Online Access Free Databricks-Certified-Professional-Data-Engineer Practice Test

When evaluating the Ganglia Metrics for a given cluster with 3 executor nodes, which indicator would signal proper utilization of the VM's resources?

• A.Total Disk Space remains constant
• B.The five Minute Load Average remains consistent/flat
• C.Network I/O never spikes
• D.CPU Utilization is around 75%
• E.Bytes Received never exceeds 80 million bytes per second

A data ingestion task requires a one-TB JSON dataset to be written out to Parquet with a target part-file size of 512 MB. Because Parquet is being used instead of Delta Lake, built-in file-sizing features such as Auto- Optimize & Auto-Compaction cannot be used.
Which strategy will yield the best performance without shuffling data?

• A.Set spark.sql.files.maxPartitionBytes to 512 MB, ingest the data, execute the narrow transformations, and then write to parquet.
• B.Set spark.sql.shuffle.partitions to 512, ingest the data, execute the narrow transformations, and then write to parquet.
• C.Set spark.sql.adaptive.advisoryPartitionSizeInBytes to 512 MB bytes, ingest the data, execute the narrow transformations, coalesce to 2,048 partitions (1TB*1024*1024/512), and then write to parquet.
• D.Set spark.sql.shuffle.partitions to 2,048 partitions (1TB*1024*1024/512), ingest the data, execute the narrow transformations, optimize the data by sorting it (which automatically repartitions the data), and then write to parquet.
• E.Ingest the data, execute the narrow transformations, repartition to 2,048 partitions (1TB* 1024*1024
  /512), and then write to parquet.

An external object storage container has been mounted to the location/mnt/finance_eda_bucket.
The following logic was executed to create a database for the finance team:

After the database was successfully created and permissions configured, a member of the finance team runs the following code:

If all users on the finance team are members of thefinancegroup, which statement describes how thetx_sales table will be created?

• A.A managed table will be created in the DBFS root storage container.
• B.An external table will be created in the storage container mounted to /mnt/finance eda bucket.
• C.A logical table will persist the query plan to the Hive Metastore in the Databricks control plane.
• D.An managed table will be created in the storage container mounted to /mnt/finance eda bucket.
• E.A logical table will persist the physical plan to the Hive Metastore in the Databricks control plane.

The business reporting tem requires that data for their dashboards be updated every hour. The total processing time for the pipeline that extracts transforms and load the data for their pipeline runs in 10 minutes.
Assuming normal operating conditions, which configuration will meet their service-level agreement requirements with the lowest cost?

• A.Schedule a jo to execute the pipeline once and hour on a dedicated interactive cluster.
• B.Configure a job that executes every time new data lands in a given directory.
• C.Schedule a Structured Streaming job with a trigger interval of 60 minutes.
• D.Schedule a job to execute the pipeline once hour on a new job cluster.

All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion. However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

• A.Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
• B.Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
• C.Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.
• D.Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
• E.All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.