IBM C2090-101 Online Practice Questions and Exam Preparation

IBM C2090-101 Online Questions & Answers

• Question 31:

  Which one of the following file formats is optimal for querying tables with many columns and performing aggregation operations such as SUM() and AVG()?

  A. Text
  B. Avro
  C. JSON
  D. PARQUET
  C. JSON

• Question 32:

  When indexing a Hive Table, which of the following is TRUE?

  A. Hive tables do not support indexes
  B. It increases query speed without the need for additional disk space
  C. It does not increase query speed but makes data insert/delete/update faster
  D. It increases query speed but requires additional processing time for data insert/update/delete and needs more disk space
  B. It increases query speed without the need for additional disk space

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  Reference: https://acadgild.com/blog/indexing-in-hive

• Question 33:

  Which one of the following statements is TRUE?

  A. Spark SQL does not support HiveQL
  B. Spark SQL does not support ANSI SQL
  C. To use Spark with Hive, HiveQL queries have to rewritten in Scala
  D. Spark SQL allows relational queries expressed in SQL, HiveQL, or Scala
  D. Spark SQL allows relational queries expressed in SQL, HiveQL, or Scala

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  Reference: https://spark.apache.org/docs/1.2.1/sql-programming-guide.html (overview)

• Question 34:

  Which of the following Big SQL statements is valid?

  A. CREATE TABLE t1 WITH CS;
  B. WITH t1 AS (...) (SELECT * FROM t1 WITH RR USE AND KEEP SHARE LOCKS) UNION ALL (SELECT * FROM t1 WITH UR);
  C. SELECT deptno, deptname, mgrno FROM t1 WHERE admrdept =`A00' FOR READ ONLY WITH RS USE AND KEEP EXCLUSIVE LOCKS
  D. ALTER TABLE t1 ALTER COLUMN deptname SET DATA TYPE VARCHAR(100) USE AND KEEP UPDATE LOCKS
  C. SELECT deptno, deptname, mgrno FROM t1 WHERE admrdept =`A00' FOR READ ONLY WITH RS USE AND KEEP EXCLUSIVE LOCKS

• Question 35:

  Which Big SQL file format could be expected to result in a longer running query?

  A. Text
  B. Avro
  C. Parquet
  D. Sequence_text
  C. Parquet

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  Reference: https://www.ibm.com/developerworks/data/library/techarticle/dm-1510-parquet-big-sql/index.html

• Question 36:

  For what purpose SPSS models are embedded within InfoSphere Streams application?

  A. To provide high availability
  B. To score streaming data using existing models
  C. To create new models based on streaming data
  D. To ingest and parse binary and other complex data types
  B. To score streaming data using existing models

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  Reference: https://www.ibm.com/developerworks/data/tutorials/dm-1109spssscoringinfospherestreams1/dm-1109spssscoringinfospherestreams1-pdf.pdf

• Question 37:

  Which of the following statements regarding importing streaming data from InfoSphere Streams into Hadoop is TRUE?

  A. InfoSphere Streams utilized Spark Streaming to interface to Hadoop
  B. The HDFS operators in InfoSphere Streams use Hadoop Java APIs to access HDFS or GPFS
  C. Incoming streams from InfoSphere Streams into Hadoop are not buffered to ensure low latency
  D. Since InfoSphere Streams processes data in Streams tuple format, Hadoop must store the data in this format
  B. The HDFS operators in InfoSphere Streams use Hadoop Java APIs to access HDFS or GPFS

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  Reference: https://www.ibm.com/support/knowledgecenter/en/SSCRJU_4.0.1/com.ibm.streams.toolkits.doc/doc/tk$com.ibm.streamsx.hdfs/tk$com.ibm.streamsx.hdfs.html

• Question 38:

  In which of the following the Flume open-source software is written?

  A. C / C++
  B. Primarily Java
  C. Python and related tools
  D. A combination of C++ and Perl
  B. Primarily Java

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  Reference: https://en.wikipedia.org/wiki/Apache_Flume

• Question 39:

  Which expression is making proper use of the "LOAD" function in Pig Latin?

  A. A = LOAD data -> name,age,gpa
  B. A = LOAD('data',[name, age, gpa]);
  C. A = LOAD 'data' -> {name:chararray, age:int, gpa:float};
  D. A = LOAD 'data' AS (name:chararray, age:int, gpa:float);
  D. A = LOAD 'data' AS (name:chararray, age:int, gpa:float);

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  Reference: https://pig.apache.org/docs/r0.17.0/basic.html

• Question 40:

  What is the primary purpose of Flume in the Hadoop ecosystem?

  A. To stream data from Hadoop
  B. To move static files from the local file system into HDFS
  C. To import data from a relational database or data warehouse into HDFS
  D. To capture log data as it is written to log files and move them into HDFS
  C. To import data from a relational database or data warehouse into HDFS

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  Reference: https://blogs.apache.org/flume/entry/flume_ng_architecture