IBM Big Data Engineer (C2090-101) Certification Sample Questions

Big Data Engineer Dumps, C2090-101 Dumps, C2090-101 PDF, Big Data Engineer VCE, IBM C2090-101 VCEThe purpose of this Sample Question Set is to provide you with information about the IBM Big Data Engineer exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the C2090-101 certification test. To get familiar with real exam environment, we suggest you try our Sample IBM Big Data Engineer Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual IBM Certified Data Engineer - Big Data certification exam.

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IBM C2090-101 Sample Questions:

01. When you configure a Map Reduce job, the inputs can include:
a) A single file
b) Paths to one or more directories
c) A file pattern (e.g., mypath/*.csv)
d) All of the above
 
02. What is a method for loading RDBMS data into an HBase table?
a) HDFSLOAD
b) SQOOP IMPORT
c) LOAD HADOOP USING
d) hadoop jar hbase-VERSIONjar importtsv
 
03. Which statement is TRUE concerning optimizing the load performance?
a) You can improve the performance by increasing the number of map tasks assigned to the load
b) When loading large files the number of files that you load does not impact the performance of the LOAD HADOOP statement
c) You can improve the performance by decreasing the number of map tasks that are assigned to the load and adjusting the heap size
d) It is advantageous to run the LOAD HADOOP statement directly pointing to large files located in the host file system as opposed to copying the files to the DFS prior to load
 
04. How are insights derived from Big Match moved to an MDM system?
a) Extract insights from HBase and load into MDM through an API call
b) Extract insights from Hive and load into MDM using standard tooling
c) Extract insights from HDFS and load into MDM by simulating delta load
d) Extract insights from HBase and load into MDM using standard MDM batch processing tool
 
05. Which of the following are capabilities of the Apache Spark project?
a) Large scale graph processing
b) Large scale machine learning
c) Live data stream processing
d) All of the above
 
06. A Resilient Distributed Dataset supports which of the following?
a) Creating a new dataset from an old one
b) Returning a computed value to the driver program
c) Both Returning a computed value to the driver program and Creating a new dataset from an old one
d) Neither Creating a new dataset from an old one nor Returning a computed value to the driver program
 
07. When we create a new table in Hive, which clause can be used in HiveQL to indicate the storage file format?
a) SAVE AS
b) MAKE AS
c) FORMAT AS
d) STORED AS
 
08. Use of Bulk Load in HBase for loading large volume of data will result in which of the following?
a) It will use less CPU but will use more network resource
b) It will use less network resource but more CPU
c) It will behave same way as using HBase API for loading large volume of data
d) None of the above
 
09. Which ONE of the following statements regarding Sqoop is TRUE?
a) HBase is not supported as an import target
b) Data imported using Sqoop is always written to a single Hive partition
c) Sqoop can be used to retrieve rows newer than some previously imported set of rows
d) Sqoop can only append new rows to a database table when exporting back to a database
 
10. The number of partitions created by Dynamic Partitions in Hive can be controlled by which of the following?
a) hive.exec.max.dynamic.partitions
b) hive.exec.max.dynamic.partitions.pernode
c) hive.exec.max.created.files
d) All of the above

Answers:

Question: 01
Answer: a
Question: 02
Answer: d
Question: 03
Answer: a
Question: 04
Answer: c
Question: 05
Answer: b
Question: 06
Answer: d
Question: 07
Answer: c
Question: 08
Answer: a
Question: 09
Answer: c
Question: 10
Answer: b

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