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Build a Health Tracking App with Spring Boot Actuator

Ever wanted to see the precise HTTP traffic going through your Spring Boot API? With the Spring Boot Actuator and some code, you can! Spring Boot Actuator manages and monitors the health of your app using HTTP endpoints. It also allows you to see everything that’s happening in the background of an OpenID Connect (OIDC) flow.

In this tutorial, we’ll look at how you can capture body contents and track the OIDC flow with the httptrace endpoints.

Create an OpenID Connect App With Spring Initializr and Okta

You can use the excellent Spring Initializr website or API for creating a sample OIDC application with Okta integration:

curl https://start.spring.io/starter.zip \
  dependencies==web,okta \
  packageName==com.okta.developer.demo -d

Before running your OIDC application, however, you will need an Okta account. Okta is a developer service that handles storing user accounts and implementing user management (including OIDC) for you. Go ahead and register for a free developer account to continue.

Once you log in to your Okta account, go to the Dashboard and then to the Applications section. Add a new Web application, and then in the General section, get the client credentials: Client ID and Client Secret.

You will need the Issuer, which is the organization URL as well, which you can find at the top right corner in the Dashboard home.

Note: By default, the built-in Everyone Okta group is assigned to this application, so any users in your Okta org will be able to authenticate to it.

With your Client ID, Client Secret and the Issuer in place, start your application by passing the credentials through the command line:

OKTA_OAUTH2_REDIRECTURI=/authorization-code/callback \
OKTA_OAUTH2_ISSUER=<issuer>/oauth2 \
OKTA_OAUTH2_CLIENT_ID=<client id> \
OKTA_OAUTH2_CLIENT_SECRET=<client secret> \
./mvnw spring-boot:run

Add Test Controller to the Spring Boot App

It’s a good practice to add a simple controller for testing the authentication flow. By default, access will only be allowed to authenticated users.

@Controller
@RequestMapping(value = "/hello")
public class HelloController {

    @GetMapping(value = "/greeting")
    @ResponseBody
    public String getGreeting(Principal user) {
        return "Good morning " + user.getName();
    }
}

Add Spring Boot Actuator Dependency

Enable Spring Boot Actuator by adding the starter Maven dependency to the pom.xml file:

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>

To enable the httptrace endpoint, edit the src/main/resources/application.properties and add the following line:

management.endpoints.web.exposure.include=info,health,httptrace

Under the auto-configuration, Spring Security filters have higher precedence than filters added by the httptrace actuator.

This means only authenticated calls are traced by default. We are going to change that here soon, but for now, you can see what is traced at /actuator/httptrace. The response should look like this JSON payload:

{
   "traces":[
      {
         "timestamp":"2019-05-19T05:38:42.726Z",
         "principal":{
            "name":"***"
         },
         "session":{
            "id":"***"
         },
         "request":{
            "method":"GET",
            "uri":"http://localhost:8080/",
            "headers":{},
            "remoteAddress":"0:0:0:0:0:0:0:1"
         },
         "response":{
            "status":200,
            "headers":{}
         },
         "timeTaken":145
      }
   ]
}

Add Custom HTTP Tracing to your Spring Boot App

HTTP tracing is not very flexible. Andy Wilkinson, the author of the httptrace actuator, suggests implementing your own endpoint if body tracing is required.

Alternatively, with some custom filters, we can enhance the base implementation without much work. In the following sections, I’ll show you how to:

  • Create a filter for capturing request and response body.
  • Configure the filters precedence for tracing OIDC calls.
  • Create the httptrace endpoint extension with a custom trace repository to store additional data.

Use Spring Boot Actuator to Capture Request and Response Body Contents

Next, create a filter for tracing the request and response of body contents. This filter will have precedence over the httptrace filter, so the cached body contents are available when the actuator saves the trace.

@Component
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class ContentTraceFilter extends OncePerRequestFilter {

    private ContentTraceManager traceManager;

    @Value("${management.trace.http.tracebody:false}")
    private boolean traceBody;

   public ContentTraceFilter(ContentTraceManager traceManager) {
        super();
        this.traceManager = traceManager;
    }

    @Override
    protected void doFilterInternal(HttpServletRequest request,
            HttpServletResponse response, FilterChain filterChain)
            throws ServletException, IOException {

        if (!isRequestValid(request) || !traceBody) {
            filterChain.doFilter(request, response);
            return;
        }

        ContentCachingRequestWrapper wrappedRequest = new ContentCachingRequestWrapper(
                request, 1000);
        ContentCachingResponseWrapper wrappedResponse = new ContentCachingResponseWrapper(
                response);
        try {
            filterChain.doFilter(wrappedRequest, wrappedResponse);
            traceManager.updateBody(wrappedRequest, wrappedResponse);
        } finally {
            wrappedResponse.copyBodyToResponse();
        }
    }

    private boolean isRequestValid(HttpServletRequest request) {
        try {
            new URI(request.getRequestURL().toString());
            return true;
        } catch (URISyntaxException ex) {
            return false;
        }
    }

}

Notice the call to a ContentTraceManager, a simple @RequestScope bean that will store the additional data:

@Component
@RequestScope
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class ContentTraceManager {

    private ContentTrace trace;

    public ContentTraceManager(ContentTrace trace) {
        this.trace=trace;
    }

    protected static Logger logger = LoggerFactory
            .getLogger(ContentTraceManager.class);

    public void updateBody(ContentCachingRequestWrapper wrappedRequest,
            ContentCachingResponseWrapper wrappedResponse) {

        String requestBody = getRequestBody(wrappedRequest);
        getTrace().setRequestBody(requestBody);

        String responseBody = getResponseBody(wrappedResponse);
        getTrace().setResponseBody(responseBody);
    }

    protected String getRequestBody(
            ContentCachingRequestWrapper wrappedRequest) {
        try {
            if (wrappedRequest.getContentLength() <= 0) {
                return null;
            }
            return new String(wrappedRequest.getContentAsByteArray(), 0,
                    wrappedRequest.getContentLength(),
                    wrappedRequest.getCharacterEncoding());
        } catch (UnsupportedEncodingException e) {
            logger.error(
                    "Could not read cached request body: " + e.getMessage());
            return null;
        }

    }

    protected String getResponseBody(
            ContentCachingResponseWrapper wrappedResponse) {

        try {
            if (wrappedResponse.getContentSize() <= 0) {
                return null;
            }
            return new String(wrappedResponse.getContentAsByteArray(), 0,
                    wrappedResponse.getContentSize(),
                    wrappedResponse.getCharacterEncoding());
        } catch (UnsupportedEncodingException e) {
            logger.error(
                    "Could not read cached response body: " + e.getMessage());
            return null;
        }

    }

    public ContentTrace getTrace() {
        if (trace == null) {
            trace = new ContentTrace();
        }
        return trace;
    }
}

For modeling the trace with additional data, compose a custom ContentTrace class with the built-in HttpTrace information, adding properties for storing the body contents.

public class ContentTrace {

    protected HttpTrace httpTrace;

    protected String requestBody;

    protected String responseBody;

    protected Authentication principal;

    public ContentTrace() {
    }

    public void setHttpTrace(HttpTrace httpTrace) {
        this.httpTrace = httpTrace;
    }
}

Add setters and getters for httpTraceprincipalrequestBody and responseBody.

Configure Filter Precedence

For capturing requests to OIDC endpoints in your application, the tracing filters have to sit before Spring Security filters. As long as ContentTraceFilter has precedence over HttpTraceFilter, both can be placed before or after SecurityContextPersistenceFilter, the first one in the Spring Security filter chain.

@Configuration
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class WebSecurityConfig extends WebSecurityConfigurerAdapter {

    private HttpTraceFilter httpTraceFilter;
    private ContentTraceFilter contentTraceFilter;

    public WebSecurityConfig(
        HttpTraceFilter httpTraceFilter, ContentTraceFilter contentTraceFilter
    ) {
        this.httpTraceFilter = httpTraceFilter;
        this.contentTraceFilter = contentTraceFilter;
    }

    @Override
    protected void configure(HttpSecurity http) throws Exception {
        http.addFilterBefore(contentTraceFilter,
                SecurityContextPersistenceFilter.class)
                .addFilterAfter(httpTraceFilter,
                        SecurityContextPersistenceFilter.class)
                .authorizeRequests().anyRequest().authenticated()
                .and().oauth2Client()
                .and().oauth2Login();
    }
}

Tracing the Authenticated User

We’re installing the trace filters before the Spring Security filter chain. This means that the Principal is no longer available when the HttpTraceFilter saves the trace. We can restore this trace data with a new filter and the ContentTraceManager.

@Component
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class PrincipalTraceFilter extends OncePerRequestFilter {

    private ContentTraceManager traceManager;
    private HttpTraceProperties traceProperties;

    public PrincipalTraceFilter(
        ContentTraceManager traceManager,
        HttpTraceProperties traceProperties
    ) {
        super();
        this.traceManager = traceManager;
        this.traceProperties = traceProperties;
    }

    @Override
    protected void doFilterInternal(HttpServletRequest request,
            HttpServletResponse response,
            FilterChain filterChain)
            throws ServletException, IOException {

        if (!isRequestValid(request)) {
            filterChain.doFilter(request, response);
            return;
        }
        try {
            filterChain.doFilter(request, response);

        } finally {
            if (traceProperties.getInclude().contains(Include.PRINCIPAL)) {
                traceManager.updatePrincipal();
            }
        }

    }

    private boolean isRequestValid(HttpServletRequest request) {
        try {
            new URI(request.getRequestURL().toString());
            return true;
        } catch (URISyntaxException ex) {
            return false;
        }
    }

}

Add the missing ContentTraceManager class for updating the principal:

public class ContentTraceManager {

    public void updatePrincipal() {
        Authentication authentication = SecurityContextHolder.getContext().getAuthentication();
        if (authentication != null) {
            getTrace().setPrincipal(authentication);
        }
  }
}

The PrincipalTraceFilter must have lower precedence than the Spring Security filter chain, so the authenticated principal is available when requested from the security context. Modify the WebSecurityConfig to insert the filter after the FilterSecurityInterceptor, the last filter in the security chain.

@Configuration
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class WebSecurityConfig extends WebSecurityConfigurerAdapter {

    private HttpTraceFilter httpTraceFilter;
    private ContentTraceFilter contentTraceFilter;
    private PrincipalTraceFilter principalTraceFilter;

    public WebSecurityConfig(
        HttpTraceFilter httpTraceFilter,
        ContentTraceFilter contentTraceFilter,
        PrincipalTraceFilter principalTraceFilter
    ) {
        super();
        this.httpTraceFilter = httpTraceFilter;
        this.contentTraceFilter = contentTraceFilter;
        this.principalTraceFilter = principalTraceFilter;
    }

    @Override
    protected void configure(HttpSecurity http) throws Exception {
        http.addFilterBefore(contentTraceFilter,
                SecurityContextPersistenceFilter.class)
                .addFilterAfter(httpTraceFilter,
                        SecurityContextPersistenceFilter.class)
                .addFilterAfter(principalTraceFilter,
                        FilterSecurityInterceptor.class)
                .authorizeRequests().anyRequest().authenticated()
                .and().oauth2Client()
                .and().oauth2Login();
    }
}

HTTPTrace Endpoint Extension

Finally, define the endpoint enhancement using the @EndpointWebExtension annotation. Implement a CustomHttpTraceRepository to store and retrieve a ContentTrace with the additional data.

@Component
@EndpointWebExtension(endpoint = HttpTraceEndpoint.class)
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class HttpTraceEndpointExtension {

    private CustomHttpTraceRepository repository;

    public HttpTraceEndpointExtension(CustomHttpTraceRepository repository) {
        super();
        this.repository = repository;
    }

    @ReadOperation
    public ContentTraceDescriptor contents() {
        List<ContentTrace> traces = repository.findAllWithContent();
        return new ContentTraceDescriptor(traces);
    }
}

Redefine a descriptor for the endpoint return type:

public class ContentTraceDescriptor {

    protected List<ContentTrace> traces;

    public ContentTraceDescriptor(List<ContentTrace> traces) {
        super();
        this.traces = traces;
    }

    public List<ContentTrace> getTraces() {
        return traces;
    }

    public void setTraces(List<ContentTrace> traces) {
        this.traces = traces;
    }

}

Create the CustomHttpTraceRepository implementing the HttpTraceRepository interface:

@Component
@ConditionalOnProperty(prefix = "management.trace.http", name = "enabled", matchIfMissing = true)
public class CustomHttpTraceRepository implements HttpTraceRepository {

    private final List<ContentTrace> contents = new LinkedList<>();

    private ContentTraceManager traceManager;

    public CustomHttpTraceRepository(ContentTraceManager traceManager) {
        super();
        this.traceManager = traceManager;
    }

    @Override
    public void add(HttpTrace trace) {
        synchronized (this.contents) {
            ContentTrace contentTrace = traceManager.getTrace();
            contentTrace.setHttpTrace(trace);
            this.contents.add(0, contentTrace);
        }
    }

    @Override
    public List<HttpTrace> findAll() {
        synchronized (this.contents) {
            return contents.stream().map(ContentTrace::getHttpTrace)
                    .collect(Collectors.toList());
        }
    }

    public List<ContentTrace> findAllWithContent() {
        synchronized (this.contents) {
            return Collections.unmodifiableList(new ArrayList<>(this.contents));
        }
    }

}

Inspect OpenID Connect HTTP Trace

Modify the application.properties file for tracing all available data by adding the following line:

management.trace.http.include=request-headers,response-headers,
cookie-headers,principal,time-taken,authorization-header,remote-address,
session-id

Run the application again and call the secured controller /hello/greeting. Authenticate against Okta and then inspect the traces at /actuator/httptrace.

You should now see OIDC calls in the trace as well as the request and response contents. For example, in the trace below, a request to the application authorization endpoint redirects to the Okta authorization server, initiating the OIDC authorization code flow.

{
    "httpTrace": {
        "timestamp": "2019-05-22T00:52:22.383Z",
        "principal": null,
        "session": {
            "id": "C2174F5E5F85B313B2284639EE4016E7"
        },
        "request": {
            "method": "GET",
            "uri": "http://localhost:8080/oauth2/authorization/okta",
            "headers": {
                "cookie": [
                    "JSESSIONID=C2174F5E5F85B313B2284639EE4016E7"
                ],
                "accept-language": [
                    "en-US,en;q=0.9"
                ],
                "upgrade-insecure-requests": [
                    "1"
                ],
                "host": [
                    "localhost:8080"
                ],
                "connection": [
                    "keep-alive"
                ],
                "accept-encoding": [
                    "gzip, deflate, br"
                ],
                "accept": [
                    "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8"
                ],
                "user-agent": [
                    "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.181 Safari/537.36"
                ]
            },
            "remoteAddress": "0:0:0:0:0:0:0:1"
        },
        "response": {
            "status": 302,
            "headers": {
                "X-Frame-Options": [
                    "DENY"
                ],
                "Cache-Control": [
                    "no-cache, no-store, max-age=0, must-revalidate"
                ],
                "X-Content-Type-Options": [
                    "nosniff"
                ],
                "Expires": [
                    "0"
                ],
                "Pragma": [
                    "no-cache"
                ],
                "X-XSS-Protection": [
                    "1; mode=block"
                ],
                "Location": [
                    "https://dev-239352.okta.com/oauth2/default/v1/authorize?response_type=code&client_id=0oalrp4qx3Do43VyI356&scope=openid%20profile%20email&state=1uzHRyaHVmyKcpb7eAvJVrdJTZ6wTgkPv3fsC14qdOk%3D&redirect_uri=http://localhost:8080/authorization-code/callback"
                ]
            }
        },
        "timeTaken": 9
    },
    "requestBody": null,
    "responseBody": null
}

All of the code in this post can be found on GitHub

Thank for reading ! If you enjoyed this article, please share it with others who may enjoy it as well.!

This post was originally published on dzone.com.

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Build a Health Tracking App with Spring Boot Actuator

Enhance Amazon Aurora Read/Write Capability with ShardingSphere-JDBC

1. Introduction

Amazon Aurora is a relational database management system (RDBMS) developed by AWS(Amazon Web Services). Aurora gives you the performance and availability of commercial-grade databases with full MySQL and PostgreSQL compatibility. In terms of high performance, Aurora MySQL and Aurora PostgreSQL have shown an increase in throughput of up to 5X over stock MySQL and 3X over stock PostgreSQL respectively on similar hardware. In terms of scalability, Aurora achieves enhancements and innovations in storage and computing, horizontal and vertical functions.

Aurora supports up to 128TB of storage capacity and supports dynamic scaling of storage layer in units of 10GB. In terms of computing, Aurora supports scalable configurations for multiple read replicas. Each region can have an additional 15 Aurora replicas. In addition, Aurora provides multi-primary architecture to support four read/write nodes. Its Serverless architecture allows vertical scaling and reduces typical latency to under a second, while the Global Database enables a single database cluster to span multiple AWS Regions in low latency.

Aurora already provides great scalability with the growth of user data volume. Can it handle more data and support more concurrent access? You may consider using sharding to support the configuration of multiple underlying Aurora clusters. To this end, a series of blogs, including this one, provides you with a reference in choosing between Proxy and JDBC for sharding.

1.1 Why sharding is needed

AWS Aurora offers a single relational database. Primary-secondary, multi-primary, and global database, and other forms of hosting architecture can satisfy various architectural scenarios above. However, Aurora doesn’t provide direct support for sharding scenarios, and sharding has a variety of forms, such as vertical and horizontal forms. If we want to further increase data capacity, some problems have to be solved, such as cross-node database Join, associated query, distributed transactions, SQL sorting, page turning, function calculation, database global primary key, capacity planning, and secondary capacity expansion after sharding.

1.2 Sharding methods

It is generally accepted that when the capacity of a MySQL table is less than 10 million, the time spent on queries is optimal because at this time the height of its BTREE index is between 3 and 5. Data sharding can reduce the amount of data in a single table and distribute the read and write loads to different data nodes at the same time. Data sharding can be divided into vertical sharding and horizontal sharding.

1. Advantages of vertical sharding

  • Address the coupling of business system and make clearer.
  • Implement hierarchical management, maintenance, monitoring, and expansion to data of different businesses, like micro-service governance.
  • In high concurrency scenarios, vertical sharding removes the bottleneck of IO, database connections, and hardware resources on a single machine to some extent.

2. Disadvantages of vertical sharding

  • After splitting the library, Join can only be implemented by interface aggregation, which will increase the complexity of development.
  • After splitting the library, it is complex to process distributed transactions.
  • There is a large amount of data on a single table and horizontal sharding is required.

3. Advantages of horizontal sharding

  • There is no such performance bottleneck as a large amount of data on a single database and high concurrency, and it increases system stability and load capacity.
  • The business modules do not need to be split due to minor modification on the application client.

4. Disadvantages of horizontal sharding

  • Transaction consistency across shards is hard to be guaranteed;
  • The performance of associated query in cross-library Join is poor.
  • It’s difficult to scale the data many times and maintenance is a big workload.

Based on the analysis above, and the available studis on popular sharding middleware, we selected ShardingSphere, an open source product, combined with Amazon Aurora to introduce how the combination of these two products meets various forms of sharding and how to solve the problems brought by sharding.

ShardingSphere is an open source ecosystem including a set of distributed database middleware solutions, including 3 independent products, Sharding-JDBC, Sharding-Proxy & Sharding-Sidecar.

2. ShardingSphere introduction:

The characteristics of Sharding-JDBC are:

  1. With the client end connecting directly to the database, it provides service in the form of jar and requires no extra deployment and dependence.
  2. It can be considered as an enhanced JDBC driver, which is fully compatible with JDBC and all kinds of ORM frameworks.
  3. Applicable in any ORM framework based on JDBC, such as JPA, Hibernate, Mybatis, Spring JDBC Template or direct use of JDBC.
  4. Support any third-party database connection pool, such as DBCP, C3P0, BoneCP, Druid, HikariCP;
  5. Support any kind of JDBC standard database: MySQL, Oracle, SQLServer, PostgreSQL and any databases accessible to JDBC.
  6. Sharding-JDBC adopts decentralized architecture, applicable to high-performance light-weight OLTP application developed with Java

Hybrid Structure Integrating Sharding-JDBC and Applications

Sharding-JDBC’s core concepts

Data node: The smallest unit of a data slice, consisting of a data source name and a data table, such as ds_0.product_order_0.

Actual table: The physical table that really exists in the horizontal sharding database, such as product order tables: product_order_0, product_order_1, and product_order_2.

Logic table: The logical name of the horizontal sharding databases (tables) with the same schema. For instance, the logic table of the order product_order_0, product_order_1, and product_order_2 is product_order.

Binding table: It refers to the primary table and the joiner table with the same sharding rules. For example, product_order table and product_order_item are sharded by order_id, so they are binding tables with each other. Cartesian product correlation will not appear in the multi-tables correlating query, so the query efficiency will increase greatly.

Broadcast table: It refers to tables that exist in all sharding database sources. The schema and data must consist in each database. It can be applied to the small data volume that needs to correlate with big data tables to query, dictionary table and configuration table for example.

3. Testing ShardingSphere-JDBC

3.1 Example project

Download the example project code locally. In order to ensure the stability of the test code, we choose shardingsphere-example-4.0.0 version.

git clone https://github.com/apache/shardingsphere-example.git

Project description:

shardingsphere-example
  ├── example-core
  │   ├── config-utility
  │   ├── example-api
  │   ├── example-raw-jdbc
  │   ├── example-spring-jpa #spring+jpa integration-based entity,repository
  │   └── example-spring-mybatis
  ├── sharding-jdbc-example
  │   ├── sharding-example
  │   │   ├── sharding-raw-jdbc-example
  │   │   ├── sharding-spring-boot-jpa-example #integration-based sharding-jdbc functions
  │   │   ├── sharding-spring-boot-mybatis-example
  │   │   ├── sharding-spring-namespace-jpa-example
  │   │   └── sharding-spring-namespace-mybatis-example
  │   ├── orchestration-example
  │   │   ├── orchestration-raw-jdbc-example
  │   │   ├── orchestration-spring-boot-example #integration-based sharding-jdbc governance function
  │   │   └── orchestration-spring-namespace-example
  │   ├── transaction-example
  │   │   ├── transaction-2pc-xa-example #sharding-jdbc sample of two-phase commit for a distributed transaction
  │   │   └──transaction-base-seata-example #sharding-jdbc distributed transaction seata sample
  │   ├── other-feature-example
  │   │   ├── hint-example
  │   │   └── encrypt-example
  ├── sharding-proxy-example
  │   └── sharding-proxy-boot-mybatis-example
  └── src/resources
        └── manual_schema.sql  

Configuration file description:

application-master-slave.properties #read/write splitting profile
application-sharding-databases-tables.properties #sharding profile
application-sharding-databases.properties       #library split profile only
application-sharding-master-slave.properties    #sharding and read/write splitting profile
application-sharding-tables.properties          #table split profile
application.properties                         #spring boot profile

Code logic description:

The following is the entry class of the Spring Boot application below. Execute it to run the project.

The execution logic of demo is as follows:

3.2 Verifying read/write splitting

As business grows, the write and read requests can be split to different database nodes to effectively promote the processing capability of the entire database cluster. Aurora uses a reader/writer endpoint to meet users' requirements to write and read with strong consistency, and a read-only endpoint to meet the requirements to read without strong consistency. Aurora's read and write latency is within single-digit milliseconds, much lower than MySQL's binlog-based logical replication, so there's a lot of loads that can be directed to a read-only endpoint.

Through the one primary and multiple secondary configuration, query requests can be evenly distributed to multiple data replicas, which further improves the processing capability of the system. Read/write splitting can improve the throughput and availability of system, but it can also lead to data inconsistency. Aurora provides a primary/secondary architecture in a fully managed form, but applications on the upper-layer still need to manage multiple data sources when interacting with Aurora, routing SQL requests to different nodes based on the read/write type of SQL statements and certain routing policies.

ShardingSphere-JDBC provides read/write splitting features and it is integrated with application programs so that the complex configuration between application programs and database clusters can be separated from application programs. Developers can manage the Shard through configuration files and combine it with ORM frameworks such as Spring JPA and Mybatis to completely separate the duplicated logic from the code, which greatly improves the ability to maintain code and reduces the coupling between code and database.

3.2.1 Setting up the database environment

Create a set of Aurora MySQL read/write splitting clusters. The model is db.r5.2xlarge. Each set of clusters has one write node and two read nodes.

3.2.2 Configuring Sharding-JDBC

application.properties spring boot Master profile description:

You need to replace the green ones with your own environment configuration.

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create-drop
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#Activate master-slave configuration item so that sharding-jdbc can use master-slave profile
spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-master-slave.properties sharding-jdbc profile description:

spring.shardingsphere.datasource.names=ds_master,ds_slave_0,ds_slave_1
# data souce-master
spring.shardingsphere.datasource.ds_master.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master.password=Your master DB password
spring.shardingsphere.datasource.ds_master.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master.jdbc-url=Your primary DB data sourceurl spring.shardingsphere.datasource.ds_master.username=Your primary DB username
# data source-slave
spring.shardingsphere.datasource.ds_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_slave_0.password= Your slave DB password
spring.shardingsphere.datasource.ds_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_slave_0.jdbc-url=Your slave DB data source url
spring.shardingsphere.datasource.ds_slave_0.username= Your slave DB username
# data source-slave
spring.shardingsphere.datasource.ds_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_slave_1.password= Your slave DB password
spring.shardingsphere.datasource.ds_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_slave_1.jdbc-url= Your slave DB data source url
spring.shardingsphere.datasource.ds_slave_1.username= Your slave DB username
# Routing Policy Configuration
spring.shardingsphere.masterslave.load-balance-algorithm-type=round_robin
spring.shardingsphere.masterslave.name=ds_ms
spring.shardingsphere.masterslave.master-data-source-name=ds_master
spring.shardingsphere.masterslave.slave-data-source-names=ds_slave_0,ds_slave_1
# sharding-jdbc configures the information storage mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log,and you can see the conversion from logical SQL to actual SQL from the print
spring.shardingsphere.props.sql.show=true

 

3.2.3 Test and verification process description

  • Test environment data initialization: Spring JPA initialization automatically creates tables for testing.

  • Write data to the master instance

As shown in the ShardingSphere-SQL log figure below, the write SQL is executed on the ds_master data source.

  • Data query operations are performed on the slave library.

As shown in the ShardingSphere-SQL log figure below, the read SQL is executed on the ds_slave data source in the form of polling.

[INFO ] 2022-04-02 19:43:39,376 --main-- [ShardingSphere-SQL] Rule Type: master-slave 
[INFO ] 2022-04-02 19:43:39,376 --main-- [ShardingSphere-SQL] SQL: select orderentit0_.order_id as order_id1_1_, orderentit0_.address_id as address_2_1_, 
orderentit0_.status as status3_1_, orderentit0_.user_id as user_id4_1_ from t_order orderentit0_ ::: DataSources: ds_slave_0 
---------------------------- Print OrderItem Data -------------------
Hibernate: select orderiteme1_.order_item_id as order_it1_2_, orderiteme1_.order_id as order_id2_2_, orderiteme1_.status as status3_2_, orderiteme1_.user_id 
as user_id4_2_ from t_order orderentit0_ cross join t_order_item orderiteme1_ where orderentit0_.order_id=orderiteme1_.order_id
[INFO ] 2022-04-02 19:43:40,898 --main-- [ShardingSphere-SQL] Rule Type: master-slave 
[INFO ] 2022-04-02 19:43:40,898 --main-- [ShardingSphere-SQL] SQL: select orderiteme1_.order_item_id as order_it1_2_, orderiteme1_.order_id as order_id2_2_, orderiteme1_.status as status3_2_, 
orderiteme1_.user_id as user_id4_2_ from t_order orderentit0_ cross join t_order_item orderiteme1_ where orderentit0_.order_id=orderiteme1_.order_id ::: DataSources: ds_slave_1 

Note: As shown in the figure below, if there are both reads and writes in a transaction, Sharding-JDBC routes both read and write operations to the master library. If the read/write requests are not in the same transaction, the corresponding read requests are distributed to different read nodes according to the routing policy.

@Override
@Transactional // When a transaction is started, both read and write in the transaction go through the master library. When closed, read goes through the slave library and write goes through the master library
public void processSuccess() throws SQLException {
    System.out.println("-------------- Process Success Begin ---------------");
    List<Long> orderIds = insertData();
    printData();
    deleteData(orderIds);
    printData();
    System.out.println("-------------- Process Success Finish --------------");
}

3.2.4 Verifying Aurora failover scenario

The Aurora database environment adopts the configuration described in Section 2.2.1.

3.2.4.1 Verification process description

  1. Start the Spring-Boot project

2. Perform a failover on Aurora’s console

3. Execute the Rest API request

4. Repeatedly execute POST (http://localhost:8088/save-user) until the call to the API failed to write to Aurora and eventually recovered successfully.

5. The following figure shows the process of executing code failover. It takes about 37 seconds from the time when the latest SQL write is successfully performed to the time when the next SQL write is successfully performed. That is, the application can be automatically recovered from Aurora failover, and the recovery time is about 37 seconds.

3.3 Testing table sharding-only function

3.3.1 Configuring Sharding-JDBC

application.properties spring boot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create-drop
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true
#spring.profiles.active=sharding-databases
#Activate sharding-tables configuration items
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
# spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-tables.properties sharding-jdbc profile description

## configure primary-key policy
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# configure the binding relation of t_order and t_order_item
spring.shardingsphere.sharding.binding-tables[0]=t_order,t_order_item
# configure broadcast tables
spring.shardingsphere.sharding.broadcast-tables=t_address
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.3.2 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC routing rules are configured, the client executes DDL, and Sharding-JDBC automatically creates corresponding tables according to the table splitting rules. If t_address is a broadcast table, create a t_address because there is only one master instance. Two physical tables t_order_0 and t_order_1 will be created when creating t_order.

2. Write operation

As shown in the figure below, Logic SQL inserts a record into t_order. When Sharding-JDBC is executed, data will be distributed to t_order_0 and t_order_1 according to the table splitting rules.

When t_order and t_order_item are bound, the records associated with order_item and order are placed on the same physical table.

3. Read operation

As shown in the figure below, perform the join query operations to order and order_item under the binding table, and the physical shard is precisely located based on the binding relationship.

The join query operations on order and order_item under the unbound table will traverse all shards.

3.4 Testing database sharding-only function

3.4.1 Setting up the database environment

Create two instances on Aurora: ds_0 and ds_1

When the sharding-spring-boot-jpa-example project is started, tables t_order, t_order_itemt_address will be created on two Aurora instances.

3.4.2 Configuring Sharding-JDBC

application.properties springboot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

# Activate sharding-databases configuration items
spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-databases.properties sharding-jdbc profile description

spring.shardingsphere.datasource.names=ds_0,ds_1
# ds_0
spring.shardingsphere.datasource.ds_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_0.jdbc-url= spring.shardingsphere.datasource.ds_0.username= 
spring.shardingsphere.datasource.ds_0.password=
# ds_1
spring.shardingsphere.datasource.ds_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_1.jdbc-url= 
spring.shardingsphere.datasource.ds_1.username= 
spring.shardingsphere.datasource.ds_1.password=
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
spring.shardingsphere.sharding.default-data-source-name=ds_0

spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.4.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s library splitting and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, physical tables will be created on ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the slave library are written on the table in the corresponding instance according to the slave library field and routing policy.

3. Read operation

Query order is routed to the corresponding Aurora instance according to the routing rules of the slave library .

Query Address. Since address is a broadcast table, an instance of address will be randomly selected and queried from the nodes used.

As shown in the figure below, perform the join query operations to order and order_item under the binding table, and the physical shard is precisely located based on the binding relationship.

3.5 Verifying sharding function

3.5.1 Setting up the database environment

As shown in the figure below, create two instances on Aurora: ds_0 and ds_1

When the sharding-spring-boot-jpa-example project is started, physical tables t_order_01, t_order_02, t_order_item_01,and t_order_item_02 and global table t_address will be created on two Aurora instances.

3.5.2 Configuring Sharding-JDBC

application.properties springboot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true
# Activate sharding-databases-tables configuration items
#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-databases.properties sharding-jdbc profile description

spring.shardingsphere.datasource.names=ds_0,ds_1
# ds_0
spring.shardingsphere.datasource.ds_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_0.jdbc-url= 306/dev?useSSL=false&characterEncoding=utf-8
spring.shardingsphere.datasource.ds_0.username= 
spring.shardingsphere.datasource.ds_0.password=
spring.shardingsphere.datasource.ds_0.max-active=16
# ds_1
spring.shardingsphere.datasource.ds_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_1.jdbc-url= 
spring.shardingsphere.datasource.ds_1.username= 
spring.shardingsphere.datasource.ds_1.password=
spring.shardingsphere.datasource.ds_1.max-active=16
# default library splitting policy
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
# Tables that do not meet the library splitting policy are placed on ds_0
spring.shardingsphere.sharding.default-data-source-name=ds_0
# t_order table splitting policy
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order_$->{0..1}
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
# t_order_item table splitting policy
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# sharding-jdbc mdoe
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.5.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s sharding and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, t_address will be created on both ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the sub-library are written to the table on the corresponding instance according to the slave library field and routing policy.

3. Read operation

The read operation is similar to the library split function verification described in section2.4.3.

3.6 Testing database sharding, table sharding and read/write splitting function

3.6.1 Setting up the database environment

The following figure shows the physical table of the created database instance.

3.6.2 Configuring Sharding-JDBC

application.properties spring boot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

# activate sharding-databases-tables configuration items
#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
spring.profiles.active=sharding-master-slave

application-sharding-master-slave.properties sharding-jdbc profile description

The url, name and password of the database need to be changed to your own database parameters.

spring.shardingsphere.datasource.names=ds_master_0,ds_master_1,ds_master_0_slave_0,ds_master_0_slave_1,ds_master_1_slave_0,ds_master_1_slave_1
spring.shardingsphere.datasource.ds_master_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0.jdbc-url= spring.shardingsphere.datasource.ds_master_0.username= 
spring.shardingsphere.datasource.ds_master_0.password=
spring.shardingsphere.datasource.ds_master_0.max-active=16
spring.shardingsphere.datasource.ds_master_0_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0_slave_0.jdbc-url= spring.shardingsphere.datasource.ds_master_0_slave_0.username= 
spring.shardingsphere.datasource.ds_master_0_slave_0.password=
spring.shardingsphere.datasource.ds_master_0_slave_0.max-active=16
spring.shardingsphere.datasource.ds_master_0_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0_slave_1.jdbc-url= spring.shardingsphere.datasource.ds_master_0_slave_1.username= 
spring.shardingsphere.datasource.ds_master_0_slave_1.password=
spring.shardingsphere.datasource.ds_master_0_slave_1.max-active=16
spring.shardingsphere.datasource.ds_master_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1.jdbc-url= 
spring.shardingsphere.datasource.ds_master_1.username= 
spring.shardingsphere.datasource.ds_master_1.password=
spring.shardingsphere.datasource.ds_master_1.max-active=16
spring.shardingsphere.datasource.ds_master_1_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1_slave_0.jdbc-url=
spring.shardingsphere.datasource.ds_master_1_slave_0.username=
spring.shardingsphere.datasource.ds_master_1_slave_0.password=
spring.shardingsphere.datasource.ds_master_1_slave_0.max-active=16
spring.shardingsphere.datasource.ds_master_1_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1_slave_1.jdbc-url= spring.shardingsphere.datasource.ds_master_1_slave_1.username=admin
spring.shardingsphere.datasource.ds_master_1_slave_1.password=
spring.shardingsphere.datasource.ds_master_1_slave_1.max-active=16
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
spring.shardingsphere.sharding.default-data-source-name=ds_master_0
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order_$->{0..1}
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# master/slave data source and slave data source configuration
spring.shardingsphere.sharding.master-slave-rules.ds_0.master-data-source-name=ds_master_0
spring.shardingsphere.sharding.master-slave-rules.ds_0.slave-data-source-names=ds_master_0_slave_0, ds_master_0_slave_1
spring.shardingsphere.sharding.master-slave-rules.ds_1.master-data-source-name=ds_master_1
spring.shardingsphere.sharding.master-slave-rules.ds_1.slave-data-source-names=ds_master_1_slave_0, ds_master_1_slave_1
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.6.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s library splitting and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, t_address will be created on both ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the slave library are written to the table on the corresponding instance according to the slave library field and routing policy.

3. Read operation

The join query operations on order and order_item under the binding table are shown below.

3. Conclusion

As an open source product focusing on database enhancement, ShardingSphere is pretty good in terms of its community activitiy, product maturity and documentation richness.

Among its products, ShardingSphere-JDBC is a sharding solution based on the client-side, which supports all sharding scenarios. And there’s no need to introduce an intermediate layer like Proxy, so the complexity of operation and maintenance is reduced. Its latency is theoretically lower than Proxy due to the lack of intermediate layer. In addition, ShardingSphere-JDBC can support a variety of relational databases based on SQL standards such as MySQL/PostgreSQL/Oracle/SQL Server, etc.

However, due to the integration of Sharding-JDBC with the application program, it only supports Java language for now, and is strongly dependent on the application programs. Nevertheless, Sharding-JDBC separates all sharding configuration from the application program, which brings relatively small changes when switching to other middleware.

In conclusion, Sharding-JDBC is a good choice if you use a Java-based system and have to to interconnect with different relational databases — and don’t want to bother with introducing an intermediate layer.

Author

Sun Jinhua

A senior solution architect at AWS, Sun is responsible for the design and consult on cloud architecture. for providing customers with cloud-related design and consulting services. Before joining AWS, he ran his own business, specializing in building e-commerce platforms and designing the overall architecture for e-commerce platforms of automotive companies. He worked in a global leading communication equipment company as a senior engineer, responsible for the development and architecture design of multiple subsystems of LTE equipment system. He has rich experience in architecture design with high concurrency and high availability system, microservice architecture design, database, middleware, IOT etc.

Fredy  Larson

Fredy Larson

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With more of us using smartphones, the popularity of mobile applications has exploded. In the digital era, the number of people looking for products and services online is growing rapidly. Smartphone owners look for mobile applications that give them quick access to companies’ products and services. As a result, mobile apps provide customers with a lot of benefits in just one device.

Likewise, companies use mobile apps to increase customer loyalty and improve their services. Mobile Developers are in high demand as companies use apps not only to create brand awareness but also to gather information. For that reason, mobile apps are used as tools to collect valuable data from customers to help companies improve their offer.

There are many types of mobile applications, each with its own advantages. For example, native apps perform better, while web apps don’t need to be customized for the platform or operating system (OS). Likewise, hybrid apps provide users with comfortable user experience. However, you may be wondering how long it takes to develop an app.

To give you an idea of how long the app development process takes, here’s a short guide.

App Idea & Research

app-idea-research

_Average time spent: two to five weeks _

This is the initial stage and a crucial step in setting the project in the right direction. In this stage, you brainstorm ideas and select the best one. Apart from that, you’ll need to do some research to see if your idea is viable. Remember that coming up with an idea is easy; the hard part is to make it a reality.

All your ideas may seem viable, but you still have to run some tests to keep it as real as possible. For that reason, when Web Developers are building a web app, they analyze the available ideas to see which one is the best match for the targeted audience.

Targeting the right audience is crucial when you are developing an app. It saves time when shaping the app in the right direction as you have a clear set of objectives. Likewise, analyzing how the app affects the market is essential. During the research process, App Developers must gather information about potential competitors and threats. This helps the app owners develop strategies to tackle difficulties that come up after the launch.

The research process can take several weeks, but it determines how successful your app can be. For that reason, you must take your time to know all the weaknesses and strengths of the competitors, possible app strategies, and targeted audience.

The outcomes of this stage are app prototypes and the minimum feasible product.

#android app #frontend #ios app #minimum viable product (mvp) #mobile app development #web development #android app development #app development #app development for ios and android #app development process #ios and android app development #ios app development #stages in app development

Carmen  Grimes

Carmen Grimes

1595491178

Best Electric Bikes and Scooters for Rental Business or Campus Facility

The electric scooter revolution has caught on super-fast taking many cities across the globe by storm. eScooters, a renovated version of old-school scooters now turned into electric vehicles are an environmentally friendly solution to current on-demand commute problems. They work on engines, like cars, enabling short traveling distances without hassle. The result is that these groundbreaking electric machines can now provide faster transport for less — cheaper than Uber and faster than Metro.

Since they are durable, fast, easy to operate and maintain, and are more convenient to park compared to four-wheelers, the eScooters trend has and continues to spike interest as a promising growth area. Several companies and universities are increasingly setting up shop to provide eScooter services realizing a would-be profitable business model and a ready customer base that is university students or residents in need of faster and cheap travel going about their business in school, town, and other surrounding areas.

Electric Scooters Trends and Statistics

In many countries including the U.S., Canada, Mexico, U.K., Germany, France, China, Japan, India, Brazil and Mexico and more, a growing number of eScooter users both locals and tourists can now be seen effortlessly passing lines of drivers stuck in the endless and unmoving traffic.

A recent report by McKinsey revealed that the E-Scooter industry will be worth― $200 billion to $300 billion in the United States, $100 billion to $150 billion in Europe, and $30 billion to $50 billion in China in 2030. The e-Scooter revenue model will also spike and is projected to rise by more than 20% amounting to approximately $5 billion.

And, with a necessity to move people away from high carbon prints, traffic and congestion issues brought about by car-centric transport systems in cities, more and more city planners are developing more bike/scooter lanes and adopting zero-emission plans. This is the force behind the booming electric scooter market and the numbers will only go higher and higher.

Companies that have taken advantage of the growing eScooter trend develop an appthat allows them to provide efficient eScooter services. Such an app enables them to be able to locate bike pick-up and drop points through fully integrated google maps.

List of Best Electric Bikes for Rental Business or Campus Facility 2020:

It’s clear that e scooters will increasingly become more common and the e-scooter business model will continue to grab the attention of manufacturers, investors, entrepreneurs. All this should go ahead with a quest to know what are some of the best electric bikes in the market especially for anyone who would want to get started in the electric bikes/scooters rental business.

We have done a comprehensive list of the best electric bikes! Each bike has been reviewed in depth and includes a full list of specs and a photo.

Billy eBike

mobile-best-electric-bikes-scooters https://www.kickstarter.com/projects/enkicycles/billy-were-redefining-joyrides

To start us off is the Billy eBike, a powerful go-anywhere urban electric bike that’s specially designed to offer an exciting ride like no other whether you want to ride to the grocery store, cafe, work or school. The Billy eBike comes in 4 color options – Billy Blue, Polished aluminium, Artic white, and Stealth black.

Price: $2490

Available countries

Available in the USA, Europe, Asia, South Africa and Australia.This item ships from the USA. Buyers are therefore responsible for any taxes and/or customs duties incurred once it arrives in your country.

Features

  • Control – Ride with confidence with our ultra-wide BMX bars and a hyper-responsive twist throttle.
  • Stealth- Ride like a ninja with our Gates carbon drive that’s as smooth as butter and maintenance-free.
  • Drive – Ride further with our high torque fat bike motor, giving a better climbing performance.
  • Accelerate – Ride quicker with our 20-inch lightweight cutout rims for improved acceleration.
  • Customize – Ride your own way with 5 levels of power control. Each level determines power and speed.
  • Flickable – Ride harder with our BMX /MotoX inspired geometry and lightweight aluminum package

Specifications

  • Maximum speed: 20 mph (32 km/h)
  • Range per charge: 41 miles (66 km)
  • Maximum Power: 500W
  • Motor type: Fat Bike Motor: Bafang RM G060.500.DC
  • Load capacity: 300lbs (136kg)
  • Battery type: 13.6Ah Samsung lithium-ion,
  • Battery capacity: On/off-bike charging available
  • Weight: w/o batt. 48.5lbs (22kg), w/ batt. 54lbs (24.5kg)
  • Front Suspension: Fully adjustable air shock, preload/compression damping /lockout
  • Rear Suspension: spring, preload adjustment
  • Built-in GPS

Why Should You Buy This?

  • Riding fun and excitement
  • Better climbing ability and faster acceleration.
  • Ride with confidence
  • Billy folds for convenient storage and transportation.
  • Shorty levers connect to disc brakes ensuring you stop on a dime
  • belt drives are maintenance-free and clean (no oil or lubrication needed)

**Who Should Ride Billy? **

Both new and experienced riders

**Where to Buy? **Local distributors or ships from the USA.

Genze 200 series e-Bike

genze-best-electric-bikes-scooters https://www.genze.com/fleet/

Featuring a sleek and lightweight aluminum frame design, the 200-Series ebike takes your riding experience to greater heights. Available in both black and white this ebike comes with a connected app, which allows you to plan activities, map distances and routes while also allowing connections with fellow riders.

Price: $2099.00

Available countries

The Genze 200 series e-Bike is available at GenZe retail locations across the U.S or online via GenZe.com website. Customers from outside the US can ship the product while incurring the relevant charges.

Features

  • 2 Frame Options
  • 2 Sizes
  • Integrated/Removable Battery
  • Throttle and Pedal Assist Ride Modes
  • Integrated LCD Display
  • Connected App
  • 24 month warranty
  • GPS navigation
  • Bluetooth connectivity

Specifications

  • Maximum speed: 20 mph with throttle
  • Range per charge: 15-18 miles w/ throttle and 30-50 miles w/ pedal assist
  • Charging time: 3.5 hours
  • Motor type: Brushless Rear Hub Motor
  • Gears: Microshift Thumb Shifter
  • Battery type: Removable Samsung 36V, 9.6AH Li-Ion battery pack
  • Battery capacity: 36V and 350 Wh
  • Weight: 46 pounds
  • Derailleur: 8-speed Shimano
  • Brakes: Dual classic
  • Wheels: 26 x 20 inches
  • Frame: 16, and 18 inches
  • Operating Mode: Analog mode 5 levels of Pedal Assist Thrott­le Mode

Norco from eBikestore

norco-best-electric-bikes-scooters https://ebikestore.com/shop/norco-vlt-s2/

The Norco VLT S2 is a front suspension e-Bike with solid components alongside the reliable Bosch Performance Line Power systems that offer precise pedal assistance during any riding situation.

Price: $2,699.00

Available countries

This item is available via the various Norco bikes international distributors.

Features

  • VLT aluminum frame- for stiffness and wheel security.
  • Bosch e-bike system – for their reliability and performance.
  • E-bike components – for added durability.
  • Hydraulic disc brakes – offer riders more stopping power for safety and control at higher speeds.
  • Practical design features – to add convenience and versatility.

Specifications

  • Maximum speed: KMC X9 9spd
  • Motor type: Bosch Active Line
  • Gears: Shimano Altus RD-M2000, SGS, 9 Speed
  • Battery type: Power Pack 400
  • Battery capacity: 396Wh
  • Suspension: SR Suntour suspension fork
  • Frame: Norco VLT, Aluminum, 12x142mm TA Dropouts

Bodo EV

bodo-best-electric-bikes-scootershttp://www.bodoevs.com/bodoev/products_show.asp?product_id=13

Manufactured by Bodo Vehicle Group Limited, the Bodo EV is specially designed for strong power and extraordinary long service to facilitate super amazing rides. The Bodo Vehicle Company is a striking top in electric vehicles brand field in China and across the globe. Their Bodo EV will no doubt provide your riders with high-level riding satisfaction owing to its high-quality design, strength, breaking stability and speed.

Price: $799

Available countries

This item ships from China with buyers bearing the shipping costs and other variables prior to delivery.

Features

  • Reliable
  • Environment friendly
  • Comfortable riding
  • Fashionable
  • Economical
  • Durable – long service life
  • Braking stability
  • LED lighting technology

Specifications

  • Maximum speed: 45km/h
  • Range per charge: 50km per person
  • Charging time: 8 hours
  • Maximum Power: 3000W
  • Motor type: Brushless DC Motor
  • Load capacity: 100kg
  • Battery type: Lead-acid battery
  • Battery capacity: 60V 20AH
  • Weight: w/o battery 47kg

#android app #autorent #entrepreneurship #ios app #minimum viable product (mvp) #mobile app development #news #app like bird #app like bounce #app like lime #autorent #best electric bikes 2020 #best electric bikes for rental business #best electric kick scooters 2020 #best electric kickscooters for rental business #best electric scooters 2020 #best electric scooters for rental business #bird scooter business model #bird scooter rental #bird scooter rental cost #bird scooter rental price #clone app like bird #clone app like bounce #clone app like lime #electric rental scooters #electric scooter company #electric scooter rental business #how do you start a moped #how to start a moped #how to start a scooter rental business #how to start an electric company #how to start electric scooterrental business #lime scooter business model #scooter franchise #scooter rental business #scooter rental business for sale #scooter rental business insurance #scooters franchise cost #white label app like bird #white label app like bounce #white label app like lime

Carmen  Grimes

Carmen Grimes

1595494844

How to start an electric scooter facility/fleet in a university campus/IT park

Are you leading an organization that has a large campus, e.g., a large university? You are probably thinking of introducing an electric scooter/bicycle fleet on the campus, and why wouldn’t you?

Introducing micro-mobility in your campus with the help of such a fleet would help the people on the campus significantly. People would save money since they don’t need to use a car for a short distance. Your campus will see a drastic reduction in congestion, moreover, its carbon footprint will reduce.

Micro-mobility is relatively new though and you would need help. You would need to select an appropriate fleet of vehicles. The people on your campus would need to find electric scooters or electric bikes for commuting, and you need to provide a solution for this.

To be more specific, you need a short-term electric bike rental app. With such an app, you will be able to easily offer micro-mobility to the people on the campus. We at Devathon have built Autorent exactly for this.

What does Autorent do and how can it help you? How does it enable you to introduce micro-mobility on your campus? We explain these in this article, however, we will touch upon a few basics first.

Micro-mobility: What it is

micro-mobility

You are probably thinking about micro-mobility relatively recently, aren’t you? A few relevant insights about it could help you to better appreciate its importance.

Micro-mobility is a new trend in transportation, and it uses vehicles that are considerably smaller than cars. Electric scooters (e-scooters) and electric bikes (e-bikes) are the most popular forms of micro-mobility, however, there are also e-unicycles and e-skateboards.

You might have already seen e-scooters, which are kick scooters that come with a motor. Thanks to its motor, an e-scooter can achieve a speed of up to 20 km/h. On the other hand, e-bikes are popular in China and Japan, and they come with a motor, and you can reach a speed of 40 km/h.

You obviously can’t use these vehicles for very long commutes, however, what if you need to travel a short distance? Even if you have a reasonable public transport facility in the city, it might not cover the route you need to take. Take the example of a large university campus. Such a campus is often at a considerable distance from the central business district of the city where it’s located. While public transport facilities may serve the central business district, they wouldn’t serve this large campus. Currently, many people drive their cars even for short distances.

As you know, that brings its own set of challenges. Vehicular traffic adds significantly to pollution, moreover, finding a parking spot can be hard in crowded urban districts.

Well, you can reduce your carbon footprint if you use an electric car. However, electric cars are still new, and many countries are still building the necessary infrastructure for them. Your large campus might not have the necessary infrastructure for them either. Presently, electric cars don’t represent a viable option in most geographies.

As a result, you need to buy and maintain a car even if your commute is short. In addition to dealing with parking problems, you need to spend significantly on your car.

All of these factors have combined to make people sit up and think seriously about cars. Many people are now seriously considering whether a car is really the best option even if they have to commute only a short distance.

This is where micro-mobility enters the picture. When you commute a short distance regularly, e-scooters or e-bikes are viable options. You limit your carbon footprints and you cut costs!

Businesses have seen this shift in thinking, and e-scooter companies like Lime and Bird have entered this field in a big way. They let you rent e-scooters by the minute. On the other hand, start-ups like Jump and Lyft have entered the e-bike market.

Think of your campus now! The people there might need to travel short distances within the campus, and e-scooters can really help them.

How micro-mobility can benefit you

benefits-micromobility

What advantages can you get from micro-mobility? Let’s take a deeper look into this question.

Micro-mobility can offer several advantages to the people on your campus, e.g.:

  • Affordability: Shared e-scooters are cheaper than other mass transportation options. Remember that the people on your campus will use them on a shared basis, and they will pay for their short commutes only. Well, depending on your operating model, you might even let them use shared e-scooters or e-bikes for free!
  • Convenience: Users don’t need to worry about finding parking spots for shared e-scooters since these are small. They can easily travel from point A to point B on your campus with the help of these e-scooters.
  • Environmentally sustainable: Shared e-scooters reduce the carbon footprint, moreover, they decongest the roads. Statistics from the pilot programs in cities like Portland and Denver showimpressive gains around this key aspect.
  • Safety: This one’s obvious, isn’t it? When people on your campus use small e-scooters or e-bikes instead of cars, the problem of overspeeding will disappear. you will see fewer accidents.

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ThruwayBundle: Bundle for Building Real-time Apps in Symfony

ThruwayBundle

This a Symfony Bundle for Thruway, which is a php implementation of WAMP (Web Application Messaging Protocol).

Note: This project is still undergoing a lot of changes, so the API will change.

Quick Start with Composer

Install the Thruway Bundle

  $ composer require "voryx/thruway-bundle"

Update AppKernel.php (when using Symfony < 4)

$bundles = array(
    // ...
    new Voryx\ThruwayBundle\VoryxThruwayBundle(),
    // ...
);

Configuration

#app/config/config.yml

voryx_thruway:
    realm: 'realm1'
    url: 'ws://127.0.0.1:8081' #The url that the clients will use to connect to the router
    router:
        ip: '127.0.0.1'  # the ip that the router should start on
        port: '8080'  # public facing port.  If authentication is enabled, this port will be protected
        trusted_port: '8081' # Bypasses all authentication.  Use this for trusted clients.
#        authentication: false # true will load the AuthenticationManager
    locations:
        bundles: ["AppBundle"]
#        files:
#            - "Acme\\DemoBundle\\Controller\\DemoController"
#
# For symfony 4, this bundle will automatically scan for annotated worker files in the src/Controller folder
      

With Symfony 4 use a filename like: config/packages/voryx.yaml

If you are using the in-memory user provider, you'll need to add a thruway to the security firewall and set the in_memory_user_provider.

#app/config/security.yml

security: 
   firewalls:
        thruway:
            security: false	     

You can also tag services with thruway.resource and any annotation will get picked up

<service id="some.service" class="Acme\Bundle\SomeService">
    <tag name="thruway.resource"/>
</service>

Note: tagging a service as thruway.resource will make it public.

services:
    App\Worker\:
        resource: '../src/Worker'
        tags: ['thruway.resource']

Authentication with FOSUserBundle via WampCRA

Change the Password Encoder (tricky on existing sites) to master wamp challenge

#app/config/security.yml

security:
    ...
    encoders:
        FOS\UserBundle\Model\UserInterface:
            algorithm:            pbkdf2
            hash_algorithm:       sha256
            encode_as_base64:     true
            iterations:           1000
            key_length:           32

set voryx_thruway.user_provider to "fos_user.user_provider"

#app/config/config.yml

voryx_thruway:
    user_provider: 'fos_user.user_provider.username' #fos_user.user_provider.username_email login with email

The WAMP-CRA service is already configured, we just need to add a tag to it to have the bundle install it:

    wamp_cra_auth:
        class: Thruway\Authentication\WampCraAuthProvider
        parent: voryx.thruway.wamp.cra.auth.client
        tags:
            - { name: thruway.internal_client }

Custom Authorization Manager

You can set your own Authorization Manager in order to check if a user (identified by its authid) is allowed to publish | subscribe | call | register

Create your Authorization Manager service, extending RouterModuleClient and implementing RealmModuleInterface (see the Thruway doc for details)

// src/ACME/AppBundle/Security/MyAuthorizationManager.php


use Thruway\Event\MessageEvent;
use Thruway\Event\NewRealmEvent;
use Thruway\Module\RealmModuleInterface;
use Thruway\Module\RouterModuleClient;

class MyAuthorizationManager extends RouterModuleClient implements RealmModuleInterface
{
    /**
     * Listen for Router events.
     * Required to add the authorization module to the realm
     *
     * @return array
     */
    public static function getSubscribedEvents()
    {
        return [
            'new_realm' => ['handleNewRealm', 10]
        ];
    }

    /**
     * @param NewRealmEvent $newRealmEvent
     */
    public function handleNewRealm(NewRealmEvent $newRealmEvent)
    {
        $realm = $newRealmEvent->realm;

        if ($realm->getRealmName() === $this->getRealm()) {
            $realm->addModule($this);
        }
    }

    /**
     * @return array
     */
    public function getSubscribedRealmEvents()
    {
        return [
            'PublishMessageEvent'   => ['authorize', 100],
            'SubscribeMessageEvent' => ['authorize', 100],
            'RegisterMessageEvent'  => ['authorize', 100],
            'CallMessageEvent'      => ['authorize', 100],
        ];
    }

    /**
     * @param MessageEvent $msg
     * @return bool
     */
    public function authorize(MessageEvent $msg)
    {
        if ($msg->session->getAuthenticationDetails()->getAuthId() === 'username') {
            return true;
        }
        return false;
    }
}

Register your authorization manager service

     my_authorization_manager:
        class: ACME\AppBundle\Security\MyAuthorizationManager

Insert your service name in the voryx_thruway config

#app/config/config.yml

voryx_thruway:
    ...
        authorization: my_authorization_manager # insert the name of your custom authorizationManager
   ...

Restart the Thruway server; it will now check authorization upon publish | subscribe | call | register. Remember to catch error when you try to subscribe to a topic (or any other action) as it may now be denied and this will be returned as an error.

Usage

Register RPC

    use Voryx\ThruwayBundle\Annotation\Register;
    
    /**
     *
     * @Register("com.example.add")
     *
     */
    public function addAction($num1, $num2)
    {
        return $num1 + $num2;
    }

Call RPC

    public function call($value)
    {
        $client = $this->container->get('thruway.client');
        $client->call("com.myapp.add", [2, 3])->then(
            function ($res) {
                echo $res[0];
            }
        );
    }

Subscribe

     use Voryx\ThruwayBundle\Annotation\Subscribe;

    /**
     *
     * @Subscribe("com.example.subscribe")
     *
     */
    public function subscribe($value)
    {
        echo $value;
    }

Publish

    public function publish($value)
    {
        $client = $this->container->get('thruway.client');
        $client->publish("com.myapp.hello_pubsub", [$value]);
    }

It uses Symfony Serializer, so it can serialize and deserialize Entities

         use Voryx\ThruwayBundle\Annotation\Register;

    /**
     *
     * @Register("com.example.addrpc", serializerEnableMaxDepthChecks=true)
     *
     */
    public function addAction(Post $post)
    {
        //Do something to $post

        return $post;
    }

Start the Thruway Process

You can start the default Thruway workers (router and client workers), without any additional configuration.

$ nohup php app/console thruway:process start &

By default, the router starts on ws://127.0.0.1:8080

Workers

The Thruway bundle will start up a separate process for the router and each defined worker. If you haven't defined any workers, all of the annotated calls and subscriptions will be started within the default worker.

There are two main ways to break your application apart into multiple workers.

Use the worker property on the Register and Subscribe annotations. The following RPC will be added to the posts worker.

  use Voryx\ThruwayBundle\Annotation\Register;

  /**
  * @Register("com.example.addrpc", serializerEnableMaxDepthChecks=true, worker="posts")
  */
  public function addAction(Post $post)

Use the @Worker annotation on the class. The following annotation will create a worker called chat that can have a max of 5 instances.

  use Voryx\ThruwayBundle\Annotation\Worker;

  /**
  * @Worker("chat", maxProcesses="5")
  */
  class ChatController

If a worker is shut down with anything other than SIGTERM, it will automatically be restarted.

More Commands

To see a list of running processes (workers)

$ php app/console thruway:process status

Stop a process, i.e. default

$ php app/console thruway:process stop default

Start a process, i.e. default

$ php app/console thruway:process start default

Javascript Client

For the client, you can use AutobahnJS or any other WAMPv2 compatible client.

Here are some examples

Symfony 4 Quick Start

composer create-project symfony/skeleton my_project
cd my_project
composer require symfony/expression-language
composer require symfony/annotations-pack
composer require voryx/thruway-bundle:dev-master

Create config/packages/my_project.yml with the following config:

voryx_thruway:
    realm: 'realm1'
    url: 'ws://127.0.0.1:8081' #The url that the clients will use to connect to the router
    router:
        ip: '127.0.0.1'  # the ip that the router should start on
        port: '8080'  # public facing port.  If authentication is enabled, this port will be protected
        trusted_port: '8081' # Bypasses all authentication.  Use this for trusted clients.

Create the controller src/Controller/TestController.php

<?php
namespace App\Controller;

use Voryx\ThruwayBundle\Annotation\Register;

class TestController
{
    /**
     * @Register("com.example.add")
     */
    public function addAction($num1, $num2)
    {
        return $num1 + $num2;
    }
}

Test to see if the RPC has been configured correctly bin/console thruway:debug

 URI             Type Worker  File                                                  Method    
 com.example.add RPC  default /my_project/src/Controller/TestController.php         addAction 

For more debug info for the RPC we created: bin/console thruway:debug com.example.add

Start everything: bin/console thruway:process start

The RPC com.example.add is now available to any WAMP client connected to ws://127.0.0.1:8081 on realm1.

Author: Voryx
Source Code: https://github.com/voryx/ThruwayBundle 
License: 

#php #symfony