pyspark differences between two dataframes

Modern Markhor answered on March 15, 2025 Popularity 1/10 Helpfulness 1/10

answer pyspark differences between two dataframes

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pyspark differences between two dataframes

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# Apply the type mapping dynamically
for col_name, new_type in type_mapping.items():
    df = df.withColumn(col_name, F.col(col_name).cast(new_type))

# get conditions for all columns except id
conditions_ = [f.when(df_facts[c]!=df_old[c], f.lit(c)).otherwise("") for c in df_facts.columns]
conditions2_ = [f.when(df_facts[c]!=df_old[c], df_old[c]).otherwise("") for c in df_facts.columns]
conditions3_ = [f.when(df_facts[c]!=df_old[c], df_facts[c]).otherwise("") for c in df_facts.columns]

select_expr =[
                *[df_old[c] for c in df_old.columns ], 
                f.array_remove(f.array(*conditions_), "").alias("column_names"),
                f.array_remove(f.array(*conditions2_), "").alias("old_values"),
                f.array_remove(f.array(*conditions2_), "").alias("old_values")
]

df_joined = df_facts.join(df_old, (df_facts.pk_invoice_line_item == df_old.pk_invoice_line_item) 
                                    & (df_facts.invoice_header_id == df_old.invoice_header_id)
                                    & (df_facts.transaction_id == df_old.transaction_id)
                                    & (df_facts.invoice_line_item_description == df_old.invoice_line_item_description)
                                    , 'left').select(*select_expr)
display(df_joined.where((f.size(f.col('column_names')) > 0) & (f.col('column_names')[0] != 'value_net_amount_mst')))

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Source: Grepper

Tags: between pyspark python

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Contributed on Mar 20 2025

Modern Markhor

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git clone git@github.com:JLospinoso/ccc

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Source: ccc.codes

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Contributed on Mar 15 2025

Helpful Hoopoe

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pyspark differences between two dataframes

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