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스파크 설치

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Dbcafe (토론 | 기여)님의 2023년 3월 23일 (목) 14:42 판
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PySpark 설치 (pip 이용)[편집]

sh

pip install pyspark

Set the necessary environment variables. PySpark needs to know the path to your Java installation.

For Linux or macOS: 

export JAVA_HOME=<path_to_java>
export SPARK_HOME=$(python -c "import site; print(site.getsitepackages()[0])")/pyspark
export PYSPARK_PYTHON=python3
export PYSPARK_DRIVER_PYTHON=python3

Replace <path_to_java> with the actual path to your Java installation. You can find it using the following command: 

/usr/libexec/java_home

For Windows:

powershell 

$env:JAVA_HOME = "<path_to_java>"
$env:SPARK_HOME = (python -c "import site; print(site.getsitepackages()[0])") + "\pyspark"
$env:PYSPARK_PYTHON = "python3"
$env:PYSPARK_DRIVER_PYTHON = "python3"

Replace <path_to_java> with the actual path to your Java installation.

Test your PySpark installation: Create a new Python script or open an interactive Python shell, and run the following code: 

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName("PySpark Test") \
    .getOrCreate()

data = [("Alice", 1), ("Bob", 2), ("Cathy", 3)]
columns = ["Name", "ID"]

df = spark.createDataFrame(data, columns)
df.show()

If the installation is successful, you will see the DataFrame displayed as output.

(Optional) Install additional packages: You may need additional packages for your PySpark projects, such as pandas, numpy, or matplotlib. Install them using pip: 

pip install pandas numpy matplotlib

With PySpark installed, you can now start working on your data processing and machine learning projects.

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