Why is Fetch task in Hive works faster than Map-only task?

FetchTask directly fetches data, whereas Mapreduce will invoke a map reduce job

<property>
  <name>hive.fetch.task.conversion</name>
  <value>minimal</value>
  <description>
    Some select queries can be converted to single FETCH task 
    minimizing latency.Currently the query should be single 
    sourced not having any subquery and should not have
    any aggregations or distincts (which incurrs RS), 
    lateral views and joins.
    1. minimal : SELECT STAR, FILTER on partition columns, LIMIT only
    2. more    : SELECT, FILTER, LIMIT only (+TABLESAMPLE, virtual columns)
  </description>
</property>

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Also there is another parameter hive.fetch.task.conversion.threshold which by default in 0.10-0.13 is -1 and >0.14 is 1G(1073741824) This indicates that, If table size is greater than 1G use Mapreduce instead of Fetch task

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