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Java Operation HDFS Development environment constructionWe have previously described how to build hdfs pseudo-distributed environment on Linux, and also introduced some common commands in HDFs. But how do you do it at the code level? This is what is going to be covered in this section:1. First use idea to create a MAVEN project:Maven defaults to a warehouse that does not support CDH, and needs to be configured with the
from time to time. I will record the installation process here for my convenience in the future, on the other hand, we hope to inspire people who encounter the same problems in the future.First of all, let's explain why we should use tarball for installation. cdh provides a manager Method for installation, apt-get for the Debian series, and yum for the Redhat series, however, these installation methods have completed some details for us. If we want t
requirements and allow organizations to start a pilot project to deploy Private clouds at the same time. The best application scenario of this deployment model is that enterprises want to use private cloud technology through the storage pool and use big data technology internally. Best practices indicate that enterprises should first deploy big data technology in your production data warehouse environment, and then build and configure your private cloud storage solution. If the Apache hadoop
1. Download Ambari-impala-service sudo git clone https://github.com/cas-bigdatalab/ambari-impala-service.git/var/lib/ambari-server/resources/stacks /hdp/2.4/services/impala 2./ETC/YUM.REPOS.D New Impala.repo [Cloudera-cdh5] # Packages for Cloudera's distribution for Hadoop, Version 5, on RedHat or CentOS 7 x86_64 Name=cloudera ' s distribution for Hadoop, Version 5 baseurl=https://archive.cloudera.com/c
basis for instant queries, introducing the Spark computing framework to support machine learning type calculations, and validating Whether spark, the new computing framework, can replace the traditional MapReduce-based computing framework. Figure 2 is the architectural evolution of the entire system.In this architecture, we deploy spark 0.8.1 on yarn and isolate the spark-based machine learning task by separating queue, calculating the rank of the daily MapReduce task and hive-based instant ana
learning type calculations. and verify that Spark's new computing framework is a complete replacement for the traditional MapReduce-based computing framework. Figure 2 is the architectural evolution of the entire system.In this architecture, we deploy spark 0.8.1 on yarn and isolate the spark-based machine learning task by separating queue, calculating the rank of the daily MapReduce task and hive-based instant analysis task.To introduce spark, the first step is to get the spark package that su
Environment Building-hadoop cluster building Before writing, we quickly set up the centos cluster environment. Next, we will start building hadoop clusters. Lab EnvironmentHadoop version: CDH 5.7.0Here, I would like to say that we have not selected the official version because the CDH version has already solved the dependencies between various components. Later, we will use more components in the hadoop fam
RHEL automatically installs the zookeeper shell script, rhelzookeeperRHEL automatically installs the zookeeper shell script A: This script runs on Linux RHEL6. B, C, D,...: The machine on which zookeeper cluster is to be installed, Linux RHEL6 First, you can log on to machine B, C, D, and ,... and then you can run the script on: $ ./install_zookeeper Prerequisites: B, C, D machine must be configured with repo, this script uses cdh5 repo, the following content is saved to:/etc/yum. repos. d/
HADOOP:CDH 5--The Journalnode of the different steps Author:fu Cloudera Manager has an HDFS warning, similar to the following image: The solution is: 1, the first to solve the simple problem, check the warning set threshold of how much, so you can quickly locate the problem where, sure enough journalnode sync status hint first eliminate, 2, and then solve the sync status problem, first find the explanation of the prompt , visible on the official web.
ObjectiveIn the use of CDH cluster process, it will inevitably cause the node IP or hostname changes due to some irresistible reasons, and CM's monitoring interface can not complete these things, but CM will all the hosts in the cluster information is in the PostgreSQL database hosts table,Now let's do this by modifying the hosts.The first step is to close the service1. Turn off the Cluster service, and Cloudera
components of the entire Hadoop ecosystem, and deep optimization, recompile to a complete high-performance big Data universal computing platform, to achieve the organic coordination of the components. As a result, DKH has up to 5 times times (maximum) performance gains in computing performance compared to open-source big data platforms. Dkhadoop simplifies the management and operation of the cluster by simplifying the complex large data cluster configuration to three nodes (master node, managem
Modify the IP address, hostName, and cdh5hostname of the host node in the cdh5 cluster.Preface When using the cdh cluster, it is inevitable that the node IP address or hostName changes due to some irresistible reasons, and the cm monitoring interface cannot complete these tasks, however, cm stores all host information in the hosts table of the postgresql database, Now let's modify the hosts to complete this operation.Step 1: Disable the service 1. Dis
Install the Impala dependency package first Add repo using Yum installation sudo wget-o/etc/yum.repos.d/bigtop.repo Http://www.apache.org/dist/bigtop/bigtop-0.7.0/repos/centos5/bigtop.repo sudo yum install bigtop-utils The version of CDH that Hadoop uses for 5.1.2 is required for the Impala version 1.4.1 Download the RMP package from the Cloudera warehouse impala1.4.1 Warehouse Address http://archive.cl
Reference http://www.mamicode.com/info-detail-1523356.html1. Remote execution: Vi/etc/profileAdd a line:Pythonpath= $SPARK _home/python/: $SPARK _home/python/lib/py4j-0.9-src.zipor pythonpath= $SPARK _home/python/: $SPARK _home/python/lib/py4j-0.8.2.1-src.zip2. Install Pip and py4jDownload pip-9.0.1.tar.gz and py4j-0.10.4.tar.gzUnzip pip-9.0.1.tar.gz and PY4J-0.10.4.TAR.GZ,CD to extract directory execution: sudo python setup.py install3. Local Pycharm settingsFile > Settings > Project interprete
-source version of cloudera ). Developers often need to install the hadoop environment on machines for testing. They found that vagrant is a very convenient tool in this regard. An example of a vagrant configuration file can be tested by yourself. You need to download and install vagrant (help address http://docs.vagrantup.com/v2/installation/index.html) and virtualbox. After everything is installed, copy and paste the following text and save it as v
Currently, hadoop versions are messy and the relationship between versions is often unclear. Below is a brief summary of the evolution of Apache hadoop and cloudera hadoop versions. The official Apache hadoop version description is as follows: 1.0.x-Current stable version, 1.0 Release 1.1.x-Current beta version, 1.1 Release 2. x. x-Current alpha version 0.23.x-Simmilar to 2. x. x but missing NN ha. 0.22.x-Does not include
Recently the company cloud host can apply for the use of, engaged in a few machines to get a small cluster, easy to debug the various components currently used. This series is just a personal memo to use, how convenient how to come, and not necessarily the normal OPS operation method. At the same time, because the focus point is limited (currently mainly spark, Storm), and will not be the current CDH of the various components are complete, just accor
1. Framework Overview ?? The architecture of event processing is as follows.2. Optimization Summary ?? When we deploy the entire solution for the first time,kafkaAndflumeThe components are executed very well,spark streamingIt takes 4-8 minutes for an application to process a singlebatch. There are two reasons for this delay: First, we useDataFrameTo strengthen the data, and the enhanced data needshiveRead a large amount of data. Second, our parameter configuration is not ideal. ?? In order to op
a generic term: We can also map this basic architecture of access, storage, and processing to the Hadoop ecosystem, as follows: Of course, this is not the only Hadoop architecture. By introducing other projects in the ecosystem, we can build more complex projects. But this is really the most common Hadoop architecture and can be a starting point for us to enter the big data world. In the remainder of this article, we'll complete an example application that uses Apache Flume, Apache HDFS,
Label:First, what is Sqoop Sqoop is an open source tool that is used primarily in Hadoop (Hive) and traditional databases (MySQL, PostgreSQL ...) Data can be transferred from one relational database (such as MySQL, Oracle, Postgres, etc.) to the HDFs in Hadoop, or the data in HDFs can be directed into a relational database. Second, the characteristics of Sqoop One of the highlights of Sqoop is the ability to import data from a relational database into HDFs through the mapreduce of Hadoop. Iii. S
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