Transform Data Using SQL and Snowpark DEA-C02 Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which Snowpark feature allows you to process data in micro-batches for streaming transformations?

   • ASnowpark DataFrame
   • BSnowpark Streaming
   • CSnowpark UDFs
   • DSnowpark Stored Procedures
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2. 17application · medium

   A data engineer needs to create a stored procedure that takes a table name as input and dynamically transforms that table using Snowpark. Which Snowpark feature should they use to handle the dynamic table name?

   • AUse a static DataFrame with a hardcoded table name
   • BUse a UDF to read the table
   • CUse a SQL string and execute it with session.sql()
   • DUse df.table_name() method
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4. 18foundation · easy

   In Snowpark, which method is used to filter rows of a DataFrame based on a condition?

   • Agroup_by()
   • Bselect()
   • Cfilter()
   • Djoin()
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5. 19foundation · easy

   Which language is NOT supported for writing Snowpark stored procedures?

   • AScala
   • BC#
   • CJava
   • DPython
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6. 20expert · hard

   A data engineer is optimizing a transformation query that joins a large fact table with a small dimension table. The query is running slowly because the fact table is large and the join causes significant shuffling. Which optimization should the engineer apply first?

   • AAdd a cluster key on the fact table's join column.
   • BIncrease the warehouse size to handle the shuffle.
   • CUse a window function instead of a join.
   • DUse a broadcast hint to distribute the dimension table to all nodes.
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