merge statement in 2 data frame

Question

Hi ,

how to use merge statement in 2 dataframe

df1=spark.sql("" sellect cole1,col2 from table1""")

df2=spark.sql("" sellect cole1,col2 from table2""")

expected results

merge into table2 using tabl1 on table1.col1=table2.col1 when not matched then insert*

Answer 1

Thanks for posting your question in the Microsoft Q&A forum.

Here’s how you can approach it:

• Import necessary libraries and create DataFrames and then using DataFrame APIs such as join and union. here’s how you can insert rows from df1 into df2 when col1 values do not already exist in df2:

    df_to_insert = df1.join(df2, df1.col1 == df2.col1, 'left_anti')
    updated_df2 = df2.union(df_to_insert)
    
  

• Once you have the merged DataFrame, you can write it back to Azure Synapse Analytics

    updated_df2.write \
        .format("synapsesql") \
        .mode("overwrite") \  # Choose appropriate write mode
        .option("table", "table2") \
        .save()
    
  

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