Hadoop Installation



If you are working with Windows Then Follow These Steps Else If(Linux) you can skip to hadoop installation.


Download VMWare: VMWare


Properties To Be Modified As Following:


RAM-4GB

ROM(MEMORY)-30GB

CORES-4


ISO FILE LINK: https://ubuntu.com/download/desktop/thank-you?version=22.04.2&architecture=amd64


Accept all permissions and start using Linux.



Hadoop Installation:Hadoop Installation Steps

Comments

Post a Comment

Popular posts from this blog

MR(Map Reduce)

Image
Introduction to Map Reduce It's a massive parallel processing framework In general without distributed data it's hard to do parallel processing. Map Reduce uses Java by default The aim of Map Reduce is to achieve data locality and Parallelism. Spark is an alternative for Map Reduce(functionality has 80% similarity) Hive, Sqoop, Pig, Oozie are abstract of Map Reduce. Daemons in Map Reduce are JT and TT. In map reduce we also have two functionalities called Mapper and Reducer which are responsible for achieving the processing. The MR has an disadvantage of Resource Pressure. Advantages of Map Reduce Cluster Monitoring Cluster Management Resource Allocating Scheduling Execution Speculative Execution(L) Working Principle of Map Reduce The task for the MR is given in the form of ZAR(java) file to the Job Tracker. The Job Tracker will be sending the request to the Name Node and in return it gives response. Then the Job Tracker will be sending the task information to Task Tracker. The
Read more

Spark Yarn Cluster

Image
  Spark Submit Cluster(Yarn)->(Hadoop+Spark) Spark Lens Integration is a profiling tool to check the memory allocation(executor memory, etc.) Spark has Hash Partition which is the same algorithm used by MapReduce also. Map(Parallelism which acts as input), Reduce(Aggregation which acts as output) No of blocks=No of tasks when it is HDFS. No of O/P tasks=No of I/P tasks Spark uses the algorithm called hash partition to decide which particular output partition should be set to particular output task. Hash Partition(output partition)=(Hash of the key)%(No of output task count) Few Commands data.getNumPartitions    (It is used to get no of partitions) reducedata.repartition(3).saveAsTextFile("out.txt"); Removing Null Values df.dropna(how="any").show() #removes row if any one column is null df.dropna(how="all").show() #removes row if all columns are null df.dropna(how="any",subset=["salary"]).show() #removes column if any null value is fo
Read more