughput can be sensitive to minor environment differences.