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Example 11 with WorkerId

use of com.tencent.angel.worker.WorkerId in project angel by Tencent.

the class MasterServiceTest method testMasterService.

@Test
public void testMasterService() throws Exception {
    try {
        LOG.info("===========================testMasterService===============================");
        Worker worker = LocalClusterContext.get().getWorker(worker0Attempt0Id).getWorker();
        Location masterLoc = LocalClusterContext.get().getMaster().getAppMaster().getAppContext().getMasterService().getLocation();
        TConnection connection = TConnectionManager.getConnection(worker.getConf());
        MasterProtocol master = connection.getMasterService(masterLoc.getIp(), masterLoc.getPort());
        int psAgentId = master.getPSAgentId(null, PSAgentMasterServiceProtos.GetPSAgentIdRequest.getDefaultInstance()).getPsAgentId();
        // worker register
        WorkerAttemptId worker1Attempt0Id = new WorkerAttemptId(new WorkerId(new WorkerGroupId(1), 0), 0);
        WorkerRegisterRequest registeRequest = WorkerRegisterRequest.newBuilder().setPsAgentId(psAgentId).setWorkerAttemptId(ProtobufUtil.convertToIdProto(worker1Attempt0Id)).setLocation(LocationProto.newBuilder().setIp("0.0.0.0").setPort(10000).build()).build();
        WorkerRegisterResponse registerResponse = master.workerRegister(null, registeRequest);
        assertTrue(registerResponse.getCommand() == WorkerCommandProto.W_SHUTDOWN);
        WorkerReportRequest.Builder reportBuilder = WorkerReportRequest.newBuilder();
        Pair.Builder kvBuilder = Pair.newBuilder();
        TaskStateProto.Builder taskBuilder = TaskStateProto.newBuilder();
        reportBuilder.setWorkerAttemptId(ProtobufUtil.convertToIdProto(worker0Attempt0Id));
        taskBuilder.setProgress(0.20f);
        taskBuilder.setState("RUNNING");
        taskBuilder.setTaskId(ProtobufUtil.convertToIdProto(task0Id));
        kvBuilder.setKey("task_key1");
        kvBuilder.setValue("100");
        taskBuilder.addCounters(kvBuilder.build());
        kvBuilder.setKey("task_key2");
        kvBuilder.setValue("200");
        taskBuilder.addCounters(kvBuilder.build());
        reportBuilder.addTaskReports(taskBuilder.build());
        taskBuilder.setProgress(0.30f);
        taskBuilder.setState("RUNNING");
        taskBuilder.setTaskId(ProtobufUtil.convertToIdProto(task1Id));
        kvBuilder.setKey("task_key1");
        kvBuilder.setValue("1000");
        taskBuilder.addCounters(kvBuilder.build());
        kvBuilder.setKey("task_key2");
        kvBuilder.setValue("2000");
        taskBuilder.addCounters(kvBuilder.build());
        reportBuilder.addTaskReports(taskBuilder.build());
        kvBuilder.setKey("worker_key1");
        kvBuilder.setValue("100");
        reportBuilder.addPairs(kvBuilder.build());
        kvBuilder.setKey("worker_key2");
        kvBuilder.setValue("200");
        reportBuilder.addPairs(kvBuilder.build());
        WorkerReportResponse reportResponse = master.workerReport(null, reportBuilder.build());
        assertTrue(reportResponse.getCommand() == WorkerCommandProto.W_SUCCESS);
        assertEquals(reportResponse.getActiveTaskNum(), 2);
        AngelApplicationMaster angelAppMaster = LocalClusterContext.get().getMaster().getAppMaster();
        WorkerAttempt worker0Attempt = angelAppMaster.getAppContext().getWorkerManager().getWorker(worker0Attempt0Id.getWorkerId()).getWorkerAttempt(worker0Attempt0Id);
        assertTrue(worker0Attempt != null);
        Map<String, String> workerMetrics = worker0Attempt.getMetrics();
        String valueForWorkerKey1 = workerMetrics.get("worker_key1");
        String valueForWorkerKey2 = workerMetrics.get("worker_key2");
        assertNotNull(valueForWorkerKey1);
        assertNotNull(valueForWorkerKey2);
        assertEquals(valueForWorkerKey1, "100");
        assertEquals(valueForWorkerKey2, "200");
        AMTaskManager amTaskManager = angelAppMaster.getAppContext().getTaskManager();
        AMTask task0 = amTaskManager.getTask(task0Id);
        AMTask task1 = amTaskManager.getTask(task1Id);
        assertTrue(task0 != null);
        assertTrue(task1 != null);
        Map<String, String> task0Metrics = task0.getMetrics();
        Map<String, String> task1Metrics = task1.getMetrics();
        String valueForTask0Key1 = task0Metrics.get("task_key1");
        String valueForTask0Key2 = task0Metrics.get("task_key2");
        String valueForTask1Key1 = task1Metrics.get("task_key1");
        String valueForTask1Key2 = task1Metrics.get("task_key2");
        assertTrue(valueForTask0Key1 != null);
        assertTrue(valueForTask0Key2 != null);
        assertTrue(valueForTask1Key1 != null);
        assertTrue(valueForTask1Key2 != null);
        assertEquals(valueForTask0Key1, "100");
        assertEquals(valueForTask0Key2, "200");
        assertEquals(valueForTask1Key1, "1000");
        assertEquals(valueForTask1Key2, "2000");
        assertEquals(task0.getProgress(), 0.20f, 0.000001);
        assertEquals(task1.getProgress(), 0.30f, 0.000001);
    } catch (Exception x) {
        LOG.error("run testMasterService failed ", x);
        throw x;
    }
}
Also used : WorkerAttemptId(com.tencent.angel.worker.WorkerAttemptId) WorkerId(com.tencent.angel.worker.WorkerId) WorkerGroupId(com.tencent.angel.worker.WorkerGroupId) TConnection(com.tencent.angel.ipc.TConnection) AMTaskManager(com.tencent.angel.master.task.AMTaskManager) Worker(com.tencent.angel.worker.Worker) WorkerAttempt(com.tencent.angel.master.worker.attempt.WorkerAttempt) AMTask(com.tencent.angel.master.task.AMTask) Location(com.tencent.angel.common.location.Location) Pair(com.tencent.angel.protobuf.generated.MLProtos.Pair) Test(org.junit.Test)

Example 12 with WorkerId

use of com.tencent.angel.worker.WorkerId in project angel by Tencent.

the class PSManagerTest method setup.

@Before
public void setup() throws Exception {
    try {
        // set basic configuration keys
        Configuration conf = new Configuration();
        conf.setBoolean("mapred.mapper.new-api", true);
        conf.setBoolean(AngelConf.ANGEL_JOB_OUTPUT_PATH_DELETEONEXIST, true);
        conf.set(AngelConf.ANGEL_TASK_USER_TASKCLASS, DummyTask.class.getName());
        // use local deploy mode and dummy dataspliter
        conf.set(AngelConf.ANGEL_DEPLOY_MODE, "LOCAL");
        conf.setBoolean(AngelConf.ANGEL_AM_USE_DUMMY_DATASPLITER, true);
        conf.set(AngelConf.ANGEL_INPUTFORMAT_CLASS, CombineTextInputFormat.class.getName());
        conf.set(AngelConf.ANGEL_SAVE_MODEL_PATH, LOCAL_FS + TMP_PATH + "/out");
        conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, LOCAL_FS + TMP_PATH + "/in");
        conf.set(AngelConf.ANGEL_LOG_PATH, LOCAL_FS + TMP_PATH + "/log");
        conf.setInt(AngelConf.ANGEL_WORKERGROUP_NUMBER, 1);
        conf.setInt(AngelConf.ANGEL_PS_NUMBER, 1);
        conf.setInt(AngelConf.ANGEL_WORKER_TASK_NUMBER, 2);
        conf.setInt(AngelConf.ANGEL_PS_BACKUP_INTERVAL_MS, 1000);
        conf.setInt(AngelConf.ANGEL_WORKER_HEARTBEAT_INTERVAL_MS, 1000);
        conf.setInt(AngelConf.ANGEL_PS_HEARTBEAT_INTERVAL_MS, 1000);
        // get a angel client
        angelClient = AngelClientFactory.get(conf);
        // add matrix
        MatrixContext mMatrix = new MatrixContext();
        mMatrix.setName("w1");
        mMatrix.setRowNum(1);
        mMatrix.setColNum(100000);
        mMatrix.setMaxRowNumInBlock(1);
        mMatrix.setMaxColNumInBlock(50000);
        mMatrix.setRowType(RowType.T_INT_DENSE);
        mMatrix.set(MatrixConf.MATRIX_OPLOG_ENABLEFILTER, "false");
        mMatrix.set(MatrixConf.MATRIX_HOGWILD, "true");
        mMatrix.set(MatrixConf.MATRIX_AVERAGE, "false");
        angelClient.addMatrix(mMatrix);
        MatrixContext mMatrix2 = new MatrixContext();
        mMatrix2.setName("w2");
        mMatrix2.setRowNum(1);
        mMatrix2.setColNum(100000);
        mMatrix2.setMaxRowNumInBlock(1);
        mMatrix2.setMaxColNumInBlock(50000);
        mMatrix2.setRowType(RowType.T_DOUBLE_DENSE);
        mMatrix2.set(MatrixConf.MATRIX_OPLOG_ENABLEFILTER, "false");
        mMatrix2.set(MatrixConf.MATRIX_HOGWILD, "false");
        mMatrix2.set(MatrixConf.MATRIX_AVERAGE, "false");
        angelClient.addMatrix(mMatrix2);
        angelClient.startPSServer();
        angelClient.run();
        Thread.sleep(5000);
        group0Id = new WorkerGroupId(0);
        worker0Id = new WorkerId(group0Id, 0);
        worker0Attempt0Id = new WorkerAttemptId(worker0Id, 0);
        task0Id = new TaskId(0);
        task1Id = new TaskId(1);
        psId = new ParameterServerId(0);
        psAttempt0Id = new PSAttemptId(psId, 0);
    } catch (Exception x) {
        LOG.error("setup failed ", x);
        throw x;
    }
}
Also used : CombineTextInputFormat(org.apache.hadoop.mapreduce.lib.input.CombineTextInputFormat) MatrixContext(com.tencent.angel.ml.matrix.MatrixContext) TaskId(com.tencent.angel.worker.task.TaskId) Configuration(org.apache.hadoop.conf.Configuration) PSAttemptId(com.tencent.angel.ps.PSAttemptId) WorkerAttemptId(com.tencent.angel.worker.WorkerAttemptId) WorkerId(com.tencent.angel.worker.WorkerId) ParameterServerId(com.tencent.angel.ps.ParameterServerId) AngelException(com.tencent.angel.exception.AngelException) WorkerGroupId(com.tencent.angel.worker.WorkerGroupId) Before(org.junit.Before)

Example 13 with WorkerId

use of com.tencent.angel.worker.WorkerId in project angel by Tencent.

the class IncrementRowTest method setup.

@Before
public void setup() throws Exception {
    // set basic configuration keys
    Configuration conf = new Configuration();
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean(AngelConf.ANGEL_JOB_OUTPUT_PATH_DELETEONEXIST, true);
    conf.set(AngelConf.ANGEL_TASK_USER_TASKCLASS, DummyTask.class.getName());
    // use local deploy mode and dummy dataspliter
    conf.set(AngelConf.ANGEL_DEPLOY_MODE, "LOCAL");
    conf.setBoolean(AngelConf.ANGEL_AM_USE_DUMMY_DATASPLITER, true);
    conf.set(AngelConf.ANGEL_INPUTFORMAT_CLASS, CombineTextInputFormat.class.getName());
    conf.set(AngelConf.ANGEL_SAVE_MODEL_PATH, LOCAL_FS + TMP_PATH + "/out");
    conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, LOCAL_FS + TMP_PATH + "/in");
    conf.set(AngelConf.ANGEL_LOG_PATH, LOCAL_FS + TMP_PATH + "/log");
    conf.setInt(AngelConf.ANGEL_WORKERGROUP_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_PS_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_WORKER_TASK_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_MODEL_PARTITIONER_PARTITION_SIZE, 1000);
    conf.setInt(AngelConf.ANGEL_PSAGENT_CACHE_SYNC_TIMEINTERVAL_MS, 10);
    conf.setInt(AngelConf.ANGEL_WORKER_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setInt(AngelConf.ANGEL_PS_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setBoolean("use.new.split", true);
    conf.setInt(AngelConf.ANGEL_WORKER_MAX_ATTEMPTS, 1);
    conf.setInt(AngelConf.ANGEL_PS_MAX_ATTEMPTS, 1);
    // get a angel client
    angelClient = AngelClientFactory.get(conf);
    // add dense double matrix
    MatrixContext dMat = new MatrixContext();
    dMat.setName(DENSE_DOUBLE_MAT);
    dMat.setRowNum(1);
    dMat.setColNum(feaNum);
    dMat.setMaxColNumInBlock(feaNum / 100);
    dMat.setRowType(RowType.T_DOUBLE_DENSE);
    dMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dMat);
    // add sparse double matrix
    MatrixContext sMat = new MatrixContext();
    sMat.setName(SPARSE_DOUBLE_MAT);
    sMat.setRowNum(1);
    sMat.setColNum(feaNum);
    sMat.setMaxColNumInBlock(feaNum / 100);
    sMat.setRowType(RowType.T_DOUBLE_SPARSE);
    angelClient.addMatrix(sMat);
    // add dense float matrix
    MatrixContext dfMat = new MatrixContext();
    dfMat.setName(DENSE_FLOAT_MAT);
    dfMat.setRowNum(1);
    dfMat.setColNum(feaNum);
    dfMat.setMaxColNumInBlock(feaNum / 3);
    dfMat.setRowType(RowType.T_FLOAT_DENSE);
    dfMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dfMat);
    // add sparse float matrix
    MatrixContext sfMat = new MatrixContext();
    sfMat.setName(SPARSE_FLOAT_MAT);
    sfMat.setRowNum(1);
    sfMat.setColNum(feaNum);
    sfMat.setMaxColNumInBlock(feaNum / 3);
    sfMat.setRowType(RowType.T_FLOAT_SPARSE);
    angelClient.addMatrix(sfMat);
    // add dense float matrix
    MatrixContext diMat = new MatrixContext();
    diMat.setName(DENSE_INT_MAT);
    diMat.setRowNum(1);
    diMat.setColNum(feaNum);
    diMat.setMaxColNumInBlock(feaNum / 3);
    diMat.setRowType(RowType.T_INT_DENSE);
    diMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(diMat);
    // add sparse float matrix
    MatrixContext siMat = new MatrixContext();
    siMat.setName(SPARSE_INT_MAT);
    siMat.setRowNum(1);
    siMat.setColNum(feaNum);
    siMat.setMaxColNumInBlock(feaNum / 3);
    siMat.setRowType(RowType.T_INT_SPARSE);
    angelClient.addMatrix(siMat);
    // add dense long matrix
    MatrixContext dlMat = new MatrixContext();
    dlMat.setName(DENSE_LONG_MAT);
    dlMat.setRowNum(1);
    dlMat.setColNum(feaNum);
    dlMat.setMaxColNumInBlock(feaNum / 3);
    dlMat.setRowType(RowType.T_LONG_DENSE);
    dlMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dlMat);
    // add sparse long matrix
    MatrixContext slMat = new MatrixContext();
    slMat.setName(SPARSE_LONG_MAT);
    slMat.setRowNum(1);
    slMat.setColNum(feaNum);
    slMat.setMaxColNumInBlock(feaNum / 3);
    slMat.setRowType(RowType.T_LONG_SPARSE);
    angelClient.addMatrix(slMat);
    // add sparse long-key double matrix
    MatrixContext dLongKeysMatrix = new MatrixContext();
    dLongKeysMatrix.setName(SPARSE_DOUBLE_LONG_MAT);
    dLongKeysMatrix.setRowNum(1);
    dLongKeysMatrix.setColNum(feaNum);
    dLongKeysMatrix.setMaxColNumInBlock(feaNum / 3);
    dLongKeysMatrix.setRowType(RowType.T_DOUBLE_SPARSE_LONGKEY);
    angelClient.addMatrix(dLongKeysMatrix);
    // add sparse long-key float matrix
    MatrixContext slfMatrix = new MatrixContext();
    slfMatrix.setName(SPARSE_FLOAT_LONG_MAT);
    slfMatrix.setRowNum(1);
    slfMatrix.setColNum(feaNum);
    slfMatrix.setMaxColNumInBlock(feaNum / 3);
    slfMatrix.setRowType(RowType.T_FLOAT_SPARSE_LONGKEY);
    angelClient.addMatrix(slfMatrix);
    // add sparse long-key int matrix
    MatrixContext sliMatrix = new MatrixContext();
    sliMatrix.setName(SPARSE_INT_LONG_MAT);
    sliMatrix.setRowNum(1);
    sliMatrix.setColNum(feaNum);
    sliMatrix.setMaxColNumInBlock(feaNum / 3);
    sliMatrix.setRowType(RowType.T_INT_SPARSE_LONGKEY);
    angelClient.addMatrix(sliMatrix);
    // add sparse long-key long matrix
    MatrixContext sllMatrix = new MatrixContext();
    sllMatrix.setName(SPARSE_LONG_LONG_MAT);
    sllMatrix.setRowNum(1);
    sllMatrix.setColNum(feaNum);
    sllMatrix.setMaxColNumInBlock(feaNum / 3);
    sllMatrix.setRowType(RowType.T_LONG_SPARSE_LONGKEY);
    angelClient.addMatrix(sllMatrix);
    // Start PS
    angelClient.startPSServer();
    // Start to run application
    angelClient.run();
    Thread.sleep(5000);
    psId = new ParameterServerId(0);
    psAttempt0Id = new PSAttemptId(psId, 0);
    WorkerGroupId workerGroupId = new WorkerGroupId(0);
    workerId = new WorkerId(workerGroupId, 0);
    workerAttempt0Id = new WorkerAttemptId(workerId, 0);
}
Also used : CombineTextInputFormat(org.apache.hadoop.mapreduce.lib.input.CombineTextInputFormat) MatrixContext(com.tencent.angel.ml.matrix.MatrixContext) Configuration(org.apache.hadoop.conf.Configuration) PSAttemptId(com.tencent.angel.ps.PSAttemptId) WorkerAttemptId(com.tencent.angel.worker.WorkerAttemptId) ParameterServerId(com.tencent.angel.ps.ParameterServerId) WorkerId(com.tencent.angel.worker.WorkerId) WorkerGroupId(com.tencent.angel.worker.WorkerGroupId) Before(org.junit.Before)

Example 14 with WorkerId

use of com.tencent.angel.worker.WorkerId in project angel by Tencent.

the class IndexGetRowTest method setup.

@Before
public void setup() throws Exception {
    // set basic configuration keys
    Configuration conf = new Configuration();
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean(AngelConf.ANGEL_JOB_OUTPUT_PATH_DELETEONEXIST, true);
    conf.set(AngelConf.ANGEL_TASK_USER_TASKCLASS, DummyTask.class.getName());
    // use local deploy mode and dummy dataspliter
    conf.set(AngelConf.ANGEL_DEPLOY_MODE, "LOCAL");
    conf.setBoolean(AngelConf.ANGEL_AM_USE_DUMMY_DATASPLITER, true);
    conf.set(AngelConf.ANGEL_INPUTFORMAT_CLASS, CombineTextInputFormat.class.getName());
    conf.set(AngelConf.ANGEL_SAVE_MODEL_PATH, LOCAL_FS + TMP_PATH + "/out");
    conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, LOCAL_FS + TMP_PATH + "/in");
    conf.set(AngelConf.ANGEL_LOG_PATH, LOCAL_FS + TMP_PATH + "/log");
    conf.setInt(AngelConf.ANGEL_WORKERGROUP_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_PS_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_WORKER_TASK_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_MODEL_PARTITIONER_PARTITION_SIZE, 100000);
    conf.setInt(AngelConf.ANGEL_PSAGENT_CACHE_SYNC_TIMEINTERVAL_MS, 10);
    conf.setInt(AngelConf.ANGEL_WORKER_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setInt(AngelConf.ANGEL_PS_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setInt(AngelConf.ANGEL_WORKER_MAX_ATTEMPTS, 1);
    conf.setInt(AngelConf.ANGEL_PS_MAX_ATTEMPTS, 1);
    // get a angel client
    angelClient = AngelClientFactory.get(conf);
    // add dense double matrix
    MatrixContext dMat = new MatrixContext();
    dMat.setName(DENSE_DOUBLE_MAT);
    dMat.setRowNum(1);
    dMat.setColNum(feaNum);
    dMat.setMaxColNumInBlock(feaNum / 3);
    dMat.setRowType(RowType.T_DOUBLE_DENSE);
    dMat.setValidIndexNum(modelSize);
    dMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dMat);
    // add sparse double matrix
    MatrixContext sMat = new MatrixContext();
    sMat.setName(SPARSE_DOUBLE_MAT);
    sMat.setRowNum(1);
    sMat.setColNum(feaNum);
    sMat.setMaxColNumInBlock(feaNum / 3);
    sMat.setRowType(RowType.T_DOUBLE_SPARSE);
    sMat.setValidIndexNum(modelSize);
    sMat.setPartitionNum(partNum);
    sMat.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sMat);
    // add dense float matrix
    MatrixContext dfMat = new MatrixContext();
    dfMat.setName(DENSE_FLOAT_MAT);
    dfMat.setRowNum(1);
    dfMat.setColNum(feaNum);
    dfMat.setMaxColNumInBlock(feaNum / 3);
    dfMat.setRowType(RowType.T_FLOAT_DENSE);
    dfMat.setValidIndexNum(modelSize);
    dfMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dfMat);
    // add sparse float matrix
    MatrixContext sfMat = new MatrixContext();
    sfMat.setName(SPARSE_FLOAT_MAT);
    sfMat.setRowNum(1);
    sfMat.setColNum(feaNum);
    sfMat.setMaxColNumInBlock(feaNum / 3);
    sfMat.setRowType(RowType.T_FLOAT_SPARSE);
    sfMat.setValidIndexNum(modelSize);
    sfMat.setPartitionNum(partNum);
    sfMat.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sfMat);
    // add dense float matrix
    MatrixContext diMat = new MatrixContext();
    diMat.setName(DENSE_INT_MAT);
    diMat.setRowNum(1);
    diMat.setColNum(feaNum);
    diMat.setMaxColNumInBlock(feaNum / 3);
    diMat.setRowType(RowType.T_INT_DENSE);
    diMat.setValidIndexNum(modelSize);
    diMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(diMat);
    // add sparse float matrix
    MatrixContext siMat = new MatrixContext();
    siMat.setName(SPARSE_INT_MAT);
    siMat.setRowNum(1);
    siMat.setColNum(feaNum);
    siMat.setMaxColNumInBlock(feaNum / 3);
    siMat.setRowType(RowType.T_INT_SPARSE);
    siMat.setValidIndexNum(modelSize);
    siMat.setPartitionNum(partNum);
    siMat.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(siMat);
    // add dense long matrix
    MatrixContext dlMat = new MatrixContext();
    dlMat.setName(DENSE_LONG_MAT);
    dlMat.setRowNum(1);
    dlMat.setColNum(feaNum);
    dlMat.setMaxColNumInBlock(feaNum / 3);
    dlMat.setRowType(RowType.T_LONG_DENSE);
    dlMat.setValidIndexNum(modelSize);
    dlMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dlMat);
    // add sparse long matrix
    MatrixContext slMat = new MatrixContext();
    slMat.setName(SPARSE_LONG_MAT);
    slMat.setRowNum(1);
    slMat.setColNum(feaNum);
    slMat.setMaxColNumInBlock(feaNum / 3);
    slMat.setRowType(RowType.T_LONG_SPARSE);
    slMat.setValidIndexNum(modelSize);
    slMat.setPartitionNum(partNum);
    slMat.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(slMat);
    // add sparse long-key float matrix
    MatrixContext sldMatrix = new MatrixContext();
    sldMatrix.setName(SPARSE_DOUBLE_LONG_MAT);
    sldMatrix.setRowNum(1);
    sldMatrix.setColNum(feaNum);
    sldMatrix.setMaxColNumInBlock(feaNum / 3);
    sldMatrix.setRowType(RowType.T_DOUBLE_SPARSE_LONGKEY);
    sldMatrix.setValidIndexNum(modelSize);
    sldMatrix.setPartitionNum(partNum);
    sldMatrix.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sldMatrix);
    // add sparse long-key float matrix
    MatrixContext slfMatrix = new MatrixContext();
    slfMatrix.setName(SPARSE_FLOAT_LONG_MAT);
    slfMatrix.setRowNum(1);
    slfMatrix.setColNum(feaNum);
    slfMatrix.setMaxColNumInBlock(feaNum / 3);
    slfMatrix.setRowType(RowType.T_FLOAT_SPARSE_LONGKEY);
    slfMatrix.setValidIndexNum(modelSize);
    slfMatrix.setPartitionNum(partNum);
    slfMatrix.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(slfMatrix);
    // add sparse long-key int matrix
    MatrixContext sliMatrix = new MatrixContext();
    sliMatrix.setName(SPARSE_INT_LONG_MAT);
    sliMatrix.setRowNum(1);
    sliMatrix.setColNum(feaNum);
    sliMatrix.setMaxColNumInBlock(feaNum / 3);
    sliMatrix.setRowType(RowType.T_INT_SPARSE_LONGKEY);
    sliMatrix.setValidIndexNum(modelSize);
    sliMatrix.setPartitionNum(partNum);
    sliMatrix.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sliMatrix);
    // add sparse long-key long matrix
    MatrixContext sllMatrix = new MatrixContext();
    sllMatrix.setName(SPARSE_LONG_LONG_MAT);
    sllMatrix.setRowNum(1);
    sllMatrix.setColNum(feaNum);
    sllMatrix.setMaxColNumInBlock(feaNum / 3);
    sllMatrix.setRowType(RowType.T_LONG_SPARSE_LONGKEY);
    sllMatrix.setValidIndexNum(modelSize);
    sllMatrix.setPartitionNum(partNum);
    sllMatrix.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sllMatrix);
    // Start PS
    angelClient.startPSServer();
    // Start to run application
    angelClient.run();
    Thread.sleep(5000);
    psId = new ParameterServerId(0);
    psAttempt0Id = new PSAttemptId(psId, 0);
    WorkerGroupId workerGroupId = new WorkerGroupId(0);
    workerId = new WorkerId(workerGroupId, 0);
    workerAttempt0Id = new WorkerAttemptId(workerId, 0);
}
Also used : CombineTextInputFormat(org.apache.hadoop.mapreduce.lib.input.CombineTextInputFormat) MatrixContext(com.tencent.angel.ml.matrix.MatrixContext) Configuration(org.apache.hadoop.conf.Configuration) PSAttemptId(com.tencent.angel.ps.PSAttemptId) WorkerAttemptId(com.tencent.angel.worker.WorkerAttemptId) ParameterServerId(com.tencent.angel.ps.ParameterServerId) WorkerId(com.tencent.angel.worker.WorkerId) WorkerGroupId(com.tencent.angel.worker.WorkerGroupId) Before(org.junit.Before)

Example 15 with WorkerId

use of com.tencent.angel.worker.WorkerId in project angel by Tencent.

the class IndexGetRowsTest method setup.

@Before
public void setup() throws Exception {
    // set basic configuration keys
    Configuration conf = new Configuration();
    conf.setBoolean("mapred.mapper.new-api", true);
    conf.setBoolean(AngelConf.ANGEL_JOB_OUTPUT_PATH_DELETEONEXIST, true);
    conf.set(AngelConf.ANGEL_TASK_USER_TASKCLASS, DummyTask.class.getName());
    // use local deploy mode and dummy dataspliter
    conf.set(AngelConf.ANGEL_DEPLOY_MODE, "LOCAL");
    conf.setBoolean(AngelConf.ANGEL_AM_USE_DUMMY_DATASPLITER, true);
    conf.set(AngelConf.ANGEL_INPUTFORMAT_CLASS, CombineTextInputFormat.class.getName());
    conf.set(AngelConf.ANGEL_SAVE_MODEL_PATH, LOCAL_FS + TMP_PATH + "/out");
    conf.set(AngelConf.ANGEL_TRAIN_DATA_PATH, LOCAL_FS + TMP_PATH + "/in");
    conf.set(AngelConf.ANGEL_LOG_PATH, LOCAL_FS + TMP_PATH + "/log");
    conf.setInt(AngelConf.ANGEL_WORKERGROUP_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_PS_NUMBER, 2);
    conf.setInt(AngelConf.ANGEL_WORKER_TASK_NUMBER, 1);
    conf.setInt(AngelConf.ANGEL_MODEL_PARTITIONER_PARTITION_SIZE, 1000);
    conf.setBoolean("use.new.split", true);
    conf.setInt(AngelConf.ANGEL_PSAGENT_CACHE_SYNC_TIMEINTERVAL_MS, 10);
    conf.setInt(AngelConf.ANGEL_WORKER_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setInt(AngelConf.ANGEL_PS_HEARTBEAT_INTERVAL_MS, 1000);
    conf.setInt(AngelConf.ANGEL_WORKER_MAX_ATTEMPTS, 1);
    conf.setInt(AngelConf.ANGEL_PS_MAX_ATTEMPTS, 1);
    // get a angel client
    angelClient = AngelClientFactory.get(conf);
    // add dense double matrix
    MatrixContext dMat = new MatrixContext();
    dMat.setName(DENSE_DOUBLE_MAT);
    dMat.setRowNum(rowNum);
    dMat.setColNum(feaNum);
    dMat.setMaxRowNumInBlock(blockRowNum);
    dMat.setMaxColNumInBlock(blockColNum);
    dMat.setRowType(RowType.T_DOUBLE_DENSE);
    dMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dMat);
    // add sparse double matrix
    MatrixContext sMat = new MatrixContext();
    sMat.setName(SPARSE_DOUBLE_MAT);
    sMat.setRowNum(rowNum);
    sMat.setColNum(feaNum);
    sMat.setMaxRowNumInBlock(blockRowNum);
    sMat.setMaxColNumInBlock(blockColNum);
    sMat.setRowType(RowType.T_DOUBLE_SPARSE);
    sMat.setPartitionNum(partNum);
    sMat.setPartitionerClass(HashPartitioner.class);
    angelClient.addMatrix(sMat);
    // add dense float matrix
    MatrixContext dfMat = new MatrixContext();
    dfMat.setName(DENSE_FLOAT_MAT);
    dfMat.setRowNum(rowNum);
    dfMat.setColNum(feaNum);
    dfMat.setMaxRowNumInBlock(blockRowNum);
    dfMat.setMaxColNumInBlock(blockColNum);
    dfMat.setRowType(RowType.T_FLOAT_DENSE);
    dfMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dfMat);
    // add sparse float matrix
    MatrixContext sfMat = new MatrixContext();
    sfMat.setName(SPARSE_FLOAT_MAT);
    sfMat.setRowNum(rowNum);
    sfMat.setColNum(feaNum);
    sfMat.setMaxRowNumInBlock(blockRowNum);
    sfMat.setMaxColNumInBlock(blockColNum);
    sfMat.setRowType(RowType.T_FLOAT_SPARSE);
    angelClient.addMatrix(sfMat);
    // add dense float matrix
    MatrixContext diMat = new MatrixContext();
    diMat.setName(DENSE_INT_MAT);
    diMat.setRowNum(rowNum);
    diMat.setColNum(feaNum);
    diMat.setMaxRowNumInBlock(blockRowNum);
    diMat.setMaxColNumInBlock(blockColNum);
    diMat.setRowType(RowType.T_INT_DENSE);
    diMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(diMat);
    // add sparse float matrix
    MatrixContext siMat = new MatrixContext();
    siMat.setName(SPARSE_INT_MAT);
    siMat.setRowNum(rowNum);
    siMat.setColNum(feaNum);
    siMat.setMaxRowNumInBlock(blockRowNum);
    siMat.setMaxColNumInBlock(blockColNum);
    siMat.setRowType(RowType.T_INT_SPARSE);
    angelClient.addMatrix(siMat);
    // add dense long matrix
    MatrixContext dlMat = new MatrixContext();
    dlMat.setName(DENSE_LONG_MAT);
    dlMat.setRowNum(rowNum);
    dlMat.setColNum(feaNum);
    dlMat.setMaxRowNumInBlock(blockRowNum);
    dlMat.setMaxColNumInBlock(blockColNum);
    dlMat.setRowType(RowType.T_LONG_DENSE);
    dlMat.setPartitionerClass(ColumnRangePartitioner.class);
    angelClient.addMatrix(dlMat);
    // add sparse long matrix
    MatrixContext slMat = new MatrixContext();
    slMat.setName(SPARSE_LONG_MAT);
    slMat.setRowNum(rowNum);
    slMat.setColNum(feaNum);
    slMat.setMaxRowNumInBlock(blockRowNum);
    slMat.setMaxColNumInBlock(blockColNum);
    slMat.setRowType(RowType.T_LONG_SPARSE);
    angelClient.addMatrix(slMat);
    // add sparse long-key double matrix
    MatrixContext dLongKeysMatrix = new MatrixContext();
    dLongKeysMatrix.setName(SPARSE_DOUBLE_LONG_MAT);
    dLongKeysMatrix.setRowNum(rowNum);
    dLongKeysMatrix.setColNum(feaNum);
    dLongKeysMatrix.setMaxRowNumInBlock(blockRowNum);
    dLongKeysMatrix.setMaxColNumInBlock(blockColNum);
    dLongKeysMatrix.setRowType(RowType.T_DOUBLE_SPARSE_LONGKEY);
    angelClient.addMatrix(dLongKeysMatrix);
    // add sparse long-key float matrix
    MatrixContext slfMatrix = new MatrixContext();
    slfMatrix.setName(SPARSE_FLOAT_LONG_MAT);
    slfMatrix.setRowNum(rowNum);
    slfMatrix.setColNum(feaNum);
    slfMatrix.setMaxRowNumInBlock(blockRowNum);
    slfMatrix.setMaxColNumInBlock(blockColNum);
    slfMatrix.setRowType(RowType.T_FLOAT_SPARSE_LONGKEY);
    angelClient.addMatrix(slfMatrix);
    // add sparse long-key int matrix
    MatrixContext sliMatrix = new MatrixContext();
    sliMatrix.setName(SPARSE_INT_LONG_MAT);
    sliMatrix.setRowNum(rowNum);
    sliMatrix.setColNum(feaNum);
    sliMatrix.setMaxRowNumInBlock(blockRowNum);
    sliMatrix.setMaxColNumInBlock(blockColNum);
    sliMatrix.setRowType(RowType.T_INT_SPARSE_LONGKEY);
    angelClient.addMatrix(sliMatrix);
    // add sparse long-key long matrix
    MatrixContext sllMatrix = new MatrixContext();
    sllMatrix.setName(SPARSE_LONG_LONG_MAT);
    sllMatrix.setRowNum(rowNum);
    sllMatrix.setColNum(feaNum);
    sllMatrix.setMaxRowNumInBlock(blockRowNum);
    sllMatrix.setMaxColNumInBlock(blockColNum);
    sllMatrix.setRowType(RowType.T_LONG_SPARSE_LONGKEY);
    angelClient.addMatrix(sllMatrix);
    // Start PS
    angelClient.startPSServer();
    // Start to run application
    angelClient.run();
    Thread.sleep(5000);
    psId = new ParameterServerId(0);
    psAttempt0Id = new PSAttemptId(psId, 0);
    WorkerGroupId workerGroupId = new WorkerGroupId(0);
    workerId = new WorkerId(workerGroupId, 0);
    workerAttempt0Id = new WorkerAttemptId(workerId, 0);
}
Also used : CombineTextInputFormat(org.apache.hadoop.mapreduce.lib.input.CombineTextInputFormat) MatrixContext(com.tencent.angel.ml.matrix.MatrixContext) Configuration(org.apache.hadoop.conf.Configuration) PSAttemptId(com.tencent.angel.ps.PSAttemptId) WorkerAttemptId(com.tencent.angel.worker.WorkerAttemptId) ParameterServerId(com.tencent.angel.ps.ParameterServerId) WorkerId(com.tencent.angel.worker.WorkerId) WorkerGroupId(com.tencent.angel.worker.WorkerGroupId) Before(org.junit.Before)

Aggregations

WorkerId (com.tencent.angel.worker.WorkerId)32 WorkerGroupId (com.tencent.angel.worker.WorkerGroupId)31 WorkerAttemptId (com.tencent.angel.worker.WorkerAttemptId)30 PSAttemptId (com.tencent.angel.ps.PSAttemptId)28 ParameterServerId (com.tencent.angel.ps.ParameterServerId)28 Configuration (org.apache.hadoop.conf.Configuration)27 CombineTextInputFormat (org.apache.hadoop.mapreduce.lib.input.CombineTextInputFormat)27 MatrixContext (com.tencent.angel.ml.matrix.MatrixContext)26 Before (org.junit.Before)22 TaskId (com.tencent.angel.worker.task.TaskId)10 Test (org.junit.Test)4 AngelException (com.tencent.angel.exception.AngelException)3 Worker (com.tencent.angel.worker.Worker)3 BeforeClass (org.junit.BeforeClass)3 ServiceException (com.google.protobuf.ServiceException)2 Location (com.tencent.angel.common.location.Location)2 WorkerAttempt (com.tencent.angel.master.worker.attempt.WorkerAttempt)2 AMWorker (com.tencent.angel.master.worker.worker.AMWorker)2 DenseIntVector (com.tencent.angel.ml.math.vector.DenseIntVector)2 MatrixStorageManager (com.tencent.angel.ps.impl.MatrixStorageManager)2