If you're looking for MapReduce Interview Questions for Experienced or Freshers, you are at right place. There are lot of opportunities from many reputed compan…
Creation of REPOSITORY in BODS:- Creation of User in HANA:- Log on to SAP HANA Studio Go to HANAS System Go to Secur…
Job Operations Submitting a workflow, coordinator or Bundle Job: Submitting Bundle feature is only supported in zones 3.0 or later. Similarly, all Bundle OP…
MapReduce in Geographically Distributed Environments The performance of MAPREDUCE across geographically distributed environments is highly dependent upon the a…
H Base Vs RDBMS: H BASE and other column-oriented DATABASE are often compared to more traditional and popular relational database or RDBMS. H Base…
HBase HBASE will come into picture, when Hadoop is stopped. HBase is an open source, non-relational, distributed database which is built on top to HDFS. …
History MapReduce was first popularized as a programming model in 2004 by Jeffery Dean and Sanjay Ghemawat of Google (Dean & Ghemawat, 2004). In their paper, “…
Pig provides extensive support for USER DEFINED FUNCTIONS as a way to specify custom processing. PIG UDF’s can currently be implemented in three languages li…
Execution Types Pig has two EXECUTION TYPES or run modes, local and Hadoop (currently called MapReduce) Local mode Map Reduce mode. 1) Local mode …
MapReduce Implementation Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that…
Introduction to Pig APACHE PIG is one of the major components of hadoop which is an abstract layer (high level) on the top of MAPREDUCE. Apache pig is meant…
Importing Data from using an RDBMS:- To connect to Mysql Database /home# Mysql-u root-p Enter Password: After successful login, it will prom…
MapReduce Programming Model Google’s MAPREDUCE IS A PROGRAMMING MODEL serves for processing large data sets in a massively parallel manner. We deliver the firs…
Hadoop Sqoop SQOOP is a tool designed to transfer data between Hadoop and relational databases. We can use sqoop to import data from a relational database m…
Counters in Hadoop MapReduce MAP REDUCE COUNTER provides a way to measure the progress or the number of operations that occur within MAP REDUCE programs. …
MapReduce Architecture Each node is part of an HDFS CLUSTER. Input data is stored in HDFS Spread across nodes and replicated. Programmer submits a job…
MapReduce is a soft work framework for easily writing applications which process vast amounts of data (multi terabytes) in- parallel on large clusters of comm…
Today, the enterprise data is generating at a rapid rate, and how we make use of this data for the development of a company matters a lot. Hadoop is evolvin…
In order to understand the goals of MapReduce, it is important to realize for which scenarios MapReduce is optimized. The MapReduce programming model is created…
HDFS Data storage Reliability The important objective of HDFS is to store data reliably, even when features occur with Name Nodes, data nodes or network part…
Organizations collect many types of data about the processes they support: marketing, operational, activity logging, etc. For example, “click stream” and log da…
[HDFS] Hadoop Distributed File System When a data set out grows the storage capacity of a single physical machine, it becomes necessary to partition it acros…
Introduction When it comes to dealing with a massive amount of data from social media, businesses, sports, research, healthcare, or any other relevant source, …
If you're looking for MapReduce Interview Questions for Experienced or Freshers, you are at right place. There are lot of opportunities from many reputed compan…
Creation of REPOSITORY in BODS:- Creation of User in HANA:- Log on to SAP HANA Studio Go to HANAS System Go to Secur…
Job Operations Submitting a workflow, coordinator or Bundle Job: Submitting Bundle feature is only supported in zones 3.0 or later. Similarly, all Bundle OP…
MapReduce in Geographically Distributed Environments The performance of MAPREDUCE across geographically distributed environments is highly dependent upon the a…
H Base Vs RDBMS: H BASE and other column-oriented DATABASE are often compared to more traditional and popular relational database or RDBMS. H Base…
HBase HBASE will come into picture, when Hadoop is stopped. HBase is an open source, non-relational, distributed database which is built on top to HDFS. …
History MapReduce was first popularized as a programming model in 2004 by Jeffery Dean and Sanjay Ghemawat of Google (Dean & Ghemawat, 2004). In their paper, “…
Pig provides extensive support for USER DEFINED FUNCTIONS as a way to specify custom processing. PIG UDF’s can currently be implemented in three languages li…
Execution Types Pig has two EXECUTION TYPES or run modes, local and Hadoop (currently called MapReduce) Local mode Map Reduce mode. 1) Local mode …
MapReduce Implementation Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that…
Introduction to Pig APACHE PIG is one of the major components of hadoop which is an abstract layer (high level) on the top of MAPREDUCE. Apache pig is meant…
Importing Data from using an RDBMS:- To connect to Mysql Database /home# Mysql-u root-p Enter Password: After successful login, it will prom…
MapReduce Programming Model Google’s MAPREDUCE IS A PROGRAMMING MODEL serves for processing large data sets in a massively parallel manner. We deliver the firs…
Hadoop Sqoop SQOOP is a tool designed to transfer data between Hadoop and relational databases. We can use sqoop to import data from a relational database m…
Counters in Hadoop MapReduce MAP REDUCE COUNTER provides a way to measure the progress or the number of operations that occur within MAP REDUCE programs. …
MapReduce Architecture Each node is part of an HDFS CLUSTER. Input data is stored in HDFS Spread across nodes and replicated. Programmer submits a job…
MapReduce is a soft work framework for easily writing applications which process vast amounts of data (multi terabytes) in- parallel on large clusters of comm…
Today, the enterprise data is generating at a rapid rate, and how we make use of this data for the development of a company matters a lot. Hadoop is evolvin…
In order to understand the goals of MapReduce, it is important to realize for which scenarios MapReduce is optimized. The MapReduce programming model is created…
HDFS Data storage Reliability The important objective of HDFS is to store data reliably, even when features occur with Name Nodes, data nodes or network part…
Organizations collect many types of data about the processes they support: marketing, operational, activity logging, etc. For example, “click stream” and log da…
[HDFS] Hadoop Distributed File System When a data set out grows the storage capacity of a single physical machine, it becomes necessary to partition it acros…
Introduction When it comes to dealing with a massive amount of data from social media, businesses, sports, research, healthcare, or any other relevant source, …