Amazon AWS Certified Solutions Architect - Associate SAA-C03 Practice Test 64

Question 630

An Athena query over logs has a restrictive WHERE date clause but still scans every month of S3 data. The table is unpartitioned. Why?

A partition predicate can prune data even when the Glue table has no registered partitions, no projected partitions and no partition folders.
Add a restrictive HAVING condition to the Athena query but leave the S3 source unpartitioned, assuming post-aggregation filters eliminate file scans.
Without usable partition metadata/pruning, the predicate may not eliminate whole S3 file groups from the scan.
Create a Glue crawler that infers the same unpartitioned table schema and assume refreshed column types alone permit date partition pruning.

Explanation

Correct Answer

Define partitions and appropriate Parquet layout; SQL filtering after full reads does not guarantee a low byte-scan charge.

Incorrect Answers

Athena needs effective partition metadata or projection for whole-partition pruning; ordinary row filters do not automatically avoid all file reads.

HAVING filters aggregation results, not the physical S3 object groups read to compute them. Partition layout and metadata are needed to prune months before scanning.

Schema discovery does not create meaningful date partitions when objects remain unpartitioned. Athena cannot skip whole S3 file groups based solely on a row-level date predicate.

Question 631

A team runs complex joins through Athena over tiny CSV files and sees high scan cost and latency every hour. Why might the chosen design be inefficient?

Convert every CSV object to gzip-compressed CSV but assume compression alone gives Redshift-style persistently optimized joins across recurring fact tables.
Add only a Glue crawler without changing the repeated full-file scans, file size layout, columnar format or Athena query plan.
Frequent broad scans of poorly organized CSV files can make serverless per-query scans costly relative to a tuned analytical warehouse.
Add more partition prefixes to the CSV lake while keeping each query unselectively scanning every partition and repeating expensive joins.

Explanation

Correct Answer

Evaluate file format/partitioning and recurring Redshift warehouse economics rather than assuming all SQL engines have the same execution cost.

Incorrect Answers

Compression can reduce scan bytes, but repeated wide joins and concurrency still require workload-based selection of Athena versus a warehouse; compression alone is not a persisted query engine.

Crawler metadata does not automatically reduce recurring query bytes or transform raw CSV into optimized Parquet partitions.

Partitioning only prunes when query predicates and catalog match; scanning every partition still incurs repeated per-query byte and planning overhead.

Question 632

An analyst has s3:GetObject on underlying raw lake objects and can bypass table-level column restrictions by reading S3 directly. What trust boundary was missed?

Lake Formation removes every principal’s direct S3 read rights whenever a Data Catalog column grant is revoked.
Direct S3 object access can bypass query-engine Lake Formation permissions unless IAM/S3 policies and registered-location controls enforce the intended lake governance.
Grant analysts unrestricted s3:GetObject to raw objects and assume removing the Athena column grant alone prevents that direct raw-object download.
Configure Lake Formation table metadata tags while leaving the analyst’s IAM permissions to fetch the same restricted raw objects unchanged.

Explanation

Correct Answer

Fine-grained catalog grants do not replace secure object-level access paths for bypass-capable principals.

Incorrect Answers

Lake Formation governs supported lake/query access paths; unmanaged direct IAM/S3 grants can persist unless separately constrained.

Column grants on supported query engines do not in general revoke a separate direct S3 read authorization; IAM, bucket and registered-location controls must enforce a complete access boundary.

Metadata tags and governed query permissions cannot replace restrictive raw S3 data access when direct GetObject remains open.

Question 633

A DataSync task completes a sync with most files skipped but the destination already has identical objects. Why might this be expected?

DataSync is guaranteed to retransmit every unchanged file on every execution and therefore cannot support incremental WAN transfers.
Force every DataSync task execution to overwrite all unchanged destination files and interpret fewer object transfers as a failed integrity check.
Incremental DataSync transfers can omit unchanged files while verifying and preserving the required dataset state.
Enable S3 object replication on the DataSync destination bucket and assume it is the only mechanism capable of verifying that unchanged source files match the destination.

Explanation

Correct Answer

A low file-transfer count does not alone prove data loss; inspect task verification and modification criteria.

Incorrect Answers

DataSync can use change detection and verification behavior; unchanged files need not be copied on each run depending on configuration.

DataSync can skip unchanged content under its selected transfer mode and verify existing destination content; a low transfer count does not itself imply failure.

Replication copies new eligible objects across buckets but does not supersede configured DataSync verification and incremental transfer semantics.

Question 634

An Internet-only import of hundreds of TiB cannot finish within the delivery window. Engineers keep increasing the client upload thread count. What fundamental limit remains?

A 10-Mbps Internet link can transfer hundreds of terabytes during a short outage window if enough concurrent HTTPS sessions are opened.
The narrow WAN line’s aggregate bandwidth and interruptions cannot be eliminated by adding upload workers.
Enable multipart uploads with thousands of parallel parts and assume parallelism can exceed the site uplink capacity even at sustained full utilization.
Use S3 Transfer Acceleration and assume it turns a limited 10-Mbps last-mile uplink into a multi-gigabit circuit.

Explanation

Correct Answer

An intermittent low-bandwidth WAN caps aggregate throughput irrespective of upload thread count. Evaluate appropriately eligible AWS Data Transfer Terminal, a partner physical transfer service or more bandwidth against the time window; AWS Snow Family is not offered to new customers.

Incorrect Answers

Physical available bandwidth and outages bound total transfer; concurrency cannot multiply the ISP’s line rate.

Multipart parallelism can improve use of available bandwidth and resume failures, but cannot make the total bytes per second exceed the actual access link throughput.

Edge acceleration may optimize Internet routing but cannot create physical upstream bandwidth unavailable at the source site.

Question 635

Kafka clients configured with their broker protocol are pointed at an Amazon Kinesis stream ARN and fail to connect. Why?

Kafka-compatible clients can connect directly to a Kinesis shard using the same broker bootstrap addresses and wire protocol.
Enable MSK broker encryption settings on a Kinesis stream ARN and assume Kinesis speaks Kafka without provisioning MSK brokers.
Add a VPC interface endpoint for the Kinesis API and use its IP as a Kafka bootstrap server without modifying the client protocol.
Amazon Kinesis Data Streams does not expose a Kafka broker protocol endpoint simply because both handle streams.

Explanation

Correct Answer

Choose MSK or adapt clients to the Kinesis APIs, as protocol-level compatibility is not automatic.

Incorrect Answers

Kinesis is not a Kafka broker endpoint. Amazon MSK offers a managed Apache Kafka environment for unchanged Kafka clients.

MSK-specific Kafka protocol and broker configuration do not apply to a Kinesis stream ARN; a compatible Kafka cluster or adapter is required.

A private API network path does not translate Amazon Kinesis requests into Kafka broker protocol semantics.

Question 636

A DMS migration runs an initial full load successfully but destination changes stop reflecting new source transactions. The task was configured full-load-only. Why?

A DMS full-load task tracks every future production write indefinitely even if CDC is explicitly disabled.
Increase the DMS task replication instance size while leaving its migration type set to full load only, expecting ongoing commits to appear.
Enable RDS Multi-AZ on the source database and assume high availability automatically mirrors every source transaction into a separate DMS target.
A full-load-only DMS task does not capture subsequent changes; CDC must be configured and sustained.

Explanation

Correct Answer

Verify source log prerequisites, replication health and lag before a final cutover.

Incorrect Answers

Without ongoing change capture the target becomes stale after initial copy as the live source continues to change.

Capacity improvements cannot activate a CDC stream that the task was never configured to collect.

Multi-AZ replication supports availability within its deployment, not change propagation to the independent DMS migration target.

Question 637

An S3 multipart upload has 200 uploaded parts but no CompleteMultipartUpload call after client failure. The final key is absent and storage charges continue. Why?

Incomplete multipart upload parts disappear instantly with no storage charges as soon as the uploader loses network connectivity.
Extend the client socket timeout after it exits and assume S3 automatically commits already-uploaded parts into the final object.
Submit a successful CompleteMultipartUpload request for a different upload ID and assume it commits the abandoned upload parts under the intended final object key.
Unfinished multipart upload parts are stored and billed until completion or abort; the completed object has not been committed.

Explanation

Correct Answer

Abort abandoned uploads or configure lifecycle cleanup rather than expecting orphaned parts to become an object.

Incorrect Answers

Uploaded multipart parts can remain stored and billed until the upload is completed or aborted, hence lifecycle abort rules matter.

Parts remain staged after failure until a valid CompleteMultipartUpload request; changing a stopped client timeout cannot complete the upload.

Multipart upload IDs are separate sessions. Completing a different upload cannot commit parts staged under an abandoned upload ID; completion must refer to the original valid ID and listed part ETags, or that upload must be aborted.

Question 638

An operator tries to replay an event written seven days ago, but stream retention is 24 hours. Why is the record unavailable?

Setting the consumer checkpoint backward automatically restores Kinesis records deleted by retention expiry.
Increase a Kinesis stream retention period from 24 to 168 hours only after the record has already expired and assume the older data becomes available for replay.
Kinesis removes expired stream records after the configured retention period; iterator changes cannot retrieve deleted data.
Seek by the record’s approximate original arrival timestamp, assuming timestamp iterators bypass expired record retention.

Explanation

Correct Answer

Plan required retention or archive events externally to S3 for longer disaster recovery replay.

Incorrect Answers

Consumer positions only locate still-retained stream data; expired records cannot be recovered by changing offsets.

Extending retention affects currently retained and future records; AWS explicitly documents that records already expired before the increase do not reappear. Preserve an external archive if historical replay is required.

Timestamp-based iterators locate only records still held by the stream; a seven-day-old record is absent from a one-day retention window.

Question 639

A team triggers validation and publication in parallel with Glue extraction; published data sometimes reflects a prior batch. What execution defect exists?

A Glue StartJobRun call means every data transformation has succeeded and no additional state-machine wait or validation is necessary.
The pipeline lacks a dependency edge waiting for Glue completion and successful validation before publication.
Place the Glue and validation steps on two parallel state-machine branches and mark publication successful as soon as either branch begins.
Configure a Glue Data Catalog crawler and treat the crawler’s completion as proof that the newest Glue transformation output is validated.

Explanation

Correct Answer

Run dependent stages sequentially in a state machine with observed service outcome conditions.

Incorrect Answers

An asynchronous job launch only acknowledges the request, not completion; Step Functions must wait for the appropriate task result.

Parallel launch does not enforce the requirement that Glue complete and row validation succeed before publication.

Catalog discovery does not prove the upstream ETL job completed and passed the required row-count quality test.

Question 640

S3 objects for a new partition are present, but Athena queries filtered by that partition return zero rows. The Glue table has no entry for it. Why?

Athena automatically knows every newly written S3 partition if the data files share an S3 bucket, regardless of table partition configuration.
Increase the Athena query timeout without adding the new partition to the catalog or configuring valid partition projection.
Create additional S3 object versions at the new prefix and assume Athena will infer missing table partition values from version history.
The catalog partition metadata is stale or incomplete, so partition pruning cannot address the new S3 prefix.

Explanation

Correct Answer

Update partitions with a crawler, partition projection or explicit catalog operations as appropriate.

Incorrect Answers

New prefixes require discoverable registered partitions or an appropriate projection strategy; S3 co-location alone does not update the query planner.

More execution time cannot make a missing table partition visible to Athena; discover or project the actual partition metadata.

S3 versioning protects object revisions, not the catalog partitions required by a partitioned Athena table.

Pass Your Amazon AWS Certified Solutions Architect - Associate SAA-C03 Exam Easy!

Question 630

Explanation

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Question 631

Explanation

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Question 632

Explanation

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Question 633

Explanation

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Question 634

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Question 635

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Question 636

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Question 637

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Question 638

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Question 639

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Question 640

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AWS Certified Solutions Architect - Associate SAA-C03 Practice Tests