DAS-C01 · Question #23
A media analytics company consumes a stream of social media posts. The posts are sent to an Amazon Kinesis data stream partitioned on user_id. An AWS Lambda function retrieves the records and…
The correct answer is D. Configure multiple Lambda functions to process the stream. AWS Lambda is introducing a new scaling parameter for Amazon Kinesis Data Streams and Amazon DynamoDB Streams event sources. Parallelization Factor can be set to increase concurrent Lambda invocations for each shard, which by default is 1. This allows for faster stream…
Question
A media analytics company consumes a stream of social media posts. The posts are sent to an Amazon Kinesis data stream partitioned on user_id. An AWS Lambda function retrieves the records and validates the content before loading the posts into an Amazon Elasticsearch cluster. The validation process needs to receive the posts for a given user in the order they were received. A data analyst has noticed that, during peak hours, the social media platform posts take more than an hour to appear in the Elasticsearch cluster. What should the data analyst do reduce this latency?
Options
- AMigrate the validation process to Amazon Kinesis Data Firehose.
- BMigrate the Lambda consumers from standard data stream iterators to an HTTP/2 stream
- CIncrease the number of shards in the stream.
- DConfigure multiple Lambda functions to process the stream.
How the community answered
(56 responses)- A16% (9)
- B4% (2)
- C7% (4)
- D73% (41)
Explanation
AWS Lambda is introducing a new scaling parameter for Amazon Kinesis Data Streams and Amazon DynamoDB Streams event sources. Parallelization Factor can be set to increase concurrent Lambda invocations for each shard, which by default is 1. This allows for faster stream processing without the need to over-scale the number of shards, while still guaranteeing order of records processed. https://aws.amazon.com/blogs/compute/new-aws-lambda-scaling-controls-for-kinesis-and- dynamodb-event-sources/
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