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Computing the hypotenuse of a right-angle triangle given the two sides using PySpark. (hypot)

   October 26, 2023
PySpark @ Freshers.in

This article provides an in-depth look into the hypot function, accompanied by practical examples. The hypot function in PySpark computes the hypotenuse of a right-angle triangle given the two sides. Specifically, for inputs a and b, it returns the square root of (a^2 + b^2).

Calculate the hypotenuse for given sides:

from pyspark.sql import SparkSession
from pyspark.sql.functions import hypot
spark = SparkSession.builder \
    .appName("PySpark hypot Function") \
    .getOrCreate()
data = [(3, 4), (5, 12), (8, 15)]
df = spark.createDataFrame(data, ["a", "b"])
df.withColumn("hypotenuse", hypot(df["a"], df["b"])).show()
Python

Output:

+---+---+----------+
|  a|  b|hypotenuse|
+---+---+----------+
|  3|  4|       5.0|
|  5| 12|      13.0|
|  8| 15|      17.0|
+---+---+----------+
Bash

Use case: Distance calculation

Imagine a scenario where you have a grid, and you need to compute the distance from the origin (0,0) to various points on this grid. The hypot function can easily compute these distances:

grid_data = [(2, 7), (10, 5), (6, 8)]
df_grid = spark.createDataFrame(grid_data, ["x", "y"])
# Calculating distance from origin
df_grid.withColumn("distance_from_origin", hypot(df_grid["x"], df_grid["y"])).show()
Python
Output
+---+---+--------------------+
|  x|  y|distance_from_origin|
+---+---+--------------------+
|  2|  7|   7.280109889280518|
| 10|  5|  11.180339887498949|
|  6|  8|                10.0|
+---+---+--------------------+
Bash

When to use hypot?

Geometry and trigonometry: Any application that deals with right-angle triangles or needs distance calculations can benefit from hypot.

Physics simulations: For scenarios involving vectors, force calculations, or other physics simulations, the hypot function can be useful.

Data visualizations: When plotting data or visualizing clusters, hypot can assist in distance calculations, which might be crucial for certain algorithms or representations.

Spark important urls to refer

  1. Spark Examples
  2. PySpark Blogs
  3. Bigdata Blogs
  4. Spark Interview Questions
  5. Official Page
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