Importing Data

A data analyst needs to quickly upload a small CSV file from their local machine into Databricks to explore its contents. They want to avoid writing code and prefer a graphical interface. Which Databricks feature should they use?

A data analyst needs to ingest a large volume of CSV files from an external S3 bucket into a Delta table. Which method provides the most efficient, fault-tolerant, and incremental loading approach in Databricks?

A data analyst is using the Databricks SQL Connector for Python to query a large Delta table. The query returns millions of rows, and the analyst wants to process the results in batches to avoid memory issues. Which method should the analyst use to fetch rows in chunks?

A data analyst is setting up a recurring ingestion job that must load only new files from a cloud storage directory into a Delta table, must track which files have already been processed, and must fail clearly if the source schema changes unexpectedly. Which TWO capabilities should the analyst rely on? (Choose two.)

Which THREE of the following are valid sources for importing data into a Databricks Delta table? (Choose three)

A data analyst has a 5 MB pipe-delimited text file with a header row on their local laptop and needs to load it into a Databricks Unity Catalog table for a one-time analysis. They want the fastest path with the least configuration. Which approach should they use?

A data analyst needs to perform a one-time upload of a 15 MB compressed Parquet file from a local laptop into a Unity Catalog volume in a Databricks workspace. The analyst has the Databricks SQL editor open and no cluster running. Which approach should the analyst take to place the file into the volume path?

An analyst is preparing to upload a small local CSV file to a Databricks workspace. Which tool is most appropriate for a quick, one-time upload without requiring infrastructure setup?

Which TWO of the following scenarios are valid use cases for using the COPY INTO command? (Choose two)

A data analyst runs COPY INTO to load new CSV files from an S3 path into a Delta table every night. One night the job completes successfully but the row count does not change, even though new files were placed in the source path. The files have the same names as files loaded previously. What is the most likely cause?

An analyst is loading Parquet files from cloud storage into a Delta table using COPY INTO. The source directory contains files with several different schemas because upstream teams added columns over time. The analyst wants the table to accept the union of all columns without manual intervention. Which COPY INTO behavior should the analyst configure?

Refer to the exhibit. An analyst is attempting to read a CSV file using Spark. Why is the code failing?

A data analyst must load a Parquet file from an S3 bucket into a Databricks DataFrame, but the bucket is in a different AWS account and requires temporary credentials. The analyst has an AWS access key ID, secret access key, and session token. Which code snippet correctly configures Spark to read the file securely?

A junior data analyst attempts to load a large JSON file into a Databricks DataFrame using spark.read.json(path), but the resulting DataFrame contains numerous null values across critical columns. Upon inspection, the raw JSON records have inconsistent nesting structures and missing attributes. What is the most effective way for the analyst to inspect the inferred schema before transforming the data?

A data analyst needs to load a daily batch of 500 CSV files from an S3 bucket into a Delta table. The files are consistently formatted, and the analyst wants to ensure that files already processed are not re-imported in subsequent runs. Which approach is most efficient for this idempotency requirement?

When importing data into Databricks using the 'Add Data' UI, what is the default file format for the created table if the source is a CSV file?

An analyst is loading a CSV file where one column contains values like 007, 012, and 003. After creating a table through the Add Data UI, those values appear as 7, 12, and 3. The analyst needs the leading zeros preserved for downstream reporting. What should the analyst do?

When importing data into Databricks, what is the primary benefit of using Delta Lake over standard Parquet files?

A data analyst is using the Databricks Add Data UI to import a CSV file from cloud storage into a Delta table. The analyst wants to ensure the import process handles the data correctly. Which two actions can the analyst perform directly in the Add Data UI? (Choose two.)

Which THREE actions occur when using Auto Loader with schema evolution enabled? (Choose three)

An analyst is using the Spark DataFrame API to read a large JSON dataset. The dataset contains nested fields that are causing schema inference to fail. Which approach best resolves this?

A data analyst needs to ingest a daily batch of comma-separated value (CSV) files stored in cloud object storage into a Databricks Delta table. The files contain a header row, use a semicolon (;) as the delimiter, and occasionally include embedded newlines within quoted fields. Which approach ensures the parser correctly handles the multi-line fields and missing values?

A user wants to import a local 50MB CSV file into a Databricks workspace for a quick ad-hoc analysis. Which TWO methods are available within the Databricks UI to accomplish this task directly?