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Source code for the framework benchmarking project

Home Page: http://www.techempower.com/benchmarks/

License: Other

Ruby 4.41% Shell 10.84% Makefile 0.16% C++ 3.28% CMake 0.30% Nginx 5.52% QMake 0.11% HTML 7.08% C 7.22% C# 11.40% PowerShell 1.72% Python 13.45% ASP 0.04% CSS 8.78% JavaScript 19.97% Clojure 2.73% Crystal 0.26% D 0.45% Dart 1.73% Elixir 0.55%

frameworkbenchmarks's Introduction

Http4s

Http4s is a minimal, idiomatic Scala interface for HTTP services. Http4s is Scala's answer to Ruby's Rack, Python's WSGI, Haskell's WAI, and Java's Servlets.

val http = HttpRoutes.of {
  case GET -> Root / "hello" =>
    Ok("Hello, better world.")
}

Learn more at http4s.org.

If you run into any difficulties please enable partial unification in your build.sbt (not needed for Scala 2.13 and beyond, because Scala 2.13.0+ has partial unification switched on by default)

scalacOptions ++= Seq("-Ypartial-unification")

Requirements

Running the blaze backend requires a modern, supported version of the JVM to build and run, as it relies on server APIs unavailable before JDK8u252. Any JDK newer than JDK8u252, including 9+ is supported.

Code of Conduct

http4s is proud to be a Typelevel project. We are committed to providing a friendly, safe and welcoming environment for all, and ask that the community adhere to the Scala Code of Conduct.

License

This software is licensed under the Apache 2 license, quoted below.

Copyright 2013-2021 http4s [https://http4s.org]

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

[http://www.apache.org/licenses/LICENSE-2.0]

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Acknowledgments

Special thanks to YourKit for supporting this project's ongoing performance tuning efforts with licenses to their excellent product.

frameworkbenchmarks's People

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frameworkbenchmarks's Issues

Use ScalaTags

While We Will Need to Run Benchmarks on Both, Scalatags states that it has performance improvements over Twirl.

We should put these to the test and see if it improves rendering time at all. This is primarily for the fortunes test. We have the database configuration already being investigated, this is looking into the server-side HTML template component

Fortunes

Requirements

In this test, the framework's ORM is used to fetch all rows from a database table containing an unknown number of Unix fortune cookie messages (the table has 12 rows, but the code cannot have foreknowledge of the table's size). An additional fortune cookie message is inserted into the list at runtime and then the list is sorted by the message text. Finally, the list is delivered to the client using a server-side HTML template. The message text must be considered untrusted and properly escaped and the UTF-8 fortune messages must be rendered properly.

Whitespace is optional and may comply with the framework's best practices.

Our Results

8	16	32	64	128	256
9,211	17,371	35,716	52,744	55,188	55,674

Fortunes responses per second

Database Performance Improvements

On the recent run we had some rather odd performance on our database queries.

We run a HikariCP pool of 256, other run much smaller pools. Recommendation I found from HikariCP was

connections = ((core_count * 2) + effective_spindle_count)

Data Updates

Requirements Summary

This test exercises database writes. Each request is processed by fetching multiple rows from a simple database table, converting the rows to in-memory objects, modifying one attribute of each object in memory, updating each associated row in the database individually, and then serializing the list of objects as a JSON response. The test is run multiple times: testing 1, 5, 10, 15, and 20 updates per request. Note that the number of statements per request is twice the number of updates since each update is paired with one query to fetch the object. All tests are run at 256 concurrency

Our Results

1	5	10	15	20
40,261	12,733	4,525	670	137

This drastic scale-back with increasing updates is unique to us.

I will comment as I find more in the other performance categories.

This is the section in question

Paging @tpolecat

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