1. What is HBase primarily used for in the Hadoop ecosystem?
Answer:
Explanation:
HBase is a distributed, scalable, big data store that supports random, real-time read/write access, making it ideal for applications requiring high throughput and low latency.
2. HBase is built on top of which of the following Hadoop components?
Answer:
Explanation:
HBase is built on top of the Hadoop Distributed File System (HDFS) and provides Bigtable-like capabilities for Hadoop.
3. In HBase, what is a 'Column Family'?
Answer:
Explanation:
In HBase, a column family is a group of related columns that are stored together on disk. Each column family must be declared upfront when creating a table.
4. What does HBase use to ensure consistency in reads and writes?
Answer:
Explanation:
HBase uses Apache Zookeeper for coordination and maintaining consistency across its cluster, particularly for metadata storage and leader election.
5. Which of the following best describes an HBase 'RowKey'?
Answer:
Explanation:
In HBase, the RowKey is a unique identifier for a row within a table. It is used for fast data retrieval and plays a critical role in the table's data model design.
6. How does HBase handle data replication?
Answer:
Explanation:
HBase relies on the underlying HDFS replication mechanism to handle data replication, thereby ensuring data durability and high availability.
7. What type of database is HBase classified as?
Answer:
Explanation:
HBase is classified as a key-value store, where each row is identified by a unique key and stores its data as a set of key-value pairs in columns.
8. In HBase, what is a 'Region'?
Answer:
Explanation:
In HBase, a Region is a horizontally partitioned subset of a table's rows. Each Region is served by a RegionServer, and a large table is split into multiple Regions.
9. What is the role of a RegionServer in HBase?
Answer:
Explanation:
In HBase, a RegionServer is responsible for serving and managing Regions. It handles read, write, update, and delete requests for the Regions assigned to it.
10. Which of the following is true about HBase's scalability?
Answer:
Explanation:
HBase is designed to scale horizontally, meaning it can expand its capacity by adding more nodes to the cluster, thereby accommodating larger data sets and more traffic.
11. How does HBase ensure high availability?
Answer:
Explanation:
HBase ensures high availability by utilizing HDFS's built-in data replication mechanism. This approach helps in handling node failures and ensuring data is not lost.
12. What is the HBase shell primarily used for?
Answer:
Explanation:
The HBase shell is an interactive command-line tool used for executing administrative commands and queries against an HBase cluster.
13. Which language does HBase natively support for table manipulation and data retrieval?
Answer:
Explanation:
HBase natively supports Java for table manipulation and data retrieval, allowing developers to interact with HBase using its Java API.
14. What mechanism does HBase use for fault tolerance?
Answer:
Explanation:
HBase uses write-ahead logging (WAL) to ensure data integrity and fault tolerance. When a change is made, it is first recorded in the WAL before being applied to the actual data store.
15. What is the purpose of Compactions in HBase?
Answer:
Explanation:
Compactions in HBase merge smaller files (HFiles) into larger ones. This process improves read efficiency by reducing the number of files to scan.
16. In HBase, what is a 'Timestamp' used for?
Answer:
Explanation:
In HBase, each cell value is associated with a timestamp, which is used for versioning the data. This allows HBase to store multiple versions of a cell's value.
17. What type of data model does HBase follow?
Answer:
Explanation:
HBase follows the wide-column store model, organizing data in tables, rows, and dynamic columns. It is optimized for sparse data sets common in big data use cases.
18. How is data in HBase tables primarily accessed?
Answer:
Explanation:
In HBase, data in tables is primarily accessed using the RowKey. Efficient design of the RowKey is crucial for optimal performance and data retrieval.
19. What does the 'flush' command do in HBase?
Answer:
Explanation:
The 'flush' command in HBase forces the writing of data from the in-memory MemStore to disk as HFiles in a RegionServer, thereby persisting the data.
20. Can HBase be used without Hadoop?
Answer:
Explanation:
HBase is tightly integrated with Hadoop and requires HDFS for its storage layer. It cannot operate independently of Hadoop.
21. What is a Bloom filter in HBase?
Answer:
Explanation:
A Bloom filter in HBase is a probabilistic data structure used to efficiently test whether an element (like a RowKey) is present in a set. It helps in reducing unnecessary disk reads.
22. Which of the following is a feature of HBase's data model?
Answer:
Explanation:
HBase follows a schema-on-read data model, where the schema of the data is not enforced at write time but rather interpreted at read time.
23. How are updates handled in HBase?
Answer:
Explanation:
In HBase, updates are handled as new inserts with timestamps. Each cell in HBase can have multiple versions, with each update creating a new version of the cell.
24. What is the primary purpose of the HBase 'scan' command?
Answer:
Explanation:
The 'scan' command in HBase is used to perform a sequential read of data from a table, based on specified criteria such as start and stop row keys.
25. How does HBase handle large-scale data distribution?
Answer:
Explanation:
HBase handles large-scale data distribution by horizontally partitioning the data into Regions, and each Region is distributed and served by different RegionServers across the cluster. This ensures scalability and load balancing.