Use Apache Avro IPC framework to implement actual combat teaching for distributed data processing

Use Apache Avro IPC framework to implement actual combat tutorials for distributed data processing Apache Avro is a high -performance, data serialization and remote process call (RPC) framework.It supports the static and dynamic types of data, and has good cross -language compatibility.In this tutorial, how to use the AVRO IPC framework for distributed data processing.We will use Java as example language to write code. Environment settings: First, let's set up a development environment.You need to use the following tools and libraries: 1. JDK (Java Development Tool Pack) 2. Apache Avro Library 3. Apache Maven Construction Tool (optional) Step 1: Define data mode First, we need to define the data of the data.In Avro, we use Avro mode to define the data structure.The following is the AVRO definition of a sample data mode (stored in the `.avsc` file): json { "type": "record", "name": "UserData", "fields": [ {"name": "id", "type": "int"}, {"name": "name", "type": "string"}, {"name": "age", "type": "int"} ] } The above mode defines a record type called `userdata`, which contains the fields of` ID` (integer type), `name` (string type), and` Age` (integer type) field. Step 2: Generate code Next, we need to use the AVRO tool to generate the Java class.In the command line terminal, execute the following command: shell $ java -jar avro-tools-1.10.2.jar compile schema <schema-file> <output-directory> In the above commands, replace the `SCHEMA-FILE>` to the path of the `.avsc` file defined by the above mode, and replaced the` Output-Directory> `` `` `` `` ` For example, if we name the pattern file `user.avsc`, run the command in the current directory (` .`): shell $ java -jar avro-tools-1.10.2.jar compile schema user.avsc . This will generate a Java class used to process the `userdata` type, such as` userdata.java`. Step 3: Create producers and consumers Now, let's create a simple producer and consumer application to demonstrate the use of the AVRO IPC framework.First, let's create a producer responsible for sending data to the remote server. import org.apache.avro.ipc.NettyTransceiver; import org.apache.avro.ipc.specific.SpecificRequestor; import org.apache.avro.ipc.specific.SpecificResponder; import org.apache.avro.protocol.Protocol; import org.apache.avro.util.Utf8; import example.avro.UserData; import java.io.IOException; import java.net.InetSocketAddress; public class AvroProducer { public static void main(String[] args) throws IOException { // Definition protocol Protocol protocol = Protocol.parse(new File("user.avpr")); // Create a transmitter NettyTransceiver client = new NettyTransceiver(new InetSocketAddress("localhost", 9090)); // Create a requestant SpecificRequestor requestor = new SpecificRequestor(protocol, client); // Create request data UserData userData = new UserData(); userData.setId(1); userData.setName(new Utf8("Alice")); userData.setAge(25); // send request UserData receivedData = (UserData) requestor.request("process", userData); System.out.println("Received data: " + receivedData); // Turn off the transmitter client.close(); } } In the above code, we use the `Nettytransceiver` to build a connection with the remote server, and then use the` SpecificRequestor` to construct a requestant.We create an `UserData" object as the input data, and send it to the server to send it to the server by calling the `Request` method. We also need to create a consumer to receive and process requests on the server. import org.apache.avro.ipc.Responder; import org.apache.avro.ipc.netty.NettyServer; import org.apache.avro.ipc.specific.SpecificRequestor; import org.apache.avro.ipc.specific.SpecificResponder; import org.apache.avro.protocol.Protocol; import org.apache.avro.util.Utf8; import example.avro.UserData; import java.io.IOException; public class AvroConsumer { public static void main(String[] args) throws IOException { // Definition protocol Protocol protocol = Protocol.parse(new File("user.avpr")); // Create a requestant SpecificResponder responder = new SpecificResponder(protocol) { @Override public Object respond(Protocol.Message message, Object request) { // Process request UserData requestData = (UserData) request; System.out.println("Received request data: " + requestData); // Return to response data UserData responseData = new UserData(); responseData.setId(requestData.getId()); responseData.setName(new Utf8("Hello, " + requestData.getName())); responseData.setAge(requestData.getAge() + 1); return responseData; } }; // Create a server NettyServer server = new NettyServer(responder, new InetSocketAddress(9090)); server.start(); } } In the above code, we use the `SpecificResponder` to implement a function to process requests.By obtaining the `UserData` object from the request, we output the object and create a response for it. Step 4: Run the application Now, we have completed the writing of producers and consumers.You can run these two applications as clients and servers. First, run consumer applications (server): shell $ java AvroConsumer Then, operate producer application (client): shell $ java AvroProducer You will see that consumer applications output the request data received on the terminal and return the response data to the producer application. in conclusion: This tutorial shows you how to use the Apache Avro IPC framework to achieve distributed data processing.We first define the data mode and then generate the Java class in the processing mode.Then, we created a producer application that sends data to the server and a consumer application for receiving and processing data.Using the AVRO IPC framework, you can easily interact with cross -language data and simplify data processing in distributed systems.