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| Section | Weight | Objectives |
|---|---|---|
| Apache Hive Development | 35% | - Hive architecture, metastore, and table management - HiveQL queries, joins, aggregations, and partitioning - Performance tuning and indexing - Data types, serialization, and file formats |
| Apache Pig Development | 40% | - Integration with HCatalog and Hive - Data transformation, filtering, grouping, and joining - User-defined functions (UDFs) and optimization - Pig Latin syntax, data loading, and storage |
| Hadoop Fundamentals & HDFS | 20% | - Hadoop 2.0 architecture & YARN - HDFS file operations, permissions, and data management |
| Data Ingestion & Ecosystem Integration | 5% | - Sqoop and Flume usage basics - Workflow orchestration with Oozie |
1. Which TWO of the following statements are true regarding Hive? Choose 2 answers
A) Offers real-time queries and row level updates
B) Allows you to define a structure for your unstructured Big Data
C) Is a relational database
D) Useful for data analysts familiar with SQL who need to do ad-hoc queries
2. You have a directory named jobdata in HDFS that contains four files: _first.txt, second.txt, .third.txt and
# data.txt. How many files will be processed by the FileInputFormat.setInputPaths () command when it's
given a path object representing this directory?
A) None, the directory cannot be named jobdata
B) One, no special characters can prefix the name of an input file
C) Three, the pound sign is an invalid character for HDFS file names
D) Four, all files will be processed
E) Two, file names with a leading period or underscore are ignored
3. How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?
A) Keys are presented to reducer in sorted order; values for a given key are not sorted.
B) Keys are presented to reducer in sorted order; values for a given key are sorted in ascending order.
C) Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
D) Keys are presented to a reducer in random order; values for a given key are not sorted.
4. Which describes how a client reads a file from HDFS?
A) The client contacts the NameNode for the block location(s). The NameNode then queries the
DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects
the client to the DataNode that holds the requested data block(s). The client then reads the data directly
off the DataNode.
B) The client queries the NameNode for the block location(s). The NameNode returns the block location(s)
to the client. The client reads the data directory off the DataNode(s).
C) The client queries all DataNodes in parallel. The DataNode that contains the requested data responds
directly to the client. The client reads the data directly off the DataNode.
D) The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode
that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then
from the NameNode to the client.
5. Which of the following tool was designed to import data from a relational database into HDFS?
A) Sqoop
B) Flume
C) HCatalog
D) Ambari
Solutions:
| Question # 1 Answer: B,D | Question # 2 Answer: E | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |
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