DP-203 Design and implement data storage Practice Question
You are a data engineer for a gaming company that uses Azure Data Lake Storage Gen2. The data lake stores player event data in JSON format. The data is organized by date and event type. The analytics team frequently runs queries that filter by player ID to analyze individual player behavior. These queries are slow because they scan entire daily partitions. You need to improve the performance of queries that filter by player ID without restructuring the entire data lake. The data is stored as JSON files. What should you do?
⚠ Common exam trap
Many exam-takers think compression alone (Option A) or indexing (Option C) can solve performance issues in a data lake, but Azure Data Lake Storage Gen2 does not support file-level indexes, and compression does not change the fundamental row-scanning nature of JSON queries.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Convert the data from JSON to Parquet format and partition by player ID
Converting JSON to Parquet enables columnar storage, which significantly reduces I/O by reading only the columns needed for queries. Partitioning by player ID further improves performance by allowing partition elimination, so queries filter only the relevant partitions instead of scanning entire daily partitions. This approach directly addresses the slow queries without restructuring the entire data lake.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Compress the JSON files using gzip to reduce I/O
Why it's wrong here
Compression reduces size but does not enable predicate pushdown.
- ✓
Convert the data from JSON to Parquet format and partition by player ID
Why this is correct
Parquet allows predicate pushdown and column pruning, speeding up player ID queries.
- ✗
Create indexes on the player ID field in the data lake
Why it's wrong here
ADLS Gen2 does not support indexing on data files.
- ✗
Repartition the data by hour to reduce the data scanned per partition
Why it's wrong here
Finer time partitions do not help with player ID filters.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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