For learning Hadoop, below are the hardwarerequirements: Minimum RAM required: 4GB (Suggested:8GB) Minimum Free Disk Space: 25GB.
Set up. Check either Java 1.8.0 is already installed onyour system or not, use "Javac -version" to check. Extract fileHadoop 2.8.0.tar.gz or Hadoop-2.8.0.zip and placeunder "C:Hadoop-2.8.0". Set the path HADOOP_HOME Environmentvariable on windows 10(see Step 1,2,3 and 4below).
What platforms and Java versions does Hadoop runon? Linux and Windows are the supported operating systems,but BSD, Mac OS/X, and OpenSolaris are known towork.
Install Hadoop
- Step 1: Click here to download the Java 8 Package.
- Step 2: Extract the Java Tar File.
- Step 3: Download the Hadoop 2.7.3 Package.
- Step 4: Extract the Hadoop tar File.
- Step 5: Add the Hadoop and Java paths in the bash file(.bashrc).
- Step 6: Edit the Hadoop Configuration files.
Steps to install Spark in local mode:Install Java 7 or later. Since we don't have a localHadoop installation on Windows we have todownload winutils.exe and place it in a bin directory under acreated Hadoop home directory. Set HADOOP_HOME = <<Hadoophome directory>> in environment variable.
As per Spark documentation, Spark can runwithout Hadoop. You may run it as a Standalone mode withoutany resource manager. But if you want to run in multi-nodesetup, you need a resource manager like YARN or Mesos and adistributed file system like HDFS,S3 etc.
Running Spark applications on Windows ingeneral is no different than running it on other operatingsystems like Linux or macOS. You do not have to installApache Hadoop to work with Spark or run Sparkapplications. Tip. Read the Apache Hadoop project's Problemsrunning Hadoop on Windows.
Hive stores data inside /hive/warehousefolder on HDFS if not specified any other folder using LOCATION tagwhile creation. It is stored in various formats (text,rc, orcetc).
Hive and HBase are two different Hadoop basedtechnologies - Hive is an SQL-like engine that runsMapReduce jobs, and HBase is a NoSQL key/value database onHadoop. Just like Google can be used for search and Facebook forsocial networking, Hive can be used for analytical querieswhile HBase for real-time querying.
Key Differences between Hadoop vsHive:
1) Hadoop is a framework to process/query theBig data while Hive is an SQL Based tool which builds overHadoop to process the data. 2) Hive process/query allthe data using HQL (Hive Query Language) it's SQL-LikeLanguage while Hadoop can understand Map Reduceonly.So a folder of the name of database will be created asbelow. Here mydb.db is a folder in which table will be created. Thedata will be placed inside this folder. If you are usinglocation keyword either in database or managed/external table, yourdata will be stored at that location.
Row and Columnar Storage For Hive. ORC isa columnar storage format used in Hadoop for Hivetables. It is an efficient file format for storing data inwhich records contain many columns. An example is Clickstream (web)data to analyze website activity andperformance.
No, we cannot call Apache Hive a relationaldatabase, as it is a data warehouse which is built on top ofApache Hadoop for providing data summarization, query and,analysis. It differs from a relational database in a waythat it stores schema in a database and processed data intoHDFS.
Apache Hive saves developers from writing complexHadoop MapReduce jobs for ad-hoc requirements. Hence, hiveprovides summarization, analysis, and query of data. Hive isvery fast and scalable. Hive reduces the complexity ofMapReduce by providing an interface where the user can submit SQLqueries.
Hive is not a complete data warehousing solutionas in it does not have its own storage system likeother RDBMS's but can instead be referred to as the SQLplugin for a hadoop cluster. Hadoop Hive uses theHDFS storage that is an integral part of Apache Hadoopecosystem.
Hence, hive provides summarization, analysis, andquery of data. Hive is very fast and scalable. It is highlyextensible. Since Apache Hive is similar to SQL, hence itbecomes very easy for the SQL developers to learn andimplement Hive Queries.
Spark SQL module of Spark can also be usedto read data from an existing Hive installation. Hiveprovides access rights for users, groups and roles whileSpark doesn't have such support yet. Spark'sin-memory processing delivers near real-time analytics whileHive is mainly used for ETL, Batch jobs.
Details such as the execution of queries, format,location and schema of hive table inside the Metastore etc.There are 4 main components as part of HiveArchitecture. Let's start off with each of thecomponents individually.
Insert into table employee Select * fromemp where dno=45; After this also You can fire select query to seeuploaded rows. You can load data into a hive tableusing Load statement in two ways. One is fromlocal file system to hive table and other is fromHDFS to Hive table.
Pig vs. Hive
1) Hive Hadoop Component is used mainly by dataanalysts whereas Pig Hadoop Component is generally used byResearchers and Programmers. 2) Hive Hadoop Component isused for completely structured Data whereas Pig HadoopComponent is used for semi structured data. 11) Pig supportsAvro whereas Hive does not.Apache Hive works by translating the inputprogram written in the hive SQL like language to one or moreJava map reduce jobs. It then runs the jobs on the cluster toproduce an answer. It functions analogously to a compiler -translating a high level construct to a lower level language forexecution.
Load Data into Hive Table from HDFS
- Create a folder on HDFS under /user/cloudera HDFS Path.
- Move the text file from local file system into newly createdfolder called javachain.
- Create Empty table STUDENT in HIVE.
- Load Data from HDFS path into HIVE TABLE.
- Select the values in the Hive table.
HBase is a NoSQL database used for real-time datastreaming whereas Hive is not ideally a database but amapreduce based SQL engine that runs on top of hadoop. Ideallycomparing Hive vs. HBase might not be right becauseHBase is a database and Hive is a SQL engine forbatch processing of big data.
Featurewise technical difference between Hive,Pig, and SQL. Hive - Apache Hive uses HiveQL,a declarative language. Hive is built on Hadoop and it is anopen source project to analyze query datasets. HiveQL is a languagethat is similar to SQL, it converts the queries intoMapReduce programmes.
The File System (FS) shell includes variousshell-like commands that directly interact with theHadoop Distributed File System (HDFS) as well asother file systems that Hadoop supports, such as LocalFS, HFTP FS, S3 FS, and others.
How Hadoop Works? Hadoop does distributedprocessing for huge data sets across the cluster of commodityservers and works on multiple machines simultaneously. To processany data, the client submits data and program to Hadoop.HDFS stores the data while MapReduce process the data and Yarndivide the tasks.
Installing Hadoop
We have installed Java and then wehave to install the Hadoop. Go to the ApacheHadoop release page to find the latest version ofApache. You have to find the latest stable versionto install hadoop 2.7 on ubuntu. Once you findthe latest stable version and then copy the link by doing the rightclick.Hadoop Installation on Windows10
You can install Hadoop in your system as wellwhich would be a feasible way to learn Hadoop. Wewill be installing single node pseudo-distributedhadoop cluster on windows 10. Prerequisite: Toinstall Hadoop, you should have Java version 1.8 in yoursystem.3 Answers. It's confusing, buthadoop.tmp.dir is used as the base fortemporary directories locally, and also in HDFS. The document isn'tgreat, but mapred.system.dir is set by default to"${hadoop.tmp.dir}/mapred/system" , and thisdefines the Path on the HDFS where where the Map/Reduce frameworkstores system files.
A Hadoop cluster is a special type ofcomputational cluster designed specifically for storing andanalyzing huge amounts of unstructured data in a distributedcomputing environment. Typically one machine in the clusteris designated as the NameNode and another machine the asJobTracker; these are the masters.
Apache Hadoop
| Developer(s) | Apache Software Foundation |
|---|
| Initial release | April 1, 2006 |
| Stable release | 2.7.x 2.7.7 / 31 May 2018 2.8.x 2.8.5 / 15 September 2018 2.9.x2.9.2 / 9 November 2018 3.1.x 3.1.2 / 6 February 2019 3.2.x 3.2.0 /16 January 2019 |
| Repository | Hadoop Repository |
| Written in | Java |
Steps
- Launch the Terminal.
- Type in sudo su and press ↵ Enter .
- Enter the root password.
- Type sudo updatedb and press ↵ Enter .
- Type locate openjdk and press ↵ Enter .
- Look to see where Java is installed.
- Type export JAVA_HOME= followed by the Java installationpath.
- Press ↵ Enter .
A single node cluster is a special implementationof a cluster running on a standalone node. You candeploy a single node cluster if your workload only requiresa single node, but does not need nondisruptive operations.For example, you could deploy a single node cluster toprovide data protection for a remote office.
