WebOct 31, 2024 · This function is intended to compare two spark DataFrames and output any differences. It is inspired from pandas testing module but for pyspark, and for use in unit tests. Additional parameters allow varying the strictness of the equality checks performed. Installation pip install pyspark-test Usage assert_pyspark_df_equal (left_df, actual_df)
I wrote a PySpark testing library called chispa that makes …
WebJun 19, 2024 · Here’s an example of how to create a SparkSession with the builder: from pyspark.sql import SparkSession. spark = (SparkSession.builder. .master("local") .appName("chispa") .getOrCreate()) getOrCreate will either create the SparkSession if one does not already exist or reuse an existing SparkSession. Let’s look at a code snippet … Webchispa. assert_df_equality ( expected_df, input_df. transform (with_full_name), ignore_nullable = True) Automatic code formatting. You should use Black to automatically format your code in a PEP 8 compliant manner. You should use automatic code formatting for both your projects and your notebooks. how do doctors use chemistry
Chispa - mrpowers.github.io
Webfrom pyspark. sql import SparkSession spark = ( SparkSession. builder . master ( "local" ) . appName ( "chispa" ) . getOrCreate ()) Create a DataFrame with a column that contains … ignore_column_order param for assert_approx_df_equality function … Add allow_nan_equality option to assert_approx_df_equality #29 opened … Write better code with AI Code review. Manage code changes Packages. Host and manage packages GitHub is where people build software. More than 94 million people use GitHub … GitHub is where people build software. More than 94 million people use GitHub … No suggested jump to results WebJul 5, 2024 · The second way is to use the Chispa library. We can use it by replacing the pandas.testing module with the assert_df_equality line. The method will directly compare two spark data frames. Unlike the previous one, we need to convert from the Pandas data frame to the Spark data frame. WebJun 21, 2024 · Here’s one way to perform a null safe equality comparison: df.withColumn( "num1_eq_num2", when(df.num1.isNull() & df.num2.isNull(), True) .when(df.num1.isNull() df.num2.isNull(), False) .otherwise(df.num1 == df.num2) ).show() +----+----+------------+ num1 num2 num1_eq_num2 +----+----+------------+ 1 null false 2 2 true how much is gastly 47/108 worth