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subtract() is row-based and requires exact row match
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If df has duplicate rows, subtract() doesn't guarantee it removes just one instance.
# Filter 20% of the data for the holdout group
df_holdout = df.sample(fraction=0.2, seed=42)
This code is functionally correct, but it's inefficient and overly complex for what it does: writing a single integer (record count) to a file.
def write_table_to_file(df, container, storage_account, out_name = None, delimiter = "|", audit_prefix = ".ok"):
ok_output_path = f"abfss://{container}@{storage_account}.dfs.core.windows.net/tmp_ok_output/"
This guide explains how to extract a .pem
file from a .p12
file using OpenSSL and troubleshoot common errors encountered during the process.
Run the following command to extract the .pem
file:
openssl pkcs12 -in /Users/dvuiw/Desktop/customer.p12 -nokeys -out /Users/dvuiw/Desktop/certicate.pem -nodes -password pass:123456789
window_spec = Window.partitionBy("rxa_claim_id", "ITEM_PRODUCT_CODE").orderBy(df_idi["EVENT_TIMESTAMP"].desc())
df_valid_claim = df_valid_claim.withColumn("row_number", F.row_number().over(window_spec))
df_valid_claim.display()
window_spec_2 = Window.partitionBy("rxa_claim_id", "ITEM_PRODUCT_CODE")
valid_claim = df_valid_claim.withColumn("row_number_count", F.count("row_number").over(window_spec_2))
df_valid_claim.display()
Excalidraw : An open source virtual hand-drawn style whiteboard. Collaborative and end-to-end encrypted.