jmeter grpc 自定义开发java请求案例

1.主要实现方法是借助JavaSamplerClient 实现接口：

import org.apache.jmeter.config.Arguments;
import org.apache.jmeter.protocol.java.sampler.JavaSamplerClient;
import org.apache.jmeter.protocol.java.sampler.JavaSamplerContext;
import org.apache.jmeter.samplers.SampleResult;


以下main注释的方法主要用于本地调试接口，setup主要实现前置操作，构造初始数据，runTest主要实现接口调用和返回

public class ClientPredictGrpc implements  JavaSamplerClient {
    private static final Logger logger = LoggerFactory.getLogger(ClientPredictGrpc.class);
    private int port ;
    private String ip ;
    private BatchInferenceRequest batchInferenceRequest;
    @Override
    public void setupTest(JavaSamplerContext ctx) {
            String serviceId = ctx.getParameter("serviceId");
            String userId = ctx.getParameter("userId");
            Random random =new Random();
            this.ip=ctx.getParameter("ip");
            this.port =ctx.getIntParameter("port");
            int columns = ctx.getIntParameter("featureCols");
            int uidNumber = ctx.getIntParameter("batchSize");
            this.batchInferenceRequest =new BatchInferenceRequest();
            this.batchInferenceRequest.setServiceId(serviceId);
            this.batchInferenceRequest.setCaseId(Long.toString(System.currentTimeMillis()));
            List<BatchInferenceRequest.SingleInferenceData> singleInferenceDataList = Lists.newArrayList();
            BatchInferenceRequest.SingleInferenceData singleInferenceData =new BatchInferenceRequest.SingleInferenceData() ;
            //todo set batch list the same batchList data each batch request
            for (int j = 0; j< columns; j++){
                String featureColumnName=String.format("x%d",j);
                singleInferenceData.getFeatureData().put(featureColumnName, random.nextInt(2));
            }
            for (int i = 0; i < uidNumber; i++) {
                Map<String,Object> uidMap=new HashMap<>();
                uidMap.put("user_id", userId);
                singleInferenceData.getSendToRemoteFeatureData().putAll(uidMap);
                singleInferenceData.setIndex(i);
                singleInferenceDataList.add(singleInferenceData);
            }
            this.batchInferenceRequest.setBatchDataList(singleInferenceDataList);

    }

    @Override
    public SampleResult runTest(JavaSamplerContext ctx) {
        SampleResult result= new SampleResult();
        result.sampleStart();
        try {
            JSONObject jsonObject= ClientGrpc.call(this.ip,this.port,this.batchInferenceRequest);
            if (jsonObject.get("retcode") == null || !jsonObject.getString("retcode").equals(InferenceRetCode.OK)){
                if (jsonObject.get("retcode") == null){
                    result.setSuccessful(false);
                    result.setResponseData(jsonObject.toJSONString(),"utf-8");
                    result.setResponseCode("retcode is null ");
                }else {
                    result.setResponseData(jsonObject.toJSONString(), "utf-8");
                    result.setDataType(SampleResult.TEXT);
                    result.setSuccessful(false);
                    result.setResponseMessage("failed");
                    result.setResponseCode(jsonObject.getString("retcode"));
                }
            }else{
                result.setResponseData(jsonObject.toJSONString(),"utf-8");
                result.setDataType(SampleResult.TEXT);
                result.setSuccessful(true);
                result.setResponseMessage("success");
                result.setResponseCode("0");
            }
        }catch (Exception e){
            result.setSuccessful(false);
            if(e.getMessage() !=null) {
                result.setResponseData(e.getMessage(), null);
                result.setResponseCode("grpc exception");
            }
        }finally {
            result.sampleEnd();
        }

        //logger.info("result finally get as String is : "+ result.getResponseDataAsString());
        return result;
    }

    @Override
    public void teardownTest(JavaSamplerContext ctx) {

    }

    @Override
    public Arguments getDefaultParameters() {
        Arguments arguments =new Arguments();
        arguments.addArgument("ip","");
        arguments.addArgument("port","");
        arguments.addArgument("featureCols","");
        arguments.addArgument("userId","");
        arguments.addArgument("serviceId","");
        arguments.addArgument("batchSize","");
        return arguments;
    }

//    public static void main(String[] args) {
//        ClientPredictGrpc demo=new ClientPredictGrpc();
//        Arguments arguments = new Arguments();
//        String uid="a36fda4444dbdfdb1714c81e86b13c06,a46458c10546bbe794dbca88cd0a4832";
//
//        arguments.addArgument("ip","172.16.153.119");
//        arguments.addArgument("port","8000");
//        arguments.addArgument("header","5");
//        arguments.addArgument("userId",uid);
//        arguments.addArgument("serviceId","heterolr01");
//        JavaSamplerContext ctx=new JavaSamplerContext(arguments);
//        demo.setupTest(ctx);
//        demo.runTest(ctx);
//        demo.teardownTest(ctx);


//    }


}

　　

grpc client类：

public class ClientGrpc {

    private static Random random = new Random();

    private static GrpcConnectionPool GRPC_CONNECTION_POOL = GrpcConnectionPool.getPool();
    public static ManagedChannel createManagedChannel(String ip, int port) throws Exception {

        return GRPC_CONNECTION_POOL.getManagedChannel(ip, port);

    }

    static JSONObject call(String ip,int port,BatchInferenceRequest batchInferenceRequest) {
            JSONObject predictMessage=null;
            ManagedChannel managedChannel = null;
            try {
                managedChannel = createManagedChannel(ip, port);
                InferenceServiceProto.InferenceMessage.Builder inferenceMessageBuilder = InferenceServiceProto.InferenceMessage.newBuilder();
                inferenceMessageBuilder.setBody(ByteString.copyFrom(JSON.toJSONString(batchInferenceRequest), "UTF-8"));
                InferenceServiceGrpc.InferenceServiceBlockingStub blockingStub = InferenceServiceGrpc.newBlockingStub(managedChannel);
                InferenceServiceProto.InferenceMessage inferenceMessage = blockingStub.batchInference(inferenceMessageBuilder.build());
                String result = new String(inferenceMessage.getBody().toByteArray());
                predictMessage = JSONObject.parseObject(result);


            } catch (Exception e) {
                e.printStackTrace();
            }
            return predictMessage;
    }



}