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clj-fast

Library for playing around with low level Clojure code for performance reasons given some assumptions. Inspired by Naked Performance (with Clojure) – Tommi Reiman.

Some of the code is based on implementations in metosin's projects. Credit in code.

Purpose

This repo serves a dual purpose:

  • Providing faster implementations of Clojure's core functions as macros.
  • Reference guide on the performance characteristics of different ways of using Clojure's data structures.

What makes it possible?

Plenty of Clojure's core functions are implemented to be generic (good) and to accept a variable number of arguments (also very good). The problem is that we pay for this in performance. Wherever we iterate over a sequence of input arguments or dispatch on the class, we lose on performance, especially when iterating on arguments and calling next, more or rest repeatedly.

Plenty of these behaviors are just forms of flow-control, and like and and or, other forms of flow control can too be statically analyzed, under certain constraints, and replaced by faster code.

Latest Version

Clojars Project

Results

See results.md for experiments' detailed benchmark results.

Usage

Requirements

Add in your project.clj:

[bsless/clj-fast "0.0.10"]

WARNING: Due to a bug in leiningen, versions built prior to 0.0.9 will pull in extra dependencies. Make sure to upgrade!

Functions and Macros

Fast(er) Functions

(require '[clj-fast.core :as fast])
  • entry-at: used like find but doesn't dispatch and has inline definition. Works for IPersistentMap.
  • val-at: used like get but doesn't dispatch and has inline definition. Works for IPersistentMap.
  • fast-assoc: Used like assoc but doesn't take variable key-values, only one pair and has inline definition. Works on Associative.
  • fast-map-merge: Slightly faster version for merge, takes only 2 maps.
  • rmerge!: merges a map into a transient map.

Inline Macros

(require '[clj-fast.inline :as inline])

Like regular core functions but sequence arguments must be written explicitly for static analysis or defed in advance (i.e. resolve-able).

Examples:

(def ks [:a :b])

(inline/assoc m :a 1 :b 2)

(inline/dissoc m :a :b)

(inline/fast-assoc m :a 1 :b 2)

(inline/get-in m ks)

(inline/get-in m [:c :d])

(inline/get-some-in m [:c :d])

(inline/assoc-in m [:c :d] foo)

(inline/assoc-in m [:c :d] foo [:c :b] bar)

(inline/update-in m [:c :d] inc)

(inline/select-keys m [:a :b :c])

(inline/merge m1 m2 m3)

(def assoc* (inline/memoize-c 3 assoc))
Notes
  • Merge analysis unrolls inline maps as well.
  • Warning: additional arities of assoc-in will cause code reordering. Beware of side effects.
Additions
  • fast-assoc: inlines in the same manner of assoc but uses clj-fast.core/fast-assoc instead.
  • fast-map-merge: inlines in the same manner of merge but uses clj-fast.core/fast-map-merge instead (Metosin).
  • fast-select-keys: like select-keys, but faster and dirtier, adds nil entries to the results map.
  • get-some-in: Like get-in at the expense of working only on callables (objects implementing clojure.lang.IFn).
  • find-some-in: like get-some-in but returns a map-entry in the end, like find.
  • memoize* & memoize-c*: Alternative implementations for memoization using a nested Clojure hash map and a nested Java concurrent hash map respectively. Fall back to core/memoize for large arities. Due to the cost of hashing objects in Clojure, it's recommended to use memoize-c* for most use cases.

Bypass dynamic dispatch with type hints

The get and nth macros operate similarly to their respective functions with one notable difference: When provided with an appropriate type hint, they will dispatch to the underlying method at compile time instead of run time.

(def arr (long-array [1 2 3]))
(nth ^longs arr 0)
(def m (doto (java.util.HashMap.) (.put :a 1)))
(get ^Map m :a)

Collections

HashMap
(require '[clj-fast.collections.hash-map :as hm])
  • ->hashmap: wraps HashMap's constructor.
  • get: wraps method call for HashMap's get. Has inline definition.
  • put: wraps method call for HashMap's put. Has inline definition.
ConcurrentHashMap
(require '[clj-fast.collections.concurrent-map :as chm])
  • ->concurrent-hash-map: constructor.
  • concurrent-map?: instance check.
  • put!?: putIfAbsent.
  • get
  • get?: get if is a concurrent hash map.
  • get-in?: like clojure core's get-in but for nested concurrent hash maps.
  • put-in!: like clojure core's assoc-in but for nested concurrent hash maps.

Lenses

(require '[clj-fast.lens :as lens])

In typed functional programming, lenses are a generic way of getting and setting nested data structures (records).

In this context, the lens namespace implements the basic code structure underlying Clojure's get-in, some->, assoc-in and update-in. They can be used in macros to expand to real code provided an appropriate 1-depth get and/or put transformer, which takes arguments and returns an expression.

For example, the get-some lens is used to define inline/get-some-in:

(defmacro get-some-in
  [m ks]
  (lens/get-some (fn [m k] `(~m ~k)) m ks))

Similarly, for assoc-in:

(defmacro assoc-in
  [m ks v]
  (lens/put
   (fn [m k v] `(c/assoc ~m ~k ~v))
   (fn [m k] `(c/get ~m ~k))
   m
   (u/simple-seq ks)
   v))

So be careful, these are not functional programming lenses, but metaprogramming lenses used for code generation.

Rewriting Core Functions And Macros

The namespace clj-fast.clojure.core contains drop-in replacement functions and macros for Clojure's core.

It opportunistically replaces functions by their inlined implementations. It also includes binding macros (let, fn, loop, defn) which will use inlining versions of get and nth when possible. (i.e. when type-hinted).

Usage

(ns com.my.app
  (:refer-clojure
   :exclude
   [get nth assoc get-in merge assoc-in update-in select-keys memoize destructure let fn loop defn defn-])
  (:require
   [clojure.core :as c]
   [clj-fast.clojure.core :refer [get nth assoc get-in merge assoc-in update-in select-keys memoize destructure let fn loop defn defn-]]))

General Note Note On Performance And Profiling

Profiling and performance measurements on the JVM are not an exact science. The variety of contributing factors and their possible interactions are far from all being accounted for.

Still, one of the most significant factors is the JVM's JIT compiler.

It is absolutely essential where performance is concerned.

Some tools such as Leiningen suppress the JIT to enable faster start-up times. While this is desirable in a development environment, it must be properly configured for profiling or production tasks.

The JVM's configuration settings can be examined by evaluating:

(into [] (.getInputArguments (java.lang.management.ManagementFactory/getRuntimeMXBean)))

If you see TieredStopAtLevel=1 or any number below 4 you're essentially running without aggressive JIT on.

With Leiningen, make sure to either use a different profile or override the :jvm-opts to get the best performance possible and realistic profiling results.

Related Projects

Structural

Structural is a small library by joinr (Tom) which provides more efficient destructuring macros with type hints.

Stringer

Stringer is a library by Shantanu Kumar for fast string operations. Of interest are the capabilities it provides in faster string building and formatting, also by "unrolling" the building operations where statically possible.

License

Copyright © 2019-2020 [email protected]

Copyright © Rich Hickey for the implementation in clj-fast.clojure.core.

This program and the accompanying materials are made available under the terms of the Eclipse Public License 2.0 which is available at http://www.eclipse.org/legal/epl-2.0.

This Source Code may also be made available under the following Secondary Licenses when the conditions for such availability set forth in the Eclipse Public License, v. 2.0 are satisfied: GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version, with the GNU Classpath Exception which is available at https://www.gnu.org/software/classpath/license.html.

Credit

Credit to Metosin wherever noted in the code.

Rich Hickey for clojure.core ns.