feat: improve performance with dynamic batch capacity
This commit is contained in:
sjdonado
@@ -2,9 +2,9 @@
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[](https://hub.docker.com/r/sjdonado/bit)
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[](https://hub.docker.com/r/sjdonado/bit)
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Lightweight URL shortener (API-only) with minimal resource requirements. Avg memory consumption under pressure is around **60MiB**, avg CPU load 60%.
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Lightweight URL shortener (API-only) with minimal resource requirements. Avg memory consumption **30MiB**, avg CPU load 20%.
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Highly performant: **6.6k req/sec**, latency 18.9ms (100k requests using 125 connections, [benchmark](docs/SETUP.md#benchmark)).
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Highly performant: **7.9k req/sec**, latency 15.8ms (100k requests using 125 connections, [benchmark](docs/SETUP.md#benchmark)).
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Self-hosted: [Dokku](docs/SETUP.md#dokku), [Docker Compose](docs/SETUP.md#docker-compose).
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@@ -18,7 +18,7 @@ It is feature-complete by design: simple and reliable without unnecessary bloat.
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- Multiple users are supported via API key authentication. Users can create, list and delete keys via the [CLI](docs/SETUP.md#cli).
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- Easy to extend, Ruby on Rails-inspired setup.
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## Minimum Requirements
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## Recommented requirements
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- 100MB disk space
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- 70MiB RAM
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- x86_64 or ARM64
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@@ -14,7 +14,6 @@ module App::Controllers
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@@processor_started = begin
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spawn do
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batch_size = 64
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batch = [] of NamedTuple(
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link_id: Int64,
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remote_address: String,
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@@ -22,21 +21,30 @@ module App::Controllers
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referer: String
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)
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batch_size = 32
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min_batch = 32
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max_batch = 512
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scaling_factor = 1.5
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loop do
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select
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when click_data = @@click_channel.receive
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batch << click_data
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# Collect clicks until we have a batch or a timeout
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if batch.size >= batch_size
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process_click_batch(batch)
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batch.clear
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# Increase batch size when reaching capacity
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batch_size = (batch_size * scaling_factor).to_i.clamp(min_batch, max_batch)
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end
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when timeout(0.5.seconds)
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# Process whatever we have after timeout
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when timeout(1.seconds)
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unless batch.empty?
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process_click_batch(batch)
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batch.clear
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batch_size = (batch_size / scaling_factor).to_i.clamp(min_batch, max_batch)
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else
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# Reset to default if idle
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batch_size = min_batch unless batch_size == min_batch
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end
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end
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end
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@@ -176,7 +176,6 @@ def analyze_resource_usage
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puts "Analyzing resource usage..."
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sleep 2.seconds
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# Read stats directly from file for more accurate results
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if File.exists?(STATS_FILE)
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lines = File.read_lines(STATS_FILE)
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# Skip header
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+25
-26
@@ -126,43 +126,42 @@ Waiting for the application to be ready...
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Seeding the database...
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Checking seed results...
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Fetching all created links from /api/links...
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Selected link for benchmarking: http://localhost:4000/slug4280
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Selected link for benchmarking: http://localhost:4000/slug2576
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Starting benchmark with Bombardier...
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Bombarding http://localhost:4000/slug4280 with 100000 request(s) using 125 connection(s)
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100000 / 100000 [==============================================================] 100.00% 6562/s 15s
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Bombarding http://localhost:4000/slug2576 with 100000 request(s) using 125 connection(s)
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100000 / 100000 [===================================================================================================================================================================] 100.00% 7795/s 12s
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Done!
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Statistics Avg Stdev Max
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Reqs/sec 6609.73 1508.34 13145.76
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Latency 18.92ms 2.34ms 74.58ms
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Reqs/sec 7900.70 7570.15 29263.59
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Latency 15.89ms 10.22ms 67.32ms
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Latency Distribution
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50% 18.83ms
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75% 20.19ms
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90% 21.80ms
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95% 23.10ms
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99% 26.54ms
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50% 4.82ms
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75% 9.24ms
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90% 51.61ms
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95% 52.74ms
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99% 55.07ms
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HTTP codes:
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1xx - 0, 2xx - 0, 3xx - 100000, 4xx - 0, 5xx - 0
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others - 0
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Throughput: 1.80MB/s
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Throughput: 2.14MB/s
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Benchmark completed successfully.
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Analyzing resource usage...
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Timestamp CPU(%) Memory(MiB)
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1742732843 0.02 44.71
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1742732845 0.02 44.71
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1742732847 85.34 69.55
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1742732849 83.5 69.93
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1742732851 84.26 69.97
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1742732853 83.64 70.01
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1742732855 84.23 70.04
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1742732857 86.41 69.17
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1742732859 85.77 69.2
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1742732861 59.67 68.55
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1742763202 0.01 44.83
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1742763204 0.01 44.78
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1742763206 91.53 68.23
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1742763208 92.03 68.17
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1742763210 91.0 68.09
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1742763212 92.73 68.38
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1742763214 92.17 67.66
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1742763216 91.1 67.69
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1742763218 2.93 67.04
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**** Resource Usage Statistics ****
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Measurements: 10
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Average CPU Usage: 65.29%
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Average Memory Usage: 64.58 MiB
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Peak CPU Usage: 86.41%
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Peak Memory Usage: 70.04 MiB
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Measurements: 9
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Average CPU Usage: 61.5%
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Average Memory Usage: 62.76 MiB
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Peak CPU Usage: 92.73%
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Peak Memory Usage: 68.38 MiB
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Cleanup completed. Resource usage data saved in resource_usage.txt
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```
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