Save Data to Persistent Tables While Applying Sorting and Partitioning to Optimize Data Retrieval. ASSOCIATE-DEVELOPER-APACHE-SPARK Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A logistics company stores shipment records in a partitioned table. The table is partitioned by `ship_date`, and each partition contains millions of rows. Analysts frequently run queries that filter on `ship_date` and then sort results by `priority` within a single day. To improve query performance for these queries, what should you do when saving the table?

   • AUse `bucketBy(16, "priority")`
   • BUse `sortBy("ship_date", "priority")` without partitioning
   • CUse `partitionBy("ship_date").sortBy("priority")`
   • DUse `partitionBy("priority")`
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2. 12application · medium

   A company stores web server logs in a table. Queries frequently filter on `date` and `hour` to analyze traffic patterns. The data volume is large, and you need to minimize data scanned for these queries. Which partitioning strategy should you use?

   • ABucket by `date` and `hour`
   • BPartition by `date` and `hour`
   • CPartition by `hour` only
   • DPartition by `date` only
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4. 13foundation · easy

   Which statement correctly describes the relationship between bucketing and sorting?

   • ABucketing and sorting are mutually exclusive; you can only use one.
   • BBucketing can be combined with sorting to sort data within each bucket.
   • CBucketing replaces sorting, so sorting is not needed.
   • DSorting is required for bucketing to work.
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5. 14application · medium

   A data scientist wants to save a DataFrame as a table that is accessible across multiple Spark sessions and will be automatically deleted when the table is dropped. They do not need to specify a custom storage location. Which approach should they use?

   • Adf.createOrReplaceTempView("persistent_table")
   • Bdf.write.mode("overwrite").saveAsTable("persistent_table")
   • Cdf.write.saveAsTable("persistent_table")
   • Ddf.write.option("path", "/custom/path").saveAsTable("persistent_table")
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6. 15foundation · easy

   Which method is used to persist a DataFrame as a table in Spark SQL?

   • Adf.write.table("table_name")
   • Bdf.save("table_name")
   • Cspark.sql("CREATE TABLE table_name AS SELECT * FROM df")
   • Ddf.write.saveAsTable("table_name")
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