\u4e88\u6e2c\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30bb\u30c3\u30c8\u30a2\u30c3\u30d7\u3001\u30c7\u30fc\u30bf\u30ed\u30fc\u30c9\u306e\u305f\u3081\u306e\u69d8\u3005\u306a\u30e1\u30bd\u30c3\u30c9\u3092\u5b9a\u7fa9\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ul>\n
GridDB\u306f\u3001\u5927\u91cf\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u30fb\u7ba1\u7406\u3059\u308b\u305f\u3081\u306b\u8a2d\u8a08\u3055\u308c\u305f\u5f37\u529b\u306a\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u30b7\u30b9\u30c6\u30e0\u3067\u3059\u3002\u305d\u306e\u9ad8\u901f\u306a\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u3068\u30af\u30a8\u30ea\u6a5f\u80fd\u306b\u3088\u308a\u3001\u6642\u7cfb\u5217\u4e88\u6e2c\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306b\u6700\u9069\u306a\u9078\u629e\u80a2\u3068\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n
\u307e\u305a\u3001\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067GridDB\u3092\u4f7f\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u305f\u3081\u306b\u3001maven\u306e\u4f9d\u5b58\u95a2\u4fc2\u3092\u8ffd\u52a0\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
\n <dependency>\n <groupId>com.github.griddb<\/groupId>\n <artifactId>gridstore-jdbc<\/artifactId>\n <version>5.3.0<\/version>\n <\/dependency>\n <dependency>\n <groupId>com.github<\/groupId>\n <artifactId>gridstore<\/artifactId>\n <version>5.3.0<\/version>\n <\/dependency> <\/code><\/pre>\n<\/div>\n\u6b21\u306b\u3001\u3084\u308a\u305f\u3044\u3053\u3068\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306b\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u6295\u5165\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002GridDBDataset\u30af\u30e9\u30b9\u306e seedDatabase<\/code> \u30e1\u30bd\u30c3\u30c9\u3067\u3001GridDB\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u6295\u5165\u3057\u307e\u3059\u3002\u30c7\u30fc\u30bf\u306f2\u3064\u306ecsv\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u8aad\u307f\u8fbc\u307e\u308c\u30012\u3064\u306e\u5225\u3005\u306e\u30b3\u30f3\u30c6\u30ca\u306b\u683c\u7d0d\u3055\u308c\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u305d\u306e\u30b3\u30fc\u30c9\u3067\u3059\u3002<\/p>\n\n
\n private static void seedDatabase() throws Exception {\n URL trainingData = Forecaster.class.getClassLoader().getResource(\"data\/weekly_sales_train_validation.csv\");\n URL validationData = Forecaster.class.getClassLoader().getResource(\"data\/weekly_sales_train_evaluation.csv\");\n String[] nextRecord;\n try ( GridStore store = GridDBDataset.connectToGridDB(); CSVReader csvReader = new CSVReader(new InputStreamReader(trainingData.openStream(), StandardCharsets.UTF_8)); CSVReader csvValidationReader = new CSVReader(new InputStreamReader(validationData.openStream(), StandardCharsets.UTF_8))) {\n store.dropContainer(TRAINING_COLLECTION_NAME);\n store.dropContainer(VALIDATION_COLLECTION_NAME);\n\n List columnInfoList = new ArrayList<>();\n\n nextRecord = csvReader.readNext();\n for (int i = 0; i < nextRecord.length; i++) {\n ColumnInfo columnInfo = new ColumnInfo(nextRecord[i], GSType.STRING);\n columnInfoList.add(columnInfo);\n }\n\n ContainerInfo containerInfo = new ContainerInfo();\n containerInfo.setColumnInfoList(columnInfoList);\n containerInfo.setName(TRAINING_COLLECTION_NAME);\n containerInfo.setType(ContainerType.COLLECTION);\n\n Container container = store.putContainer(TRAINING_COLLECTION_NAME, containerInfo, false);\n\n while ((nextRecord = csvReader.readNext()) != null) {\n Row row = container.createRow();\n for (int i = 0; i < nextRecord.length; i++) {\n row.setString(i, nextRecord[i]);\n }\n container.put(row);\n }\n\n nextRecord = csvValidationReader.readNext();\n columnInfoList.clear();\n for (int i = 0; i < nextRecord.length; i++) {\n ColumnInfo columnInfo = new ColumnInfo(nextRecord[i], GSType.STRING);\n columnInfoList.add(columnInfo);\n }\n\n containerInfo = new ContainerInfo();\n containerInfo.setName(VALIDATION_COLLECTION_NAME);\n containerInfo.setColumnInfoList(columnInfoList);\n containerInfo.setType(ContainerType.COLLECTION);\n\n container = store.putContainer(VALIDATION_COLLECTION_NAME, containerInfo, false);\n while ((nextRecord = csvValidationReader.readNext()) != null) {\n Row row = container.createRow();\n for (int i = 0; i < nextRecord.length; i++) {\n String cell = nextRecord[i];\n row.setString(i, cell);\n }\n container.put(row);\n }\n }\n }<\/code><\/pre>\n<\/div>\nDJL \u3068 GridDB \u306e\u7d71\u5408<\/h2>\n
DJL\u3068GridDB\u306f\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u9023\u643a\u3057\u307e\u3059\u3002GridDB\u306b\u63a5\u7d9a\u3057\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001DJL\u3092\u4f7f\u7528\u3057\u3066\u4e88\u6e2c\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3001\u5b66\u7fd2\u3001\u30c7\u30d7\u30ed\u30a4\u3057\u307e\u3059\u3002GridDBDataset<\/code> \u30af\u30e9\u30b9\u306f\u3001GridDB\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3068\u3084\u308a\u53d6\u308a\u3059\u308b\u305f\u3081\u306b\u5fc5\u8981\u306a\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/p>\nDJL\u306eTimeSeriesDataset\u306e\u30ab\u30b9\u30bf\u30e0\u5b9f\u88c5\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3057\u305f\u3002\u3053\u308c\u306f\u3001DJL\u3068\u30ab\u30b9\u30bf\u30e0\u30c7\u30fc\u30bf\u30ea\u30dd\u30b8\u30c8\u30ea\u3092\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u7d71\u5408\u3059\u308b\u305f\u3081\u306e\u6700\u3082\u72ec\u5275\u7684\u306a\u65b9\u6cd5\u306e1\u3064\u3067\u3059\u3002\u305d\u306e\u5b9f\u88c5\u304c\u3053\u3061\u3089\u3067\u3059\u3002<\/p>\n
\n
\n...\npublic class GridDBDataset extends M5Forecast {\n\n ...\n\n public static GridStore connectToGridDB() throws GSException {\n Properties props = new Properties();\n props.setProperty(\"notificationMember\", \"127.0.0.1:10001\");\n props.setProperty(\"clusterName\", \"defaultCluster\");\n props.setProperty(\"user\", \"admin\");\n props.setProperty(\"password\", \"admin\");\n return GridStoreFactory.getInstance().getGridStore(props);\n }\n\n public static class GridDBBuilder extends M5Forecast.Builder {\n ...\n\n private File fetchDBDataAndSaveCSV(GridStore store) throws GSException, FileNotFoundException {\n File csvOutputFile = new File(this.getContainerName()+ \".csv\");\n try ( GridStore store2 = store) {\n Container container = store2.getContainer(this.getContainerName());\n\n Query query = container.query(\"Select *\");\n RowSet rowSet = query.fetch();\n\n int columnCount = rowSet.getSchema().getColumnCount();\n\n List csv = new LinkedList<>();\n StringBuilder builder = new StringBuilder();\n\n \/\/Loan column headers\n ContainerInfo cInfo = rowSet.getSchema();\n for (int i = 0; i < cInfo.getColumnCount(); i++) {\n ColumnInfo columnInfo = rowSet.getSchema().getColumnInfo(i);\n builder.append(columnInfo.getName());\n appendComma(builder, i, cInfo.getColumnCount());\n }\n csv.add(builder.toString());\n\n \/\/Load each row\n while (rowSet.hasNext()) {\n Row row = rowSet.next();\n builder = new StringBuilder();\n for (int i = 0; i < columnCount; i++) {\n String val = row.getString(i);\n builder.append(val);\n appendComma(builder, i, columnCount);\n }\n csv.add(builder.toString());\n }\n try ( PrintWriter pw = new PrintWriter(csvOutputFile)) {\n csv.stream()\n .forEach(pw::println);\n }\n }\n return csvOutputFile;\n }\n\n public GridDBBuilder initData() throws GSException, FileNotFoundException {\n this.csvFile = fetchDBDataAndSaveCSV(this.store);\n return this;\n }\n\n @Override\n public GridDBDataset build() {\n GridDBDataset gridDBDataset = null;\n try {\n gridDBDataset = new GridDBDataset(this);\n } catch (GSException | FileNotFoundException ex) {\n Logger.getLogger(GridDBDataset.class.getName()).log(Level.SEVERE, null, ex);\n }\n return gridDBDataset;\n }\n\n }\n}<\/code><\/pre>\n<\/div>\n\u9ad8\u5ea6\u306a\u6642\u7cfb\u5217\u4e88\u6e2c\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9<\/h2>\n
\u6211\u3005\u306e\u4e88\u6e2c\u80fd\u529b\u306e\u4e2d\u6838\u306fDeepAR\u30e2\u30c7\u30eb\u306b\u3042\u308a\u307e\u3059\u3002startTraining<\/code> \u30e1\u30bd\u30c3\u30c9\u3067DeepAR\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3001\u8a13\u7df4\u3001\u8a55\u4fa1\u3057\u307e\u3059\u3002DJL\u306e\u4f7f\u3044\u3084\u3059\u3044API\u306b\u3088\u308a\u3001\u30e2\u30c7\u30eb\u30fb\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u5b9a\u7fa9\u3057\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3067\u8a13\u7df4\u3059\u308b\u3053\u3068\u304c\u5bb9\u6613\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n
\nprivate static void startTraining() throws IOException, TranslateException, Exception {\n\n DistributionOutput distributionOutput = new NegativeBinomialOutput();\n\n Model model = null;\n Trainer trainer = null;\n NDManager manager = null;\n try {\n manager = NDManager.newBaseManager();\n model = Model.newInstance(\"deepar\");\n DeepARNetwork trainingNetwork = getDeepARModel(distributionOutput, true);\n model.setBlock(trainingNetwork);\n\n List trainingTransformation = trainingNetwork.createTrainingTransformation(manager);\n\n Dataset trainSet = getDataset(Dataset.Usage.TRAIN, trainingNetwork.getContextLength(), trainingTransformation);\n\n trainer = model.newTrainer(setupTrainingConfig(distributionOutput));\n trainer.setMetrics(new Metrics());\n\n int historyLength = trainingNetwork.getHistoryLength();\n Shape[] inputShapes = new Shape[9];\n \/\/ (N, num_cardinality)\n inputShapes[0] = new Shape(1, 1);\n \/\/ (N, num_real) if use_feat_stat_real else (N, 1)\n inputShapes[1] = new Shape(1, 1);\n \/\/ (N, history_length, num_time_feat + num_age_feat)\n inputShapes[2] = new Shape(1, historyLength, TimeFeature.timeFeaturesFromFreqStr(FREQ).size() + 1);\n inputShapes[3] = new Shape(1, historyLength);\n inputShapes[4] = new Shape(1, historyLength);\n inputShapes[5] = new Shape(1, historyLength);\n inputShapes[6] = new Shape(1, 1, TimeFeature.timeFeaturesFromFreqStr(FREQ).size() + 1);\n inputShapes[7] = new Shape(1, 1);\n inputShapes[8] = new Shape(1, 1);\n trainer.initialize(inputShapes);\n int epoch = 10;\n EasyTrain.fit(trainer, epoch, trainSet, null);\n } finally {\n if (trainer != null) {\n trainer.close();\n }\n if (model != null) {\n model.close();\n }\n if (manager != null) {\n manager.close();\n }\n }\n }<\/code><\/pre>\n<\/div>\n\u305d\u308c\u3067\u306f startTraining<\/code> \u30e1\u30bd\u30c3\u30c9\u306e\u5404\u30b9\u30c6\u30c3\u30d7\u3092\u5206\u89e3\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\u30b9\u30c6\u30c3\u30d7 1\uff1a\u30e2\u30c7\u30eb\u306e\u5206\u5e03\u51fa\u529b\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001NegativeBinomialOutput\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002\u5206\u5e03\u51fa\u529b\u306f\u3001\u30e2\u30c7\u30eb\u304c\u4e88\u6e2c\u3092\u751f\u6210\u3059\u308b\u65b9\u6cd5\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 2: getDeepARModel \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001DeepAR \u5b66\u7fd2\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u3053\u306e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306f\u3001DeepAR \u30e2\u30c7\u30eb\u306e\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u91cd\u8981\u306a\u306e\u306f\u3001\u3053\u308c\u304c\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3067\u3042\u308b\u3053\u3068\u3092\u793a\u3059\u305f\u3081\u306b true \u3092\u6e21\u3059\u3053\u3068\u3067\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 3: \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u5909\u63db\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u5909\u63db\u306f\u5165\u529b\u30c7\u30fc\u30bf\u306b\u9069\u7528\u3055\u308c\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306b\u5099\u3048\u307e\u3059\u3002\u30c7\u30fc\u30bf\u306e\u6b63\u898f\u5316\u3001\u7279\u5fb4\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306a\u3069\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 4\uff1agetDataset\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u6e96\u5099\u3057\u307e\u3059\u3002\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306fDeepAR\u30e2\u30c7\u30eb\u306e\u5b66\u7fd2\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u306f\u3001\u904e\u53bb\u306e\u30c7\u30fc\u30bf\u3068\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306e\u76ee\u6a19\u5024\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 5: \u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3059\u308b\u305f\u3081\u306e\u30c8\u30ec\u30fc\u30ca\u30fc\u3092\u4f5c\u6210\u3057\u3001\u8a2d\u5b9a\u3057\u307e\u3059\u3002setupTrainingConfig\u30e1\u30bd\u30c3\u30c9\u306f\u3001\u640d\u5931\u95a2\u6570\u3001\u8a55\u4fa1\u5b50\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30ea\u30b9\u30ca\u30fc\u3092\u542b\u3080\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u69cb\u6210\u3092\u8a2d\u5b9a\u3057\u307e\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 6\uff1a\u5165\u529b\u5f62\u72b6\u3067\u30c8\u30ec\u30fc\u30ca\u3092\u521d\u671f\u5316\u3057\u307e\u3059\u3002\u3053\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u306f\uff0c\u30c8\u30ec\u30fc\u30ca\u304c\u30e2\u30c7\u30eb\u306b\u671f\u5f85\u3055\u308c\u308b\u5165\u529b\u5f62\u72b6\u3092\u77e5\u3063\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u307e\u3059\uff0einputShapes \u914d\u5217\u306b\u306f\u3001\u30e2\u30c7\u30eb\u306e\u69d8\u3005\u306a\u5165\u529b\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u306e\u5f62\u72b6\u304c\u683c\u7d0d\u3055\u308c\u307e\u3059\u3002<\/p>\n
\u30b9\u30c6\u30c3\u30d7 7: \u6700\u5f8c\u306b\u3001EasyTrain.fit\u30e1\u30bd\u30c3\u30c9\u3092\u7528\u3044\u3066\u30e2\u30c7\u30eb\u306e\u5b66\u7fd2\u3092\u958b\u59cb\u3057\u307e\u3059\u3002\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30a8\u30dd\u30c3\u30af\u6570\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\uff08trainSet\uff09\u3001\u305d\u306e\u4ed6\u306e\u30aa\u30d7\u30b7\u30e7\u30f3\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002\u30c8\u30ec\u30fc\u30ca\u306f\u30e2\u30c7\u30eb\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6700\u9069\u5316\u3057\u3066\u3001\u5b9a\u7fa9\u3055\u308c\u305f\u640d\u5931\u95a2\u6570\u3092\u6700\u5c0f\u5316\u3057\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u3067\u306e\u6027\u80fd\u3092\u5411\u4e0a\u3055\u305b\u307e\u3059\u3002<\/p>\n
\u5168\u4f53\u3068\u3057\u3066 startTraining<\/code> \u30e1\u30bd\u30c3\u30c9\u306f\u30e2\u30c7\u30eb\u3092\u8a2d\u5b9a\u3057\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u6e96\u5099\u3057\u3001\u30c8\u30ec\u30fc\u30ca\u3092\u521d\u671f\u5316\u3059\u308b\u3053\u3068\u3067\u3001\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u305f\u3081\u306e DeepAR \u30e2\u30c7\u30eb\u3092\u8a2d\u5b9a\u3057\u3001\u8a13\u7df4\u3057\u307e\u3059\u3002\u3053\u306e\u30b9\u30c6\u30c3\u30d7\u306e\u7d44\u307f\u5408\u308f\u305b\u306b\u3088\u308a\u3001\u904e\u53bb\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306b\u57fa\u3065\u3044\u3066\u6b63\u78ba\u306a\u4e88\u6e2c\u3092\u884c\u3046\u305f\u3081\u306e\u30e2\u30c7\u30eb\u306e\u52b9\u679c\u7684\u306a\u5b66\u7fd2\u304c\u4fdd\u8a3c\u3055\u308c\u307e\u3059\u3002<\/p>\n\u4e88\u6e2c\u3059\u308b<\/h2>\n
\u5b66\u7fd2\u5f8c\u3001predict<\/code> \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u3063\u3066\u5b66\u7fd2\u3057\u305f\u30e2\u30c7\u30eb\u306b\u57fa\u3065\u3044\u3066\u4e88\u6e2c\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u30e2\u30c7\u30eb\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u8a55\u4fa1\u3059\u308b\u305f\u3081\u306b\u3001RMSSE (Root Mean Squared Scaled Error)\u3001MSE (Mean Squared Error)\u3001\u5206\u4f4d\u70b9\u640d\u5931\u306a\u3069\u306e\u69d8\u3005\u306a\u30e1\u30c8\u30ea\u30af\u30b9\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002<\/p>\n\u7d50\u8ad6<\/h2>\n
\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001DJL\u3068GridDB\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u4e88\u6e2c\u3059\u308b\u65b9\u6cd5\u3092\u63a2\u308a\u307e\u3057\u305f\u3002\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3001DJL\u3001GridDB \u306e\u4e3b\u8981\u6982\u5ff5\u3092\u7d39\u4ecb\u3057\u3001\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u305f\u3081\u306e DeepAR \u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3068\u5b66\u7fd2\u306b\u95a2\u308f\u308b\u30b3\u30fc\u30c9\u306e\u8a73\u7d30\u306a\u8aac\u660e\u3092\u884c\u3044\u307e\u3057\u305f\u3002\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306e\u30d1\u30ef\u30fc\u3068GridDB\u306e\u52b9\u7387\u6027\u3092\u7d44\u307f\u5408\u308f\u305b\u308b\u3053\u3068\u3067\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u304b\u3089\u8cb4\u91cd\u306a\u6d1e\u5bdf\u3092\u5f15\u304d\u51fa\u3057\u3001\u30d3\u30b8\u30cd\u30b9\u3084\u7814\u7a76\u306e\u305f\u3081\u306b\u60c5\u5831\u306b\u57fa\u3065\u3044\u305f\u610f\u601d\u6c7a\u5b9a\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002DJL\u306e\u4f7f\u3044\u3084\u3059\u3055\u3068\u67d4\u8edf\u6027\u306f\u3001\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u8ab2\u984c\u306b\u53d6\u308a\u7d44\u3082\u3046\u3068\u3059\u308b\u3042\u3089\u3086\u308bJava\u958b\u767a\u8005\u306b\u3068\u3063\u3066\u8cb4\u91cd\u306a\u30c4\u30fc\u30eb\u3068\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n
\u7d50\u8ad6\u3068\u3057\u3066\u3001DJL\u3068GridDB\u306e\u76f8\u4e57\u52b9\u679c\u306b\u3088\u308a\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u6f5c\u5728\u80fd\u529b\u3092\u6d3b\u7528\u3057\u3001\u69d8\u3005\u306a\u9818\u57df\u3067\u3088\u308a\u826f\u3044\u610f\u601d\u6c7a\u5b9a\u3092\u4fc3\u9032\u3059\u308b\u6b63\u78ba\u306a\u4e88\u6e2c\u3092\u63d0\u4f9b\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u672c\u8a18\u4e8b\u3067\u5f97\u305f\u77e5\u8b58\u306b\u3088\u308a\u3001\u6700\u5148\u7aef\u306e\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u6280\u8853\u3068\u5805\u7262\u306a\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u30fb\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u7528\u3044\u305f\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u65c5\u306b\u51fa\u308b\u305f\u3081\u306e\u5341\u5206\u306a\u6e96\u5099\u304c\u6574\u3044\u307e\u3057\u305f\u3002<\/p>\n
DJL\u3068GridDB\u306e\u878d\u5408\u306f\u3001\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u4e16\u754c\u306b\u65b0\u305f\u306a\u53ef\u80fd\u6027\u3092\u958b\u304d\u307e\u3059\u3002\u3053\u306e\u5206\u91ce\u3092\u3088\u308a\u6df1\u304f\u6398\u308a\u4e0b\u3052\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u99c6\u52d5\u578b\u6d1e\u5bdf\u306e\u529b\u3068\u3001\u305d\u308c\u304c\u91d1\u878d\u304b\u3089\u30d8\u30eb\u30b9\u30b1\u30a2\u307e\u3067\u5e45\u5e83\u3044\u696d\u754c\u306b\u3069\u306e\u3088\u3046\u306a\u9769\u547d\u3092\u3082\u305f\u3089\u3059\u304b\u3092\u767a\u898b\u3067\u304d\u308b\u3067\u3057\u3087\u3046\u3002\u63a2\u6c42\u3057\u7d9a\u3051\u307e\u3057\u3087\u3046\u3001\u5b66\u3073\u7d9a\u3051\u3001\u81ea\u4fe1\u3092\u6301\u3063\u3066\u672a\u6765\u3092\u4e88\u6e2c\u3057\u7d9a\u3051\u307e\u3057\u3087\u3046\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u306f\u3058\u3081\u306b \u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306f\u3069\u3053\u306b\u3067\u3082\u3042\u308a\u307e\u3059\u3002\u682a\u4fa1\u3084\u5929\u5019\u30d1\u30bf\u30fc\u30f3\u304b\u3089\u58f2\u4e0a\u9ad8\u3084\u30bb\u30f3\u30b5\u30fc\u30c7\u30fc\u30bf\u307e\u3067\u3001\u79c1\u305f\u3061\u306e\u751f\u6d3b\u306e\u69d8\u3005\u306a\u5834\u9762\u3067\u91cd\u8981\u306a\u5f79\u5272\u3092\u679c\u305f\u3057\u3066\u3044\u307e\u3059\u3002\u904e\u53bb\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306b\u57fa\u3065\u3044\u3066\u5c06\u6765\u306e\u5024\u3092\u4e88\u6e2c\u3067\u304d\u308b\u3053\u3068\u306f\u3001\u60c5\u5831\u306b\u57fa\u3065\u3044\u305f\u610f […]<\/p>\n","protected":false},"author":41,"featured_media":49118,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50879","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"\n
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