Java tutorial
/* * Copyright (c) 2015, WSO2 Inc. (http://www.wso2.org) All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.wso2.carbon.ml.rest.api; import java.io.*; import java.nio.charset.StandardCharsets; import java.util.List; import javax.ws.rs.*; import javax.ws.rs.core.MediaType; import javax.ws.rs.core.Response; import javax.ws.rs.core.StreamingOutput; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.apache.cxf.jaxrs.ext.multipart.Multipart; import org.apache.hadoop.fs.InvalidRequestException; import org.apache.http.HttpHeaders; import org.wso2.carbon.context.PrivilegedCarbonContext; import org.wso2.carbon.ml.commons.constants.MLConstants; import org.wso2.carbon.ml.commons.domain.MLModel; import org.wso2.carbon.ml.commons.domain.MLModelData; import org.wso2.carbon.ml.commons.domain.MLStorage; import org.wso2.carbon.ml.commons.domain.ModelSummary; import org.wso2.carbon.ml.core.exceptions.MLModelBuilderException; import org.wso2.carbon.ml.core.exceptions.MLModelHandlerException; import org.wso2.carbon.ml.core.exceptions.MLModelPublisherException; import org.wso2.carbon.ml.core.exceptions.MLPmmlExportException; import org.wso2.carbon.ml.core.impl.MLModelHandler; import org.wso2.carbon.ml.core.utils.MLUtils; import org.wso2.carbon.ml.rest.api.model.MLErrorBean; import org.wso2.carbon.ml.rest.api.model.MLResponseBean; /** * This class is to handle REST verbs GET , POST and DELETE. */ @Path("/models") public class ModelApiV10 extends MLRestAPI { private static final Log logger = LogFactory.getLog(ModelApiV10.class); private MLModelHandler mlModelHandler; public ModelApiV10() { mlModelHandler = new MLModelHandler(); } @OPTIONS public Response options() { return Response.ok().header(HttpHeaders.ALLOW, "GET POST DELETE").build(); } /** * Create a new Model. * @param model {@link org.wso2.carbon.ml.commons.domain.MLModelData} object * @return JSON of {@link org.wso2.carbon.ml.commons.domain.MLModelData} object */ @POST @Produces("application/json") @Consumes("application/json") public Response createModel(MLModelData model) { if (model.getAnalysisId() == 0 || model.getVersionSetId() == 0) { logger.error("Required parameters missing"); return Response.status(Response.Status.BAD_REQUEST).entity("Required parameters missing").build(); } PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); try { int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); model.setTenantId(tenantId); model.setUserName(userName); MLModelData insertedModel = mlModelHandler.createModel(model); return Response.ok(insertedModel).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg("Error occurred while creating a model : " + model, e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Create a new model storage * @param modelId Unique id of the model * @param storage {@link org.wso2.carbon.ml.commons.domain.MLStorage} object */ @POST @Path("/{modelId}/storages") @Produces("application/json") @Consumes("application/json") public Response addStorage(@PathParam("modelId") long modelId, MLStorage storage) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { mlModelHandler.addStorage(modelId, storage); return Response.ok().build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while adding storage for the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Build the model * @param modelId Unique id of the model to be built. */ @POST @Path("/{modelId}") @Produces("application/json") @Consumes("application/json") public Response buildModel(@PathParam("modelId") long modelId) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { mlModelHandler.buildModel(tenantId, userName, modelId); return Response.ok().build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while building the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } catch (MLModelBuilderException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while building the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Publish the model to ML registry * @param modelId Unique id of the model to be published * @return JSON of {@link org.wso2.carbon.ml.rest.api.model.MLResponseBean} containing the published location of the model */ @POST @Path("/{modelId}/publish") @Produces("application/json") @Consumes("application/json") public Response publishModel(@PathParam("modelId") long modelId) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { String registryPath = mlModelHandler.publishModel(tenantId, userName, modelId, MLModelHandler.Format.SERIALIZED); return Response.ok(new MLResponseBean(registryPath)).build(); } catch (InvalidRequestException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while publishing the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.BAD_REQUEST).entity(new MLErrorBean(e.getMessage())).build(); } catch (MLModelPublisherException | MLModelHandlerException | MLPmmlExportException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while publishing the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Predict using a file and return as a list of predicted values. * @param modelId Unique id of the model * @param dataFormat Data format of the file (CSV or TSV) * @param inputStream File input stream generated from the file used for predictions * @return JSON array of predictions */ @POST @Path("/predict") @Produces(MediaType.APPLICATION_JSON) @Consumes(MediaType.MULTIPART_FORM_DATA) public Response predict(@Multipart("modelId") long modelId, @Multipart("dataFormat") String dataFormat, @Multipart("file") InputStream inputStream) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { // validate input parameters // if it is a file upload, check whether the file is sent if (inputStream == null || inputStream.available() == 0) { String msg = String.format( "Error occurred while reading the file for model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName); logger.error(msg); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(msg)).build(); } List<?> predictions = mlModelHandler.predict(tenantId, userName, modelId, dataFormat, inputStream); return Response.ok(predictions).build(); } catch (IOException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while reading the file for model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.BAD_REQUEST).entity(new MLErrorBean(e.getMessage())).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while predicting from model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Predict using a file and return predictions as a CSV. * @param modelId Unique id of the model * @param dataFormat Data format of the file (CSV or TSV) * @param columnHeader Whether the file contains the column header as the first row (YES or NO) * @param inputStream Input stream generated from the file used for predictions * @return A file as a {@link javax.ws.rs.core.StreamingOutput} */ @POST @Path("/predictionStreams") @Produces(MediaType.APPLICATION_OCTET_STREAM) @Consumes(MediaType.MULTIPART_FORM_DATA) public Response streamingPredict(@Multipart("modelId") long modelId, @Multipart("dataFormat") String dataFormat, @Multipart("columnHeader") String columnHeader, @Multipart("file") InputStream inputStream) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { // validate input parameters // if it is a file upload, check whether the file is sent if (inputStream == null || inputStream.available() == 0) { String msg = String.format( "Error occurred while reading the file for model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName); logger.error(msg); return Response.status(Response.Status.BAD_REQUEST).entity(new MLErrorBean(msg)).build(); } final String predictions = mlModelHandler.streamingPredict(tenantId, userName, modelId, dataFormat, columnHeader, inputStream); StreamingOutput stream = new StreamingOutput() { @Override public void write(OutputStream outputStream) throws IOException { Writer writer = new BufferedWriter( new OutputStreamWriter(outputStream, StandardCharsets.UTF_8)); writer.write(predictions); writer.flush(); writer.close(); } }; return Response.ok(stream).header("Content-disposition", "attachment; filename=Predictions_" + modelId + "_" + MLUtils.getDate() + MLConstants.CSV) .build(); } catch (IOException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while reading the file for model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.BAD_REQUEST).entity(new MLErrorBean(e.getMessage())).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while predicting from model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Make predictions using a model * @param modelId Unique id of the model * @param data List of string arrays containing the feature values used for predictions * @return JSON array of predicted values */ @POST @Path("/{modelId}/predict") @Produces("application/json") @Consumes("application/json") public Response predict(@PathParam("modelId") long modelId, List<String[]> data) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { long t1 = System.currentTimeMillis(); List<?> predictions = mlModelHandler.predict(tenantId, userName, modelId, data); logger.info(String.format("Prediction from model [id] %s finished in %s seconds.", modelId, (System.currentTimeMillis() - t1) / 1000.0)); return Response.ok(predictions).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while predicting from model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Get the model data * @param modelName Name of the model * @return JSON of {@link org.wso2.carbon.ml.commons.domain.MLModelData} object */ @GET @Path("/{modelId}/getRecommendations/{userId}/{noOfProducts}") @Produces("application/json") public Response getRecommendations(@PathParam("modelId") long modelId, @PathParam("userId") int userId, @PathParam("noOfProducts") int noOfProducts) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { List<?> recommendations = mlModelHandler.getProductRecommendations(tenantId, userName, modelId, userId, noOfProducts); return Response.ok(recommendations).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while getting recommendations from model [id] %s of tenant [id] %s and [user] %s.", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } @GET @Path("/{modelName}") @Produces("application/json") public Response getModel(@PathParam("modelName") String modelName) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { MLModelData model = mlModelHandler.getModel(tenantId, userName, modelName); if (model == null) { return Response.status(Response.Status.NOT_FOUND).build(); } return Response.ok(model).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while retrieving a model [name] %s of tenant [id] %s and [user] %s .", modelName, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Get all models * @return JSON array of {@link org.wso2.carbon.ml.commons.domain.MLModelData} objects */ @GET @Produces("application/json") public Response getAllModels() { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { List<MLModelData> models = mlModelHandler.getAllModels(tenantId, userName); return Response.ok(models).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg( String.format("Error occurred while retrieving all models of tenant [id] %s and [user] %s .", tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Delete a model * @param modelId Unique id of the model */ @DELETE @Path("/{modelId}") @Produces("application/json") public Response deleteModel(@PathParam("modelId") long modelId) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { mlModelHandler.deleteModel(tenantId, userName, modelId); auditLog.info(String.format("User [name] %s of tenant [id] %s deleted a model [id] %s ", userName, tenantId, modelId)); return Response.ok().build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg( String.format("Error occurred while deleting a model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); auditLog.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Get the model summary * @param modelId Unique id of the model * @return JSON of {@link org.wso2.carbon.ml.commons.domain.ModelSummary} object */ @GET @Path("/{modelId}/summary") @Produces("application/json") @Consumes("application/json") public Response getModelSummary(@PathParam("modelId") long modelId) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { ModelSummary modelSummary = mlModelHandler.getModelSummary(modelId); return Response.ok(modelSummary).build(); } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while retrieving summary of the model [id] %s of tenant [id] %s and [user] %s .", modelId, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } /** * Download the model * @param modelName Name of the model * @return A {@link org.wso2.carbon.ml.commons.domain.MLModel} as a {@link javax.ws.rs.core.StreamingOutput} */ @GET @Path("/{modelName}/export") @Produces(MediaType.APPLICATION_OCTET_STREAM) public Response exportModel(@PathParam("modelName") String modelName) { PrivilegedCarbonContext carbonContext = PrivilegedCarbonContext.getThreadLocalCarbonContext(); int tenantId = carbonContext.getTenantId(); String userName = carbonContext.getUsername(); try { MLModelData model = mlModelHandler.getModel(tenantId, userName, modelName); if (model != null) { final MLModel generatedModel = mlModelHandler.retrieveModel(model.getId()); StreamingOutput stream = new StreamingOutput() { public void write(OutputStream outputStream) throws IOException { ObjectOutputStream out = new ObjectOutputStream(outputStream); out.writeObject(generatedModel); } }; return Response.ok(stream).header("Content-disposition", "attachment; filename=" + modelName) .build(); } else { return Response.status(Response.Status.NOT_FOUND).build(); } } catch (MLModelHandlerException e) { String msg = MLUtils.getErrorMsg(String.format( "Error occurred while retrieving model [name] %s of tenant [id] %s and [user] %s .", modelName, tenantId, userName), e); logger.error(msg, e); return Response.status(Response.Status.INTERNAL_SERVER_ERROR).entity(new MLErrorBean(e.getMessage())) .build(); } } }