java basics for hadoop

Computing ClustersHigh-performance computing clusters, referred to as HPC clusters. Such clusters are dedicated to providing powerful computing power that a single computer cannot provide, including numerical computation and data processing, and tends to pursue comprehensive performance. HPG is similar to supercomputing, but different, and computing speed is the first goal of Supercomputing pursuit. The fastest speed, maximum storage, the largest volume, and the most expensive price represent t

01_note_hadoop introduction of source and system; Hadoop cluster; CDH FamilyUnzip Tar Package Installation JDK and environment variable configurationTAR-XZVF jdkxxx.tar.gz to/usr/app/(custom app to store the app after installation)Java-version View current system Java version and environmentRpm-qa | grep Java View inst

Part 1: hadoop RPC Basics RPC, remote program call, an application instance of the C/S model in distributed computing. Like other RPC frameworks, hadoop is divided into four parts: Serialization layer: supports multiple frameworks for serialization and deserialization. Function call layer: implemented using Java re

; Resultrdd1.take (100)res7:array[(String, Int)] = Array ((because,1), (-reconfig,2), (guide,4), (under-replicated,1), (blocks,5), (maintained , 1), (responsibility,1), (filled,1), (order,5), ([key-value,1), (prematurely,1), (cluster:,1), (type,1), (behind,1), ( however,,1), (competing,1), (been,2), (begins,1), (up-to-date,3), (permissions,3), (browse,1), (list:,1), (improved,1) , (balancer,2), (fine.,1), (over,1), (dfs.hosts,,2), (any,7), (connect,1), (select,2), (version,7), (disks.,1), file,3

Environment[Email protected] soft]#Cat/etc/Issuecentos Release6.5(Final) Kernel \ r \m[[email protected] soft]#uname-Alinux vm80282.6. +-431. el6.x86_64 #1SMP Fri Nov A Geneva: the: theUtc -x86_64 x86_64 x86_64 gnu/Linux[[email protected] soft]# Hadoop versionhadoop2.7.1Subversion https://git-wip-us.apache.org/repos/asf/hadoop.git-r 15ecc87ccf4a0228f35af08fc56de536e6ce657aCompiled by Jenkins on -- .-29t06:04zcompiled with Protoc2.5.0From source with c

(1) First create Java projectSelect File->new->java Project on the Eclipse menu.and is named UploadFile.(2) Add the necessary Hadoop jar packagesRight-click the JRE System Library and select Configure build path under Build path.Then select Add External Jars. Add the jar package and all the jar packages under Lib to your extracted

directories under the HDFs root directory: Hadoop FS-LSR/(2) Creating a folder in HDFs:hadoop fs-mkdir folder nameIn the root directory, create a folder called Di:(3) Uploading files to HDFs:Hadoop fs-put Local source path destination storage pathUpload a log file from the local system to the Di folder: Hadoop fs-put Test.log/di *ps: The files that we upload through the

The following error is reported:Workaround:1. Increase Debugging informationAdd the following information in the hadoop_home/etc/hadoop/hadoop-env.sh file2. Perform another operation to see what errors are reportedThe above information shows that 2.14 GLIBC library is requiredWorkaround:1. View the libc version of the system (LL/LIB64/LIBC.SO.6)Display version is 2.12The first solution, using the 2.12 versi

overload the protected function, such as issplitable (), which is used to determine whether you can slice a block and return it by default to true, indicating that as long as the data block is larger than the HDFS block size, Then it will be sliced.But sometimes you don't want to slice a file, such as when some binary sequence files cannot be sliced, you need to overload the function to return FALSE. when using Fileinputformat, your primary focus should be on the decomposition of data blocks

First, the Linux basic Environment1. Linux common version and VMware virtual machine install Linux system2. Virtual Machine Network configuration (IP address, host name, firewall)3. File Basic command operation4. Four Remote connection tools useIi. Linux Basic commands1. User and group creation, deletion, change, and authorization2. File/directory creation, deletion, movement, and copy renaming3. Editor Vi/vim basic use4. File Common operation (content view, append, etc.)Third, Linux system mana

now let's take a closer look at the FileSystem class for Hadoop. This class is used to interact with Hadoop's file system. While we are mainly targeting HDFS here, we should let our code use only abstract class filesystem so that our code can interact with any Hadoop file system. When we write the test code, we can test it with the local file system, use HDFs when deploying, just configure it, no need to mo

xxx.tar.gz to extract two packages separately and copy them to the/OPT directory. 4. Configure the Java Environment root permission to open the/etc/profile file and add the following at the end:Java_home=/opt/jdk1.7.17path= $JAVA _home/bin: $PATHCLASSPATH =.: $JAVA _home/lib/tools.jar: $JAVA _home/lib/ Dt.jarexport ja

Learn a few basics before you go through API operationsFirst, the basic data types of Hadoop are different from the basic data types of Java, but there are corresponding relationshipsSuch asIf you need to define your own data type, you must implement writableHadoop data types can be obtained using the Get method for the corresponding

IntroductionSince Hadoop is installed on Linux systems, it is necessary to use Eclipse to develop Java on Linux systems. Many companies now require the experience of developing Java on Linux, so this is a great opportunity for a practiced hand. Learning Hadoop is not just learning