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Introduction to hadoop
1.
Marc Cluet –
Lynx Consultants What’s behind Big Data
2.
What we’ll cover? ¡
Understand Hadoop components ¡ Understand different technologies involved ¡ Embrace Big Data! Lynx Consultants © 2013
3.
What is Big
Data? Lynx Consultants © 2013
4.
What is Big
Data? ¡ SQL has a limited ability to process changing data § SQL schemas are the truth, data needs to fit that Lynx Consultants © 2013
5.
What is Big
Data? ¡ Big Data is the solution! § Data can be truly dynamic Lynx Consultants © 2013
6.
What is Big
Data? ¡ Big Data is the solution! § Data can be truly dynamic § Designed to handle Terabytes of data Lynx Consultants © 2013
7.
What is Big
Data? ¡ Big Data is the solution! § Data can be truly dynamic § Designed to handle Terabytes of data § Designed for fault tolerance and securing data Lynx Consultants © 2013
8.
What is Big
Data? ¡ Big Data is the solution! § Data can be truly dynamic § Designed to handle Terabytes of data § Designed for fault tolerance and securing data § Designed around exploiting hardware to the fullest Lynx Consultants © 2013
9.
What is Big
Data? ¡ Big Data is the solution! § Data can be truly dynamic § Designed to handle Terabytes of data § Designed for fault tolerance and securing data § Designed around exploiting hardware to the fullest § Designed around Map/Reduce Lynx Consultants © 2013
10.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
11.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
12.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
13.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
14.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
15.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
16.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
17.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
18.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
19.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
20.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
21.
Who runs Big
Data? ¡ A few small companies Lynx Consultants © 2013
22.
What is Hadoop? Lynx
Consultants © 2013
23.
What is Hadoop? ¡
Hadoop is one of the big players for Big Data § Developed as an Open Source implementation to implement Google BigTable Lynx Consultants © 2013
24.
What is Hadoop? ¡
Hadoop is one of the big players for Big Data § Developed as an Open Source implementation to implement Google BigTable § Mainly developed at Yahoo! Lynx Consultants © 2013
25.
What is Hadoop? ¡
Hadoop is one of the big players for Big Data § Developed as an Open Source implementation to implement Google BigTable § Mainly developed at Yahoo! § Current companies behind it: Hortonworks and Cloudera Lynx Consultants © 2013
26.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System § HDFS is a distributed filesystem across many nodes § Has many copies of your data (default: 3) § If one node goes down makes sure all the data is rebalanced Lynx Consultants © 2013
27.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System Lynx Consultants © 2013
28.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database § Schemaless Key-‐Value storage § All data exportable in JSON Lynx Consultants © 2013
29.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database Lynx Consultants © 2013
30.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database ¡ Map/Reduce – The key to it all § This was invented by Google § Given a dataset we Map all that match a criteria § Then we Reduce this to a result Lynx Consultants © 2013
31.
What are the
features of Hadoop? ¡ Map/Reduce – The key to it all Lynx Consultants © 2013
32.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database ¡ Map/Reduce – The key to it all ¡ Hive – SQL for NoSQL § Hive provides a SQL language called HiveSQL § Provides a good entrance for SQL users :) Lynx Consultants © 2013
33.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database ¡ Map/Reduce – The key to it all ¡ Hive – SQL for NoSQL ¡ Pig – Map/Reduce made easy § Creates data results given a reduced language § Reinvents SQL somehow Lynx Consultants © 2013
34.
What are the
features of Hadoop? ¡ Hive Lynx Consultants © 2013
35.
What are the
features of Hadoop? ¡ Pig Lynx Consultants © 2013
36.
What are the
features of Hadoop? ¡ HDFS – Hadoop Distributed File System ¡ Hbase – Hadoop NoSQL Database ¡ Map/Reduce – The key to it all ¡ Hive – SQL for NoSQL ¡ Pig – Map/Reduce made easy ¡ Flume – Fault Tolerant transport Lynx Consultants © 2013
37.
What are the
features of Hadoop? ¡ Flume § Divides in Sources, Channels, Sinks § Can have multiple of everything, makes it fault tolerant § Many sources! ▪ Avro, Exec, JMS, Syslog, HTTP, NetCat, Your Own (Java) Lynx Consultants © 2013
38.
What are the
features of Hadoop? ¡ Flume § Divides in Sources, Channels, Sinks § Can have multiple of everything, makes it fault tolerant § Many sources! § Many channels! ▪ Memory, File, Your Own (Java) Lynx Consultants © 2013
39.
What are the
features of Hadoop? ¡ Flume § Divides in Sources, Channels, Sinks § Can have multiple of everything, makes it fault tolerant § Many sources! § Many channels! § Many sinks! ▪ Avro, HDFS, Logger, IRC, File, Hbase, ElasticSearch, S3, Community sinks, Your Own (Java) Lynx Consultants © 2013
40.
What are the
features of Hadoop? ¡ Flume Lynx Consultants © 2013
41.
How Hadoop looks
like in a DC ¡ Components § Primary Namenode § Secondary Namenode § Data Node Lynx Consultants © 2013
42.
How Hadoop looks
like in a DC ¡ Components § Primary Namenode ▪ Controls all the cluster, knows where the data resides ▪ Runs the job tracker to keep track of Map/Reduce jobs ▪ Biggest point of failure, shadowing it is a potential option § Secondary Namenode § Data Node Lynx Consultants © 2013
43.
How Hadoop looks
like in a DC ¡ Components § Primary Namenode § Secondary Namenode ▪ Performs secondary cleanup options § Data Node Lynx Consultants © 2013
44.
How Hadoop looks
like in a DC ¡ Components § Primary Namenode § Secondary Namenode § Data Node ▪ Stores all the information ▪ Runs Map/Reduce Lynx Consultants © 2013
45.
How Hadoop looks
like in a DC ¡ Components Lynx Consultants © 2013
46.
Questions? Lynx Consultants ©
2013
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