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Coalesce With Care
In Spark, there are two common transformations to change the number of tasks; coalesce and repartition. They are very similar but not identical. Let's see how.
January 19, 2022
by Avi Yehuda
· 4,231 Views · 3 Likes
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Open-Source SPL That Can Execute SQL Without RDB
There is no RDB in many scenarios, such as encountering CSV/RESTful JSON /MongoDB and other data sources, or performing mixed calculations between these data sources.
January 19, 2022
by Jerry Zhang
· 5,447 Views · 4 Likes
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Data Integrity: A Data-Driven Organization's Biggest Concern
Although many organizations have implemented a system for data collection and analysis, it's crucial that they can also maintain the integrity of their data.
January 18, 2022
by Zara Ziad
· 3,172 Views · 3 Likes
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Solving Four Kubernetes Networking Challenges
Deploying across multiple clouds, maintaining multiple environments, and ensuring reliable and scalable network policies; we’ll look at how to tackle those challenges.
January 18, 2022
by Michael Bogan DZone Core CORE
· 120,060 Views · 6 Likes
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Service Discovery From Within the Kubernetes Cluster
Does Java Kubernetes Client live up to the promise of being a Java library to operate the Kubernetes cluster by accessing Kubernetes API? Find out here.
January 17, 2022
by Jan-Rudolph Bührmann
· 6,924 Views · 4 Likes
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Database Integration in WSO2 EI 7.1.0
This article demonstrates how we can integrate with databases and do data manipulation in WSO2 EI 7.1.0.
January 17, 2022
by Suman Mohan
· 4,735 Views · 3 Likes
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Querying SQL Databases With PySpark
In this article, we'll learn about how to combine Postgres, PySpark, and Arctype to create powerful visualizations and queries on large data sets.
January 17, 2022
by Everett Berry
· 4,605 Views · 2 Likes
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Sample Architecture Using Amazon AWS, Microsoft Azure, Google GCP, MongoDB, and Couchbase
In this article, I explore how we can architect an example using products and components from Amazon AWS, Microsoft Azure, Google GCP, MongoDB, and Couchbase.
January 17, 2022
by Keshav Murthy DZone Core CORE
· 3,834 Views · 4 Likes
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Small-Scale Logs Processing and Analysis
It’s good to know how to process and extract data from logs manually, using tools that are already available or easy to bootstrap.
January 16, 2022
by Pavel Zinovkin
· 3,685 Views · 3 Likes
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Migrating Feature Toggles With Unleash and CockroachDB
This tutorial will demonstrate a real-world migration story. Migrations are not easy and challenges exist no matter the source database, including PostgreSQL.
January 16, 2022
by Artem Ervits DZone Core CORE
· 3,012 Views · 3 Likes
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Parsing Data With Just SQL
Simple SQL operations like LOAD, ALTER, INSERT, and UPDATE can turn parsing data from a chore into an efficient and mistake-free task.
January 16, 2022
by Everett Berry
· 3,333 Views · 2 Likes
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How To Deploy and Manage Redis Database on AWS Using Terraform
Infrastructure-as-code (IaC) has become an essential capability for any cloud service for it allows you to manage infrastructure with configuration files rather than through a GUI.
January 16, 2022
by Ajeet Raina
· 6,122 Views · 3 Likes
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ClickHouse or StarRocks? Here is a Detailed Comparison
While StarRocks and ClickHouse have a lot in common, there are also differences in functions, performance, and application scenarios. Check out this breakdown of both!
Updated January 16, 2022
by tianyi wang
· 10,994 Views · 6 Likes
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Chain of Responsibility In Microservices
In this article, we are going to understand the concept of chain of responsibility in microservices and how it helps developers solve development issues.
January 16, 2022
by Vishal Rustagi
· 9,374 Views · 4 Likes
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Chart.js Line Chart Tutorial: Visualize Route Elevation Data
Learn how to create a Chart.js line chart on an example of a route elevations profile graph. This tutorial includes code samples and JSFiddle to start quickly.
January 16, 2022
by Alfiya Tarasenko
· 7,970 Views · 4 Likes
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Less Code With Spring Data Rest
We programmers are constantly solving various problems and always looking for a way to make life easier for others. On the other hand, we make life difficult for ourselves, because sometimes our code contains a lot of boilerplate code and modules that are not needed. For better understanding, consider a normal Spring Boot project that is only responsible for creating/reading/updating/deleting (CRUD) a client. First of all, we should create an entity called "Customer" which should be mapped to the table in the database, next, we should create a repository and the controller to call this repository and expose the service to the outside, sometimes we go one step further and add another layer to the architecture. Is all this extra work really necessary to provide multiple simple services? The answer is no, we can use "spring data rest" which can help us to provide our services directly from the data layer. Spring Data Rest With Spring Data Rest, the BL and controller layers are removed from your project. In fact, all REST services are provided by your Spring Data layer, and all you need to do is create a simple repository for your project, and Spring will do the rest. How Spring Data Rest Works everything is very simple, Spring Data Rest searches your projects and any commodity that finds the repository creates REST services for the corresponding entities related to the repository, consider the following example: Java public interface CustomerRepository extends CrudRepository {} If spring data rest finds this repository class, generates all REST APIs related to the client class. Rest APIs And Standards Spring Data Rest is based on a very simple and standard contract and creates REST APIs based on the entity type. In the example above, APIs were generated based on the entity type "customer", and the APIs followed a simple pluralized form, e.g. the first character of the entity is a lowercase letter and an "s" is simply added to the end of the entity. "/customers", you can see some generated REST for "customer" in the table below: HTTP Method URL Pattern Status Code Description GET /customers 200 get all customers GET /customers{id} 200 get customer by id POST /customers 201(created) creates new customer PUT /customers{id} 200 existing customer by id DELETE /customers{id} 200 customer by id REST APIs exposes in HATAOS format Spring Data Rest provides APIs in this format: Hypermedia as the Engine of application state(HATAOS), as you know hypermedia format can refer to any format or URL or even an image from the content, here is a simple HATAOS JSON from wiki : JSON HTTP/1.1 200 OK { "account": { "account_number": 12345, "balance": { "currency": "usd", "value": 100.00 }, "links": { "deposits": "/accounts/12345/deposits", "withdrawals": "/accounts/12345/withdrawals", "transfers": "/accounts/12345/transfers", "close-requests": "/accounts/12345/close-requests" } } } Useful and practical information about HATAOS can be found here. Also, learn more about this format in the rest of the article. Simple Case Study For better understanding, I will try to continue with a very simple example. Again, this example is not very unusual, because we are trying to create a project around the entity "customer". So let us get started. First of all, we need to add the required dependency to our pom: XML org.springframework.boot spring-boot-starter-data-rest Now it is time to create the main entity of the project, "Customer". This is a very simple entity that contains only one property: id, name, phone, and address of the customer Java package com.rgn.model; import lombok.Data; import javax.persistence.Column; import javax.persistence.Entity; import javax.persistence.Id; import javax.persistence.Table; import java.io.Serializable; @Data @Entity @Table(name = "customer") public class Customer implements Serializable { @Id @Column(name = "id") private Long id; @Column(name = "customername") private String customerName; @Column(name = "customerphonno") private Long customerPhoneNo; @Column(name = "customraddress") private String customerAddress; } Using Lombok @Data annotation helps us to prevent additional, setter, and getter in our code. the second most important part of our code is the creation of an appropriate repository for our entity customer: Java package com.rgn.repository; import com.rgn.model.Customer; import org.springframework.data.repository.CrudRepository; public interface CustomerRepository extends CrudRepository { } Also, we have a simple application class like every spring boot project: Java import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.context.ApplicationContext; import org.springframework.context.annotation.Bean; import java.util.Arrays; @SpringBootApplication public class MainApplication { public static void main(String[] args) { SpringApplication.run(MainApplication.class, args); } @Bean public CommandLineRunner commandLineRunner(ApplicationContext ctx) { return args -> { System.out.println("Let's inspect the beans provided by Spring Boot:"); String[] beanNames = ctx.getBeanDefinitionNames(); Arrays.sort(beanNames); for (String beanName : beanNames) { System.out.println(beanName); } }; } } Here is the configuration (application. properties)file of our project, we created our customer table in the Oracle database so we need to set database URL, username, and password: Shell spring.datasource.url=jdbc:oracle:thin:@localhost:1521:ORA81 spring.datasource.username=scott spring.datasource.password=tiger spring.datasource.driver-class-name=oracle.jdbc.OracleDriver # HikariCP settings spring.datasource.hikari.minimumIdle=5 spring.datasource.hikari.maximumPoolSize=20 spring.datasource.hikari.idleTimeout=30000 spring.datasource.hikari.maxLifetime=2000000 spring.datasource.hikari.connectionTimeout=30000 spring.datasource.hikari.poolName=HikariPoolBooks # JPA settings spring.jpa.database-platform=org.hibernate.dialect.Oracle12cDialect spring.jpa.hibernate.use-new-id-generator-mappings=false Note: the default address of exposed APIs is "/", for example, if you run the above project you can see the APIs at address "http://localhost:8080", unless, you should add your own address to the application.properties file with the following code : Shell spring.data.rest.basePath=/myApi By adding the above code you can see your rest in "http://localhost:8080/myApi" HAL explorer Spring also surprises developers and DevOps engineers with the capabilities it offers. There is a strong REST APIs explore that shows the APIs in HATAOS format, to use them you need to add the following dependency to your project: XML org.springframework.data spring-data-rest-hal-explorer org.springframework.boot spring-boot-starter-security In order for us to use standard annotations at both the class and method levels, the following code represents the application of class-level security roles, which means that any caller wishing to invoke any service of this class should have the "ALL" role: Java @PreAuthorize("hasRole('ALL')") public interface CustomerRepository extends CrudRepository { } If you want to create a method with different access roles, you should simply override the method and apply a different role. In the code below, "findAll()" has been overridden and applied to an "ADMIN" role: import com.rgn.model.Customer; import org.springframework.data.repository.CrudRepository; import org.springframework.security.access.prepost.PreAuthorize; @PreAuthorize("hasRole('ALL')") public interface CustomerRepository extends CrudRepository { @Override @PreAuthorize("hasRole('ADMIN')") public Iterable findAll(); } You can find detailed information about spring security and annotations and mechanism here. Performance When I decide to use new technology, after all the technical considerations and studies of that technology, before I use it, I try to compare its performance either with the older technology I am using now or with similar technologies that exist in the field. For this purpose, firstly, I search for reputable websites to know the experience of others with this technology in terms of its performance and benchmarks, and secondly, I try to make performance comparisons myself. in this part, let us compare the performance between Spring Data Rest and the regular architecture that includes the controller layer. So I have two test cases with and without spring data rest. For the performance tests, I used JMeter, with 1000000 threads and 1000 as a threshold for the graph and the regular PC. OK, here we go: Test Result With Spring Data Rest As you can see, the graph of response times has stabilized after slight fluctuations and we have a normal response time. Test Result Without Spring Data Rest Before we start this step, we should remove the dependency on spring data rest from our pom and add the following class as a controller layer to our project: Java package com.rgn.model; import com.rgn.repository.CustomerRepository; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.*; @RestController public class CustomerService { @Autowired CustomerRepository repository; @GetMapping("/customers") public Customer getCustomer(@RequestParam(value = "id") Long id){ return repository.findById(id.longValue()).get(); } } The result can be seen in the following figure. You can see that we get better performance when using spring data.
January 16, 2022
by Reza Ganji DZone Core CORE
· 10,971 Views · 9 Likes
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5 JavaScript Concepts Every Web Developer Should Learn
In this article, I will share essential JavaScript features like arrow functions, let and const keywords, restructuring, spread operator, etc., to learn this year.
January 16, 2022
by Javin Paul
· 34,540 Views · 18 Likes
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MSA as a Project
MSA, or microservice architecture, has established itself as a great purpose for building services for several years. Here's how to implement MSA.
January 15, 2022
by Gyuseok Lee
· 4,458 Views · 2 Likes
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Easy Oracle Database Migration with SQLcl
Migrate Oracle databases using SQLcl with built-in Data Pump and OCI support
January 15, 2022
by Brian Spendolini
· 4,979 Views · 3 Likes
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Building With Open Policy Agent (OPA) for Better Policy as Code
Dive into a new way of thinking about Policy as Code. Learn to leverage OPA for learning deep insights about your systems, their resource utilization, and more.
Updated January 15, 2022
by Liav Yona
· 12,434 Views · 7 Likes
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