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_sql = f"""
                SELECT {cust_id}, date(end_observation) as end_observation, value, token 
                FROM 
                    ( SELECT {cust_id}, end_observation,
                             {', '.join([f"CAST({x} AS FLOAT64) AS {x}" for x in _cols2process])}
                             FROM {table_id} )
                UNPIVOT(value FOR token IN ({', '.join(_cols2process)}))
                WHERE end_observation='{end_observation}' 
                """

        _df = (
            spark.read.format("bigquery")
            .option("maxParallelism", 666)
            .load(_sql)
            .withColumn(
                "token_sfx",
                F.concat(F.lit(table_api), F.lit("__"), F.col("token")),
            )
            .withColumn("source", F.lit(table_api))
            .select(
                "cust_id", "end_observation", "value", "token_sfx", "source"
            )
        )