Databricks Databricks-Certified-Professional-Data-Engineer Exam With Confidence Using Practice Dumps

The correct answer is A. withWatermark(“event_time”, “10 minutes”). This is because the question asks for incremental state information to be maintained for 10 minutes for late-arriving data. The withWatermark method is used to define the watermark for late data. The watermark is a timestamp column and a threshold that tells the system how long to wait for late data. In this case, the watermark is set to 10 minutes. The other options are incorrect because they are not valid methods or syntax for watermarking in Structured Streaming. References:

Watermarking:

Windowed aggregations:

The code is using %sh to execute shell code on the driver node. This means that the code is not taking advantage of the worker nodes or Databricks optimized Spark. This is why the code is taking longer to execute. A better approach would be to use Databricks libraries and APIs to read and write data from Git and DBFS, and to leverage the parallelism and performance of Spark. For example, you can use the Databricks Connect feature to run your Python code on a remote Databricks cluster, or you can use the Spark Git Connector to read data from Git repositories as Spark DataFrames.

When viewing a Databricks Python notebook in a text editor, the first line indicates the format and source type of the notebook. The correct option is % Databricks notebook source, which is a magic command that specifies the start of a Databricks notebook source file.