Hadoop download

Author: a | 2025-04-25

Downloading Hadoop; Visit the Apache Hadoop website: Navigate to the official Apache Hadoop website to download the latest stable release. Download Hadoop: Click on Step 1: Download Hadoop. First, download the Hadoop binary from the official Apache Hadoop website. Go to the Apache Hadoop website, navigate to the download

Hadoop, Hadoop Config, HDFS, Hadoop MapReduce

On the authorized_keys file, run:sudo chmod 640 ~/.ssh/authorized_keysFinally, you are ready to test SSH configuration:ssh localhostNotes:If you didn’t set a passphrase, you should be logged in automatically.If you set a passphrase, you’ll be prompted to enter it.Step 3: Download the latest stable releaseTo download Apache Hadoop, visit the Apache Hadoop download page. Find the latest stable release (e.g., 3.3.4) and copy the download link.Also, you can download the release using wget command:wget extract the downloaded file:tar -xvzf hadoop-3.3.4.tar.gzTo move the extracted directory, run:sudo mv hadoop-3.3.4 /usr/local/hadoopUse the command below to create a directory for logs:sudo mkdir /usr/local/hadoop/logsNow, you need to change ownership of the Hadoop directory. So, use:sudo chown -R hadoop:hadoop /usr/local/hadoopStep 4: Configure Hadoop Environment VariablesEdit the .bashrc file using the command below:sudo nano ~/.bashrcAdd environment variables to the end of the file by running the following command:export HADOOP_HOME=/usr/local/hadoopexport HADOOP_INSTALL=$HADOOP_HOMEexport HADOOP_MAPRED_HOME=$HADOOP_HOMEexport HADOOP_COMMON_HOME=$HADOOP_HOMEexport HADOOP_HDFS_HOME=$HADOOP_HOMEexport YARN_HOME=$HADOOP_HOMEexport HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/nativeexport PATH=$PATH:$HADOOP_HOME/sbin:$HADOOP_HOME/binexport HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib/native"To save changes and source the .bashrc file, type:source ~/.bashrcWhen you are finished, you are ready for Ubuntu Hadoop setup.Step 5: Configure Hadoop Environment VariablesFirst, edit the hadoop-env.sh file by running the command below:sudo nano $HADOOP_HOME/etc/hadoop/hadoop-env.shNow, you must add the path to Java. If you haven’t already added the JAVA_HOME variable in your .bashrc file, include it here:export JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64export HADOOP_CLASSPATH+=" $HADOOP_HOME/lib/*.jar"Save changes and exit when you are done.Then, change your current working directory to /usr/local/hadoop/lib:cd /usr/local/hadoop/libThe below command lets you download the javax activation file:sudo wget you are finished, you can check the Hadoop version:hadoop versionIf you have passed the steps correctly, you can now configure Hadoop Core Site. To edit the core-site.xml file, run:sudo nano $HADOOP_HOME/etc/hadoop/core-site.xmlAdd the default filesystem URI: fs.default.name hdfs://0.0.0.0:9000 The default file system URI Save changes and exit.Use the following command to create directories for NameNode and DataNode:sudo mkdir -p /home/hadoop/hdfs/{namenode,datanode}Then, change ownership of the directories:sudo chown -R hadoop:hadoop /home/hadoop/hdfsTo change the ownership of the created directory to the hadoop user:sudo chown -R hadoop:hadoop /home/hadoop/hdfsTo edit the hdfs-site.xml file, first run:sudo nano $HADOOP_HOME/etc/hadoop/hdfs-site.xmlThen, paste the following line to set the replication factor: dfs.replication 1 Save changes and exit.At this point, you can configure MapReduce. Run the command below to edit the mapred-site.xml file:sudo nano $HADOOP_HOME/etc/hadoop/mapred-site.xmlTo set the MapReduce framework, paste the following line: mapreduce.framework.name yarn Save changes and exit.To configure YARN, run the command below and edit the yarn-site.xml file:sudo nano $HADOOP_HOME/etc/hadoop/yarn-site.xmlPaste the following to enable the MapReduce shuffle service: yarn.nodemanager.aux-services mapreduce_shuffle Save changes and exit.Format the NameNode by

hadoop/hadoop-mapreduce-project/hadoop-mapreduce

Hadoop is a distributed computing framework for processing and storing massive datasets. It runs on Ubuntu and offers scalable data storage and parallel processing capabilities.Installing Hadoop enables you to efficiently handle big data challenges and extract valuable insights from your data.To Install Hadoop on Ubuntu, the below steps are required:Install Java.Create a User.Download Hadoop.Configure Environment.Configure Hadoop.Start Hadoop.Access Web Interface.Prerequisites to Install Hadoop on UbuntuComplete Steps to Install Hadoop on UbuntuStep 1: Install Java Development Kit (JDK)Step 2: Create a dedicated user for Hadoop & Configure SSHStep 3: Download the latest stable releaseStep 4: Configure Hadoop Environment VariablesStep 5: Configure Hadoop Environment VariablesStep 6: Start the Hadoop ClusterStep 7: Open the web interfaceWhat is Hadoop and Why Install it on Linux Ubuntu?What are the best Features and Advantages of Hadoop on Ubuntu?What to do after Installing Hadoop on Ubuntu?How to Monitor the Performance of the Hadoop Cluster?Why Hadoop Services are Not starting on Ubuntu?How to Troubleshoot issues with HDFS?Why My MapReduce jobs are failing?ConclusionPrerequisites to Install Hadoop on UbuntuBefore installing Hadoop on Ubuntu, make sure your system is meeting below specifications:A Linux VPS running Ubuntu.A non-root user with sudo privileges.Access to Terminal/Command line.Complete Steps to Install Hadoop on UbuntuOnce you provided the above required options for Hadoop installation Ubuntu including buying Linux VPS, you are ready to follow the steps of this guide.In the end, you will be able to leverage its capabilities to efficiently manage and analyze large datasets.Step 1: Install Java Development Kit (JDK)Since Hadoop requires Java to run, use the following command to install the default JDK and JRE:sudo apt install default-jdk default-jre -yThen, run the command below to Verify the installation by checking the Java version:java -versionOutput:java version "11.0.16" 2021-08-09 LTSOpenJDK 64-Bit Server VM (build 11.0.16+8-Ubuntu-0ubuntu0.22.04.1)As you see, if Java is installed, you’ll see the version information.Step 2: Create a dedicated user for Hadoop & Configure SSHTo create a new user, run the command below and create the Hadoop user:sudo adduser hadoopTo add the user to the sudo group, type:sudo usermod -aG sudo hadoopRun the command below to switch to the Hadoop user:sudo su - hadoopTo install OpenSSH server and client, run:sudo apt install openssh-server openssh-client -yThen, generate SSH keys by running the following command:ssh-keygen -t rsaNotes:Press Enter to save the key to the default location.You can optionally set a passphrase for added security.Now, you can add the public key to authorized_keys:cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keysTo set permissions

Hadoop – Apache Hadoop 3.3.6

Running the following command:hdfs namenode -formatThis initializes the Hadoop Distributed File System (HDFS).Step 6: Start the Hadoop ClusterRun the command below to start the NameNode and DataNode:start-dfs.shTo start the ResourceManager and NodeManager, run:start-yarn.shCheck running processes by running the command below:jpsYou should see processes like NameNode, DataNode, ResourceManager, and NodeManager running.If all is correct, you are ready to access the Hadoop Web Interface.Step 7: Open the web interfaceWhile you know your IP, navigate to in your web browser: should see the Hadoop web interface.To access the DataNodes, use the URL to view the below screen:Also, you can use the URL to access the YARN Resource Manager as you see below:The Resource Manager is an indispensable tool for monitoring all the running processes within your Hadoop cluster.What is Hadoop and Why Install it on Linux Ubuntu?Hadoop is a distributed computing framework designed to process and store massive amounts of data efficiently.It runs on various operating systems, including Ubuntu, and offers scalable data storage and parallel processing capabilities.Installing Hadoop on Ubuntu empowers you to handle big data challenges, extract valuable insights, and perform complex data analysis tasks that would be impractical on a single machine.What are the best Features and Advantages of Hadoop on Ubuntu?Scalability: Easily scale Hadoop clusters to handle growing data volumes by adding more nodes.Fault Tolerance: Data is replicated across multiple nodes, ensuring data durability and availability.Parallel Processing: Hadoop distributes data processing tasks across multiple nodes, accelerating performance.Cost-Effective: Hadoop can run on commodity hardware, making it a cost-effective solution for big data processing.Open Source: Hadoop is freely available and has a large, active community providing support and development.Integration with Other Tools: Hadoop integrates seamlessly with other big data tools like Spark, Hive, and Pig, expanding its capabilities.Flexibility: Hadoop supports various data formats and can be customized to meet specific use cases.What to do after Installing Hadoop on Ubuntu?Configure and start the Hadoop cluster: Set up Hadoop services like the NameNode, DataNode, ResourceManager, and NodeManager.Load data into HDFS: Upload your data files to the Hadoop Distributed File System (HDFS) for storage and processing.Run MapReduce jobs: Use MapReduce to perform data processing tasks, such as word counting, filtering, and aggregation.Use other Hadoop components: Explore tools like Hive, Pig, and Spark for more advanced data analysis and machine learning tasks.Monitor and manage the cluster: Use the Hadoop web interface to monitor resource usage, job execution, and troubleshoot issues.Integrate with other systems: Connect Hadoop. Downloading Hadoop; Visit the Apache Hadoop website: Navigate to the official Apache Hadoop website to download the latest stable release. Download Hadoop: Click on

Hadoop – Apache Hadoop 3.3.3

Database Service Node to Run the Examples with Oracle SQL Connector for HDFSYou must configure the co-managed Database service node in order to run the examples, as shown below. See Oracle Big Data Connectors User's Guide, section Installing and Configuring a Hadoop Client on the Oracle Database System for more details. Generate Oracle SQL Connector for HDFS zip file on the cluster node and copy to the database node. Example:cd /opt/oraclezip -r /tmp/orahdfs-.zip orahdfs-/*Unzip the Oracle SQL Connector for HDFS zip file on the database node. Example:mkdir -p /u01/misc_products/bdcunzip orahdfs-.zip -d /u01/misc_products/bdcInstall the Hadoop client on the database node in the /u01/misc_products/ directory.Connect as the sysdba user for the PDB and verify that both OSCH_BIN_PATH and OSCH_DEF_DIR database directories exist and point to valid operating system directories. For example, create or replace directory OSCH_BIN_PATH as '/u01/misc_products/bdc/orahdfs-/bin'; grant read,execute on directory OSCH_BIN_PATH to OHSH_EXAMPLES; where OHSH_EXAMPLES is the user created in Step 2: Create the OHSH_EXAMPLES User, above.create or replace directory OSCH_DEF_DIR as '/u01/misc_products/bdc/xtab_dirs'; grant read,write on directory OSCH_DEF_DIR to OHSH_EXAMPLES; Note: create the xtab_dirs operating system directory if it doesn't exist. Change to your OSCH (Oracle SQL Connector for HDFS) installation directory, and edit the configuration file hdfs_stream. For example,sudo su -l oracle cd /u01/misc_products/bdc/orahdfs- vi bin/hdfs_streamCheck that the following variables are configured correctly. Read the instructions included in the hdfs_stream file for more details.#Include Hadoop client bin directory to the PATH variable export PATH=/u01/misc_products/hadoop-/bin:/usr/bin:/bin export JAVA_HOME=/usr/java/jdk #See explanation below export HADOOP_CONF_DIR=/u01/misc_products/hadoop-conf#Activate the Kerberos configuration for secure clustersexport HADOOP_CLIENT_OPTS="-Djava.security.krb5.conf=/u01/misc_products/krb5.conf"Configure the Hadoop configuration directory (HADOOP_CONF_DIR). If it's not already configured, use Apache Ambari to download the Hadoop Client configuration archive file, as follows:Login to Apache Ambari. the HDFS service, and select the action Download Client Configuration. Extract the files under the HADOOP_CONF_DIR (/u01/misc_products/hadoop-conf) directory. Ensure that the hostnames and ports configured in HADOOP_CONF_DIR/core-site.xml are accessible from your co-managed Database service node (see the steps below). For example, fs.defaultFS hdfs://bdsmyhostmn0.bmbdcsxxx.bmbdcs.myvcn.com:8020 In this example host bdsmyhostmn0.bmbdcsxxx.bmbdcs.myvcn.com and port 8020 must be accessible from your co-managed Database service node. For secure clusters:Copy the Kerberos configuration file from the cluster node to the database node. Example:cp krb5.conf /u01/misc_products/Copy the Kerberos keytab file from the cluster node to the database node. Example:cp /u01/misc_products/Run the following commands to verify that HDFS access is working. #Change to the Hadoop client bin directory cd /u01/misc_products/hadoop-/bin #--config points to your HADOOP_CONF_DIR directory. ./hadoop --config /u01/misc_products/hadoop-conf fs -ls This command should list the HDFS contents. If you get a timeout or "no route to host" or "unknown host" errors, you will need to update your /etc/hosts file and verify your Big Data Service Console network configuration, as follows:Sign into the Cloud Console, click Big Data, then Clusters, then your_cluster>, then Cluster Details. Under the List of cluster nodes section, get the fully qualified name of all your cluster nodes and all the IP addresses .Edit your co-managed Database service configuration file /etc/hosts, for example: #BDS hostnames xxx.xxx.xxx.xxx bdsmynodemn0.bmbdcsad1.bmbdcs.oraclevcn.com bdsmynodemn0 xxx.xxx.xxx.xxx bdsmynodewn0.bmbdcsad1.bmbdcs.oraclevcn.com bdsmynodewn0 xxx.xxx.xxx.xxx bdsmynodewn2.bmbdcsad1.bmbdcs.oraclevcn.com bdsmynodewn2 xxx.xxx.xxx.xxx bdsmynodewn1.bmbdcsad1.bmbdcs.oraclevcn.com bdsmynodewn1 xxx.xxx.xxx.xxx bdsmynodeun0.bmbdcsad1.bmbdcs.oraclevcn.com bdsmynodeun0

Hadoop – Apache Hadoop 2.9.2

Group: Apache HadoopApache Hadoop CommonLast Release on Oct 18, 2024Apache Hadoop Client aggregation pom with dependencies exposedLast Release on Oct 18, 2024Apache Hadoop HDFSLast Release on Oct 18, 2024Apache Hadoop MapReduce CoreLast Release on Oct 18, 2024Hadoop CoreLast Release on Jul 24, 2013Apache Hadoop AnnotationsLast Release on Oct 18, 2024Apache Hadoop Auth - Java HTTP SPNEGOLast Release on Oct 18, 2024Apache Hadoop Mini-ClusterLast Release on Oct 18, 2024Apache Hadoop YARN APILast Release on Oct 18, 2024Apache Hadoop MapReduce JobClientLast Release on Oct 18, 2024Apache Hadoop YARN CommonLast Release on Oct 18, 2024Apache Hadoop MapReduce CommonLast Release on Oct 18, 2024Apache Hadoop YARN ClientLast Release on Oct 18, 2024This module contains code to support integration with Amazon Web Services.It also declares the dependencies needed to work with AWS services.Last Release on Oct 18, 2024Apache Hadoop HDFS ClientLast Release on Oct 18, 2024Apache Hadoop MapReduce AppLast Release on Oct 18, 2024Apache Hadoop YARN Server TestsLast Release on Oct 18, 2024Apache Hadoop MapReduce ShuffleLast Release on Oct 18, 2024Hadoop TestLast Release on Jul 24, 2013Apache Hadoop YARN Server CommonLast Release on Oct 18, 2024Prev12345678910Next

Hadoop – Apache Hadoop 3.1.0

To configure bds-database-create-bundle.sh to download the Hadoop, Hive, and HBase tarballs, you must supply an URL to each these parameters:--hive-client-ws--hadoop-client-ws--hbase-client-ws To get the information needed to provide the correct URL, first check the content management service (CM or Ambari) and find the version of the Hadoop, Hive, and HBase services running on the Hadoop cluster. The compatible clients are of the same versions. In each case, the client tarball filename includes a version string segment that matches the version of the service installed on the cluster. In the case of CDH, you can then browse the public repository and find the URL to the client that matches the service version. For the HDP repository this would require a tool that can browse Amazon S3 storage. However you can also compose the correct URL using the known URL pattern along with information that you can acquire from Ambari, as described in this section. For CDH (Both Oracle Big Data Appliance and Commodity CDH Systems): Log on to Cloudera Manager and go to the Hosts menu. Select All Hosts , then Inspect All Hosts. When the inspection is finished, select either Show Inspector Results (on the screen) or Download Result Data (to a JSON file). In either case, scan the result set and find the service versions. In JSON version of the inspector results, there is a componentInfo section for each cluster that shows the versions of software installed on that cluster. For example: "componentInfo": [ ... { "cdhVersion": "CDH5", "componentRelease": "1.cdh5.11.1.p0.6", "componentVersion": "2.6.0+cdh5.11.1+2400", "name": "hadoop" }, ... Go to Look in the ”hadoop,” hive,” and “hbase” subdirectories of the CDH5 section of the archive. In the listings, you should find the client packages for the versions of the services installed on the cluster. Copy the URLs and use them as the parameter values supplied to bds-database-create-bundle.sh. For example: See Also:Search for “Host Inspector” on Cloudera website if you need more help using this tool to determine installed software versions. For HDP: Log on to Ambari. Go to Admin, then Stack and Versions. On the Stack tab, locate the entries for the HDFS, Hive, and HBase services and note down the version number of each as the “service version.” Click the Versions tab. Note down the version of HDP that is running on the cluster as the “HDP version base.” Click Show Details to display a pop-up window that shows the full version string for the installed HDP release. Note this down as the “HDP full version” The last piece of information needed is the Linux version (“centos5,” “centos6,” or “centos7”). Note this down as “OS version.” To search though the HDP repository in Amazon S3 storage to find the correct client

Hadoop Apache Hadoop 2.9.2

Browse Presentation Creator Pro Upload Jun 05, 2020 170 likes | 239 Views This presentation gives an overview of the Apache Ranger project. It explains Apache Ranger in terms of it's architecture, security, audit and plugin features. Links for further information and connecting Download Presentation Apache Ranger An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher. Presentation Transcript What Is Apache Ranger ? ● For data security across the Hadoop platform ● A framework to enable, monitor and manage security ● Supports security in – A multi tenant data lake – Hadoop eco system ● Open source / Apache 2.0 license ● Administration of security policies ● Monitoring of user access ● Offers central UI and REST API'sWhat Is Apache Ranger ? ● Manage policies for resource access – File, folder, database, table, column ● Policies for users and groups ● Has audit tracking ● Enables policy analytics ● Offers decentralizing data ownershipRanger Projects ● Which projects does Ranger support ? – Apache Hadoop – Apache Hive – Apache HBase – Apache Storm – Apache Knox – Apache Solr – Apache Kafka – YARN – ATLAS ● No additional OS level process to manageRanger Enforcement ● Ranger enforces policy with Java plugins ●. Downloading Hadoop; Visit the Apache Hadoop website: Navigate to the official Apache Hadoop website to download the latest stable release. Download Hadoop: Click on Step 1: Download Hadoop. First, download the Hadoop binary from the official Apache Hadoop website. Go to the Apache Hadoop website, navigate to the download

Hadoop Apache Hadoop 3.3.6

SearchJar File DownloadhhbaseDownload hbase-0.90.1.jarhbase/hbase-0.90.1.jar.zip( 2,084 k)The download jar file contains the following class files or Java source files.META-INF/DEPENDENCIESMETA-INF/LICENSEMETA-INF/MANIFEST.MFMETA-INF/NOTICEMETA-INF/maven/org.apache.hbase/hbase/pom.propertiesMETA-INF/maven/org.apache.hbase/hbase/pom.xmlhbase-default.xmlhbase-webapps/master/WEB-INF/web.xmlhbase-webapps/master/index.htmlhbase-webapps/regionserver/WEB-INF/web.xmlhbase-webapps/regionserver/index.htmlhbase-webapps/static/hbase.csshbase-webapps/static/hbase_logo_med.giforg.apache.hadoop.hbase.Abortable.classorg.apache.hadoop.hbase.Chore.classorg.apache.hadoop.hbase.ClockOutOfSyncException.classorg.apache.hadoop.hbase.ClusterStatus.classorg.apache.hadoop.hbase.DoNotRetryIOException.classorg.apache.hadoop.hbase.DroppedSnapshotException.classorg.apache.hadoop.hbase.HBaseConfiguration.classorg.apache.hadoop.hbase.HColumnDescriptor.classorg.apache.hadoop.hbase.HConstants.classorg.apache.hadoop.hbase.HMsg.classorg.apache.hadoop.hbase.HRegionInfo.classorg.apache.hadoop.hbase.HRegionLocation.classorg.apache.hadoop.hbase.HServerAddress.classorg.apache.hadoop.hbase.HServerInfo.classorg.apache.hadoop.hbase.HServerLoad.classorg.apache.hadoop.hbase.HTableDescriptor.classorg.apache.hadoop.hbase.InvalidFamilyOperationException.classorg.apache.hadoop.hbase.KeyValue.classorg.apache.hadoop.hbase.LocalHBaseCluster.classorg.apache.hadoop.hbase.MasterAddressTracker.classorg.apache.hadoop.hbase.MasterNotRunningException.classorg.apache.hadoop.hbase.NotAllMetaRegionsOnlineException.classorg.apache.hadoop.hbase.NotServingRegionException.classorg.apache.hadoop.hbase.PleaseHoldException.classorg.apache.hadoop.hbase.RegionException.classorg.apache.hadoop.hbase.RemoteExceptionHandler.classorg.apache.hadoop.hbase.Server.classorg.apache.hadoop.hbase.Stoppable.classorg.apache.hadoop.hbase.TableExistsException.classorg.apache.hadoop.hbase.TableNotDisabledException.classorg.apache.hadoop.hbase.TableNotFoundException.classorg.apache.hadoop.hbase.UnknownRegionException.classorg.apache.hadoop.hbase.UnknownRowLockException.classorg.apache.hadoop.hbase.UnknownScannerException.classorg.apache.hadoop.hbase.VersionAnnotation.classorg.apache.hadoop.hbase.YouAreDeadException.classorg.apache.hadoop.hbase.ZooKeeperConnectionException.classorg.apache.hadoop.hbase.avro.AvroServer.classorg.apache.hadoop.hbase.avro.AvroUtil.classorg.apache.hadoop.hbase.avro.generated.AAlreadyExists.classorg.apache.hadoop.hbase.avro.generated.AClusterStatus.classorg.apache.hadoop.hbase.avro.generated.AColumn.classorg.apache.hadoop.hbase.avro.generated.AColumnFamilyDescriptor.classorg.apache.hadoop.hbase.avro.generated.AColumnValue.classorg.apache.hadoop.hbase.avro.generated.ACompressionAlgorithm.classorg.apache.hadoop.hbase.avro.generated.ADelete.classorg.apache.hadoop.hbase.avro.generated.AFamilyDescriptor.classorg.apache.hadoop.hbase.avro.generated.AGet.classorg.apache.hadoop.hbase.avro.generated.AIOError.classorg.apache.hadoop.hbase.avro.generated.AIllegalArgument.classorg.apache.hadoop.hbase.avro.generated.AMasterNotRunning.classorg.apache.hadoop.hbase.avro.generated.APut.classorg.apache.hadoop.hbase.avro.generated.ARegionLoad.classorg.apache.hadoop.hbase.avro.generated.AResult.classorg.apache.hadoop.hbase.avro.generated.AResultEntry.classorg.apache.hadoop.hbase.avro.generated.AScan.classorg.apache.hadoop.hbase.avro.generated.AServerAddress.classorg.apache.hadoop.hbase.avro.generated.AServerInfo.classorg.apache.hadoop.hbase.avro.generated.AServerLoad.classorg.apache.hadoop.hbase.avro.generated.ATableDescriptor.classorg.apache.hadoop.hbase.avro.generated.ATableExists.classorg.apache.hadoop.hbase.avro.generated.ATimeRange.classorg.apache.hadoop.hbase.avro.generated.HBase.classorg.apache.hadoop.hbase.avro.generated.IOError.classorg.apache.hadoop.hbase.avro.generated.TCell.classorg.apache.hadoop.hbase.catalog.CatalogTracker.classorg.apache.hadoop.hbase.catalog.MetaEditor.classorg.apache.hadoop.hbase.catalog.MetaReader.classorg.apache.hadoop.hbase.catalog.RootLocationEditor.classorg.apache.hadoop.hbase.client.Action.classorg.apache.hadoop.hbase.client.Delete.classorg.apache.hadoop.hbase.client.Get.classorg.apache.hadoop.hbase.client.HBaseAdmin.classorg.apache.hadoop.hbase.client.HConnection.classorg.apache.hadoop.hbase.client.HConnectionManager.classorg.apache.hadoop.hbase.client.HTable.classorg.apache.hadoop.hbase.client.HTableFactory.classorg.apache.hadoop.hbase.client.HTableInterface.classorg.apache.hadoop.hbase.client.HTableInterfaceFactory.classorg.apache.hadoop.hbase.client.HTablePool.classorg.apache.hadoop.hbase.client.Increment.classorg.apache.hadoop.hbase.client.MetaScanner.classorg.apache.hadoop.hbase.client.MultiAction.classorg.apache.hadoop.hbase.client.MultiPut.classorg.apache.hadoop.hbase.client.MultiPutResponse.classorg.apache.hadoop.hbase.client.MultiResponse.classorg.apache.hadoop.hbase.client.NoServerForRegionException.classorg.apache.hadoop.hbase.client.Put.classorg.apache.hadoop.hbase.client.RegionOfflineException.classorg.apache.hadoop.hbase.client.Result.classorg.apache.hadoop.hbase.client.ResultScanner.classorg.apach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ase.mapreduce.Driver.classorg.apache.hadoop.hbase.mapreduce.Export.classorg.apache.hadoop.hbase.mapreduce.GroupingTableMapper.classorg.apache.hadoop.hbase.mapreduce.HFileOutputFormat.classorg.apache.hadoop.hbase.mapreduce.HRegionPartitioner.classorg.apache.hadoop.hbase.mapreduce.IdentityTableMapper.classorg.apache.hadoop.hbase.mapreduce.IdentityTableReducer.classorg.apache.hadoop.hbase.mapreduce.Import.classorg.apache.hadoop.hbase.mapreduce.ImportTsv.classorg.apache.hadoop.hbase.mapreduce.KeyValueSortReducer.classorg.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles.classorg.apache.hadoop.hbase.mapreduce.MultiTableOutputFormat.classorg.apache.hadoop.hbase.mapreduce.PutSortReducer.classorg.apache.hadoop.hbase.mapreduce.RowCounter.classorg.apache.hadoop.hbase.mapreduce.SimpleTotalOrderPartitioner.classorg.apache.hadoop.hbase.mapreduce.TableInputFormat.classorg.apache.hadoop.hbase.mapreduce.TableInputFormatBase.classorg.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.classorg.apache.hadoop.hbase.mapreduce.TableMapper.classorg.apache.hadoop.hbase.mapreduce.TableOutputCommitter.classorg.apache.hadoop.hbase.mapreduce.TableOutputFormat.classorg.apache.hadoop.hbase.mapreduce.TableRecordReader.classorg.apache.hadoop.hbase.mapreduce.TableRecordReaderImpl.classorg.apache.hadoop.hbase.mapreduce.TableReducer.classorg.apache.hadoop.hbase.mapreduce.TableSplit.classorg.apache.hadoop.hbase.mapreduce.hadoopbackport.InputSampler.classorg.apache.hadoop.hbase.mapreduce.hadoopbackport.TotalOrderPartitioner.classorg.apache.hadoop.hbase.mapreduce.replication.VerifyReplication.classorg.apache.hadoop.hbase.master.ActiveMasterManager.classorg.apache.hadoop.hbase.master.AssignmentManager.classorg.apache.hadoop.hbase.master.BulkAssigner.classorg.apache.hadoop.hbase.master.CatalogJanitor.classorg.apache.hadoop.hbase.master.DeadServer.classorg.apache.hadoop.hbase.master.HMaster.classorg.apache.hadoop.hbase.master.HMasterCommandLine.classorg.apache.hadoop.hbase.master.LoadBalancer.classorg.apache.hadoop.hbase.master.LogCleaner.classorg.apache.hadoop.hbase.master.LogCleanerDelegate.classorg.apache.hadoop.hbase.master.MasterFileSystem.classorg.apache.hadoop.hbase.master.MasterServices.classorg.apache.hadoop.hbase.master.ServerManager.classorg.apache.hadoop.hbase.master.TimeToLiveLogCleaner.classorg.apache.hadoop.hbase.master.handler.ClosedRegionHandler.classorg.apache.hadoop.hbase.master.handler.DeleteTableHandler.classorg.apache.hadoop.hbase.master.handler.DisableTableHandler.classorg.apache.hadoop.hbase.master.handler.EnableTableHandler.classorg.apache.hadoop.hbase.master.handler.MetaServerShutdownHandler.classorg.apache.hadoop.hbase.master.handler.ModifyTableHandler.classorg.apache.hadoop.hbase.master.handler.OpenedRegionHandler.classorg.apache.hadoop.hbase.master.handler.ServerShutdownHandler.classorg.apache.hadoop.hbase.master.handler.TableAddFamilyHandler.classorg.apache.hadoop.hbase.master.handler.TableDeleteFamilyHandler.classorg.apache.hadoop.hbase.master.handler.TableEventHandler.classorg.apache.hadoop.hbase.master.handler.TableModifyFamilyHandler.classorg.apache.hadoop.hbase.master.handler.TotesHRegionInfo.classorg.apache.hadoop.hbase.master.metrics.MasterMetrics.classorg.apache.hadoop.hbase.master.metrics.MasterStatistics.classorg.apache.hadoop.hbase.metrics.HBaseInfo.classorg.apache.hadoop.hbase.metrics.MetricsMBeanBase.classorg.apache.hadoop.hbase.metrics.MetricsRate.classorg.apache.hadoop.hbase.metrics.MetricsString.classorg.apache.hadoop.hbase.metrics.PersistentMetricsTimeVaryingRate.classorg.apache.hadoop.hbase.metrics.file.TimeStampingFileContext.classorg.apache.hadoop.hbase.package-info.classorg.apache.hadoop.hbase.regionserver.ChangedReadersObserver.classorg.apache.hadoop.hbase.regionserver.ColumnCount.classorg.apache.hadoop.hbase.regionserver.ColumnTracker.classorg.apache.hadoop.hbase.regionserver.CompactSplitThread.classorg.apache.hadoop.hbase.regionserver.CompactionRequestor.classorg.apache.hadoop.hbase.regionserver.DebugPrint.classorg.apache.hadoop.hbase.regionserver.DeleteTracker.classorg.apache.hadoop.hbase.regionserver.ExplicitColumnTracker.classorg.apache.hadoop.hbase.regionserver.FlushRequester.classorg.apache.hadoop.hbase.regionserver.GetClosestRowBeforeTracker.classorg.apache.hadoop.hbase.regionserver.HRegion.classorg.apache.hadoop.hbase.regionserver.HRegionServer.classorg.apache.hadoop.hbase.regionserver.HRegionServerCommandLine.classorg.apache.hadoop.hbase.regionserver.InternalScan.classorg.apache.hadoop.hbase.regionserver.InternalScanner.classorg.apache.hadoop.hbase.regionserver.KeyValueHeap.classorg.apache.hadoop.hbase.regionserver.KeyValueScanner.classorg.apache.hadoop.hbase.regionserver.KeyValueSkipListSet.classorg.apache.hadoop.hbase.regionserver.LeaseException.classorg.apache.hadoop.hbase.regionserver.LeaseListener.classorg.apache.hadoop.hbase.regionserver.Leases.classorg.apache.hadoop.hbase.regionserver.LogRoller.classorg.apache.hadoop.hbase.regionserver.LruHashMap.classorg.apache.hadoop.hbase.regi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classorg.apache.hadoop.hbase.rest.model.ColumnSchemaModel.classorg.apache.hadoop.hbase.rest.model.RowModel.classorg.apache.hadoop.hbase.rest.model.ScannerModel.classorg.apache.hadoop.hbase.rest.model.StorageClusterStatusModel.classorg.apache.hadoop.hbase.rest.model.StorageClusterVersionModel.classorg.apache.hadoop.hbase.rest.model.TableInfoModel.classorg.apache.hadoop.hbase.rest.model.TableListModel.classorg.apache.hadoop.hbase.rest.model.TableModel.classorg.apache.hadoop.hbase.rest.model.TableRegionModel.classorg.apache.hadoop.hbase.rest.model.TableSchemaModel.classorg.apache.hadoop.hbase.rest.model.VersionModel.classorg.apache.hadoop.hbase.rest.protobuf.generated.CellMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.CellSetMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.ColumnSchemaMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.ScannerMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.StorageClusterStatusMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.TableInfoMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.TableListMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.TableSchemaMessage.classorg.apache.hadoop.hbase.rest.protobuf.generated.VersionMessage.classorg.apache.hadoop.hbase.rest.provider.JAXBContextResolver.classorg.apache.hadoop.hbase.rest.provider.consumer.ProtobufMessageBodyConsumer.classorg.apache.hadoop.hbase.rest.provider.producer.PlainTextMessageBodyProducer.classorg.apache.hadoop.hbase.rest.provider.producer.ProtobufMessageBodyProducer.classorg.apache.hadoop.hbase.rest.transform.Base64.classorg.apache.hadoop.hbase.rest.transform.NullTransform.classorg.apache.hadoop.hbase.rest.transform.Transform.classorg.apache.hadoop.hbase.security.User.classorg.apache.hadoop.hbase.thrift.ThriftServer.classorg.apache.hadoop.hbase.thrift.ThriftUtilities.classorg.apache.hadoop.hbase.thrift.generated.AlreadyExists.classorg.apache.hadoop.hbase.thrift.generated.BatchMutation.classorg.apache.hadoop.hbase.thrift.generated.ColumnDescriptor.classorg.apache.hadoop.hbase.thrift.generated.Hbase.classorg.apache.hadoop.hbase.thrift.generated.IOError.classorg.apache.hadoop.hbase.thrift.generated.IllegalArgument.classorg.apache.hadoop.hbase.thrift.generated.Mutation.classorg.apache.hadoop.hbase.thrift.generated.TCell.classorg.apache.hadoop.hbase.thrift.generated.TRegionInfo.classorg.apache.hadoop.hbase.thrift.generated.TRowResult.classorg.apache.hadoop.hbase.util.Base64.classorg.apache.hadoop.hbase.util.BloomFilter.classorg.apache.hadoop.hbase.util.ByteBloomFilter.classorg.apache.hadoop.hbase.util.Bytes.classorg.apache.hadoop.hbase.util.CancelableProgressable.classorg.apache.hadoop.hbase.util.ClassSize.classorg.apache.hadoop.hbase.util.CompressionTest.classorg.apache.hadoop.hbase.util.DefaultEnvironmentEdge.classorg.apache.hadoop.hbase.util.DynamicByteBloomFilter.classorg.apache.hadoop.hbase.util.EnvironmentEdge.classorg.apache.hadoop.hbase.util.EnvironmentEdgeManager.classorg.apache.hadoop.hbase.util.FSUtils.classorg.apache.hadoop.hbase.util.FileSystemVersionException.classorg.apache.hadoop.hbase.util.HBaseConfTool.classorg.apache.hadoop.hbase.util.HBaseFsck.classorg.apache.hadoop.hbase.util.HBaseFsckRepair.classorg.apache.hadoop.hbase.util.HMerge.classorg.apache.hadoop.hbase.util.Hash.classorg.apache.hadoop.hbase.util.IncrementingEnvironmentEdge.classorg.apache.hadoop.hbase.util.InfoServer.classorg.apache.hadoop.hbase.util.JVMClusterUtil.classorg.apache.hadoop.hbase.util.JenkinsHash.classorg.apache.hadoop.hbase.util.JvmVersion.classorg.apache.hadoop.hbase.util.Keying.classorg.apache.hadoop.hbase.util.MD5Hash.classorg.apache.hadoop.hbase.util.ManualEnvironmentEdge.classorg.apache.hadoop.hbase.util.Merge.classorg.apache.hadoop.hbase.util.MetaUtils.classorg.apache.hadoop.hbase.util.MurmurHash.classorg.apache.hadoop.hbase.util.Pair.classorg.apache.hadoop.hbase.util.PairOfSameType.classorg.apache.hadoop.hbase.util.ServerCommandLine.classorg.apache.hadoop.hbase.util.Sleeper.classorg.apache.hadoop.hbase.util.SoftValueSortedMap.classorg.apache.hadoop.hbase.util.Strings.classorg.apache.hadoop.hbase.util.Threads.classorg.apache.hadoop.hbase.util.VersionInfo.classorg.apache.hadoop.hbase.util.Writables.classorg.apache.hadoop.hbase.zookeeper.ClusterStatusTracker.classorg.apache.hadoop.hbase.zookeeper.HQuorumPeer.classorg.apache.hadoop.hbase.zookeeper.MetaNodeTracker.classorg.apache.hadoop.hbase.zookeeper.MiniZooKeeperCluster.classorg.apache.hadoop.hbase.zookeeper.RegionServerTracker.classorg.apache.hadoop.hbase.zookeeper.RootRegionTracker.classorg.apache.hadoop.hbase.zookeeper.ZKAssign.classorg.apache.hadoop.hbase.zookeeper.ZKConfig.classorg.apache.hadoop.hbase.zookeeper.ZKServerTool.classorg.apache.hadoop.hbase.zookeeper.ZKTable.classorg.apache.hadoop.hbase.zookeeper.ZKUtil.classorg.apache.hadoop.hbase.zookeeper.ZooKeeperListener.classorg.apache.hadoop.hbase.zookeeper.ZooKeeperMainServerArg.classorg.apache.hadoop.hbase.zookeeper.ZooKeeperNodeTracker.classorg.apache.hadoop.hbase.zookeeper.ZooKeeperWatcher.classRelated examples in the same category1.Download hbase-hadoop-compat-0.95.1-hadoop1-sources.jar2.Download hbase-hadoop-compat-0.95.1-hadoop1.jar3.Download hbase-hadoop1-compat-0.95.0-sources.jar4.Download hbase-hadoop1-compat-0.95.0.jar5.Download hbase-smoke-0.2.0-incubating-sources.jar6.Download hbase-smoke-0.2.0-incubating.jar7.Download hbase-hadoop2-compat-0.95.2-hadoop2-sources.jar8.Download hbase-hadoop2-compat-0.95.2-hadoop2.jar9.Download hbase-smoke-0.5.0.jar10.Download hbase-smoke-0.3.0-incubating-sources.jar11.Download hbase-smoke-0.3.0-incubating.jar12.Download hbase-smoke-0.4.0-incubating.jar13.Download hbase-hadoop1-compat-0.95.1-hadoop1-sources.jar14.Download hbase-hadoop1-compat-0.95.1-hadoop1.jar15.Download hbase-smoke-execution-0.2.0-incubating-sources.jar16.Download hbase-smoke-execution-0.2.0-incubating.jar17.Download hbase-0.21.0-20100622-sources.jar18.Download hbase-0.21.0-20100622.jar19.Download hbase-smoke-0.6.0.jar20.Download hbase-0.20.3-1.cloudera-indexed.jar21.Download hbase-0.20.3-1.cloudera-stargate.jar22.Download hbase-0.20.3-1.cloudera-transactional.jar23.Download hbase-0.20.6-test.jar24.Download hbase-0.20.6-transactional.jar25.Download hbase-0.20.6.jar26.Download hbase-0.90.0.jar27.Download hbase-0.90.1-cdh3u0.jar28.Download hbase-0.90.2.jar29.Download hbase-0.90.3.jar30.Download hbase-0.90.4-cdh3u3.jar31.Download hbase-0.90.4.jar32.Download hbase-0.90.5.jar33.Download hbase-0.92.0.jar34.Download hbase-0.92.1.jar35.Download hbase-0.92.2.jar36.Download hbase-0.94.0.jar37.Download hbase-0.94.1.jar38.Download hbase-0.94.2.jar39.Download hbase-0.94.3.jar40.Download hbase-0.94.5.jar41.Download hbase-mini-mr.jar42.Download hbase_bulkloader.jar43.Download hbase-0.94.10-sources.jar44.Download hbase-0.94.10.jar45.Download hbase-0.94.11-sources.jar46.Download hbase-0.94.11.jar47.Download hbase-examples-0.95.1-hadoop1-sources.jar48.Download hbase-examples-0.95.1-hadoop1.jar49.Download hbase-prefix-tree-0.95.0-sources.jar50.Download hbase-prefix-tree-0.95.0.jar51.Download hbase-0.90.0-sources.jar52.Download hbase-0.90.2-sources.jar53.Download hbase-0.90.3-sources.jar54.Download hbase-0.90.4-sources.jar55.Download hbase-0.90.5-sources.jar56.Download hbase-common-0.95.1-hadoop1-sources.jar57.Download hbase-common-0.95.1-hadoop1.jar58.Download hbase-prefix-tree-0.95.2-hadoop1-sources.jar59.Download hbase-prefix-tree-0.95.2-hadoop1.jar60.Download hbase-prefix-tree-0.95.2-hadoop2-sources.jar61.Download hbase-prefix-tree-0.95.2-hadoop2.jar62.Download hbase-server-0.95.0-sources.jar63.Download hbase-server-0.95.0.jar64.Download hbase-server-0.95.1-hadoop1-sources.jar65.Download hbase-server-0.95.1-hadoop1.jar66.Download hbase-examples-0.95.0-sources.jar67.Download hbase-examples-0.95.0.jar68.Download hbase-common-0.95.2-hadoop1-sources.jar69.Download hbase-common-0.95.2-hadoop1.jar70.Download hbase-common-0.95.2-hadoop2-sources.jar71.Download hbase-common-0.95.2-hadoop2.jar72.Download hbase-it-0.95.2-hadoop2-sources.jar73.Download hbase-it-0.95.2-hadoop2.jar74.Download hbase-it-0.95.1-hadoop1-sources.jar75.Download hbase-it-0.95.1-hadoop1.jar76.Download hbase-it-0.95.2-hadoop1-sources.jar77.Download hbase-it-0.95.2-hadoop1.jar78.Download hbase-server-0.95.2-hadoop1-sources.jar79.Download hbase-server-0.95.2-hadoop1.jar80.Download hbase-server-0.95.2-hadoop2-sources.jar81.Download hbase-server-0.95.2-hadoop2.jar82.Download hbase-client-0.95.1-hadoop1-sources.jar83.Download hbase-client-0.95.1-hadoop1.jar84.Download hbase-it-0.95.0-sources.jar85.Download hbase-it-0.95.0.jar86.Download hbase-common-0.95.0-sources.jar87.Download hbase-common-0.95.0.jar88.Download hbase-protocol-0.95.1-hadoop1-sources.jar89.Download hbase-protocol-0.95.1-hadoop1.jar90.Download hbase-examples-0.95.2-hadoop1-sources.jar91.Download hbase-examples-0.95.2-hadoop1.jar92.Download hbase-examples-0.95.2-hadoop2-sources.jar93.Download hbase-examples-0.95.2-hadoop2.jar94.Download hbase-0.92.0-sources.jar95.Download hbase-0.92.1-sources.jar96.Download hbase-0.92.2-sources.jar97.Download hbase-0.94.6.1-sources.jar98.Download hbase-0.94.6.1.jar99.Download hbase-protocol-0.95.2-hadoop1-sources.jar100.Download hbase-protocol-0.95.2-hadoop1.jar101.Download hbase-protocol-0.95.2-hadoop2-sources.jar102.Download hbase-protocol-0.95.2-hadoop2.jar103.Download hbase-protocol-0.95.0-sources.jar104.Download hbase-protocol-0.95.0.jar105.Download hbase-0.94.6-sources.jar106.Download hbase-0.94.6.jar107.Download hbase-0.94.7-sources.jar108.Download hbase-0.94.7.jar109.Download hbase-0.94.9-sources.jar110.Download hbase-0.94.9.jar111.Download hbase-client-0.95.0-sources.jar112.Download hbase-client-0.95.0.jar113.Download hbase-prefix-tree-0.95.1-hadoop1-sources.jar114.Download hbase-prefix-tree-0.95.1-hadoop1.jar115.Download hbase-0.94.0-sources.jar116.Download hbase-0.94.1-sources.jar117.Download hbase-0.94.2-sources.jar118.Download hbase-0.94.3-sources.jar119.Download hbase-0.94.4-sources.jar120.Download hbase-0.94.4.jar121.Download hbase-0.94.5-sources.jar122.Download hbase-client-0.95.2-hadoop1-sources.jar123.Download hbase-client-0.95.2-hadoop1.jar124.Download hbase-client-0.95.2-hadoop2-sources.jar125.Download hbase-client-0.95.2-hadoop2.jar126.Download hbase-hadoop-compat-0.95.2-hadoop1-sources.jar127.Download hbase-hadoop-compat-0.95.2-hadoop1.jar128.Download hbase-hadoop-compat-0.95.2-hadoop2-sources.jar129.Download hbase-hadoop-compat-0.95.2-hadoop2.jar

Hadoop – Apache Hadoop 2.7.1

Into manageable smaller pieces, then saved on clusters of community servers. This offers scalability and economy.Furthermore, Hadoop employs MapReduce to run parallel processings, which both stores and retrieves data faster than information residing on a traditional database. Traditional databases are great for handling predictable and constant workflows; otherwise, you need Hadoop’s power of scalable infrastructure.5 Advantages of Hadoop for Big DataHadoop was created to deal with big data, so it’s hardly surprising that it offers so many benefits. The five main benefits are:Speed. Hadoop’s concurrent processing, MapReduce model, and HDFS lets users run complex queries in just a few seconds.Diversity. Hadoop’s HDFS can store different data formats, like structured, semi-structured, and unstructured.Cost-Effective. Hadoop is an open-source data framework.Resilient. Data stored in a node is replicated in other cluster nodes, ensuring fault tolerance.Scalable. Since Hadoop functions in a distributed environment, you can easily add more servers.How Is Hadoop Being Used?Hadoop is being used in different sectors to date. The following sectors have the usage of Hadoop.1. Financial Sectors:Hadoop is used to detect fraud in the financial sector. Hadoop is also used to analyse fraud patterns. Credit card companies also use Hadoop to find out the exact customers for their products. 2. Healthcare Sectors:Hadoop is used to analyse huge data such as medical devices, clinical data, medical reports etc. Hadoop analyses and scans the reports thoroughly to reduce the manual work.3. Hadoop Applications in the Retail Industry:Retailers use Hadoop to improve their sales. Hadoop also helped in tracking the products bought by the customers. Hadoop also helps retailers to predict the price range of the products. Hadoop also helps retailers to make their products online. These advantages of Hadoop help the retail industry a lot.4. Security and Law Enforcement:The National Security Agency of the USA uses Hadoop to prevent terrorist attacks. Data tools are used by the cops to chase criminals and predict their plans. Hadoop is also used in defence, cybersecurity etc.5. Hadoop Uses in Advertisements:Hadoop is also used in the advertisement sector too. Hadoop is used for capturing video, analysing transactions and handling social media platforms. The data analysed is generated through social media platforms like Facebook, Instagram etc. Hadoop is also used in the promotion of the products.There are many more advantages of Hadoop in daily life as well as in the Software sector too.Hadoop Use CaseIn this case study, we will discuss how Hadoop can combat fraudulent activities. Let us look at the case of Zions Bancorporation. Their main challenge was in how to use the Zions security team’s approaches to combat fraudulent activities taking place. The problem was that they used an RDBMS dataset, which was unable to store and analyze huge amounts of data.In other words,. Downloading Hadoop; Visit the Apache Hadoop website: Navigate to the official Apache Hadoop website to download the latest stable release. Download Hadoop: Click on Step 1: Download Hadoop. First, download the Hadoop binary from the official Apache Hadoop website. Go to the Apache Hadoop website, navigate to the download

Hadoop Apache Hadoop 2.7.0

سیستم Hadoop را ذخیره می‌کنند. NameNode متادیتا را مدیریت نموده و DataNode بلوک‌های داده واقعی را ذخیره می‌نماید.برای نمونه به D:\Hadoop\etc\hadoop بروید و این مراحل را برای ویرایش فایل‌های Configuration دنبال کنید.فایل زیر به Hadoop می‌گوید که فایل سیستم پیشفرض کجاست:* core-site.xml* hdfs-site.xml* mapred-site.xml* yarn-site.xml* hadoop-env.cmdبرای ویرایش core-site.xml، آن را در یک ویرایشگر متن، باز و کد زیر را بین تگ‌های configuration اضافه کنید:ویرایش hdfs-site.xml مکان‌های ذخیره سازی NameNode و DataNode Hadoop را پیکربندی می‌کند: برای پیکربندی MapReduce، این را به فایل اضافه کنید: mapreduce.framework.name yarn YARN مدیر منابع Hadoop است. برای ویرایش yarn-site.xml، خطوط زیر را اضافه کنید:در نهایت، hadoop-env.cmd را ویرایش خواهید کرد. بررسی کنید که مسیر JAVA_HOME به درستی در hadoop-env.cmd تنظیم شده باشد. در صورت نیاز، خط پیش فرض را با:set JAVA_HOME=%JAVA_HOME%یاset JAVA_HOME="C:\Program Files\Java\jdk1.8.0_221"مرحله ۵: پوشه Bin را جایگزین کنیدپوشه bin پیشفرض Hadoop ممکن است در برخی از نسخه‌ها به راحتی در ویندوز کار نکند، بنابراین بهتر است آن را با یک پوشه از پیش پیکربندی شده جایگزین کنید.برای جایگزینی پوشه bin برای Hadoop در ویندوز، باید فایل‌های لازم را دانلود کنید. می‌توانید پوشه bin از پیش پیکربندی شده برای نسخه مورد نظر خود را مستقیم از مخزن GitHub دریافت کنید. برای سازگاری بهتر با ویندوز، فایل‌ها را دانلود و اکستراکت کنید تا جایگزین فایل‌های موجود در دایرکتوری Hadoop شود.مرحله ۶: تست تنظیماتاکنون زمان آن است که آزمایش کنید آیا همه چیز به درستی تنظیم شده است یا خیر:NameNode را فرمت کنیددر یک خط فرمان جدید، اجرا کنید:hadoop namenode -formatسیستم ذخیره سازی NameNode را مقداردهی اولیه می‌کند. به یاد داشته باشید، این دستور فقط برای بار اول ضروری است.سرویس Hadoop را استارت کنیدبرای راه اندازی Hadoop، دستور زیر را اجرا کنید:start-all.cmdبا این کار چندین پنجره فرمان باز می‌شود که نشان می‌دهد دیمن‌های مختلف Hadoop در حال اجرا هستند، مانند NameNode، DataNode، ResourceManager و NodeManager.مرحله ۷: تایید