HIGH VELOCITY DATA PROCESSING WITH
APACHE SPARK STREAMING 2025
UPDATED EXAM QUESTIONS WITH
ANSWERS ALREADY GRADED A+
What is the primary reason for the need for streaming big data
processing? - CORRECT ANSWER>>>>Data is being created at
unprecedented rates, with exponential growth from mobile, web, and
social sources.
What was the projected number of connected devices by 2020? -
CORRECT ANSWER>>>>50 billion connected devices.
What is the annual growth rate of datacenter IP traffic? - CORRECT
ANSWER>>>>25% annually.
What are the two main components of Big Data in the past? -
CORRECT ANSWER>>>>Volume and Variety.
What additional component has been added to the definition of Big Data
in the present? - CORRECT ANSWER>>>>Velocity.
What are the time to insight differences between batch processing and
stream processing? - CORRECT ANSWER>>>>Batch processing has a
time to insight of hours, while stream processing has a time to insight of
seconds.
What are the key requirements for a streaming system? - CORRECT
ANSWER>>>>Scalability to large clusters, second-scale latencies, a
simple programming model, integration with batch and interactive
processing, and efficient fault-tolerance in stateful computations.
1
,What is the purpose of a streaming architecture? - CORRECT
ANSWER>>>>To handle stream processing by taking action on data at
the moment it is accepted.
Which technology commonly acts as the store for incoming streaming
data in modern deployments? - CORRECT ANSWER>>>>Apache
Kafka.
What is Spark Streaming? - CORRECT ANSWER>>>>An extension of
the core Spark API that enables scalable high-throughput, fault-tolerant
stream processing of live data streams.
What high-level functions can be used in Spark Streaming? - CORRECT
ANSWER>>>>Map, reduce, join, and window.
What types of algorithms can be applied to data streams in Spark
Streaming? - CORRECT ANSWER>>>>Machine learning and graph
processing algorithms.
What is the difference between Kafka and stream processing systems? -
CORRECT ANSWER>>>>Kafka is primarily a message-processing
system that passes messages from producers to consumers without
modification, while stream processing systems analyze and transform
data.
What are the key components of streaming in Hadoop? - CORRECT
ANSWER>>>>Real-time data serving, data ingestion and transportation
service, real-time stream processing engine, security, system
management, and data management & integration.
What is the canonical Hadoop stream processing architecture composed
of? - CORRECT ANSWER>>>>HDFS, HBase, data sources, data
ingestion, and applications.
2
, What is the Lambda architecture? - CORRECT ANSWER>>>>An
architectural paradigm to handle both batch and streaming data in
parallel.
What are the benefits of Lambda architecture? - CORRECT
ANSWER>>>>Combines batch processing with stream processing,
keeps raw information forever, and allows rerunning analytics
operations on the entire dataset.
What is the significance of keeping raw information in the batch layer of
Lambda architecture? - CORRECT ANSWER>>>>It allows for
rerunning analytics operations if necessary, such as correcting errors or
applying better algorithms.
What is the role of Kafka in a streaming architecture? - CORRECT
ANSWER>>>>Kafka serves as a data ingestion and transportation
service that accepts messages from producers and passes them to
consumers.
What is the expected outcome of integrating Spark Streaming with batch
processing? - CORRECT ANSWER>>>>It allows for a unified
processing model that can handle both real-time and historical data.
What is the expected latency that Spark Streaming can achieve? -
CORRECT ANSWER>>>>Second-scale latencies.
How does Spark Streaming handle live data streams? - CORRECT
ANSWER>>>>It can absorb live data streams from sources like Kafka
and Flume.
What types of outputs can Spark Streaming produce? - CORRECT
ANSWER>>>>Processed data can be pushed out to filesystems,
databases, and live dashboards.
3
APACHE SPARK STREAMING 2025
UPDATED EXAM QUESTIONS WITH
ANSWERS ALREADY GRADED A+
What is the primary reason for the need for streaming big data
processing? - CORRECT ANSWER>>>>Data is being created at
unprecedented rates, with exponential growth from mobile, web, and
social sources.
What was the projected number of connected devices by 2020? -
CORRECT ANSWER>>>>50 billion connected devices.
What is the annual growth rate of datacenter IP traffic? - CORRECT
ANSWER>>>>25% annually.
What are the two main components of Big Data in the past? -
CORRECT ANSWER>>>>Volume and Variety.
What additional component has been added to the definition of Big Data
in the present? - CORRECT ANSWER>>>>Velocity.
What are the time to insight differences between batch processing and
stream processing? - CORRECT ANSWER>>>>Batch processing has a
time to insight of hours, while stream processing has a time to insight of
seconds.
What are the key requirements for a streaming system? - CORRECT
ANSWER>>>>Scalability to large clusters, second-scale latencies, a
simple programming model, integration with batch and interactive
processing, and efficient fault-tolerance in stateful computations.
1
,What is the purpose of a streaming architecture? - CORRECT
ANSWER>>>>To handle stream processing by taking action on data at
the moment it is accepted.
Which technology commonly acts as the store for incoming streaming
data in modern deployments? - CORRECT ANSWER>>>>Apache
Kafka.
What is Spark Streaming? - CORRECT ANSWER>>>>An extension of
the core Spark API that enables scalable high-throughput, fault-tolerant
stream processing of live data streams.
What high-level functions can be used in Spark Streaming? - CORRECT
ANSWER>>>>Map, reduce, join, and window.
What types of algorithms can be applied to data streams in Spark
Streaming? - CORRECT ANSWER>>>>Machine learning and graph
processing algorithms.
What is the difference between Kafka and stream processing systems? -
CORRECT ANSWER>>>>Kafka is primarily a message-processing
system that passes messages from producers to consumers without
modification, while stream processing systems analyze and transform
data.
What are the key components of streaming in Hadoop? - CORRECT
ANSWER>>>>Real-time data serving, data ingestion and transportation
service, real-time stream processing engine, security, system
management, and data management & integration.
What is the canonical Hadoop stream processing architecture composed
of? - CORRECT ANSWER>>>>HDFS, HBase, data sources, data
ingestion, and applications.
2
, What is the Lambda architecture? - CORRECT ANSWER>>>>An
architectural paradigm to handle both batch and streaming data in
parallel.
What are the benefits of Lambda architecture? - CORRECT
ANSWER>>>>Combines batch processing with stream processing,
keeps raw information forever, and allows rerunning analytics
operations on the entire dataset.
What is the significance of keeping raw information in the batch layer of
Lambda architecture? - CORRECT ANSWER>>>>It allows for
rerunning analytics operations if necessary, such as correcting errors or
applying better algorithms.
What is the role of Kafka in a streaming architecture? - CORRECT
ANSWER>>>>Kafka serves as a data ingestion and transportation
service that accepts messages from producers and passes them to
consumers.
What is the expected outcome of integrating Spark Streaming with batch
processing? - CORRECT ANSWER>>>>It allows for a unified
processing model that can handle both real-time and historical data.
What is the expected latency that Spark Streaming can achieve? -
CORRECT ANSWER>>>>Second-scale latencies.
How does Spark Streaming handle live data streams? - CORRECT
ANSWER>>>>It can absorb live data streams from sources like Kafka
and Flume.
What types of outputs can Spark Streaming produce? - CORRECT
ANSWER>>>>Processed data can be pushed out to filesystems,
databases, and live dashboards.
3
