____ is the process by which HDFS ensures that each data block has the correct number of replicas.
- Balancing
- Redundancy
- Replication
- Synchronization
Replication is the process by which HDFS ensures that each data block has the correct number of replicas. This helps in achieving fault tolerance by storing multiple copies of data across different nodes in the cluster.
In Cascading, what does a 'Tap' represent in the data processing pipeline?
- Data Partition
- Data Transformation
- Input Source
- Output Sink
In Cascading, a 'Tap' represents an input source or output sink in the data processing pipeline. It serves as a connection to external data sources or destinations, allowing data to flow through the Cascading application for processing.
In Hadoop, which InputFormat is ideal for processing structured data stored in databases?
- AvroKeyInputFormat
- DBInputFormat
- KeyValueTextInputFormat
- TextInputFormat
DBInputFormat is ideal for processing structured data stored in databases in Hadoop. It allows Hadoop MapReduce jobs to read data from relational database tables, providing a convenient way to integrate Hadoop with structured data sources.
Which command in Sqoop is used to import data from a relational database to HDFS?
- sqoop copy
- sqoop import
- sqoop ingest
- sqoop transfer
The command used to import data from a relational database to HDFS in Sqoop is 'sqoop import.' This command initiates the process of transferring data from a source database to the Hadoop ecosystem for further analysis and processing.
In complex data pipelines, how does Oozie's bundling feature enhance workflow management?
- Consolidates Workflows
- Enhances Fault Tolerance
- Facilitates Parallel Execution
- Optimizes Resource Usage
Oozie's bundling feature in complex data pipelines enhances workflow management by consolidating multiple workflows into a single unit. This simplifies coordination and execution, making it easier to manage and monitor complex data processing tasks efficiently.
____ is the process in Hadoop that ensures no data loss in case of a DataNode failure.
- Data Compression
- Data Encryption
- Data Replication
- Data Shuffling
Data Replication is the process in Hadoop that ensures no data loss in case of a DataNode failure. Hadoop replicates data across multiple DataNodes, and if one node fails, the replicated data on other nodes can be used, preventing data loss.
The integration of Apache Pig with ____ allows for enhanced data processing and analysis in Hadoop.
- Apache HBase
- Apache Hive
- Apache Mahout
- Apache Spark
The integration of Apache Pig with Apache Spark allows for enhanced data processing and analysis in Hadoop. Apache Spark provides in-memory processing and advanced analytics capabilities, complementing Pig's data processing capabilities and enabling more sophisticated data workflows.
For a complex data transformation task involving multiple data sources, which approach in Hadoop ensures both efficiency and accuracy?
- Apache Flink
- Apache Nifi
- Apache Oozie
- Apache Sqoop
In complex data transformation tasks involving multiple data sources, Apache Sqoop is a preferred approach. Sqoop facilitates efficient and accurate data transfer between Hadoop and relational databases, ensuring seamless integration of diverse data sources for comprehensive transformations.
The process of ____ is key to maintaining the efficiency of a Hadoop cluster as data volume grows.
- Data Indexing
- Data Replication
- Data Shuffling
- Load Balancing
Load Balancing is key to maintaining the efficiency of a Hadoop cluster as data volume grows. It ensures that the computational load is evenly distributed among the nodes in the cluster, preventing any single node from becoming a bottleneck.
In the Hadoop ecosystem, which tool is best known for data ingestion from various sources into HDFS?
- Flume
- HBase
- Pig
- Sqoop
Sqoop is the tool in the Hadoop ecosystem best known for data ingestion from various sources into HDFS. It simplifies the transfer of data between Hadoop and relational databases, facilitating the import and export of data in a Hadoop cluster.