AWS · MLA-C02 · BETA
Streaming ingestion and merging sources
MLA-C02 · Lesson 2 of 23 · 11:38
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In this lesson
Lesson 2 of the free MLA-C02 beta series (AWS Certified Machine Learning Engineer – Associate, domain 1, data preparation). In this lesson: streaming sources with Kinesis Data Streams and Apache Kafka, delivering records with Amazon Data Firehose, transforming streams with Lambda, Apache Flink, and Spark, and merging sources with joins over time. With three quick checks and a recap, and AnyCompany Mobility, a car sharing service, as the running example.
Preview the topics
- The team must land car telemetry from a Kinesis data stream in S3 as Parquet files, for nightly training, with the least operational effort. What should the ML engineer use?
- For each neighborhood, the team needs the number of free cars over a sliding 15-minute window, updated every minute from the telemetry stream. What should the ML engineer use?
- A Glue job joins trips with car maintenance records on the car ID, and the result has three times more rows than there are trips. What is the most likely cause?