A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non- overlapping five-minute interval. Events are recorded once per minute per device.
df has the following schema: device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT Code block:
df.withWatermark("event_time", "10 minutes")
.groupBy(
________,
"device_id"
)
.agg(
avg("temp").alias("avg_temp"),
avg("humidity").alias("avg_humidity")
)
.writeStream
.format("delta")
.saveAsTable("sensor_avg")
Which line of code correctly fills in the blank within the code block to complete this task?