Identify a scenario to use an external table.A Data Engineer needs to create a parquet bronze table and wants to ensure that it gets stored in a specific path in an external location.Which table can be created in this scenario?
Answer(s): A
In this scenario, the Data Engineer wants to create a parquet bronze table and ensure that it gets stored in a specific path in an external location. An external table allows you to define the table's structure while storing the actual data in an external location, which can be beneficial for data sharing and managing storage separately from the data warehouse catalog.An external table where the schema has managed location pointing to specific path in external location:This is incorrect because an external table does not have a managed location; its data is stored in an external location specified by the user.A managed table where the catalog has managed location pointing to specific path in external location:This is incorrect as managed tables typically store their data in the default location of the database unless specified otherwise, which does not fit the requirement for external storage.A managed table where the location is pointing to specific path in external location: This is incorrect because managed tables do not allow you to specify an external location; they manage their own data storage.
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).Which code block creates this SQL UDF?
What describes the relationship between Bronze tables and raw data?
Answer(s): C
In the medallion architecture of data lakes (Bronze, Silver, Gold layers), Bronze tables are designed to store raw data with a schema applied to enable querying and processing. This is the initial stage of data ingestion,where raw data is ingested into a table format to make it accessible for further transformations, validations, and analysis.
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.Which control flow statement should the data engineer use to begin this conditionally executed code block?
Answer(s): D
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.Which command should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?
Answer(s): B
The UNION operator is used to combine the results of two SELECT statements and remove duplicate records from the result set. Since there are no duplicate records between march_transactions and april_transactions, this query will correctly combine all records from both tables into the new all_transactions table without introducing duplicates.
A data analyst has developed a query that runs against Delta table. They want help from the data engineering team to implement a series of tests to ensure the data returned by the query is clean. However, the data engineering team uses Python for its tests rather than SQL.Which operation could the data engineering team use to run the query and operate with the results in PySpark?
The spark.sql operation allows PySpark users to execute SQL queries, such as the one developed by the data analyst, and operate with the results programmatically in Python. This makes it possible to integrate SQL- based logic into the data engineering team's PySpark workflows while ensuring compatibility with their testing framework.
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.They run the following command:Which line of code fills in the above blank to successfully complete the task?
The USING org.apache.spark.sql.jdbc is used to create a table in Databricks by reading from a JDBC source. In this scenario, the data engineer is trying to create a Databricks table from an existing SQLite database, and the JDBC (Java Database Connectivity) is the appropriate method to use for connecting to and reading from relational databases like SQLite.
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.Which relational object should the data engineer create?
A temporary view is a logical relational object in Spark that:1. Does not persist physical data it only exists for the duration of the session and references the data dynamically.2. Avoids storage costs because no data is physically copied or stored.3. Is session-scoped, meaning it cannot be accessed by other data engineers in different sessions, which aligns with the data engineer's requirements.
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