Linux Commands | Miscellaneous | Part 2

-
Linux commands | Miscellaneous

Comments

Post a Comment

Popular posts from this blog

Parallel Database design, query processing

-
Image
Parallel Database design, query processing, and case study In this post, we are going to analyze the concepts of Parallel Database design, query processing, and case study. Parallel database design Hardware Architecture Data partitioning Query processing Hardware Architecture Shared Memory Shared Disk> Shared Nothing Data Partitioning Partitioning a relation involves distributing its tuples over several disks Three Kinds – Range Partitioning Round-robin Partitioning Hashing Partitioning Range Partitioning is good for Ideal for point and range queries on the partitioning attribute Hash partitioning Ideal for point queries based on the partitioning attribute Ideal for sequential sca...
Read more

Starting with Apache Hadoop

-
Image
Starting with Apache Hadoop In Hadoop, a single master is managing many slaves The master node consists of a JobTracker , Tasktracker , NameNode , and DataNode . A slave or worker node acts as both DataNode and TaskTracker though it is possible to have data-only worker node, and compute-only workerNodes. NameNode holds the file system metadata. The files are broken up and spread over the DataNode and JobTracker schedules and the manager's job. The TaskTracker executes the individual map and reduced function. If a machine fails, Hadoop continues to operate the cluster by shifting work to the remaining machines. The input file, which resides on a distributed file system throughout the cluster, is split into even-sized chunks replicated for fault tolerance. Haddopp divides each map to reduce jobs into a set of tasks. Each chunk of input is processed by a map task, which outputs a list of key-value pairs. In Hadoop, the shuffle phase o...
Read more

Apache Hadoop | Use Case | Association Rule Mapping | Part 1

-
Apache Hadoop | Use Case | Association Rule Mapping | Part 1 The classes required to run a Hadoop application: org.apache.zookeeper.*; org.apache.log4j.*; org.apache.hadoop.conf.Configuration; org.apache.hadoop.fs.Path; org.apache.hadoop.hbase.*; org.apache.hadoop.hbase.HBaseConfiguration; org.apache.hadoop.hbase.client.HTable; org.apache.hadoop.hbase.client.Put; org.apache.hadoop.hbase.client.Get; org.apache.hadoop.hbase.util.Bytes; org.apache.hadoop.hbase.client.Result; org.apache.hadoop.hbase.client.ResultScanner; org.apache.hadoop.hbase.client.Scan; org.apache.hadoop.io.IntWritable; org.apache.hadoop.io.LongWritable; org.apache.hadoop.io.ObjectWritable; org.apache.hadoop.io.Text; org.apache.hadoop.mapreduce.Job; org.apache.hadoop.mapreduce.Mapper; org.apache.hadoop.mapreduce.Reducer; org.apache.hadoop.mapreduce.lib.input.FileInputFormat; org.apache.hadoop.mapreduce.lib.input.TextInputFormat; org.apache.hadoop.mapreduce.lib.o...
Read more