How to process all available data in one micro-batch using availableNow trigger

Question

Hi Azure community,

Based on documentation, in Databricks Runtime 11.3 LTS and above, the Trigger.Once setting is deprecated. Databricks recommends you use Trigger.AvailableNow for all incremental batch processing workloads.

In our case, we are running our jobs in batch fashion, the source is a streaming table, and we want to process all available data in one micro-batch each time. Since Trigger.Once is deprecated, if we switch to AvailableNow, we are concerned AvailableNow cannot guanrantee one micro-batch. How to figure this out?

Thanks.

Answer 1

@Quan Sun

It looks like you're trying to find a way to process all available data in one micro-batch using the AvailableNow trigger in Azure Databricks, especially since Trigger.Once is deprecated now.

You're correct that switching to AvailableNow can lead to some uncertainty in terms of batch processing, especially since it doesn't inherently guarantee delivering all available data in a single micro-batch. However, using AvailableNow is designed to consume all data available at that moment, which should ideally cover your requirement to process all available records.

Here’s what you can try to ensure you're processing everything in one go:

Use Trigger.AvailableNow: This trigger is meant for incremental batch workloads, and it will process all the available data in one operation. Here's an example in Python:

(df.writeStream
  .option("checkpointLocation", "<checkpoint-path>")
  .trigger(availableNow=True)
  .toTable("table_name")
)

Check Your Compute Capacity: Ensure you have adequate compute resources allocated to handle the data coming in. If you find data is spilling over into multiple micro-batches, it might be time to scale up your resources.

Review Data Arrival Patterns: Keep an eye on how data is arriving in your source. If data is constantly streaming in while you process, it might affect how much data you can handle in one go.

Use ProcessAllAvailable Method: If you’re testing, consider using the ProcessAllAvailable method which will keep processing until all data has been consumed from the source. Just remember this method is mainly intended for testing as it can block indefinitely if data continuously arrives.

Experiment with Batch Size Configuration: While AvailableNow processes all available records, you can configure batch size options (like maxBytesPerTrigger) to help manage and optimize how data is handled.

could you please clarify:

What specific data source are you working with?

• Are you experiencing any issues with data being missed in the processing?
• How much data do you typically handle in a single batch?