Winutils.Exe Hadoop
Posted by admin- in Home -11/11/17Hadoop installation on windows, This tutorial will explain you how to Hadoop installation on windows without cygwin in 10 mints hadoop 2. Native Spark Modeling feature has been released since SAP BusinessObjects Predictive Analytics version 2. This version supported Native Spark Modeling for. Use HDInsight Tools in Azure Toolkit for Eclipse to develop Spark applications written in Scala and submit them to an Azure HDInsight Spark cluster, directly from the. We recommend debugging spark applications remotely through SSH. For instructions, see Remotely debug Spark applications on an HDInsight cluster with Azure Toolkit for. Hi,I have a problem with connection to Hadoop. I have a project, that contains stream, that is connected to WebService provider. I succesfully get data with REST or. Azure Toolkit for Intelli. J Debug applications remotely in HDInsight Spark. This article provides step by step guidance on how to use the HDInsight Tools in Azure Toolkit for Intelli. J to submit a Spark job on an HDInsight Spark cluster, and then debug it remotely from your desktop computer. To complete these tasks, you must perform the following high level steps Follow the instructions from the following links to create an Azure virtual network, and then verify the connectivity between your desktop computer and the virtual network We recommend that you also create an Apache Spark cluster in Azure HDInsight that is part of the Azure virtual network that you created. Use the information available in Create Linux based clusters in HDInsight. As part of optional configuration, select the Azure virtual network that you created in the previous step. Get the IP address of the head node. Open Ambari UI for the cluster. From the cluster blade, select Dashboard. From the Ambari UI, select Hosts. You see a list of head nodes, worker nodes, and zookeeper nodes. The head nodes have an hn prefix. Select the first head node. From the Summary pane at the bottom of the page that opens, copy the IP Address of the head node and the Hostname. Add the IP address and the hostname of the head node to the hosts file on the computer where you want to run and remotely debug the Spark job. This enables you to communicate with the head node by using the IP address, as well as the hostname. Open a Notepad file with elevated permissions. From the File menu, select Open, and then find the location of the hosts file. On a Windows computer, the location is C WindowsSystem. Driversetchosts. Add the following information to the hosts file For headnode. For headnode. 1. 1. From the computer that you connected to the Azure virtual network that is used by the HDInsight cluster, verify that you can ping the head nodes by using the IP address, as well as the hostname. Use SSH to connect to the cluster head node by following the instructions in Connect to an HDInsight cluster using SSH. From the cluster head node, ping the IP address of the desktop computer. Test the connectivity to both IP addresses assigned to the computer One for the network connection. One for the Azure virtual network. Repeat the steps for the other head node. Open Intelli. J IDEA and create a new project. In the New Project dialog box, do the following a. Select HDInsight Spark on HDInsight Scala. Select Next. In the next New Project dialog box, do the following, and then select Finish Enter a project name and location. In the Project SDK drop down list, select Java 1. Spark 2. x cluster, or select Java 1. Spark 1. x cluster. In the Spark version drop down list, the Scala project creation wizard integrates the proper version for the Spark SDK and the Scala SDK. If the Spark cluster version is earlier than 2. Spark 1. x. Otherwise, select Spark. This example uses Spark 2. Scala 2. 1. 1. 8. The Spark project automatically creates an artifact for you. To view the artifact, do the following a. From the File menu, select Project Structure. In the Project Structure dialog box, select Artifacts to view the default artifact that is created. You can also create your own artifact by selecting the plus sign. Add libraries to your project. To add a library, do the following a. Right click the project name in the project tree, and then select Open Module Settings. In the Project Structure dialog box, select Libraries, select the symbol, and then select From Maven. In the Download Library from Maven Repository dialog box, search for and add the following libraries org. Copy yarn site. xml and core site. Use the following commands to copy the files. You can use Cygwin to run the following scp commands to copy the files from the cluster head nodes scp lt ssh user name lt headnode IP address or host name etchadoopconfcore site. Because we already added the cluster head node IP address and hostnames for the hosts file on the desktop, we can use the scp commands in the following manner scp sshuserhn. To add these files to your project, copy them under the src folder in your project tree, for example lt your project directory src. Update the core site. Replace the encrypted key. The core site. xml file includes the encrypted key to the storage account associated with the cluster. In the core site. For more information, see Manage your storage access keys. Remove the following entries from core site. Shell. Decryption. Key. Providerlt value. Save the file. Add the main class for your application. From the Project Explorer, right click src, point to New, and then select Scala class. In the Create New Scala Class dialog box, provide a name, select Object in the Kind box, and then select OK. In the My. Cluster. App. Main. scala file, paste the following code. This code creates the Spark context and opens an execute. Job method from the Spark. Sample object. import org. Spark. Conf, Spark. Context. object Spark. Sample. Main. def main arg ArrayString Unit. Spark. Conf. set. App. NameSpark. Sample. Output. Specs, false. Spark. Contextconf. Spark. Sample. execute. Jobsc. wasb Hdi. SamplesHdi. SamplesSensor. Sample. DatahvacHVAC. HVACOut. Repeat steps 8 and 9 to add a new Scala object called park. Sample. Add the following code to this class. This code reads the data from the HVAC. HDInsight Spark clusters. It retrieves the rows that only have one digit in the seventh column in the CSV file, and then writes the output to HVACOut under the default storage container for the cluster. Spark. Context. object Spark. Sample. def execute. Job sc Spark. Context, input String, output String Unit. Fileinput. find the rows which have only one digit in the 7th column in the CSV. As. Text. Fileoutput. Repeat steps 8 and 9 to add a new class called Remote. Cluster. Debugging. This class implements the Spark test framework that is used to debug the applications. Add the following code to the Remote. Cluster. Debugging class import org. Spark. Conf, Spark. Context. import org. Fun. Suite. class Remote. Cluster. Debugging extends Fun. Suite. testRemote run. Spark. Conf. set. App. NameSpark. Sample. Masteryarn client. Java. Options, Dhdp. JarsSeqC workspaceIdea. ProjectsMy. Cluster. AppoutartifactsMy. Cluster. AppDefault. Artifactdefaultartifact. Output. Specs, false. Spark. Contextconf. Spark. Sample. execute. Jobsc. wasb Hdi. SamplesHdi. SamplesSensor. Sample. DatahvacHVAC. HVACOut. There are a couple of important things to note For. Spark assembly JAR is available on the cluster storage at the specified path. For set. Jars, specify the location where the artifact JAR is created. Typically, it is lt Your Intelli. J project directory outlt project name Default. Artifactdefaultartifact. In theemote. Cluster. Debugging class, right click the test keyword, and then select Create Remote. Cluster. Debugging Configuration. In the Create Remote. Cluster. Debugging Configuration dialog box, provide a name for the configuration, and then select Test kind as the Test name. Leave all the other values as the default settings. America Counterintelligence Domestic Fbis Program Spying. Select Apply, and then select OK. You should now see a Remote run configuration drop down list in the menu bar. In your Intelli. J IDEA project, open Spark. Sample. scala and create a breakpoint next to val rdd.