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MongoDB $asinh Operator

Updated on Nov 24, 2024
By Mari Selvan
👁️ 18 - Views
⏳ 4 mins
💬 1 Comment
MongoDB $asinh Operator

Photo Credit to CodeToFun

🙋 Introduction

In MongoDB's aggregation framework, the $asinh operator serves as a powerful tool for computing the inverse hyperbolic sine of numerical values. This operator enables users to perform complex mathematical computations within aggregation pipelines, facilitating advanced data analysis and manipulation.

Let's delve into the details of how the $asinh operator can be effectively utilized within MongoDB's aggregation framework.

💡 Syntax

The syntax for the $asinh method is straightforward:

syntax.js
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{ $asinh: <expression> }
  • $asinh: This operator signifies that the subsequent operation will compute the inverse hyperbolic sine.
  • <expression>: This represents the numerical expression for which the inverse hyperbolic sine will be calculated. It could be a field reference, a mathematical expression, or a value.

📝 Example

⌨️ Input

Consider a collection named data containing documents with fields value representing numerical values. Here are sample documents from the data collection:

Input
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[
  { "_id": ObjectId("609c26812e9274a86871bc6a"), "value": 1 },
  { "_id": ObjectId("609c26812e9274a86871bc6b"), "value": 2 },
  { "_id": ObjectId("609c26812e9274a86871bc6c"), "value": 3 }
]

🔄 Aggregation

Suppose we want to compute the inverse hyperbolic sine for each value in the value field. Here's how you can achieve this using the $asinh operator:

example.js
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db.data.aggregate([
  {
    $project: {
      asinhValue: { $asinh: "$value" }
    }
  }
])

🧩 Explanation

  • $project: This stage reshapes documents, including or excluding fields or adding new computed fields.
  • $asinh: Computes the inverse hyperbolic sine of the specified value.

When discussing how the above aggregation works:

  • For the document with _id ObjectId("609c26812e9274a86871bc6a") and "value" 1: asinh(1) = 0.881373587
  • For the document with _id ObjectId("609c26812e9274a86871bc6b") and "value" 2: asinh(2) = 1.443635475
  • For the document with _id ObjectId("609c26812e9274a86871bc6c") and "value" 3: asinh(3) = 1.81844646

💻 Output

Now, let's take a look at the output generated by the aggregation pipeline:

Output
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{ "_id": ObjectId("609c26812e9274a86871bc6a"), "asinhValue": 0.881373587019543 }
{ "_id": ObjectId("609c26812e9274a86871bc6b"), "asinhValue": 1.443635475 }
{ "_id": ObjectId("609c26812e9274a86871bc6c"), "asinhValue": 1.81844645923207 }

📚 Use Cases

  1. Data Transformation:

    The $asinh operator is useful for transforming numerical values according to the inverse hyperbolic sine function, enabling users to preprocess data for further analysis.

  2. Signal Processing:

    In signal processing applications, inverse hyperbolic sine transformations can be utilized to preprocess sensor data or signals before subsequent analysis or visualization.

  3. Statistical Analysis:

    In statistical analyses, inverse hyperbolic sine transformations may be employed to normalize or stabilize skewed data distributions.

🎉 Conclusion

The $asinh operator in MongoDB's aggregation framework provides a powerful means for computing the inverse hyperbolic sine of numerical values, enabling users to perform advanced mathematical computations within aggregation pipelines. Whether you're transforming data, processing signals, or conducting statistical analyses, mastering the usage of $asinh empowers you to efficiently manipulate numerical data and derive valuable insights from your datasets.

With its intuitive syntax and diverse applications, the $asinh operator proves to be a valuable asset for handling numerical data effectively within MongoDB. Incorporate it into your aggregation pipelines to unlock new dimensions of data analysis and gain deeper insights into your datasets.

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Author

author
👋 Hey, I'm Mari Selvan

For over eight years, I worked as a full-stack web developer. Now, I have chosen my profession as a full-time blogger at codetofun.com.

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