Flashcards

Real-time Processing

Processing and analyzing data in real-time

Real-time Processing involves processing and analyzing data as it is generated, enabling decision-making and action in real-time.

5 minutes 5 Questions

Real-time processing in big data represents a paradigm where data is analyzed immediately as it arrives, enabling insights and actions with minimal latency. Unlike batch processing systems that handle data in large chunks periodically, real-time systems process each data point continuously, often w…

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Big Data Scientist - Real-time Processing Example Questions

Test your knowledge of Real-time Processing

Question 1

What is the purpose of a CEP engine in real-time processing?

To detect patterns and anomalies in high-speed data streams To store and archive data for future analysis To perform complex machine learning algorithms in real-time To ensure high availability and fault tolerance in a distributed system To perform real-time analytics on historical data To optimize resource usage in a cluster environment

Correct Answer: To detect patterns and anomalies in high-speed data streams

A CEP (complex event processing) engine is a software system that is designed to detect patterns and anomalies in real-time data streams. It is used for applications such as fraud detection, network monitoring, and sensor data processing. The engine can be configured to trigger alerts or take specific actions when certain events or patterns are detected.

Question 2

What is the purpose of a streaming API?

A streaming API enables applications to store data in real-time. A streaming API enables applications to send data in real-time to other applications. A streaming API enables applications to receive data once it has been processed in batches. A streaming API enables applications to perform batch processing on data. A streaming API enables applications to receive continuous data as soon as it is created or updated in real-time. A streaming API enables applications to receive data from offline sources.

Correct Answer: A streaming API enables applications to receive continuous data as soon as it is created or updated in real-time.

A streaming API allows applications to subscribe to topic feeds and receive continuous data updates in real-time, allowing for real-time processing and analysis of the data.

Question 3

What is a watermark in stream processing?

A marker in the stream indicating the time of the first unprocessed event in the stream. A marker in the stream indicating the latest processed event time. A marker in the stream indicating the last processing time of the system. A marker in the stream indicating the earliest event time. A marker in the stream indicating the earliest event time of the system. A marker in the stream indicating the last processing time of the stream.

Correct Answer: A marker in the stream indicating the latest processed event time.

A watermark is a marker in the stream indicating the latest processed event time. This helps in preventing late data from affecting results and allows for calculation of processing latency.

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