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Sqoop and Impala



Sqoop is a automated volume data transfer tool which permits to simple import, export of data from structured data stores like NoSql systems, relational databases and enterprise data warehouses to Hadoop ecosystems.

Key features of Sqoop

It has following features:

  • JDBC based implementation
  • Auto generation of tedious user side code
  • Integration with hive
  • Extensible Backend

Why Sqoop

  • Forcing Map Reduce to access data from RDBMS is repetitive, error prone and costlier
  • Data needs to prepared for effective map reduce consumption

architecture of sqoop



It is an open source massively parallel processing (MPP) SQL query engine for data stored in a computer cluster running Apache Hadoop.

Goals of Impala

1. General purpose SQL query engine:

  • should work both for transactional and analytical workloads
  • will support queries that get from milliseconds to hours

2. Runs directly within Hadoop:

  • reads Hadoop file formats which are broadly used
  • talks to Hadoop storage managers which are extensively used
  • runs on same nodes that run Hadoop processes

3.  High performance:

  • Runtime code generation
  • Use C++ in place of Java
  • Completely new execution engine which does not build on MapReduce

architecture of impala

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