Huseyin ABANOZ

This document shows my experience on following apache document titled “ Hadoop Cluster Setup ” [1] which is for Hadoop version 3.0.0-Alpha2. This document is successor to Hadoop Installation Document-Standalone  [2]. “ ubuntul_hadoop_master ” machine is used in the rest of the machine. You will need to read and follow Hadoop Installation Document-Standalone [2] before reading any further. A. Prepare the guest environments for slave nodes. It is easy to clone virtual machines using Virtualbox. Right click “ ubuntul_hadoop_master ” and clone. Name new VM as “ ubuntul_hadoop_slave1 ”. You can have as many slaves as you like. Since we simply clone the master machine, much of the configuration comes ready. Practically slave nodes needs more disk space while master node needs more memory. But this is an educational setup and these details are not necessary. B. Install Hadoop Hadoop comes installed with " ubuntul_hadoop_master ”. C. Running Cluster In maste

This document shows my experience on following apache document titled “Hadoop:Setting up a Single Node Cluster”[1] which is for Hadoop version 3.0.0-Alpha2 [2]. A. Prepare the guest environment Install VirtualBox. Create a virtual 64 bit Linux machine. Name it “ubuntul_hadoop_master”. Give it 500MB memory. Create a VMDK disc which is dynamically allocated up to 30GB. In network settings in first tab you should see Adapter 1 enabled and attached to “NAT”. In second table enable adapter 2 and attach to “Host Only Adaptor”. First adapter is required for internet connection. Second one is required for letting outside connect to a guest service. In storage settings, attach a Linux iso file to IDE channel. Use any distribution you like. Because of small installation size, I choose minimal Ubuntu iso [1]. In package selection menu, I only left standard packages selected.  Login to system.  Setup JDK. $ sudo apt-get install openjdk-8-jdk Install ssh and pdsh, if not already i

It is very easy to create a rest service. We even do not need a servlet container to run the application. Spring Boot will prepare a container for us. We only need to add what is necessary. Even a web.xml file is not necessary. This rest service searches a text in elasticsearch and returns the result as JSON. Amount of code needed for this task is amazingly low. First class is the controller. Request will be served with this controller. For elasticsearch repository see [1]. Now comes the spring boot application entry point. In order to use the rest service use the request like this: http://localhost:8080/recipe/by-name?name=mynameis For complete code listing in github see [2]. 1.  Spring Boot Elasticsearch Application 2.  Github - essync

Assume you have large amount of text data and want to do search on your data. You decided to use elasticsearch or solr as search engine. Spring Data is your friend. This document shows an example application that uses elasticsearch with spring data. This application uses elasticsearch and JPA at the same time. Data comes from mysql and goes to elasticsearch. Create document class to represent your domain object. Next thing you need is repository class to manage your domain object. Query methods are possible. Now we can work store data to elasticsearch using repository object. For JPA entity and repository classes see [1]. Component annotation makes this class spring managed. Autowired annotation tells spring to create required repository objects. Transactional annotation is required for declarative transaction management. Now spring boot application entry point comes. EnableElasticsearchRepositories is need to activate elasticsearch repository. Since another repository is

Spring framework comes with many modules that makes java developers' life easier. Spring Boot works like a charm. It has never been easier to write java applications. This document is created to show how simple a JPA application can be written. A JPA application starts with creating JPA entity and DAO classes. JPA entity classes can be generated using a tool that comes with any Java IDE. In spring data, DAO classes are called as Repository classes. A repository or DAO object is used to save,update,delete or retrieve entity objects. Traditionally DAO classes were created using Base Dao classes. Base classes were saving us from writing boiler plates for save, update or delete methods. But when it comes to retrieval methods, boiler plate codes were unavoidable. Good news is that, spring data comes with a good idea. Query methods save us from boiler plates. See [1] for more details. Entity class is a standard JPA entity. An example service class is given below. By use of A

In recent years GIT has had great momentum it is increasing its popularity. More and more teams are switching to GIT from SVN. This fact raises the question of should I switch to Git from SVN. To answer this question I made internet investigation relying on poplar search engines. I looked at the user reviews, considered their arguments. Then I started to use Git in parallel with SVN.  Here comes my experience with both of them. Both of them are great version control systems. Most apparent difference is that Git is decentralized which means you do not have to use a single repository at the center.   I found SVN is better in simplicity. Every body easily starts using SVN. It is workflow is quiet simple: update, modify, commit. Revision number logic in SVN is great to have. I use version number to name jar files, This way I can easily follow which jar corresponds to which version.  I found Git is better for not needing constant connection to central repository. I can f