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python: pyspark data quality checks example as a function/ module

Allie Ubisse answered on December 20, 2023 Popularity 1/10 Helpfulness 1/10

answer python: pyspark data quality checks example as a function/ module

python: pyspark data quality checks example as a function/ module

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# data_quality_checks.py
from pyspark.sql import SparkSession
from pyspark.sql.functions import col

def perform_data_quality_checks(input_df):
    """
    Perform basic data quality checks on a PySpark DataFrame.

    Args:
        input_df (pyspark.sql.DataFrame): Input DataFrame for data quality checks.

    Returns:
        pyspark.sql.DataFrame: DataFrame with additional columns indicating data quality test results.
    """
    # Initialize Spark session (if not already created)
    spark = SparkSession.builder.getOrCreate()

    # Create a copy of the input DataFrame to store data quality test results
    output_df = input_df

    # Check for NULL values in all columns
    for column in input_df.columns:
        output_df = output_df.withColumn(f"{column}_isNull", col(column).isNull())

    # Check for duplicate records
    output_df = output_df.withColumn("is_duplicate", col("count").over(Window.partitionBy(input_df.columns).orderBy("count")).cast("boolean"))

    # Check if the record count matches the expected count
    expected_count = input_df.count()
    output_df = output_df.withColumn("is_expected_count", col("count") == expected_count)

    return output_df

Popularity 1/10 Helpfulness 1/10 Language python

Source: chat.openai.com

Tags: data-quality module pyspark python

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Contributed on Dec 20 2023

Allie Ubisse

0 Answers Avg Quality 2/10

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