Cannot resolve due to data type mismatch: incompatible types ("STRING" and ARRAY<STRING>

[oussValrho]

hey i have this error from a while : 
Cannot resolve "(needed_skill_id = needed_skill_id)" due to data type mismatch: the left and right operands of the binary operator have incompatible types ("STRING" and "ARRAY<STRING>"). SQLSTATE: 42K09;
and these are the lines responsible for that : 

 to_update = current_link_df.where(col("active") == True).join(dataframe, ["position_id", "needed_skill_id"], how="left_anti")

    (

        DeltaTable.forName(spark, table_name).alias("t")

            .merge(to_update.withColumn("end_date", current_date()).alias("s"), "s.position_id = t.position_id AND s.needed_skill_id = t.needed_skill_id")

Any idea ?

Thank you !!

[Kaniz]

Hi @oussValrho, The error message you’re encountering indicates a data type mismatch in your SQL query. Specifically, it states that the left and right operands of the binary operator have incompatible types: a STRING and an ARRAY<STRING>.

Let’s break down the issue:

1. The problematic expression is (needed_skill_id = needed_skill_id).
2. The error occurs because needed_skill_id on the left side is expected to be a STRING, but the right side (presumably from your data) is an ARRAY<STRING>.

To resolve this, you’ll need to ensure that both sides of the equality comparison have compatible data types.

Here are some steps you can take:

1. Check Data Types:

   • Inspect the data in your needed_skill_id column. Make sure it contains only single values (strings) rather than arrays.
   • Verify that the needed_skill_id column in your dataframe is also of type STRING.

2. Data Transformation:

   • If the needed_skill_id column in your dataframe is indeed an array, you might need to transform it to a single value (string) before performing the join.
   • Consider using functions like explode or getItem to extract individual elements from the array.

3. Debugging the Merge:

   • The merge operation you’ve shown involves joining two tables (current_link_df and a Delta table) based on position_id and needed_skill_id.
   • Double-check that the column names and data types match between the two tables.
   • Ensure that the join condition is correctly specified.

4. Review the Schema:

   • Examine the schema of both current_link_df and the Delta table. Confirm that the data types align.

Remember to thoroughly inspect your data and verify the data types to pinpoint the issue. If you encounter any specific issues during this process, feel free to provide additional context, and I’ll be happy to assist further! 😊