Realtime Processing With Apache Spark MCQ

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• Hive, Pig, and Cascading all use a . . . . . . . . data model.
  ক

  value centric

  খ

  columnar

  গ

  tuple-centric

  ঘ

  none of the mentioned
• The . . . . . . . . class allows developers to exercise precise control over how data is partitioned, sorted, and grouped by the underlying execution engine.
  ক

  Grouping

  খ

  GroupingOptions

  গ

  RowGrouping

  ঘ

  None of the mentioned
• GraphX provides an API for expressing graph computation that can model the . . . . . . . . abstraction.
  ক

  GaAdt

  খ

  Spark Core

  গ

  Pregel

  ঘ

  None of the mentioned
• DoFns provide direct access to the . . . . . . . . object that is used within a given Map or Reduce task via the getContext method.
  ক

  TaskInputContext

  খ

  TaskInputOutputContext

  গ

  TaskOutputContext

  ঘ

  All of the mentioned
• You can write to a single partition by specifying the partition key(s) and value(s) in the . . . . . . . . method.
  ক

  setOutput

  খ

  setOut

  গ

  put

  ঘ

  get
• Hive does not have a data type corresponding to the . . . . . . . . type in Pig.
  ক

  decimal

  খ

  short

  গ

  biginteger

  ঘ

  datetime
• . . . . . . . . is a distributed machine learning framework on top of Spark.
  ক

  MLlib

  খ

  Spark Streaming

  গ

  GraphX

  ঘ

  RDDs
• . . . . . . . . mode is used when you just have a single server and want to launch all the daemon processes.
  ক

  Local Mode

  খ

  Pseudo Distributed Mode

  গ

  Distributed Mode

  ঘ

  All of the mentioned
• Apache . . . . . . . . provides direct queries on self-describing and semi-structured data in files.
  ক

  Drill

  খ

  Mahout

  গ

  Oozie

  ঘ

  All of the mentioned
• . . . . . . . . is a distributed graph processing framework on top of Spark.
  ক

  MLlib

  খ

  Spark Streaming

  গ

  GraphX

  ঘ

  All of the mentioned
• During merging, . . . . . . . . now always checks the incoming segments for corruption before merging.
  ক

  LocalWriter

  খ

  IndexWriter

  গ

  ReadWriter

  ঘ

  All of the mentioned
• A key of type . . . . . . . . is generated which is used later to join ngrams with their heads and tails in the reducer phase.
  ক

  GramKey

  খ

  Primary

  গ

  Secondary

  ঘ

  None of the mentioned
• The Avros class also has a . . . . . . . . method for creating PTypes for POJOs using Avro's reflection-based serialization mechanism.
  ক

  spot

  খ

  reflects

  গ

  gets

  ঘ

  all of the mentioned
• Drill provides a . . . . . . . . like internal data model to represent and process data.
  ক

  XML

  খ

  JSON

  গ

  TIFF

  ঘ

  None of the mentioned
• . . . . . . . . method is used to include a projection schema, to specify the output fields.
  ক

  OutputSchema

  খ

  setOut

  গ

  setOutputSchema

  ঘ

  none of the mentioned
• Hama is a general . . . . . . . . computing engine on top of Hadoop.
  ক

  BSP

  খ

  ASP

  গ

  MPP

  ঘ

  None of the mentioned
• Spark includes a collection over . . . . . . . . operators for transforming data and familiar data frame APIs for manipulating semi-structured data.
  ক

  50

  খ

  60

  গ

  70

  ঘ

  80
• Mahout provides . . . . . . . . libraries for common and primitive Java collections.
  ক

  Java

  খ

  Javascript

  গ

  Perl

  ঘ

  Python
• Hama requires JRE . . . . . . . . or higher and ssh to be set up between nodes in the cluster.
  ক

  1.6

  খ

  1.7

  গ

  1.8

  ঘ

  2.0
• . . . . . . . . is responsible for maintaining groom server status.
  ক

  GroomServers

  খ

  BSPMaster

  গ

  Zookeeper

  ঘ

  All of the mentioned
• Lucene provides scalable, high-Performance indexing over . . . . . . . . per hour on modern hardware.
  ক

  1 TB

  খ

  150GB

  গ

  10 GB

  ঘ

  None of the mentioned
• . . . . . . . . executes the pipeline as a series of MapReduce jobs.
  ক

  SparkPipeline

  খ

  MRPipeline

  গ

  MemPipeline

  ঘ

  None of the mentioned
• . . . . . . . . is a human-readable text format to aid in debugging.
  ক

  TMemory

  খ

  TDebugProtocol

  গ

  TBinaryProtocol

  ঘ

  TSimpleJSONProtocol
• HCatalog maintains a cache of . . . . . . . . to talk to the metastore.
  ক

  HiveServer

  খ

  HiveClients

  গ

  HCatClients

  ঘ

  All of the mentioned
• Apache Hama provides complete clone of . . . . . . . .
  ক

  Pragmatic

  খ

  Pregel

  গ

  ServePreg

  ঘ

  All of the mentioned
• . . . . . . . . property allows us to specify a custom dir location pattern for all the writes, and will interpolate each variable.
  ক

  hcat.dynamic.partitioning.custom.pattern

  খ

  hcat.append.limit

  গ

  hcat.pig.storer.external.location

  ঘ

  hcatalog.hive.client.cache.expiry.time
• For Scala users, there is the . . . . . . . . API, which is built on top of the Java APIs.
  ক

  Prunch

  খ

  Scrunch

  গ

  Hivench

  ঘ

  All of the mentioned
• Crunch uses Java serialization to serialize the contents of all of the . . . . . . . . in a pipeline definition.
  ক

  Transient

  খ

  DoFns

  গ

  Configuration

  ঘ

  All of the mentioned
• MapR . . . . . . . . Solution Earns Highest Score in Gigaom Research Data Warehouse Interoperability Report.
  ক

  SQL-on-Hadoop

  খ

  Hive-on-Hadoop

  গ

  Pig-on-Hadoop

  ঘ

  All of the mentioned
• A . . . . . . . . represents a distributed, immutable collection of elements of type T.
  ক

  PCollect<T>

  খ

  PCollection<T>

  গ

  PCol<T>

  ঘ

  All of the mentioned