Exam AWS Certified Machine Learning - Specialty topic 1 question 3 discussion

Answer is B

D is wrong as kinesis firehose can convert from JSON to parquet but here we have CSV. B is correct and here is another proof link: https://medium.com/searce/convert-csv-json-files-to-apache-parquet-using-aws-glue-a760d177b45f

Kinesis Data Firehose supports real-time streaming ingestion and can automatically convert CSV to Parquet before storing it in S3.

Amazon Kinesis Data Streams + Amazon Kinesis Data Firehose Effort: Lowest effort Why? Amazon Kinesis Data Firehose natively supports real-time CSV ingestion and automatic conversion to Parquet. Fully managed, serverless, and directly integrates with Amazon S3. Requires zero infrastructure management compared to other solutions.

Although I'd go with Glue and option B I'm pretty sure that this is one of those "15 unscored questions that do not affect your score. AWS collects information about performance on these unscored questions to evaluate these questions for future use as scored questions" Just for fun I asked perplexity, chatgpt, gemini, deepseek and claude: all gave D as first response When I pointed out that "according to this https://docs.aws.amazon.com/firehose/latest/dev/record-format-conversion.html Kinesis can't convert directly cvs to parquet. It needs a Lambda" each model responded in a different way (some of them contradictory). My reasoning is that D (Kinesis + Firehose) is incorrect because Firehose does not support direct CSV-to-Parquet conversion and needs a Lambda not mentioned in the option. But discussing about questions like this one is nothing but I big waste of time ;-P

D Kinesis Data Firehose is designed specifically for streaming data delivery to destinations like S3. It has built-in support for data format conversion, including CSV to Parquet. This eliminates the need for managing separate transformation services like Glue or Spark. The setup is significantly simpler: you configure a Firehose delivery stream, specify the data format conversion, and point it to your S3 bucket. Therefore, option D requires the least implementation effort because it leverages a fully managed service (Kinesis Data Firehose) with built-in functionality for data format conversion.

Amazon Kinesis Data Firehose can only convert from JSON to Apache Parquet or Apache ORC before storing the data in Amazon S3.

Answer B, Yes, Amazon Kinesis Data Firehose can convert CSV to Apache Parquet, but you need to use a Lambda function to transform the CSV to JSON first: here the question is least effort to build, so B is the right answer with least effort to build the solution

Use Amazon Kinesis Data Streams to ingest customer data and configure a Kinesis Data Firehose delivery stream as a consumer to convert the data into Apache Parquet is incorrect. Although this could be a valid solution, it entails more development effort as Kinesis Data Firehose does not support converting CSV files directly into Apache Parquet, unlike JSON.

Amazon Kinesis Data Firehose can convert the format of your input data from JSON to Apache Parquet or Apache ORC before storing the data in Amazon S3. Parquet and ORC are columnar data formats that save space and enable faster queries compared to row-oriented formats like JSON. If you want to convert an input format other than JSON, such as comma-separated values (CSV) or structured text, you can use AWS Lambda to transform it to JSON first. https://docs.aws.amazon.com/firehose/latest/dev/record-format-conversion.html

Between B and D chose D. Because Firehose can't handle csv directly.

Answer is B. https://docs.aws.amazon.com/firehose/latest/dev/record-format-conversion.html "If you want to convert an input format other than JSON, such as comma-separated values (CSV) or structured text, you can use AWS Lambda to transform it to JSON first."

u need glue to convert to parquet

D for sure, Firehose can convert csv to parquet

Answer is unfortunately B. firehose cannot convert coma separated CSV to parquet directly.

b is not goog but - >given the context of "finding the solution that requires the least effort to implement," option D is the most suitable choice. Ingesting data from Amazon Kinesis Data Streams and using Amazon Kinesis Data Firehose to convert the data to Parquet format is a serverless approach. It allows for automatic data transformation and storage in Amazon S3 without the need for additional development or management of data conversion logic. Therefore, under the given conditions, option D is considered the solution that requires the "least effort" to implement

Amazon Kinesis Data Streams is a service that can capture, store, and process streaming data in real time. Amazon Kinesis Data Firehose is a service that can deliver streaming data to various destinations, such as Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service. Amazon Kinesis Data Firehose can also transform the data before delivering it, such as converting the data format, compressing the data, or encrypting the data. One of the supported data formats that Amazon Kinesis Data Firehose can convert to is Apache Parquet, which is a columnar storage format that can improve the performance and cost-efficiency of analytics queries. By using Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose, the Mobile Network Operator can ingest the .CSV data from the source systems and use Amazon Kinesis Data Firehose to convert the data into Parquet before storing it on Amazon S3