A data team's Structured Streaming job is configured to calculate running aggregates for item sales to update a downstream marketing dashboard. The marketing team has introduced a new promotion and wants to add a field tracking how often this promotion code is used per item. A junior data engineer proposes updating the query as shown below (changes in bold): Original query: ```python df.groupBy("item") .agg(count("item").alias("total_count"), mean("sale_price").alias("avg_price")) .writeStream .outputMode("complete") .option("checkpointLocation", "/item_agg/_checkpoint") .start("/item_agg") ``` Proposed query: ```python df.groupBy("item") .agg(count("item").alias("total_count"), mean("sale_price").alias("avg_price"), count("promo_code = 'NEW_MEMBER'").alias("new_member_promo")) .writeStream .outputMode("complete") .option("mergeSchema", "true") .option("checkpointLocation", "/item_agg/_checkpoint") .start("/item_agg") ``` What additional step is required to deploy the proposed query to production? | Databricks Certified Data Engineer - Professional Quiz - LeetQuiz