Execute SQL Queries Directly on Files, Including ORC Files, JSON Files, CSV Files, Text Files, and Delta Files, and Understand the Different Save Modes for Outputting Data in Spark SQL. ASSOCIATE-DEVELOPER-APACHE-SPARK Practice Questions (Page 1)

Questions 1–5

1. 1application · medium

   A team has a mix of ORC and CSV files in /data/source. They want to query both formats directly without creating tables in the metastore. Which approach allows this?

   • AUse a single query with a UNION of both files using the same format prefix.
   • BUse format-specific path references like orc.`/data/source/file.orc` and csv.`/data/source/file.csv` in separate queries.
   • CCreate temporary views for each file using CREATE TEMP VIEW and then query the views.
   • DRegister both files in the Hive metastore before querying.
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2. 2foundation · easy

   Which feature of Delta Lake allows you to query a previous version of a Delta table using Spark SQL?

   • AChange data feed
   • BTime travel
   • CSchema inference
   • DACID transactions
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4. 3expert · hard

   A team has a Delta table at /data/orders and a JSON file at /data/new_orders.json. They need to join these datasets in a SQL query. The Delta table has a 'user_id' column, and the JSON file has a nested 'user.id' field. Which approach is most efficient?

   • AQuery both directly using delta.`path` and json.`path`, then join on user_id = user.id.
   • BUse a UNION of both datasets, then filter by user_id.
   • CQuery the Delta table directly and use a LIKE condition to match the JSON file's user.id.
   • DLoad the JSON file into a DataFrame, explode the nested field, register a temp view, then join.
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5. 4foundation · easy

   What is the correct way to reference an ORC file in a Spark SQL query so that Spark reads it with the ORC format?

   • AUse the `format('orc')` function in the FROM clause.
   • BUse the file extension `.orc` in the path and rely on Spark's automatic format detection.
   • CRegister the file as a temporary view using `CREATE TEMP VIEW ... USING orc`.
   • DUse the `orc.` prefix before the file path in backticks.
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6. 5foundation · easy

   When querying a JSON file directly with Spark SQL, how does Spark handle the schema of the data?

   • ASpark uses the file name to determine the schema of the JSON data.
   • BSpark requires you to define the schema manually before querying any JSON file.
   • CSpark treats all JSON values as strings unless you cast them in the query.
   • DSpark infers the schema by sampling the JSON data, including nested structures.
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