An elections office must process multi-terabyte historical ballot and precinct datasets with Apache Spark transformations before loading analytic tables. Which AWS service best provides managed big-data compute for that heavy processing?
Select an answer to reveal the explanation.
Short Explanation
Multi-TB election math needs a real Spark yard, not a blog host. EMR gives you managed big-data clusters for heavy transforms at that scale. Lightsail, SES, and Amplify Hosting aren’t Spark processing platforms for precinct lakes.
Full Explanation
Amazon EMR provides managed big-data compute clusters that run Apache Spark at multi-terabyte scale, which matches an elections office that must transform historical ballot and precinct datasets before loading analytic tables. EMR handles cluster provisioning, scalable Spark execution, and integration with lake storage so heavy municipal election processing does not land on unsuitable app-hosting platforms. Amazon Lightsail fixed VPS instances under a municipal WordPress plan are small application hosts, not a Spark processing fabric for multi-TB transforms. Amazon SES bulk email workers parsing CSV in the mail transport layer misuse an email service as a compute engine and cannot replace distributed Spark jobs. AWS Amplify Hosting build minutes are for front-end app builds/hosting, not election-scale Spark execution. Exam caveat: right-size core/task nodes, consider Spot where appropriate for cost, and persist outputs to S3 with clear partitioning; transient clusters should store results off-cluster. Operational check: run a representative precinct transform on a sized EMR/Spark job, verify output table row counts and key distributions, track job duration and cost, and only then schedule the full historical ballot backfill window.