Benchmark: Multiple Attributes Performance IV

HTML Preparation code:

<script src="https://d3js.org/d3.v5.min.js"></script>

Script Preparation code:

const data = d3.range(100).map(() => ({
  x: Math.random() * 300,
  y: Math.random() * 150
}));

const svg = d3.select("body")
  .append("svg");
  
const circles = svg.selectAll("circle")
	.data(data)
  .enter()
  .append("circle")
  .attr("cx", d=>d.x)
  .attr("cy", d=>d.y)
  .attr("r", 2)
  .style("fill", "teal");

Tests:

Default
const data = d3.range(100).map(() => ({ x: Math.random() * 300, y: Math.random() * 150 })); const svg = d3.select("svg"); const circles = svg.selectAll("circle") .data(data) .attr("cx", d=>d.x) .attr("cy", d=>d.y) .attr("r", 2) .style("fill", "teal");
each with setAttribute
const data = d3.range(100).map(() => ({ x: Math.random() * 300, y: Math.random() * 150 })); const svg = d3.select("svg"); const circles = svg.selectAll("circle") .data(data) .each((d, i, n) => { n[i].setAttribute("cx", d.x); n[i].setAttribute("cy", d.y); n[i].setAttribute("r", 2); }) .style("fill", "teal")
setAttribute with loop
const data = d3.range(100).map(() => ({ cx: Math.random() * 300, cy: Math.random() * 150, r: 2 })); const svg = d3.select("svg"); const circles = svg.selectAll("circle") .data(data) .each((d, i, n) => { for(let key in d){ n[i].setAttribute(key, d[key]) } }) .style("fill", "teal")
Detached
const data = d3.range(100).map(() => ({ cx: Math.random() * 300, cy: Math.random() * 150, r: 2 })); const svg = d3.select("svg").remove(); const circles = svg.selectAll("circle") .data(data) .attr("cx", d=>d.cx) .attr("cy", d=>d.cy) .attr("r", 2) .style("fill", "teal"); d3.select("body") .append(() => svg.node())

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Default
each with setAttribute
setAttribute with loop
Detached

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):

LLMs can make mistakes. Check important info.

Let's break down what is being tested in this benchmark and the different approaches being compared.

**Benchmark Overview**

The benchmark measures the performance of D3.js, a popular JavaScript library for producing dynamic, interactive data visualizations. The test case generates 100 random circles with x and y coordinates, and then appends them to an SVG element using D3.js.

**Options Compared**

Four different approaches are being compared:

1. **Default**: This is the original D3.js code that creates the circles.
2. **each with setAttribute**: In this version, the `setAttribute` method is called on each data object in the `data` array, which allows for more flexibility but may be slower due to the overhead of attribute setting.
3. **setAttribute with loop**: This approach uses a loop to iterate over the properties of each data object and sets the attributes using `setAttribute`. This can be faster than calling `setAttribute` on each individual property.
4. **Detached**: In this version, the SVG element is created separately from the D3.js code, which may lead to slower performance due to the extra overhead of creating a separate DOM node.

**Pros and Cons**

* **Default**: Pros: Simple and straightforward implementation, easy to read and maintain. Cons: May have performance issues due to the repeated use of `setAttribute`.
* **each with setAttribute**: Pros: More flexible than calling `setAttribute` on each individual property, but may be slower due to attribute setting overhead.
* **setAttribute with loop**: Pros: Faster than calling `setAttribute` on each individual property, but requires more code and can be harder to read. Cons: May have performance issues if not optimized correctly.
* **Detached**: Pros: None apparent from the benchmark data, but creating a separate SVG element may lead to slower performance.

**Library Used**

The D3.js library is used in all four test cases. D3.js provides a powerful and flexible way to manipulate the DOM and create interactive data visualizations.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntaxes being tested in this benchmark, as it only focuses on comparing different implementation approaches using standard JavaScript.

**Alternatives**

If you're looking for alternative libraries or frameworks for creating data visualizations, some popular options include:

* Chart.js
* Highcharts
* Plotly
* React Vis

Keep in mind that each library has its own strengths and weaknesses, and the choice of library will depend on your specific use case and requirements.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36

Browser/OS: Chrome 93 on Linux

View result in a separate tab

Test name	Executions per second
Default	1541.7 Ops/sec
each with setAttribute	1583.6 Ops/sec
setAttribute with loop	1605.0 Ops/sec
Detached	1796.9 Ops/sec

Related benchmarks:

Multiple Attributes Performance IV (version: 0)

Comparing performance of: Default vs each with setAttribute vs setAttribute with loop vs Detached

Created: 4 years ago by: Guest

Jump to the latest result

Default

each with setAttribute

setAttribute with loop

Detached

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):