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The data architect has mandated that all tables in the Lakehouse should be configured asexternal Delta Lake tables.Which approach will ensure that this requirement is met?
A. Whenever a database is being created, make sure that the location keyword is used B. When configuring an external data warehouse for all table storage. leverage Databricksfor all ELT. C. Whenever a table is being created, make sure that the location keyword is used. D. When tables are created, make sure that the external keyword is used in the createtable statement. E. When the workspace is being configured, make sure that external cloud object storagehas been mounted.
Answer: C
Explanation: This is the correct answer because it ensures that this requirement is met.
The requirement is that all tables in the Lakehouse should be configured as external Delta
Lake tables. An external table is a table that is stored outside of the default warehouse
directory and whose metadata is not managed by Databricks. An external table can be
created by using the location keyword to specify the path to an existing directory in a cloud
storage system, such as DBFS or S3. By creating external tables, the data engineering
team can avoid losing data if they drop or overwrite the table, as well as leverage existing
data without moving or copying it. Verified References: [Databricks Certified Data Engineer
Professional], under “Delta Lake” section; Databricks Documentation, under “Create an
external table” section.
Sample Question 2
A small company based in the United States has recently contracted a consulting firm inIndia to implement several new data engineering pipelines to power artificial intelligenceapplications. All the company's data is stored in regional cloud storage in the United States.The workspace administrator at the company is uncertain about where the Databricksworkspace used by the contractors should be deployed Assuming that all data governance considerations are accounted for, which statementaccurately informs this decision?
A. Databricks runs HDFS on cloud volume storage; as such, cloud virtual machines mustbe deployed in the region where the data is stored. B. Databricks workspaces do not rely on any regional infrastructure; as such, the decisionshould be made based upon what is most convenient for the workspace administrator. C. Cross-region reads and writes can incur significant costs and latency; wheneverpossible, compute should be deployed in the same region the data is stored. D. Databricks leverages user workstations as the driver during interactive development; assuch, users should always use a workspace deployed in a region they are physically near. E. Databricks notebooks send all executable code from the user's browser to virtualmachines over the open internet; whenever possible, choosing a workspace region nearthe end users is the most secure.
Answer: C Explanation: This is the correct answer because it accurately informs this decision. The
decision is about where the Databricks workspace used by the contractors should be
deployed. The contractors are based in India, while all the company’s data is stored in
regional cloud storage in the United States. When choosing a region for deploying a
Databricks workspace, one of the important factors to consider is the proximity to the data
sources and sinks. Cross-region reads and writes can incur significant costs and latency
due to network bandwidth and data transfer fees. Therefore, whenever possible, compute
should be deployed in the same region the data is stored to optimize performance and
reduce costs. Verified References: [Databricks Certified Data Engineer Professional], under
“Databricks Workspace” section; Databricks Documentation, under “Choose a region”
section.
Sample Question 3
Each configuration below is identical to the extent that each cluster has 400 GB total ofRAM, 160 total cores and only one Executor per VM.Given a job with at least one wide transformation, which of the following clusterconfigurations will result in maximum performance?
A. • Total VMs; 1• 400 GB per Executor• 160 Cores / Executor B. • Total VMs: 8• 50 GB per Executor • 20 Cores / Executor C.• Total VMs: 4• 100 GB per Executor• 40 Cores/Executor D.• Total VMs:2• 200 GB per Executor• 80 Cores / Executor
Answer: B
Explanation: This is the correct answer because it is the cluster configuration that will
result in maximum performance for a job with at least one wide transformation. A wide
transformation is a type of transformation that requires shuffling data across partitions,
such as join, groupBy, or orderBy. Shuffling can be expensive and time-consuming,
especially if there are too many or too few partitions. Therefore, it is important to choose a
cluster configuration that can balance the trade-off between parallelism and network
overhead. In this case, having 8 VMs with 50 GB per executor and 20 cores per executor
will create 8 partitions, each with enough memory and CPU resources to handle the
shuffling efficiently. Having fewer VMs with more memory and cores per executor will
create fewer partitions, which will reduce parallelism and increase the size of each shuffle
block. Having more VMs with less memory and cores per executor will create more
partitions, which will increase parallelism but also increase the network overhead and the
number of shuffle files. Verified References: [Databricks Certified Data Engineer
Professional], under “Performance Tuning” section; Databricks Documentation, under