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

JSON data is a text-based format that represents data as a collection of name-value pairs. By default, when Auto Loader infers the schema of JSON data, it treats all columns as strings. This is because JSON data can have varying data types for the same column across different files or records, and Auto Loader does not attempt to reconcile these differences. For example, a column named “age” may have integer values in some files, but string values in others. To avoid data loss or errors, Auto Loader infers the column as a string type. However, Auto Loader also provides an option to infer more precise column types based on the sample data. This option is called cloudFiles.inferColumnTypes and it can be set to true or false. When set to true, Auto Loader tries to infer the exact data types of the columns, such as integers, floats, booleans, or nested structures. When set to false, Auto Loader infers all columns as strings. The default value of this option is false. References: Configure schema inference and evolution in Auto Loader, Schema inference with auto loader (non-DLT and DLT), Using and Abusing Auto Loader’s Inferred Schema, Explicit path to data or a defined schema required for Auto loader.

This approach would allow the data engineering team to use the existing SQL program and add some logic to control the execution of the final query based on the day of the week. They could use the datetime module in Python to get the current date and check if it is a Sunday. If so, they could run the final query, otherwise they could skip it. This way, they could schedule the program to run every day without changing the data model or the source table. References: PySpark SQL Module, Python datetime Module, Databricks Jobs