cloudera cdh

First of all, the environment, there are two clusters, a new one of the old, is going to put the new debugging good then turn the old off.NEW: Cloudera Express 5.6.0,cdh-5.6.0Old: Cloudera Express 5.0.5,cdh-5.0.5A problem was found during the new cluster setup, the following command was used to create an index to the L

First, introduceOozie is a Hadoop-based workflow Scheduler that can submit different types of jobs programmatically through the Oozie Client, such as mapreduce jobs and spark jobs to the underlying computing platform, such as Cloudera Hadoop.Quartz is an open-source scheduling software that provides a variety of triggers and listeners for scheduling execution of tasksThe following uses Quartz + Oozie to submit a MapReduce program to

, the current version management of Apache is chaotic, and various versions emerge one after another, so many beginners are overwhelmed. In contrast, Cloudera has a lot to do with Hadoop version management. We know that Hadoop complies with the Apache open-source protocol and users can freely use and modify Hadoop for free. As a result, many Hadoop versions are available on the market, one of the most famous ones is the release of

from the above, the current version management of Apache is chaotic, and various versions emerge one after another, so many beginners are overwhelmed. In contrast, Cloudera has a lot to do with Hadoop version management. We know that Hadoop complies with the Apache open-source protocol and users can freely use and modify Hadoop for free. As a result, many Hadoop versions are available on the market, one of the most famous ones is the release of

The difference between apache and cloudera is that apache released hadoop2.0.4aplha in April 25, 2013, which is still not applicable to the production environment. Cloudera released CDH4 Based on hadoop0.20 to achieve high namenode availability. The new MR framework MR2 (also known as YARN) also supports MR and MR2 switching. cloudera is not recommended for produ

.x86_64.rpm -Rw-r -- 1 root 4.6 K July 6 16:53 hadoop-hdfs-secondarynamenode-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 root 4.6 K July 6 16:53 hadoop-hdfs-zkfc-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 root 17 M July 6 16:53 hadoop-httpfs-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 root 26 K July 6 16:53 hadoop-libhdfs-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 root 11 M July 6 16:53 hadoop-mapreduce-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 root 4.6 K July 6 16:53 hadoop-mapreduce-historyserver-2.0.5-1.el6.x86_64.rpm -Rw-r -- 1 r

The environment is implemented under vmware7, and the operating system is fedora14 (Nima 12 and 13 have all tried it. Due to Yum source problems, some RPM packages are searched for by themselves, which cannot afford to hurt ..) Talk less, work! 1. Ensure that your yum source is up-to-date and availableThis saves a lot of trouble. For example, Pax, patch, and Python-setuptools are all dependent on the cdh3 component. 2. Install JDK and JRE. But for non-rpm version does not recognize, when i

Currently, there are three main versions of Hadoop that are not charged (all foreign vendors), respectively:Apache (the most original version, all distributions are improved based on this version), the Cloudera version (Cloudera ' s distribution including Apache Hadoop, abbreviated CDH), Hortonworks version ( Hortonworks Data Platform, referred to as "HDP") Hort

= $JAVA _home/bin: $JRE _home/bin: $PATH$ sudo chmod +x/etc/profile.d/java.sh$ source/etc/profile 3. Configure the Hadoop installation source The code is as follows Copy Code $ sudo rpm--import Http://archive.cloudera.com/cdh4/redhat/5/x86_64/cdh/RPM-GPG-KEY-cloudera$ cd/etc/yum.repos.d/$ sudo wget http://archive.cloudera.com/cdh4/redhat/6/x86_64/

Label:Error Description: Since my Hadoop cluster is automatically installed with Cloudera Manager online, their installation path must follow the Cloudera rules, and only see the official documentation for Cloudera, see:/http Www.cloudera.com/content/cloudera/en/documentation/core/latest/topics/cdh_ig_jdbc_driver_insta

Problem descriptionWhen running a mapreduce job on HBase, the following exception is reported: Illegalaccesserror:class com.google.protobuf.HBaseZeroCopyByteString cannot access its Superclass com.google.protobuf.LiteralByteStringUse the HBase environment as follows: CDH5.0.1, hbase version: 0.96.1Cause of the problemThis isssue occurs because of the optimization introduced in HBASE-9867 that inadvertently introduced a classloader Depende Ncy. This affects both jobs using the-libjars option and

The official cloudera Impala tutorial explains some basic Impala operations, but there is a lack of coherence before and after the operation steps. In this section, W selects some examples in impala tutorial, A complete example is provided from scratch: creating tables, loading data, and querying data. An entry-level tutorial is provided to explain "Hello World" to Impala through the operations in this article ". This article assumes that you have alr

Build your own big data platform product based on Ambari Currently, there are two mainstream enterprise-level Big Data Platform products on the market: CDH launched by Cloudera and HDP launched by Hortonworks, among them, HDP uses the open-source Ambari as a management and monitoring tool. CDH corresponds to Cloudera M

Brief introductionSpark SQL provides JDBC connectivity, which is useful for connecting business intelligence (BI) tools to a spark cluster And for sharing a cluster across multipleusers. The JDBC server runs as a standalone Spark driver program The can is shared by multiple clients. Any client can cache tables in memory, query them, and so on and the cluster resources and cached data would be shared Amon g all of them.Spark SQL ' s JDBC server corresponds to the HiveServer2 in Hive. It is also k

CDH to us already encapsulated, if we need spark on Yarn, just need yum to install a few packages. The previous article I have written if you build your own intranet CDH Yum server, please refer to "CDH 5.5.1 Yum Source Server Building"http://www.cnblogs.com/luguoyuanf/p/56187ea1049f4011f4798ae157608f1a.html If you do not have an intranet yarn server, use the

Rhel automatic installation of zookeeper shell scriptsA: This script runs the machine, Linux RHEL6B,c,d,... : Machine to be installed zookeeper cluster, Linux RHEL6First, on machine A that the script runs, determine that you can log on to the machine b,c,d to install ZK without password ssh,... , then you can run this script on a:$./install_zookeeperPremise:B, C, D machine must be configured well repo, this script uses Cdh5 repo, the following content is saved to:/etc/yum.repos.d/

A: This script runs the machine, the Linux RHEL6B,c,d,... : To be installed zookeeper cluster machine, Linux RHEL6 First, on the machine A that runs the script, determine if SSH can be logged in without a password to the machine b,c,d to install ZK,... , and then you can run this script on a: Copy Code code as follows: $./install_zookeeper Premise: B, C, D machine must be configured well repo, this script uses Cdh5 repo, the following content is saved to:/etc/yum.repo

] For more information on the errors and possible solutions, please REA D the following articles:[error] [Help 1] http://cwiki.apache.org/conflUence/display/maven/mojoexecutione Xception[error][error] After correcting the problems, you can resume the build with the Command[error] mvn 　　Helpless, and then went to compile, 3.3.2, the result:It's not going to compile anymore.Here, I go to the net to find the rea

Datanode nodemanager server: 192.168.1.100 192.168.1.101 192.168.1.102 Zookeeper server cluster (for namenode high-availability automatic failover): 192.168.1.100 192.168.1.101 Jobhistory server (used to record mapreduce logs): 192.168.1.1 NFS for namenode HA: 192.168.1.100 Environment deployment 1. Add the YUM repository to CDH4 1. the best way is to put the cdh4 package in the self-built yum warehouse. For how to build a self-built yum warehouse, see self-built YUM Warehouse 2. if you do

sqlite3 to a familiar relational database. Currently, MySQL, Postgresql, and Oracle are supported. If necessary, it may combine the underlying access control mechanism of the Hadoop cluster, such as Kerberos or Hadoop SLA, with the user management and authorization authentication functions of Hue to better restrict and control access permissions. Based on the Hue features we mentioned earlier, we can select different Hue applications based on our actual application scenarios. Through this plu