Simplify Data Layout Decisions and Optimize Query Performance Using Liquid Clustering. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 3)

Questions 11–15

1. 11foundation · easy

   What are clustering keys in the context of Liquid Clustering?

   • AIndexes that speed up all types of queries on a table
   • BPrimary keys that enforce uniqueness constraints on a Delta table
   • CForeign keys that link tables in a relational database
   • DColumns used to organize data files so that rows with similar values are co-located
   Reveal Solution Discussion Select an answer first
2. 12foundation · easy

   Which of the following is a key benefit of Liquid Clustering over traditional partitioning?

   • AIt guarantees that all queries will have zero scan time
   • BIt automatically converts all tables to Delta format
   • CIt requires more storage space than partitioning
   • DIt eliminates the need to choose partition columns upfront, allowing flexibility to change clustering keys later
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4. 13expert · hard

   A Delta table stores financial transactions with columns `account_id`, `transaction_date`, and `amount`. Queries frequently filter by `account_id` and `transaction_date`, but the table also needs to support time travel and Change Data Feed (CDF). The team wants to use Liquid Clustering to improve query performance. What is the best approach?

   • ADisable CDF and time travel to enable Liquid Clustering.
   • BCreate a separate table for time travel queries and another for CDF.
   • CUse partitioning on account_id instead of Liquid Clustering to preserve CDF and time travel.
   • DEnable Liquid Clustering with CLUSTER BY (account_id, transaction_date) while keeping CDF and time travel enabled.
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5. 14foundation · easy

   Which operation does Liquid Clustering use to maintain an optimal data layout over time?

   • AVACUUM
   • BANALYZE TABLE
   • COPTIMIZE
   • DMERGE
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6. 15foundation · easy

   How do clustering keys help optimize query performance?

   • ABy reducing the number of files that need to be scanned through data skipping
   • BBy compressing all data into a single file for faster reads
   • CBy creating indexes on every column automatically
   • DBy caching the entire table in memory
   Reveal Solution Discussion Select an answer first