HBase DATA-SCIENCE-OPTIMIZE Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which of the following is a best practice for designing HBase row keys?

   • AUse a monotonically increasing counter as the row key to ensure even distribution.
   • BUse the same row key for all rows in a table to simplify access.
   • CDesign row keys to spread writes across multiple regions to avoid hot spotting.
   • DKeep row keys as long as possible to store more data in each row.
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   A startup is building a real-time recommendation system that needs to serve user preferences with sub-millisecond latency. The dataset is large (hundreds of terabytes) and grows continuously. Which storage solution is most appropriate?

   • AA relational database like MySQL
   • BHBase
   • CApache Hive on HDFS
   • DHDFS with Parquet files
   Reveal Solution Discussion Select an answer first
4. 18application · hard

   An HBase administrator notices that reads of recently written data are slow, but reads of older data are fast. The cluster has enough memory. What is the most likely cause and solution?

   • AThe BlockCache is too small; increase the BlockCache size
   • BThe MemStore is not being flushed; force a flush
   • CThe WAL is causing a bottleneck; disable the WAL
   • DThe data is being read from HDFS instead of the MemStore; enable in-memory compaction
   Reveal Solution Discussion Select an answer first
5. 19application · medium

   A social media analytics platform stores user event data in HBase. Each event has a user ID, a timestamp, and various attributes. The team needs to query all events for a specific user within a given time range. Which row key design best supports this access pattern?

   • ARow key = random UUID
   • BRow key = event timestamp + user ID
   • CRow key = event type + user ID
   • DRow key = user ID + event timestamp
   Reveal Solution Discussion Select an answer first
6. 20foundation · easy

   Which scenario is most appropriate for using HBase?

   • AStoring and processing large files in a batch-oriented manner.
   • BComplex multi-table joins and transactions with strict ACID guarantees.
   • CRunning ad-hoc analytical queries with complex aggregations over large datasets.
   • DReal-time random read/write access to a large dataset with millions of rows.
   Reveal Solution Discussion Select an answer first