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DEA-C01 Data Store Management Practice Question

A data engineer is migrating an on-premises Apache Hive data warehouse to Amazon EMR. The warehouse contains partitioned tables stored in HDFS. The engineer wants to use Amazon S3 as the storage layer for the EMR cluster. What is the MOST important consideration for maintaining query performance on S3?

⚠ Common exam trap

The trap here is that candidates may focus on metastore performance (Option C) or alternative query engines (Option D), missing the fundamental S3 performance bottleneck of LIST requests when querying partitioned data on EMR.

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

Ensure that the table partitions are organized in a way that minimizes S3 LIST requests

When using Amazon S3 as the storage layer for an EMR cluster, the most critical factor for query performance is minimizing S3 LIST requests. S3 LIST operations are significantly slower and more expensive than GET requests, and Hive/Spark queries on partitioned tables often issue LIST requests to discover partition locations. By organizing partitions with a common prefix (e.g., `year=2023/month=01/day=15/`) and using partition pruning, you reduce the number of LIST calls, directly improving query latency and reducing S3 API costs.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Ensure that the table partitions are organized in a way that minimizes S3 LIST requests

    Why this is correct

    S3 LIST operations are slower than HDFS; partitioning by common query filters and using partition projection can improve performance.

  • Configure EMR to use HDFS for storage instead of S3 for better performance

    Why it's wrong here

    HDFS is ephemeral; the migration is to S3 for durability.

  • Use DynamoDB as the Hive metastore to improve metadata access

    Why it's wrong here

    The Hive metastore can be in MySQL or external, but DynamoDB is not standard for Hive.

  • Use Amazon Redshift Spectrum to query the data directly from S3

    Why it's wrong here

    Redshift Spectrum is separate from EMR; the question is about EMR.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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