Hive learning Roadmap
The hadoop family articles mainly introduce hadoop family products. Common projects include hadoop, hive, pig, hbase, sqoop, mahout, Zookeeper, Avro, ambari, chukwa, new projects include yarn, hcatalog, oozie, Cassandra, hamr, whirr, flume, bigtop, crunch, and hue.
Since 2011, China has entered the age of big data. Family software represented by hadoop occupies a vast territory of big data processing. Open-source communities and
corresponding Configuration Service
Select a service and click "Check role assignment". The allocation scheme is different because the number of machines in each province is inconsistent. for details about each province, see the separate settings document. uniform installation services: HDFS, YARN, Zookeeper, Hive, Impala, Oozie, Sqoop, Hue
The NameDome and YARN roles must be determined. Other roles can be assigned after logon.
Copyright
8.8 M July 6 16:53 hadoop-yarn-2.0.5-1.el6.x86_64.rpm
-Rw-r -- 1 root 4.5 K July 6 16:53 hadoop-yarn-nodemanager-2.0.5-1.el6.x86_64.rpm
-Rw-r -- 1 root 4.4 K July 6 16:53 hadoop-yarn-proxyserver-2.0.5-1.el6.x86_64.rpm
-Rw-r -- 1 root 4.5 K July 6 16:53 hadoop-yarn-resourcemanager-2.0.5-1.el6.x86_64.rpm
The only difference is that there is no cdh prefix in front of Cloudera. In addition to compiling 2.x, 1.x, I also tried. By default, the source code file cannot be found remotely.
I also
system on to HDFS, and populate tables in Hive and HBase. Sqoop integrates with Oozie, allowing your to schedule and automate import and export tasks. Sqoop uses a connector based architecture which supports plugins that provide connectivity to new external systems.What happens underneath the covers when you run Sqoop is very straightforward. The dataset being transferred is sliced to different partitions and a map-only job is launched with individua
can use tools to read and write data in the hive associated column format. Hcatalog provides a command line tool for users who do not operate metasotre using hive DDL statements. It also provides the notification service. If you use a workflow tool such as oozie, you will be notified when new data is available.Hadoop rest Interface
Templeton is a role in the novel Charlotte's Web. It is a greedy mouse that will help the protagonist (pig Wilber), but
server scripts. The server's script involves scheduling the environment variables, Oracle databases, and Hadoop ecosystem components. Returns the script run state after the execution of the server script schedule and provides a failed re-run interface.In order to achieve the requirements, has dispatched a variety of scheduling tools, such as Apache Oozie, Azkaban, Pentaho, etc., and finally compared the various advantages and disadvantages of the att
=/data1/mysql/mysql.sock
Default-character-set=utf8
[mysqld]
#skip-grant-tables
socket=/ Data1/mysql/mysql.sock #增加此行, previously only [MySQL] added this
interactive_timeout=300
wait_timeout=300
14, restart the MySQL service.
15, using the root user before the upgrade to connect MySQL:
[hadoop@zlyh08 report_script]$ mysql-hzlyh08-uroot-p
Enter Password:
Welcome to the MySQL monitor. Commands End With; or \g.
Your MySQL connection ID is 233
Server version:5.6.25 mysql Community ser
.
Octopy is a pure Python mapreduce implementation that has only one source file and is not suitable for "real" computing.
Mortar is another Python option, which was released not long ago, and allows users to submit data to the Amazon S3 via a Web application that the Apache Pig or Python jobs handles.
There are some higher levels of Hadoop ecosystem interfaces, like Apache hive and Pig. Pig allows users to write custom functions in Python, which is run by Jython. Hive also has a Python
FileSystem class can specify whether to cache filesystem instances by "Fs.%s.impl.disable.cache" (where% S is replaced with the corresponding scheme, such as HDFs, Local, S3, S3n, and so on, once the corresponding filesystem instance is created, the instance is saved in the cache, and each get gets the same instance each time thereafter. So when set to true, the above exception can be resolved.
Reference Link: 1.http://stackoverflow.com/questions/23779186/ Ioexception-filesystem-closed-except
provides connectors for mapreduce and pig, and users can use the tool to read and write associated column-format data for hive. Hcatalog provides command-line tools for users who do not operate metasotre by Hive DDL statements on hive. It also provides notification services that can be notified when new data is available, using a workflow tool such as Oozie.
The rest interface of Hadoop
Templeton is a role in the novel "Charlotte's Web". It is a gr
structure diagram of off-line analysis system
The overall architecture of the entire offline analysis is to use Flume to collect log files from the FTP server and store them on the Hadoop HDFS file system, then clean the log file with the MapReduce of Hadoop, and finally use HIVE to build the Data warehouse for offline analysis. Task scheduling is done using Shell scripts, and of course you can try some automated task scheduling tools, such as Azkaban or O
installation package.
Oracle version of JDK
Requires Oracle's java1.7 and above JDK
Download Address
Http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html
I have chosen a rpm here.
MySQL offline installation package
http://dev.mysql.com/downloads/mysql/Open URL: Select Platform: Choose Linux-genericSelect Linux-generic (glibc 2.5) (x86, 64-bit), RPM for download
I download here 5.6.34 version, if the same as I downloaded, you can use the link
Http://cdn.mysql.
The Hadoop family of articles, mainly about the Hadoop family of products, commonly used projects include Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, Chukwa, and new additions to the project including, YARN, Hcatalog, Oozie, Cassandra, Hama, Whirr, Flume, Bigtop, Crunch, hue, etc.
Since 2011, China has entered the era of big data surging, and the family software, represented by Hadoop, occupies a vast expanse of data processing.
process the data and gives a feasible view. To convert to a relational schema, we can replace it with 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
Tag: CAs ORC value try ignores HDFs body overwrite resourceFirst, the basic offline data processing architecture:
Data acquisition Flume:web Log writes to HDFs
Data cleansing of dirty data by Spark, Hive, Mr and other computational frameworks. When you're done cleaning, put it back in HDFs.
Data processing According to needs, conduct business statistics and analysis. Also done through the computational framework
Processing results stored in RDBMS, NoSQL
The visualization
you the flexibility to choose your database and configuration.Of course, you can install a number of different databases in a single set of systems. But this can bring a lot of uncertainties. So Cloudera recommends that you always use the same database.In very diverse cases, you need to install the corresponding service with database on the same machine, which reduces network IO. Improve overall efficiency. Of course, you can also install the service and database separately on different machine
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