Big Data Technologies Flashcards
7 cards from real DSE practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 7 Big Data Technologies flashcards as text
Which consistency model does Apache Cassandra use by default to optimize for availability?
Answer: Eventual consistency
Cassandra defaults to eventual consistency, trading strict consistency for high availability and partition tolerance in line with the CAP theorem.
What does the term 'hot partition' mean in a distributed NoSQL system?
Answer: A partition receiving disproportionately high read or write traffic, creating a bottleneck
A hot partition occurs when one partition key attracts far more traffic than others, overloading the node responsible for that partition.
In Apache Spark, what is a 'shuffle' operation?
Answer: Redistributing data across partitions, typically during wide transformations like groupBy or join
A shuffle redistributes data across the network to group records with the same key onto the same partition, and is one of the most expensive Spark operations.
What is Apache NiFi primarily designed for?
Answer: Automating and managing data flow between systems with a visual interface
Apache NiFi provides a web-based graphical interface for designing, managing, and monitoring data flows between systems with built-in provenance tracking.
Which of the following best describes a Delta Lake?
Answer: An open-source storage layer that adds ACID transactions and versioning to data lakes
Delta Lake is an open-source storage layer that brings ACID transactions, schema enforcement, and time-travel versioning to data lakes built on cloud object storage.
What is 'compaction' in Apache Cassandra?
Answer: Merging SSTables on disk to reclaim space and improve read performance
Compaction merges multiple SSTables into fewer, larger ones, removing deleted or overwritten data (tombstones) and improving read efficiency.
In the context of stream processing, what is 'watermarking' used for?
Answer: Handling late-arriving events by defining how long the system waits before closing a time window
Watermarks define the maximum lateness a stream processor will tolerate, after which a time window is finalized and late data is either dropped or handled separately.