Which solution would you implement for a large company requiring near real-time processing of hundreds of pipelines that perform parallel updates on multiple tables handling extremely high-volume, high-velocity data?

Exam-Like

Use Databricks High Concurrency clusters, which leverage optimized cloud storage connections to maximize data throughput.

18.2%

Partition ingestion tables by a small time duration to allow for many data files to be written in parallel.

38.2%

Configure Databricks to save all data to attached SSD volumes instead of object storage, increasing file I/O significantly.

10.8%

Isolate Delta Lake tables in their own storage containers to avoid API limits imposed by cloud vendors.

22.4%

Store all tables in a single database to ensure that the Databricks Catalyst Metastore can load balance overall throughput.

10.5%

Databricks Certified Data Engineer - Professional