{"id":31652,"date":"2025-10-12T09:40:59","date_gmt":"2025-10-12T06:40:59","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/?p=31652"},"modified":"2025-10-12T09:40:59","modified_gmt":"2025-10-12T06:40:59","slug":"ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/","title":{"rendered":"Ubuntu 16.04 \u00dczerine Hadoop’u Stand-Alone Modda Kurulum Rehberi"},"content":{"rendered":"

Ubuntu 16.04 \u00dczerine Hadoop’u Stand-Alone Modda Kurulum Rehberi<\/h2>\n

<\/p>\n

Giri\u015f<\/h2>\n

B\u00fcy\u00fck veri (Big Data) d\u00fcnyas\u0131nda en pop\u00fcler ve yayg\u0131n kullan\u0131lan \u00e7er\u00e7evelerden biri olan Apache Hadoop, da\u011f\u0131t\u0131k depolama ve b\u00fcy\u00fck veri k\u00fcmelerinin i\u015flenmesi i\u00e7in g\u00fc\u00e7l\u00fc bir platform sunar. Hadoop’un temel mimarisi, HDFS (Hadoop Distributed File System) ve YARN (Yet Another Resource Negotiator) gibi bile\u015fenleri i\u00e7erir. HDFS, verileri birden \u00e7ok makineye da\u011f\u0131tarak g\u00fcvenilirlik ve y\u00fcksek eri\u015filebilirlik sa\u011flarken, YARN, k\u00fcme kaynaklar\u0131n\u0131 y\u00f6netir ve veri i\u015fleme uygulamalar\u0131n\u0131 (\u00f6rne\u011fin MapReduce) \u00e7al\u0131\u015ft\u0131r\u0131r.<\/p>\n

Hadoop’u kullanmaya ba\u015flamak isteyenler veya k\u00fc\u00e7\u00fck \u00f6l\u00e7ekli testler yapmak isteyen geli\u015ftiriciler i\u00e7in, Hadoop’u tek bir makine \u00fczerinde “Stand-Alone Modda” kurmak olduk\u00e7a pratik bir y\u00f6ntemdir. Stand-Alone mod, Hadoop’un varsay\u0131lan \u00e7al\u0131\u015fma modudur ve t\u00fcm Hadoop bile\u015fenlerinin tek bir JVM (Java Virtual Machine) i\u00e7inde \u00e7al\u0131\u015ft\u0131\u011f\u0131 anlam\u0131na gelir. Bu mod, da\u011f\u0131t\u0131k dosya sistemi veya kaynak y\u00f6netimi gerektirmeyen, tamamen yerel bir dosya sistemi \u00fczerinde \u00e7al\u0131\u015fan MapReduce programlar\u0131 i\u00e7in idealdir. Genellikle \u00f6\u011frenme, hata ay\u0131klama ve geli\u015ftirme ama\u00e7l\u0131 kullan\u0131l\u0131r.<\/p>\n

Bu kapsaml\u0131 rehberde, Ubuntu 16.04 i\u015fletim sistemi \u00fczerine Apache Hadoop’u Stand-Alone modda ad\u0131m ad\u0131m nas\u0131l kuraca\u011f\u0131n\u0131z\u0131 detayl\u0131 bir \u015fekilde anlataca\u011f\u0131z. Kurulum s\u00fcreci, gerekli \u00f6n ko\u015fullar\u0131n haz\u0131rlanmas\u0131ndan, Hadoop’un indirilip yap\u0131land\u0131r\u0131lmas\u0131na ve \u00f6rnek bir MapReduce i\u015finin \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131na kadar t\u00fcm ad\u0131mlar\u0131 i\u00e7erecektir.<\/p>\n

\u00d6n Gereksinimler<\/h2>\n

Hadoop kurulumuna ba\u015flamadan \u00f6nce, sisteminizin belirli gereksinimleri kar\u015f\u0131lad\u0131\u011f\u0131ndan emin olman\u0131z \u00f6nemlidir. Bu ad\u0131mlar, sorunsuz bir kurulum deneyimi i\u00e7in temel olu\u015fturacakt\u0131r.<\/p>\n

Ubuntu 16.04 \u0130\u015fletim Sistemi<\/h3>\n

Bu rehber, Ubuntu 16.04 LTS (Long Term Support) s\u00fcr\u00fcm\u00fc i\u00e7in \u00f6zel olarak haz\u0131rlanm\u0131\u015ft\u0131r. Farkl\u0131 Ubuntu s\u00fcr\u00fcmlerinde veya di\u011fer Linux da\u011f\u0131t\u0131mlar\u0131nda benzer ad\u0131mlar izlenebilir, ancak baz\u0131 komutlar veya paket adlar\u0131 farkl\u0131l\u0131k g\u00f6sterebilir. Bir sanal makine (VMware, VirtualBox) veya fiziksel bir makine kullanabilirsiniz.<\/p>\n

\u0130nternet Ba\u011flant\u0131s\u0131<\/h3>\n

Gerekli paketleri ve Hadoop dosyalar\u0131n\u0131 indirmek i\u00e7in aktif bir internet ba\u011flant\u0131s\u0131 gereklidir.<\/p>\n

Sudo Yetkileri<\/h3>\n

Kurulum s\u0131ras\u0131nda sistem d\u00fczeyinde de\u011fi\u015fiklikler yap\u0131lmas\u0131 gerekece\u011finden, sudo<\/code> komutunu kullanma yetkisine sahip bir kullan\u0131c\u0131 hesab\u0131n\u0131z olmal\u0131d\u0131r. Genellikle, kurulumu ger\u00e7ekle\u015ftiren kullan\u0131c\u0131n\u0131n zaten bu yetkilere sahip oldu\u011fu varsay\u0131l\u0131r.<\/p>\n

Temel Linux Komut Bilgisi<\/h3>\n

Terminal \u00fczerinde temel dosya sistemi navigasyonu (cd<\/code>, ls<\/code>), dosya d\u00fczenleme (nano<\/code>, vi<\/code> veya gedit<\/code>), paket y\u00f6netimi (apt<\/code>) gibi komutlara a\u015fina olman\u0131z beklenir.<\/p>\n

Java Geli\u015ftirme Kiti (JDK) Kurulumu<\/h2>\n

Hadoop, Java ile yaz\u0131lm\u0131\u015ft\u0131r ve \u00e7al\u0131\u015fmak i\u00e7in bir Java Runtime Environment (JRE) veya bir Java Development Kit (JDK) gerektirir. Geli\u015ftirme ve daha ileri d\u00fczey Hadoop bile\u015fenleri i\u00e7in JDK tercih edilir. Ubuntu 16.04 i\u00e7in OpenJDK 8 en uygun ve kararl\u0131 s\u00fcr\u00fcmlerden biridir.<\/p>\n

Sistem Paketlerini G\u00fcncelleme<\/h3>\n

\u00d6ncelikle, sisteminizdeki paket listesini g\u00fcncelleyelim ve mevcut paketleri y\u00fckseltelim:<\/p>\n

sudo apt update\nsudo apt upgrade -y<\/code><\/pre>\n
OpenJDK 8 Kurulumu<\/h3>\n
A\u015fa\u011f\u0131daki komutla OpenJDK 8’i kurabilirsiniz:<\/p>\n
sudo apt install openjdk-8-jdk -y<\/code><\/pre>\n
Kurulum tamamland\u0131ktan sonra, Java s\u00fcr\u00fcm\u00fcn\u00fc do\u011frulayarak kurulumun ba\u015far\u0131l\u0131 olup olmad\u0131\u011f\u0131n\u0131 kontrol edebilirsiniz:<\/p>\n
java -version\njavac -version<\/code><\/pre>\n
\u00c7\u0131kt\u0131 olarak “openjdk version “1.8.0_XXX”” benzeri bir \u015fey g\u00f6rmelisiniz.<\/p>\n
JAVA_HOME Ortam De\u011fi\u015fkenini Ayarlama<\/h3>\n
Hadoop’un Java’y\u0131 nerede bulaca\u011f\u0131n\u0131 bilmesi i\u00e7in JAVA_HOME<\/code> ortam de\u011fi\u015fkenini ayarlamam\u0131z gerekir. Bu, genellikle \/etc\/environment<\/code> dosyas\u0131na veya kullan\u0131c\u0131n\u0131n ~\/.bashrc<\/code> dosyas\u0131na eklenerek yap\u0131l\u0131r. Kullan\u0131c\u0131 baz\u0131nda ayarlamak daha esnektir.<\/p>\n
\u00d6ncelikle Java’n\u0131n y\u00fckl\u00fc oldu\u011fu dizini bulal\u0131m:<\/p>\n
sudo update-alternatives --config java<\/code><\/pre>\n
Bu komut, sistemdeki Java kurulumlar\u0131n\u0131 listeler ve size yolunu g\u00f6sterir. Genellikle OpenJDK 8 i\u00e7in yol \/usr\/lib\/jvm\/java-8-openjdk-amd64<\/code> gibi bir \u015feydir. Bu yolu kopyalay\u0131n.<\/p>\n
\u015eimdi ~\/.bashrc<\/code> dosyas\u0131n\u0131 d\u00fczenleyelim:<\/p>\n
nano ~\/.bashrc<\/code><\/pre>\n
Dosyan\u0131n sonuna a\u015fa\u011f\u0131daki sat\u0131rlar\u0131 ekleyin (kendi Java yolunuzu kullanarak):<\/p>\n
export JAVA_HOME=\/usr\/lib\/jvm\/java-8-openjdk-amd64\nexport PATH=$PATH:$JAVA_HOME\/bin<\/code><\/pre>\n
De\u011fi\u015fiklikleri kaydedin (Ctrl+O, Enter) ve dosyadan \u00e7\u0131k\u0131n (Ctrl+X).<\/p>\n
~\/.bashrc<\/code> dosyas\u0131ndaki de\u011fi\u015fiklikleri uygulamak i\u00e7in terminali yeniden ba\u015flatabilir veya a\u015fa\u011f\u0131daki komutu \u00e7al\u0131\u015ft\u0131rabilirsiniz:<\/p>\n
source ~\/.bashrc<\/code><\/pre>\n
JAVA_HOME<\/code> de\u011fi\u015fkeninin do\u011fru ayarland\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in:<\/p>\n
echo $JAVA_HOME<\/code><\/pre>\n
Do\u011fru yolu g\u00f6rmelisiniz.<\/p>\n
SSH Kurulumu ve Yap\u0131land\u0131rmas\u0131<\/h2>\n
Hadoop, k\u00fcmedeki d\u00fc\u011f\u00fcmler aras\u0131nda (hatta tek d\u00fc\u011f\u00fcml\u00fc bir kurulumda bile kendi bile\u015fenleri aras\u0131nda) \u015fifresiz SSH ba\u011flant\u0131lar\u0131na ihtiya\u00e7 duyar. Bu, NameNode’un DataNode’lar\u0131, ResourceManager’\u0131n NodeManager’lar\u0131 ba\u015flatmas\u0131 gibi i\u015flemlerde kullan\u0131l\u0131r. Stand-Alone modda bile bu iyi bir uygulamad\u0131r ve ileride Pseudo-Distributed veya Fully-Distributed modlara ge\u00e7i\u015f yapmay\u0131 planl\u0131yorsan\u0131z zorunludur.<\/p>\n
OpenSSH Kurulumu<\/h3>\n
E\u011fer sisteminizde OpenSSH sunucusu ve istemcisi kurulu de\u011filse, a\u015fa\u011f\u0131daki komutla kurun:<\/p>\n
sudo apt install openssh-server openssh-client -y<\/code><\/pre>\n
\u015eifresiz SSH Anahtar \u00c7ifti Olu\u015fturma<\/h3>\n
\u015eifresiz ba\u011flant\u0131 kurmak i\u00e7in bir SSH anahtar \u00e7ifti olu\u015fturmam\u0131z ve ortak anahtar\u0131 yetkilendirilmi\u015f anahtarlar listesine eklememiz gerekir.<\/p>\n
ssh-keygen -t rsa -P '' -f ~\/.ssh\/id_rsa<\/code><\/pre>\n
*   -t rsa<\/code>: RSA algoritmas\u0131n\u0131 kullanarak bir anahtar olu\u015fturur.
\n*   -P ''<\/code>: Parola bo\u015f b\u0131rak\u0131l\u0131r, bu da \u015fifresiz eri\u015fim sa\u011flar.
\n*   -f ~\/.ssh\/id_rsa<\/code>: Anahtar dosyas\u0131n\u0131n yolunu belirtir.<\/p>\n
Ortak anahtar\u0131 (public key) yetkilendirilmi\u015f anahtarlar (authorized keys) dosyas\u0131na ekleyin:<\/p>\n
cat ~\/.ssh\/id_rsa.pub >> ~\/.ssh\/authorized_keys<\/code><\/pre>\n
Yetkilendirilmi\u015f anahtarlar dosyas\u0131n\u0131n izinlerini ayarlay\u0131n:<\/p>\n
chmod 0600 ~\/.ssh\/authorized_keys<\/code><\/pre>\n
SSH Ba\u011flant\u0131s\u0131n\u0131 Test Etme<\/h3>\n
\u015eimdi kendi makinenize \u015fifresiz olarak SSH yap\u0131p yapamad\u0131\u011f\u0131n\u0131z\u0131 kontrol edin:<\/p>\n
ssh localhost<\/code><\/pre>\n
\u0130lk ba\u011flant\u0131da bir parmak izi uyar\u0131s\u0131 alabilirsiniz, “yes” yazarak devam edin. E\u011fer parola sormadan ba\u011flanabiliyorsan\u0131z, SSH yap\u0131land\u0131rmas\u0131 ba\u015far\u0131l\u0131d\u0131r. Ba\u011flant\u0131y\u0131 kapatmak i\u00e7in exit<\/code> yaz\u0131n.<\/p>\n
Hadoop \u0130ndirme ve \u00c7\u0131kartma<\/h2>\n
\u015eimdi Apache Hadoop’un kendisini indirip sistemimize kurma zaman\u0131.<\/p>\n
Hadoop S\u00fcr\u00fcm\u00fcn\u00fc Se\u00e7me<\/h3>\n
Apache Hadoop’un resmi indirme sayfas\u0131ndan (Apache Hadoop Releases) uygun bir s\u00fcr\u00fcm se\u00e7melisiniz. Ubuntu 16.04 ile uyumlu olmas\u0131 ve Stand-Alone mod i\u00e7in genellikle Hadoop 2.x serisi (\u00f6rne\u011fin 2.7.x, 2.8.x, 2.9.x) tercih edilir. Bu rehberde, genel bir 2.x s\u00fcr\u00fcm\u00fc \u00fczerinden ilerleyece\u011fiz. Genellikle en son kararl\u0131 2.x s\u00fcr\u00fcm\u00fcn\u00fc tercih etmek iyi bir fikirdir.<\/p>\n
\u00d6rnek olarak, Hadoop 2.7.7 s\u00fcr\u00fcm\u00fcn\u00fc indirelim. Bu s\u00fcr\u00fcm\u00fcn indirme ba\u011flant\u0131s\u0131n\u0131 Apache Hadoop web sitesinden bulabilirsiniz. Genellikle bir ayna (mirror) sitesinden indirme yap\u0131l\u0131r.<\/p>\n
Hadoop Dosyas\u0131n\u0131 \u0130ndirme<\/h3>\n
wget<\/code> komutunu kullanarak Hadoop tar.gz dosyas\u0131n\u0131 indirin. \u00d6nce \/opt<\/code> dizinine ge\u00e7ebiliriz, bu t\u00fcr yaz\u0131l\u0131mlar i\u00e7in yayg\u0131n bir konumdur:<\/p>\n
cd \/opt\nsudo wget https:\/\/archive.apache.org\/dist\/hadoop\/common\/hadoop-2.7.7\/hadoop-2.7.7.tar.gz<\/code><\/pre>\n
Not: Yukar\u0131daki URL, Hadoop 2.7.7 i\u00e7in bir \u00f6rnek olup, se\u00e7ti\u011finiz s\u00fcr\u00fcme g\u00f6re de\u011fi\u015febilir. L\u00fctfen Apache Hadoop web sitesinden g\u00fcncel ve do\u011fru indirme ba\u011flant\u0131s\u0131n\u0131 kontrol edin.<\/em><\/p>\n
Hadoop Dosyas\u0131n\u0131 \u00c7\u0131kartma<\/h3>\n
\u0130ndirdi\u011finiz tar.gz dosyas\u0131n\u0131 \/usr\/local<\/code> dizinine \u00e7\u0131kar\u0131n. Bu, Hadoop i\u00e7in standart bir kurulum dizinidir.<\/p>\n
sudo tar -xzvf hadoop-2.7.7.tar.gz -C \/usr\/local\/<\/code><\/pre>\n
\u00c7\u0131kartma i\u015flemi tamamland\u0131ktan sonra, daha kolay eri\u015fim i\u00e7in dizin ad\u0131n\u0131 k\u0131saltabiliriz:<\/p>\n
sudo mv \/usr\/local\/hadoop-2.7.7 \/usr\/local\/hadoop<\/code><\/pre>\n
Dizin \u0130zinlerini Ayarlama<\/h3>\n
Hadoop dizininin sahibi ve grubu, kurulumu yapan kullan\u0131c\u0131 olmal\u0131d\u0131r. Bu, yap\u0131land\u0131rma dosyalar\u0131n\u0131 d\u00fczenlerken veya Hadoop \u00e7al\u0131\u015f\u0131rken izin sorunlar\u0131 ya\u015fanmas\u0131n\u0131 \u00f6nler.<\/p>\n
sudo chown -R : \/usr\/local\/hadoop<\/code><\/pre>\n
\u00d6rnek: sudo chown -R alperen:alperen \/usr\/local\/hadoop<\/code><\/em><\/p>\n
Kullan\u0131c\u0131 ad\u0131n\u0131z\u0131 ve grup ad\u0131n\u0131z\u0131 \u00f6\u011frenmek i\u00e7in whoami<\/code> ve id -gn<\/code> komutlar\u0131n\u0131 kullanabilirsiniz.<\/p>\n
Hadoop Ortam De\u011fi\u015fkenlerinin Yap\u0131land\u0131r\u0131lmas\u0131<\/h2>\n
Hadoop’un komutlar\u0131na her yerden eri\u015febilmek ve Hadoop’un ihtiya\u00e7 duydu\u011fu di\u011fer ortam de\u011fi\u015fkenlerini ayarlamak i\u00e7in ~\/.bashrc<\/code> dosyas\u0131n\u0131 tekrar d\u00fczenlememiz gerekecek.<\/p>\n
~\/.bashrc Dosyas\u0131n\u0131 D\u00fczenleme<\/h3>\n
nano ~\/.bashrc<\/code> komutu ile dosyan\u0131z\u0131 a\u00e7\u0131n ve daha \u00f6nce ekledi\u011finiz JAVA_HOME<\/code> sat\u0131rlar\u0131n\u0131n alt\u0131na a\u015fa\u011f\u0131daki sat\u0131rlar\u0131 ekleyin:<\/p>\n
# Hadoop Ortam De\u011fi\u015fkenleri\nexport HADOOP_HOME=\/usr\/local\/hadoop\nexport HADOOP_INSTALL=$HADOOP_HOME\nexport HADOOP_MAPRED_HOME=$HADOOP_HOME\nexport HADOOP_COMMON_HOME=$HADOOP_HOME\nexport HADOOP_HDFS_HOME=$HADOOP_HOME\nexport YARN_HOME=$HADOOP_HOME\nexport HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME\/lib\/native\nexport PATH=$PATH:$HADOOP_HOME\/sbin:$HADOOP_HOME\/bin\nexport HADOOP_OPTS=\"-Djava.library.path=$HADOOP_HOME\/lib\/native\"<\/code><\/pre>\n
De\u011fi\u015fiklikleri kaydedin (Ctrl+O, Enter) ve dosyadan \u00e7\u0131k\u0131n (Ctrl+X).<\/p>\n
De\u011fi\u015fiklikleri Uygulama<\/h3>\n
Yeni ortam de\u011fi\u015fkenlerini aktif hale getirmek i\u00e7in:<\/p>\n
source ~\/.bashrc<\/code><\/pre>\n
Hadoop Kurulumunu Do\u011frulama<\/h3>\n
Hadoop’un do\u011fru \u015fekilde kurulup ortam de\u011fi\u015fkenlerinin ayarland\u0131\u011f\u0131n\u0131 do\u011frulamak i\u00e7in hadoop version<\/code> komutunu \u00e7al\u0131\u015ft\u0131r\u0131n:<\/p>\n
hadoop version<\/code><\/pre>\n
Hadoop s\u00fcr\u00fcm bilgileri \u00e7\u0131kt\u0131s\u0131n\u0131 g\u00f6rmelisiniz. Bu, Hadoop komutlar\u0131n\u0131n PATH’inizde oldu\u011funu ve \u00e7al\u0131\u015ft\u0131r\u0131labildi\u011fini g\u00f6sterir.<\/p>\n
Hadoop Yap\u0131land\u0131rma Dosyalar\u0131n\u0131n D\u00fczenlenmesi<\/h2>\n
Hadoop’un Stand-Alone modda bile d\u00fczg\u00fcn \u00e7al\u0131\u015fabilmesi i\u00e7in birka\u00e7 temel yap\u0131land\u0131rma dosyas\u0131n\u0131 d\u00fczenlememiz gerekir. Bu dosyalar \/usr\/local\/hadoop\/etc\/hadoop\/<\/code> dizininde bulunur.<\/p>\n
hadoop-env.sh<\/h3>\n
Bu dosya, Hadoop’un \u00e7al\u0131\u015faca\u011f\u0131 ortam de\u011fi\u015fkenlerini i\u00e7erir. \u00d6zellikle JAVA_HOME<\/code> de\u011fi\u015fkenini burada belirtmemiz gerekmektedir.<\/p>\n
nano \/usr\/local\/hadoop\/etc\/hadoop\/hadoop-env.sh<\/code><\/pre>\n
Dosyay\u0131 a\u00e7t\u0131ktan sonra, export JAVA_HOME=<\/code> ile ba\u015flayan sat\u0131r\u0131 bulun ve kendi JAVA_HOME<\/code> yolunuzla g\u00fcncelleyin (genellikle 25. sat\u0131r civar\u0131ndad\u0131r). Ba\u015ftaki #<\/code> i\u015faretini kald\u0131rarak yorum sat\u0131r\u0131 olmaktan \u00e7\u0131kar\u0131n.<\/p>\n
export JAVA_HOME=\/usr\/lib\/jvm\/java-8-openjdk-amd64<\/code><\/pre>\n
De\u011fi\u015fiklikleri kaydedip \u00e7\u0131k\u0131n.<\/p>\n
core-site.xml<\/h3>\n
Bu dosya, Hadoop k\u00fcmesinin temel yap\u0131land\u0131rma ayarlar\u0131n\u0131 i\u00e7erir. Stand-Alone modda bile HDFS’i kullanmak istiyorsak, varsay\u0131lan dosya sistemini belirtmeliyiz.<\/p>\n
nano \/usr\/local\/hadoop\/etc\/hadoop\/core-site.xml<\/code><\/pre>\n
<\/code> etiketleri aras\u0131na a\u015fa\u011f\u0131daki \u00f6zellikleri ekleyin:<\/p>\n
\n    \n        fs.defaultFS<\/name>\n        hdfs:\/\/localhost:9000<\/value>\n        NameNode URI<\/description>\n    <\/property>\n<\/configuration><\/code><\/pre>\n
Bu ayar, HDFS NameNode’un localhost<\/code> \u00fczerinde 9000 portunda \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 belirtir.<\/p>\n
hdfs-site.xml<\/h3>\n
Bu dosya, HDFS ile ilgili yap\u0131land\u0131rma ayarlar\u0131n\u0131 i\u00e7erir. Tek d\u00fc\u011f\u00fcml\u00fc bir kurulum i\u00e7in replikasyon fakt\u00f6r\u00fcn\u00fc 1 olarak ayarlamal\u0131 ve NameNode ile DataNode verileri i\u00e7in yerel dizinler belirtmeliyiz.<\/p>\n
\u00d6ncelikle, HDFS verileri i\u00e7in dizinleri olu\u015ftural\u0131m:<\/p>\n
mkdir -p \/usr\/local\/hadoop\/data\/namenode\nmkdir -p \/usr\/local\/hadoop\/data\/datanode<\/code><\/pre>\n
\u015eimdi hdfs-site.xml<\/code> dosyas\u0131n\u0131 d\u00fczenleyelim:<\/p>\n
nano \/usr\/local\/hadoop\/etc\/hadoop\/hdfs-site.xml<\/code><\/pre>\n
<\/code> etiketleri aras\u0131na a\u015fa\u011f\u0131daki \u00f6zellikleri ekleyin:<\/p>\n
\n    \n        dfs.replication<\/name>\n        1<\/value>\n        Default block replication. The actual number of replications can be specified when the file is created.<\/description>\n    <\/property>\n    \n        dfs.namenode.name.dir<\/name>\n        file:\/\/\/usr\/local\/hadoop\/data\/namenode<\/value>\n        The directory where the namenode stores the namespace and transactional logs.<\/description>\n    <\/property>\n    \n        dfs.datanode.data.dir<\/name>\n        file:\/\/\/usr\/local\/hadoop\/data\/datanode<\/value>\n        The directory where the datanode stores its blocks.<\/description>\n    <\/property>\n<\/configuration><\/code><\/pre>\n
dfs.replication<\/code> ayar\u0131, verilerin ka\u00e7 kopyas\u0131n\u0131n tutulaca\u011f\u0131n\u0131 belirtir. Tek d\u00fc\u011f\u00fcml\u00fc bir kurulumda bu de\u011feri 1 olarak ayarlamak mant\u0131kl\u0131d\u0131r.<\/p>\n
mapred-site.xml<\/h3>\n
Bu dosya, MapReduce \u00e7er\u00e7evesi ile ilgili ayarlar\u0131 i\u00e7erir. Hadoop 2.x ve sonras\u0131, MapReduce i\u015flerini y\u00f6netmek i\u00e7in YARN’\u0131 kullan\u0131r. Bu nedenle, MapReduce \u00e7er\u00e7evesinin YARN \u00fczerinde \u00e7al\u0131\u015faca\u011f\u0131n\u0131 belirtmeliyiz.<\/p>\n
Bu dosyan\u0131n varsay\u0131lan olarak mapred-site.xml.template<\/code> ad\u0131yla geldi\u011fini g\u00f6receksiniz. \u00d6nce onu mapred-site.xml<\/code> olarak kopyalayal\u0131m:<\/p>\n
cp \/usr\/local\/hadoop\/etc\/hadoop\/mapred-site.xml.template \/usr\/local\/hadoop\/etc\/hadoop\/mapred-site.xml<\/code><\/pre>\n
\u015eimdi mapred-site.xml<\/code> dosyas\u0131n\u0131 d\u00fczenleyelim:<\/p>\n
nano \/usr\/local\/hadoop\/etc\/hadoop\/mapred-site.xml<\/code><\/pre>\n
<\/code> etiketleri aras\u0131na a\u015fa\u011f\u0131daki \u00f6zellikleri ekleyin:<\/p>\n
\n    \n        mapreduce.framework.name<\/name>\n        yarn<\/value>\n        The runtime framework for executing MapReduce jobs.<\/description>\n    <\/property>\n<\/configuration><\/code><\/pre>\n
yarn-site.xml<\/h3>\n
Bu dosya, YARN ile ilgili ayarlar\u0131 i\u00e7erir. ResourceManager ve NodeManager gibi YARN bile\u015fenlerinin nas\u0131l \u00e7al\u0131\u015faca\u011f\u0131n\u0131 yap\u0131land\u0131r\u0131r\u0131z.<\/p>\n
nano \/usr\/local\/hadoop\/etc\/hadoop\/yarn-site.xml<\/code><\/pre>\n
<\/code> etiketleri aras\u0131na a\u015fa\u011f\u0131daki \u00f6zellikleri ekleyin:<\/p>\n
\n    \n        yarn.nodemanager.aux-services<\/name>\n        mapreduce_shuffle<\/value>\n        A comma-separated list of services that the NodeManager will run.<\/description>\n    <\/property>\n    \n        yarn.nodemanager.aux-services.mapreduce.shuffle.class<\/name>\n        org.apache.hadoop.mapred.ShuffleHandler<\/value>\n        The class name of the auxiliary service for MapReduce shuffle.<\/description>\n    <\/property>\n    \n        yarn.resourcemanager.hostname<\/name>\n        localhost<\/value>\n        The hostname of the ResourceManager.<\/description>\n    <\/property>\n<\/configuration><\/code><\/pre>\n
Bu ayarlar, YARN’\u0131n MapReduce i\u015fleri i\u00e7in gerekli olan ShuffleHandler’\u0131 kullanmas\u0131n\u0131 ve ResourceManager’\u0131n localhost<\/code> \u00fczerinde \u00e7al\u0131\u015fmas\u0131n\u0131 sa\u011flar.<\/p>\n
T\u00fcm yap\u0131land\u0131rma dosyalar\u0131n\u0131 kaydetti\u011finizden ve \u00e7\u0131kt\u0131\u011f\u0131n\u0131zdan emin olun.<\/p>\n
Hadoop Kurulumunun Do\u011frulanmas\u0131<\/h2>\n
T\u00fcm yap\u0131land\u0131rmalar tamamland\u0131ktan sonra, Hadoop servislerini ba\u015flat\u0131p kurulumu do\u011frulayabiliriz.<\/p>\n
HDFS NameNode’u Bi\u00e7imlendirme (Sadece Bir Kez!)<\/h3>\n
HDFS’i ilk kez kullanmadan \u00f6nce NameNode’u bi\u00e7imlendirmeniz gerekir. Bu i\u015flem, NameNode \u00fczerindeki t\u00fcm meta verileri silece\u011fi i\u00e7in yaln\u0131zca ilk kurulumda veya veri kayb\u0131n\u0131 g\u00f6ze alarak yap\u0131lmal\u0131d\u0131r.<\/strong> Mevcut bir HDFS kurulumunu bi\u00e7imlendirmek, t\u00fcm HDFS verilerinizin silinmesine yol a\u00e7ar.<\/p>\n
hdfs namenode -format<\/code><\/pre>\n
Komut \u00e7al\u0131\u015ft\u0131ktan sonra “successfully formatted” mesaj\u0131n\u0131 g\u00f6rmelisiniz.<\/p>\n
Hadoop Servislerini Ba\u015flatma<\/h3>\n
\u015eimdi HDFS ve YARN servislerini ba\u015flatal\u0131m:<\/p>\n
start-dfs.sh\nstart-yarn.sh<\/code><\/pre>\n
Bu komutlar, s\u0131ras\u0131yla NameNode, DataNode, SecondaryNameNode (HDFS i\u00e7in) ve ResourceManager, NodeManager (YARN i\u00e7in) s\u00fcre\u00e7lerini ba\u015flat\u0131r.<\/p>\n
Servislerin \u00c7al\u0131\u015ft\u0131\u011f\u0131n\u0131 Kontrol Etme<\/h3>\n
jps<\/code> (Java Virtual Machine Process Status Tool) komutu ile \u00e7al\u0131\u015fan Java s\u00fcre\u00e7lerini kontrol edebiliriz:<\/p>\n
jps<\/code><\/pre>\n
A\u015fa\u011f\u0131dakine benzer bir \u00e7\u0131kt\u0131 g\u00f6rmelisiniz:<\/p>\n
XXXX NameNode\nXXXX DataNode\nXXXX SecondaryNameNode\nXXXX ResourceManager\nXXXX NodeManager\nXXXX Jps<\/code><\/pre>\n
E\u011fer bu s\u00fcre\u00e7leri g\u00f6r\u00fcyorsan\u0131z, Hadoop servisleriniz ba\u015far\u0131yla \u00e7al\u0131\u015f\u0131yor demektir.<\/p>\n
Web Aray\u00fczlerini Kontrol Etme<\/h3>\n
Hadoop, \u00e7e\u015fitli bile\u015fenler i\u00e7in web aray\u00fczleri sunar. Bu aray\u00fczleri taray\u0131c\u0131n\u0131zdan kontrol ederek servislerin durumunu ve k\u00fcme bilgilerini g\u00f6rebilirsiniz:<\/p>\n
*   NameNode UI:<\/strong> http:\/\/localhost:50070<\/code>
\n*   ResourceManager UI:<\/strong> http:\/\/localhost:8088<\/code><\/p>\n
Bu adreslere eri\u015febiliyorsan\u0131z, web aray\u00fczleri de d\u00fczg\u00fcn \u00e7al\u0131\u015f\u0131yor demektir.<\/p>\n
\u00d6rnek Bir MapReduce \u0130\u015fini \u00c7al\u0131\u015ft\u0131rma<\/h3>\n
Hadoop kurulumunuzun tamamen i\u015flevsel oldu\u011funu do\u011frulamak i\u00e7in, Hadoop’un kendi \u00f6rnek JAR dosyalar\u0131n\u0131 kullanarak basit bir MapReduce i\u015fi \u00e7al\u0131\u015ft\u0131rabiliriz. WordCount (kelime say\u0131m\u0131) \u00f6rne\u011fi, Hadoop’un temel MapReduce yetene\u011fini test etmek i\u00e7in harika bir yoldur.<\/p>\n
1.  HDFS \u00fczerinde bir giri\u015f dizini olu\u015fturun:<\/strong><\/p>\n
hdfs dfs -mkdir \/input<\/code><\/pre>\n
2.  HDFS’e \u00f6rnek bir dosya kopyalay\u0131n:<\/strong>
\n    Hadoop’un kendi yap\u0131land\u0131rma dizinindeki README.txt<\/code> dosyas\u0131n\u0131 kullanabiliriz.<\/p>\n
hdfs dfs -put \/usr\/local\/hadoop\/etc\/hadoop\/README.txt \/input<\/code><\/pre>\n
    Dosyan\u0131n HDFS’e kopyaland\u0131\u011f\u0131n\u0131 do\u011frulamak i\u00e7in:<\/p>\n
hdfs dfs -ls \/input<\/code><\/pre>\n
3.  WordCount MapReduce i\u015fini \u00e7al\u0131\u015ft\u0131r\u0131n:<\/strong><\/p>\n
hadoop jar \/usr\/local\/hadoop\/share\/hadoop\/mapreduce\/hadoop-mapreduce-examples-*.jar wordcount \/input \/output<\/code><\/pre>\n
    Not: hadoop-mapreduce-examples-<\/em>.jar<\/code> k\u0131sm\u0131ndaki <\/code> i\u015fareti, s\u00fcr\u00fcm numaras\u0131n\u0131 otomatik olarak e\u015fle\u015ftirmek i\u00e7indir. E\u011fer bu komut \u00e7al\u0131\u015fmazsa, ls \/usr\/local\/hadoop\/share\/hadoop\/mapreduce\/<\/code> komutu ile do\u011fru JAR dosyas\u0131n\u0131n ad\u0131n\u0131 bulup yerine yazman\u0131z gerekebilir (\u00f6rne\u011fin hadoop-mapreduce-examples-2.7.7.jar<\/code>).<\/em><\/p>\n
    \u0130\u015fin tamamlanmas\u0131n\u0131 bekleyin. Terminalde ilerleme durumunu g\u00f6receksiniz.<\/p>\n
4.  Sonu\u00e7lar\u0131 HDFS’ten okuyun:<\/strong><\/p>\n
hdfs dfs -cat \/output\/part-r-00000<\/code><\/pre>\n
    Bu komut, WordCount i\u015finin \u00e7\u0131kt\u0131s\u0131n\u0131 (kelimeler ve say\u0131mlar\u0131) g\u00f6sterecektir. E\u011fer \u00e7\u0131kt\u0131y\u0131 g\u00f6rebiliyorsan\u0131z, Hadoop kurulumunuz ba\u015far\u0131l\u0131 bir \u015fekilde \u00e7al\u0131\u015f\u0131yor demektir!<\/p>\n
5.  \u00c7\u0131kt\u0131 dizinini temizleyin (iste\u011fe ba\u011fl\u0131):<\/strong><\/p>\n
    Yeni bir i\u015f \u00e7al\u0131\u015ft\u0131rmadan \u00f6nce \u00e7\u0131kt\u0131 dizinini silmeniz gerekebilir, \u00e7\u00fcnk\u00fc Hadoop ayn\u0131 \u00e7\u0131kt\u0131 dizinine yazmaya izin vermez.<\/p>\n
hdfs dfs -rm -r \/output<\/code><\/pre>\n
Hadoop Servislerini Durdurma<\/h3>\n
\u0130\u015finiz bitti\u011finde veya sistemi kapatmadan \u00f6nce Hadoop servislerini d\u00fczg\u00fcn bir \u015fekilde durdurmak iyi bir uygulamad\u0131r:<\/p>\n
stop-dfs.sh\nstop-yarn.sh<\/code><\/pre>\n
jps<\/code> komutunu tekrar \u00e7al\u0131\u015ft\u0131rarak t\u00fcm Hadoop s\u00fcre\u00e7lerinin durdu\u011funu do\u011frulayabilirsiniz.<\/p>\n
Sonu\u00e7<\/h2>\n
Tebrikler! Ubuntu 16.04 i\u015fletim sisteminiz \u00fczerine Apache Hadoop’u Stand-Alone modda ba\u015far\u0131yla kurdunuz ve basit bir MapReduce i\u015fini \u00e7al\u0131\u015ft\u0131rarak kurulumunuzu do\u011frulad\u0131n\u0131z. Bu rehber, Hadoop ekosistemine giri\u015f yapmak, temel kavramlar\u0131 \u00f6\u011frenmek ve geli\u015ftirme ortam\u0131n\u0131z\u0131 kurmak i\u00e7in sa\u011flam bir temel sa\u011flam\u0131\u015ft\u0131r.<\/p>\n
Stand-Alone mod, b\u00fcy\u00fck veri projeleri geli\u015ftirmeye ba\u015flamak, MapReduce algoritmalar\u0131n\u0131 test etmek ve Hadoop bile\u015fenlerinin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 anlamak i\u00e7in m\u00fckemmel bir ba\u015flang\u0131\u00e7 noktas\u0131d\u0131r. Bu kurulum, ger\u00e7ek d\u00fcnya da\u011f\u0131t\u0131k k\u00fcme senaryolar\u0131ndan farkl\u0131 olsa da, Hadoop’un temel i\u015flevselli\u011fini deneyimlemenizi sa\u011flar.<\/p>\n
Bir sonraki ad\u0131m olarak, Hadoop’u Pseudo-Distributed (sahte da\u011f\u0131t\u0131k) moda veya Fully-Distributed (tamamen da\u011f\u0131t\u0131k) moda kurarak daha karma\u015f\u0131k senaryolar\u0131 ke\u015ffedebilir, birden \u00e7ok d\u00fc\u011f\u00fcm \u00fczerinde \u00e7al\u0131\u015fman\u0131n getirdi\u011fi avantajlar\u0131 ve zorluklar\u0131 deneyimleyebilirsiniz. Bu, b\u00fcy\u00fck veri d\u00fcnyas\u0131ndaki yolculu\u011funuzun sadece ba\u015flang\u0131c\u0131d\u0131r.<\/p>\n
S\u0131k\u00e7a Sorulan Sorular (SSS)<\/h2>\n
1. JAVA_HOME<\/code> hatas\u0131 al\u0131yorum, ne yapmal\u0131y\u0131m?<\/h3>\n
Bu genellikle JAVA_HOME<\/code> ortam de\u011fi\u015fkeninin yanl\u0131\u015f ayarland\u0131\u011f\u0131 veya hi\u00e7 ayarlanmad\u0131\u011f\u0131 anlam\u0131na gelir. ~\/.bashrc<\/code> dosyan\u0131zdaki yolu kontrol edin ve Java’n\u0131n ger\u00e7ekten o dizine y\u00fcklendi\u011finden emin olun. sudo update-alternatives --config java<\/code> komutuyla do\u011fru Java yolunu bulabilirsiniz. Ayr\u0131ca, source ~\/.bashrc<\/code> komutunu \u00e7al\u0131\u015ft\u0131rarak de\u011fi\u015fiklikleri uygulad\u0131\u011f\u0131n\u0131zdan emin olun.<\/p>\n
2. jps<\/code> komutu hi\u00e7bir Hadoop s\u00fcrecini g\u00f6stermiyorsa ne anlama gelir?<\/h3>\n
Bu, Hadoop servislerinin ba\u015flamad\u0131\u011f\u0131 anlam\u0131na gelir. A\u015fa\u011f\u0131daki olas\u0131 nedenleri kontrol edin:<\/p>\n
    \n
  • hadoop-env.sh<\/code> dosyas\u0131nda JAVA_HOME<\/code> do\u011fru ayarlanm\u0131\u015f m\u0131?<\/li>\n
  • SSH \u015fifresiz ba\u011flant\u0131 \u00e7al\u0131\u015f\u0131yor mu? ssh localhost<\/code> ile test edin.<\/li>\n
  • Hadoop yap\u0131land\u0131rma dosyalar\u0131nda (core-site.xml<\/code>, hdfs-site.xml<\/code>, vb.) herhangi bir yaz\u0131m hatas\u0131 veya yanl\u0131\u015f yol var m\u0131?<\/li>\n
  • Log dosyalar\u0131n\u0131 kontrol edin: \/usr\/local\/hadoop\/logs\/<\/code> dizinindeki log dosyalar\u0131, neden servislerin ba\u015flamad\u0131\u011f\u0131n\u0131 g\u00f6steren ipu\u00e7lar\u0131 i\u00e7erebilir.<\/li>\n
  • NameNode’u bi\u00e7imlendirmeyi unuttunuz mu? (hdfs namenode -format<\/code> – sadece bir kez!)<\/li>\n<\/ul>\n
    3. Hadoop servisleri neden ba\u015flam\u0131yor? (Port \u00c7ak\u0131\u015fmalar\u0131, \u0130zinler vb.)<\/h3>\n
    Nadiren de olsa, baz\u0131 portlar ba\u015fka bir uygulama taraf\u0131ndan kullan\u0131l\u0131yor olabilir. Hadoop’un kulland\u0131\u011f\u0131 varsay\u0131lan portlar \u015funlard\u0131r: NameNode (8020, 9000), DataNode (50010, 50020, 50075), SecondaryNameNode (50090), ResourceManager (8032, 8030, 8031, 8033, 8088), NodeManager (8040, 8042). netstat -tulnp | grep <\/code> komutuyla portlar\u0131n kullan\u0131m durumunu kontrol edebilirsiniz.<\/p>\n
    \u0130zin sorunlar\u0131 da s\u0131k\u00e7a kar\u015f\u0131la\u015f\u0131lan bir problemdir. Hadoop dizininin (\/usr\/local\/hadoop<\/code>) ve HDFS veri dizinlerinin (\/usr\/local\/hadoop\/data\/namenode<\/code>, \/usr\/local\/hadoop\/data\/datanode<\/code>) do\u011fru kullan\u0131c\u0131ya ait oldu\u011fundan emin olun (sudo chown -R kullan\u0131c\u0131:grup \/usr\/local\/hadoop<\/code>).<\/p>\n
    4. Ubuntu 16.04 yerine ba\u015fka bir s\u00fcr\u00fcmde kurabilir miyim?<\/h3>\n
    Evet, bu rehberdeki ad\u0131mlar genel olarak Linux tabanl\u0131 sistemler i\u00e7in ge\u00e7erlidir. Ancak, Ubuntu’nun daha yeni s\u00fcr\u00fcmlerinde (\u00f6rne\u011fin 18.04, 20.04, 22.04) veya di\u011fer da\u011f\u0131t\u0131mlarda (CentOS, Fedora), Java kurulumu i\u00e7in paket adlar\u0131 (openjdk-8-jdk<\/code> yerine openjdk-11-jdk<\/code> gibi) veya varsay\u0131lan dizin yollar\u0131 farkl\u0131l\u0131k g\u00f6sterebilir. Ayr\u0131ca, Hadoop’un daha yeni s\u00fcr\u00fcmleri (Hadoop 3.x) farkl\u0131 Java s\u00fcr\u00fcmleri (Java 11 gibi) gerektirebilir. Bu nedenle, kulland\u0131\u011f\u0131n\u0131z i\u015fletim sistemi ve Hadoop s\u00fcr\u00fcm\u00fc i\u00e7in spesifik gereksinimleri kontrol etmeniz \u00f6nerilir.<\/p>\n
    5. Hadoop’un hangi s\u00fcr\u00fcm\u00fcn\u00fc se\u00e7meliyim?<\/h3>\n
    Genellikle, bir Hadoop kurulumu i\u00e7in en son kararl\u0131 s\u00fcr\u00fcm\u00fc se\u00e7mek iyi bir fikirdir. Ancak, belirli bir uygulama veya ekosistem arac\u0131 (\u00f6rne\u011fin Hive, Spark) belirli bir Hadoop s\u00fcr\u00fcm\u00fcyle daha iyi entegre olabilir. Ubuntu 16.04 gibi eski bir i\u015fletim sistemi i\u00e7in Hadoop 2.x serisi (2.7.x, 2.8.x, 2.9.x) genellikle daha uyumludur. Hadoop 3.x serisi daha yeni \u00f6zellikler sunsa da, genellikle daha yeni Java s\u00fcr\u00fcmleri (Java 11+) ve daha modern i\u015fletim sistemleri gerektirir. Stand-Alone modda \u00f6\u011frenme ama\u00e7l\u0131 kurulumlar i\u00e7in Hadoop 2.x serisi hala olduk\u00e7a yeterlidir.<\/p>\n
    <\/body><\/p>\n","protected":false},"excerpt":{"rendered":"Ubuntu 16.04 \u00dczerine Hadoop’u Stand-Alone Modda Kurulum Rehberi\nGiri\u015f\nB\u00fcy\u00fck veri (Big Data) d\u00fcnyas\u0131nda en pop\u00fcler ve yayg\u0131n kullan\u0131lan \u00e7","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1468],"tags":[],"class_list":{"0":"post-31652","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-ubuntu","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nUbuntu 16.04 \u00dczerine Hadoop'u Stand-Alone Modda Kurulum Rehberi - Kodlar\u0131n Gizemli D\u00fcnyas\u0131<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Ubuntu 16.04 \u00dczerine Hadoop'u Stand-Alone Modda Kurulum Rehberi\" \/>\n<meta property=\"og:description\" content=\"Ubuntu 16.04 \u00dczerine Hadoop'u Stand-Alone Modda Kurulum Rehberi  Giri\u015f B\u00fcy\u00fck veri (Big Data) d\u00fcnyas\u0131nda en pop\u00fcler ve yayg\u0131n kullan\u0131lan \u00e7\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-10-12T06:40:59+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"17 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"Ubuntu 16.04 \u00dczerine Hadoop’u Stand-Alone Modda Kurulum Rehberi\",\"datePublished\":\"2025-10-12T06:40:59+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\"},\"wordCount\":2749,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"articleSection\":[\"Ubuntu\"],\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/ubuntu-16-04-uzerine-hadoopu-stand-alone-modda-kurulum-rehberi\/\",\"name\":\"Ubuntu 16.04 \u00dczerine Hadoop'u Stand-Alone Modda Kurulum Rehberi - 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