QUIZZ-EXAMEN-PREPARATION-SQL1

Question 1: Which of the following describes a benefit of a data lakehouse that is unavailable in a traditional data warehouse?

• A. A data lakehouse provides a relational system of data management.

• B. A data lakehouse captures snapshots of data for version control purposes.

• C. A data lakehouse couples storage and compute for complete control.

• D. A data lakehouse utilizes proprietary storage formats for data.

• E. A data lakehouse enables both batch and streaming analytics.

Question 2: Which of the following describes a scenario in which a data engineer will want to use a Job cluster instead of an all-purpose cluster?

• A. An ad-hoc analytics report needs to be developed while minimizing compute costs.

• B. A data team needs to collaborate on the development of a machine learning model.

• C. An automated workflow needs to be run every 30 minutes.

• D. A Databricks SQL query needs to be scheduled for upward reporting.

• E. A data engineer needs to manually investigate a production error.

Question 3: A data engineer needs to create a database called customer360 at the location /customer/customer360. The data engineer is unsure if one of their colleagues has already created the database. Which of the following commands should the data engineer run to complete this task?

• A. CREATE DATABASE customer360 MANAGE LOCATION '/customer/customer360';

• B. CREATE DATABASE IF NOT EXISTS customer360;

• C. CREATE DATABASE IF NOT EXISTS customer360 MANAGE LOCATION '/customer/customer360';

• D. CREATE DATABASE IF NOT EXISTS customer360 DELTA LOCATION '/customer/customer360';

• E. CREATE DATABASE customer360 DELTA LOCATION '/customer/customer360';

Question 4: A data engineer wants to horizontally combine two tables as a part of a query. They want to use a shared column as a key column, and they only want the query result to contain rows whose value in the key column is present in both tables. Which of the following SQL commands can they use to accomplish this task?

• A. INNER JOIN

• B. OUTER JOIN

• C. LEFT JOIN

• D. MERGE

• E. UNION

Question 5: A new data engineer has started at a company. The data engineer has recently been added to the company’s Databricks workspace as [e-mail]. The data engineer needs to be able to query the table sales in the database retail. The new data engineer already has been granted USAGE on the database retail. Which of the following commands can be used to grant the appropriate permissions to the new data engineer

• A. GRANT USAGE ON TABLE sales TO [e-mail];

• B. GRANT CREATE ON TABLE sales TO [e-mail];

• C. GRANT SELECT ON TABLE sales TO [e-mail];

• D. GRANT USAGE ON TABLE [e-mail] TO sales;

• E. GRANT SELECT ON TABLE [e-mail] TO sales;

Question 6: Which of the following locations hosts the driver and worker nodes of a Databricks-managed cluster?

• A. Data plane

• B. Control plane

• C. Databricks Filesystem

• D. JDBC data source

• E. Databricks web application

Question 7: A data architect is designing a data model that works for both video-based machine learning workloads and highly audited batch ETL/ELT workloads. Which of the following describes how using a data lakehouse can help the data architect meet the needs of both workloads?

• A. A data lakehouse requires very little data modeling

• B. A data lakehouse combines compute and storage for simple governance.

• C. A data lakehouse provides autoscaling for compute clusters.

• D. A data lakehouse stores unstructured data and is ACID-compliant.

• E. A data lakehouse fully exists in the cloud.

Question 8: A junior data engineer needs to create a Spark SQL table my_table for which Spark manages both the data and the metadata. The metadata and data should also be stored in the Databricks Filesystem (DBFS). Which of the following commands should a senior data engineer share with the junior data engineer to complete this task?

• A. CREATE TABLE my_table (id STRING, value STRING) USING org.apache.spark.sql.parquet OPTIONS (PATH "storage-path");

• B. CREATE MANAGED TABLE my_table (id STRING, value STRING) USING org.apache.spark.sql.parquet OPTIONS (PATH "storage-path");

• C. CREATE MANAGED TABLE my_table (id STRING, value STRING);

• D. CREATE TABLE my_table (id STRING, value STRING) USING DBFS;

• E. CREATE TABLE my_table (id STRING, value STRING);

Question 9: A data engineering team has created a series of tables using Parquet data stored in an external system. The team is noticing that after appending new rows to the data in the external system, their queries within Databricks are not returning the new rows. They identify the caching of the previous data as the cause of this issue. Which of the following approaches will ensure that the data returned by queries is always up-to-date?

• A. The tables should be converted to the Delta format

• B. The tables should be stored in a cloud-based external system

• C. The tables should be refreshed in the writing cluster before the next query is run

• D. The tables should be altered to include metadata to not cache

• E. The tables should be updated before the next query is run

Question 10: Which of the following statements describes Delta Lake?

• A. Delta Lake is an open source analytics engine used for big data workloads.

• B. Delta Lake is an open format storage layer that delivers reliability, security, and performance.

• C. Delta Lake is an open source platform to help manage the complete machine learning lifecycle.

• D. Delta Lake is an open source data storage format for distributed data.

• E. Delta Lake is an open format storage layer that processes data.