Examples with KeyValueTable io.cdap.cdap.api.dataset.lib.KeyValueTable used on opensource projects

Example 36 with KeyValueTable

use of io.cdap.cdap.api.dataset.lib.KeyValueTable in project cdap by cdapio.

the class SparkTest method testSparkWithGetDataset.

private void testSparkWithGetDataset(Class<? extends Application> appClass, String sparkProgram) throws Exception {
    ApplicationManager applicationManager = deploy(appClass);
    DataSetManager<FileSet> filesetManager = getDataset("logs");
    FileSet fileset = filesetManager.get();
    Location location = fileset.getLocation("nn");
    prepareInputFileSetWithLogData(location);
    Map<String, String> inputArgs = new HashMap<>();
    FileSetArguments.setInputPath(inputArgs, "nn");
    Map<String, String> args = new HashMap<>();
    args.putAll(RuntimeArguments.addScope(Scope.DATASET, "logs", inputArgs));
    args.put("input", "logs");
    args.put("output", "logStats");
    SparkManager sparkManager = applicationManager.getSparkManager(sparkProgram);
    sparkManager.startAndWaitForGoodRun(args, ProgramRunStatus.COMPLETED, 2, TimeUnit.MINUTES);
    DataSetManager<KeyValueTable> logStatsManager = getDataset("logStats");
    KeyValueTable logStatsTable = logStatsManager.get();
    validateGetDatasetOutput(logStatsTable);
    // Cleanup after run
    location.delete(true);
    logStatsManager.flush();
    try (CloseableIterator<KeyValue<byte[], byte[]>> scan = logStatsTable.scan(null, null)) {
        while (scan.hasNext()) {
            logStatsTable.delete(scan.next().getKey());
        }
    }
    logStatsManager.flush();
}

Example 37 with KeyValueTable

use of io.cdap.cdap.api.dataset.lib.KeyValueTable in project cdap by cdapio.

the class SparkTest method testClassicSpark.

@Test
public void testClassicSpark() throws Exception {
    ApplicationManager appManager = deploy(TestSparkApp.class);
    for (Class<?> sparkClass : Arrays.asList(TestSparkApp.ClassicSpark.class, TestSparkApp.ScalaClassicSpark.class)) {
        final SparkManager sparkManager = appManager.getSparkManager(sparkClass.getSimpleName());
        sparkManager.startAndWaitForGoodRun(ProgramRunStatus.COMPLETED, 5, TimeUnit.MINUTES);
    }
    KeyValueTable resultTable = this.<KeyValueTable>getDataset("ResultTable").get();
    Assert.assertEquals(1L, Bytes.toLong(resultTable.read(ClassicSparkProgram.class.getName())));
    Assert.assertEquals(1L, Bytes.toLong(resultTable.read(ScalaClassicSparkProgram.class.getName())));
}

Example 38 with KeyValueTable

use of io.cdap.cdap.api.dataset.lib.KeyValueTable in project cdap by cdapio.

the class SparkTest method testTransaction.

@Test
public void testTransaction() throws Exception {
    ApplicationManager applicationManager = deploy(TestSparkApp.class);
    // Write some data to a local file
    File inputFile = TEMP_FOLDER.newFile();
    try (PrintWriter writer = new PrintWriter(Files.newBufferedWriter(inputFile.toPath(), StandardCharsets.UTF_8))) {
        writer.println("red fox");
        writer.println("brown fox");
        writer.println("grey fox");
        writer.println("brown bear");
        writer.println("black bear");
    }
    // Run the spark program
    SparkManager sparkManager = applicationManager.getSparkManager(TransactionSpark.class.getSimpleName());
    sparkManager.start(ImmutableMap.of("input.file", inputFile.getAbsolutePath(), "keyvalue.table", "KeyValueTable", "result.all.dataset", "SparkResult", "result.threshold", "2", "result.threshold.dataset", "SparkThresholdResult"));
    // Verify result from dataset before the Spark program terminates
    final DataSetManager<KeyValueTable> resultManager = getDataset("SparkThresholdResult");
    final KeyValueTable resultTable = resultManager.get();
    // Expect the threshold result dataset, with threshold >=2, contains [brown, fox, bear]
    Tasks.waitFor(ImmutableSet.of("brown", "fox", "bear"), () -> {
        // This is to start a new TX
        resultManager.flush();
        LOG.info("Reading from threshold result");
        try (CloseableIterator<KeyValue<byte[], byte[]>> itor = resultTable.scan(null, null)) {
            return ImmutableSet.copyOf(Iterators.transform(itor, input -> {
                String word = Bytes.toString(input.getKey());
                LOG.info("{}, {}", word, Bytes.toInt(input.getValue()));
                return word;
            }));
        }
    }, 3, TimeUnit.MINUTES, 1, TimeUnit.SECONDS);
    sparkManager.stop();
    sparkManager.waitForRun(ProgramRunStatus.KILLED, 60, TimeUnit.SECONDS);
}

Example 39 with KeyValueTable

use of io.cdap.cdap.api.dataset.lib.KeyValueTable in project cdap by cdapio.

the class TestFrameworkTestRun method executeWorkflow.

private String executeWorkflow(ApplicationManager applicationManager, Map<String, String> additionalParams, int expectedComplete) throws Exception {
    WorkflowManager wfManager = applicationManager.getWorkflowManager(WorkflowAppWithLocalDatasets.WORKFLOW_NAME);
    Map<String, String> runtimeArgs = new HashMap<>();
    File waitFile = new File(TMP_FOLDER.newFolder(), "/wait.file");
    File doneFile = new File(TMP_FOLDER.newFolder(), "/done.file");
    runtimeArgs.put("input.path", "input");
    runtimeArgs.put("output.path", "output");
    runtimeArgs.put("wait.file", waitFile.getAbsolutePath());
    runtimeArgs.put("done.file", doneFile.getAbsolutePath());
    runtimeArgs.putAll(additionalParams);
    wfManager.start(runtimeArgs);
    // Wait until custom action in the Workflow is triggered.
    while (!waitFile.exists()) {
        TimeUnit.MILLISECONDS.sleep(50);
    }
    // Now the Workflow should have RUNNING status. Get its runid.
    List<RunRecord> history = wfManager.getHistory(ProgramRunStatus.RUNNING);
    Assert.assertEquals(1, history.size());
    String runId = history.get(0).getPid();
    // Get the local datasets for this Workflow run
    DataSetManager<KeyValueTable> localDataset = getDataset(testSpace.dataset(WorkflowAppWithLocalDatasets.WORDCOUNT_DATASET + "." + runId));
    Assert.assertEquals("2", Bytes.toString(localDataset.get().read("text")));
    DataSetManager<FileSet> fileSetDataset = getDataset(testSpace.dataset(WorkflowAppWithLocalDatasets.CSV_FILESET_DATASET + "." + runId));
    Assert.assertNotNull(fileSetDataset.get());
    // Local datasets should not exist at the namespace level
    localDataset = getDataset(testSpace.dataset(WorkflowAppWithLocalDatasets.WORDCOUNT_DATASET));
    Assert.assertNull(localDataset.get());
    fileSetDataset = getDataset(testSpace.dataset(WorkflowAppWithLocalDatasets.CSV_FILESET_DATASET));
    Assert.assertNull(fileSetDataset.get());
    // Verify that the workflow hasn't completed on its own before we signal it to
    history = wfManager.getHistory(ProgramRunStatus.RUNNING);
    Assert.assertEquals(1, history.size());
    // Signal the Workflow to continue
    doneFile.createNewFile();
    // Wait for workflow to finish
    wfManager.waitForRuns(ProgramRunStatus.COMPLETED, expectedComplete, 1, TimeUnit.MINUTES);
    Map<String, WorkflowNodeStateDetail> nodeStateDetailMap = wfManager.getWorkflowNodeStates(runId);
    Map<String, String> workflowMetricsContext = new HashMap<>();
    workflowMetricsContext.put(Constants.Metrics.Tag.NAMESPACE, testSpace.getNamespace());
    workflowMetricsContext.put(Constants.Metrics.Tag.APP, applicationManager.getInfo().getName());
    workflowMetricsContext.put(Constants.Metrics.Tag.WORKFLOW, WorkflowAppWithLocalDatasets.WORKFLOW_NAME);
    workflowMetricsContext.put(Constants.Metrics.Tag.RUN_ID, runId);
    Map<String, String> writerContext = new HashMap<>(workflowMetricsContext);
    writerContext.put(Constants.Metrics.Tag.NODE, WorkflowAppWithLocalDatasets.LocalDatasetWriter.class.getSimpleName());
    Assert.assertEquals(2, getMetricsManager().getTotalMetric(writerContext, "user.num.lines"));
    Map<String, String> wfSparkMetricsContext = new HashMap<>(workflowMetricsContext);
    wfSparkMetricsContext.put(Constants.Metrics.Tag.NODE, "JavaSparkCSVToSpaceConverter");
    Assert.assertEquals(2, getMetricsManager().getTotalMetric(wfSparkMetricsContext, "user.num.lines"));
    // check in spark context
    Map<String, String> sparkMetricsContext = new HashMap<>();
    sparkMetricsContext.put(Constants.Metrics.Tag.NAMESPACE, testSpace.getNamespace());
    sparkMetricsContext.put(Constants.Metrics.Tag.APP, applicationManager.getInfo().getName());
    sparkMetricsContext.put(Constants.Metrics.Tag.SPARK, "JavaSparkCSVToSpaceConverter");
    sparkMetricsContext.put(Constants.Metrics.Tag.RUN_ID, nodeStateDetailMap.get("JavaSparkCSVToSpaceConverter").getRunId());
    Assert.assertEquals(2, getMetricsManager().getTotalMetric(sparkMetricsContext, "user.num.lines"));
    Map<String, String> appMetricsContext = new HashMap<>();
    appMetricsContext.put(Constants.Metrics.Tag.NAMESPACE, testSpace.getNamespace());
    appMetricsContext.put(Constants.Metrics.Tag.APP, applicationManager.getInfo().getName());
    // app metrics context should have sum from custom action and spark metrics.
    Assert.assertEquals(4, getMetricsManager().getTotalMetric(appMetricsContext, "user.num.lines"));
    Map<String, String> wfMRMetricsContext = new HashMap<>(workflowMetricsContext);
    wfMRMetricsContext.put(Constants.Metrics.Tag.NODE, "WordCount");
    Assert.assertEquals(7, getMetricsManager().getTotalMetric(wfMRMetricsContext, "user.num.words"));
    // mr metrics context
    Map<String, String> mrMetricsContext = new HashMap<>();
    mrMetricsContext.put(Constants.Metrics.Tag.NAMESPACE, testSpace.getNamespace());
    mrMetricsContext.put(Constants.Metrics.Tag.APP, applicationManager.getInfo().getName());
    mrMetricsContext.put(Constants.Metrics.Tag.MAPREDUCE, "WordCount");
    mrMetricsContext.put(Constants.Metrics.Tag.RUN_ID, nodeStateDetailMap.get("WordCount").getRunId());
    Assert.assertEquals(7, getMetricsManager().getTotalMetric(mrMetricsContext, "user.num.words"));
    final Map<String, String> readerContext = new HashMap<>(workflowMetricsContext);
    readerContext.put(Constants.Metrics.Tag.NODE, "readerAction");
    Tasks.waitFor(6L, new Callable<Long>() {

        @Override
        public Long call() throws Exception {
            return getMetricsManager().getTotalMetric(readerContext, "user.unique.words");
        }
    }, 60, TimeUnit.SECONDS);
    return runId;
}

Example 40 with KeyValueTable

use of io.cdap.cdap.api.dataset.lib.KeyValueTable in project cdap by cdapio.

the class SparkLogParser method run.

@Override
public void run(JavaSparkExecutionContext sec) throws Exception {
    JavaSparkContext jsc = new JavaSparkContext();
    Map<String, String> runtimeArguments = sec.getRuntimeArguments();
    String inputFileSet = runtimeArguments.get("input");
    final String outputTable = runtimeArguments.get("output");
    JavaPairRDD<LongWritable, Text> input = sec.fromDataset(inputFileSet);
    final JavaPairRDD<String, String> aggregated = input.mapToPair(new PairFunction<Tuple2<LongWritable, Text>, LogKey, LogStats>() {

        @Override
        public Tuple2<LogKey, LogStats> call(Tuple2<LongWritable, Text> input) throws Exception {
            return SparkAppUsingGetDataset.parse(input._2());
        }
    }).reduceByKey(new Function2<LogStats, LogStats, LogStats>() {

        @Override
        public LogStats call(LogStats stats1, LogStats stats2) throws Exception {
            return stats1.aggregate(stats2);
        }
    }).mapPartitionsToPair(new PairFlatMapFunction<Iterator<Tuple2<LogKey, LogStats>>, String, String>() {

        @Override
        public Iterator<Tuple2<String, String>> call(Iterator<Tuple2<LogKey, LogStats>> itor) throws Exception {
            final Gson gson = new Gson();
            return Lists.newArrayList(Iterators.transform(itor, new Function<Tuple2<LogKey, LogStats>, Tuple2<String, String>>() {

                @Override
                public Tuple2<String, String> apply(Tuple2<LogKey, LogStats> input) {
                    return new Tuple2<>(gson.toJson(input._1()), gson.toJson(input._2()));
                }
            })).iterator();
        }
    });
    // Collect all data to driver and write to dataset directly. That's the intend of the test.
    sec.execute(new TxRunnable() {

        @Override
        public void run(DatasetContext context) throws Exception {
            KeyValueTable kvTable = context.getDataset(outputTable);
            for (Map.Entry<String, String> entry : aggregated.collectAsMap().entrySet()) {
                kvTable.write(entry.getKey(), entry.getValue());
            }
        }
    });
}