Exam DP-300 topic 1 question 16 discussion

Azure Synapse is not part of DP-300

answer c

To ensure that tables created in DB1 are available automatically as external tables to the built-in serverless SQL pool in Azure Synapse Analytics, you should use format C. Parquet. Parquet is a columnar storage file format that is well-suited for big data processing frameworks like Apache Spark and is natively supported by Azure Synapse Analytics. When you create tables in DB1 using the Parquet format, the data can be directly accessed by the serverless SQL pool without requiring additional data movement or conversion. By using Parquet as the format, you enable seamless integration between the Apache Spark pool (Pool1) and the serverless SQL pool, allowing both to work with the same data without any extra configuration or manual steps. Option A (JSON), Option B (CSV), and Option D (ORC) are valid file formats, but for the given scenario where you want to automatically access data from DB1 in the serverless SQL pool, Parquet is the most appropriate choice due to its native support in Azure Synapse Analytics.

Parquet

Actually , both B/CSV and C/Parquet are correct, because for each Spark external table based on Parquet or CSV and located in Azure Storage, an external table is created in a serverless SQL pool database.

For each Spark external table based on Parquet or CSV and located in Azure Storage, an external table is created in a serverless SQL pool database. As such, you can shut down your Spark pools and still query Spark external tables from serverless SQL pool.

Again Please fix this....

Is it correct?