Examples with AppRequest co.cask.cdap.proto.artifact.AppRequest used on opensource projects

Example 66 with AppRequest

use of co.cask.cdap.proto.artifact.AppRequest in project cdap by caskdata.

the class DataPipelineTest method testParallelAggregators.

private void testParallelAggregators(Engine engine) throws Exception {
    String source1Name = "pAggInput1-" + engine.name();
    String source2Name = "pAggInput2-" + engine.name();
    String sink1Name = "pAggOutput1-" + engine.name();
    String sink2Name = "pAggOutput2-" + engine.name();
    Schema inputSchema = Schema.recordOf("testRecord", Schema.Field.of("user", Schema.of(Schema.Type.STRING)), Schema.Field.of("item", Schema.of(Schema.Type.LONG)));
    /*
       source1 --|--> agg1 --> sink1
                 |
       source2 --|--> agg2 --> sink2
     */
    ETLBatchConfig etlConfig = ETLBatchConfig.builder("* * * * *").setEngine(engine).addStage(new ETLStage("source1", MockSource.getPlugin(source1Name, inputSchema))).addStage(new ETLStage("source2", MockSource.getPlugin(source2Name, inputSchema))).addStage(new ETLStage("sink1", MockSink.getPlugin(sink1Name))).addStage(new ETLStage("sink2", MockSink.getPlugin(sink2Name))).addStage(new ETLStage("agg1", FieldCountAggregator.getPlugin("user", "string"))).addStage(new ETLStage("agg2", FieldCountAggregator.getPlugin("item", "long"))).addConnection("source1", "agg1").addConnection("source1", "agg2").addConnection("source2", "agg1").addConnection("source2", "agg2").addConnection("agg1", "sink1").addConnection("agg2", "sink2").build();
    AppRequest<ETLBatchConfig> appRequest = new AppRequest<>(APP_ARTIFACT, etlConfig);
    ApplicationId appId = NamespaceId.DEFAULT.app("ParallelAggApp-" + engine);
    ApplicationManager appManager = deployApplication(appId.toId(), appRequest);
    // write few records to each source
    DataSetManager<Table> inputManager = getDataset(NamespaceId.DEFAULT.dataset(source1Name));
    MockSource.writeInput(inputManager, ImmutableList.of(StructuredRecord.builder(inputSchema).set("user", "samuel").set("item", 1L).build(), StructuredRecord.builder(inputSchema).set("user", "samuel").set("item", 2L).build()));
    inputManager = getDataset(NamespaceId.DEFAULT.dataset(source2Name));
    MockSource.writeInput(inputManager, ImmutableList.of(StructuredRecord.builder(inputSchema).set("user", "samuel").set("item", 3L).build(), StructuredRecord.builder(inputSchema).set("user", "john").set("item", 4L).build(), StructuredRecord.builder(inputSchema).set("user", "john").set("item", 3L).build()));
    WorkflowManager workflowManager = appManager.getWorkflowManager(SmartWorkflow.NAME);
    workflowManager.start();
    workflowManager.waitForRun(ProgramRunStatus.COMPLETED, 5, TimeUnit.MINUTES);
    Schema outputSchema1 = Schema.recordOf("user.count", Schema.Field.of("user", Schema.of(Schema.Type.STRING)), Schema.Field.of("ct", Schema.of(Schema.Type.LONG)));
    Schema outputSchema2 = Schema.recordOf("item.count", Schema.Field.of("item", Schema.of(Schema.Type.LONG)), Schema.Field.of("ct", Schema.of(Schema.Type.LONG)));
    // check output
    DataSetManager<Table> sinkManager = getDataset(sink1Name);
    Set<StructuredRecord> expected = ImmutableSet.of(StructuredRecord.builder(outputSchema1).set("user", "all").set("ct", 5L).build(), StructuredRecord.builder(outputSchema1).set("user", "samuel").set("ct", 3L).build(), StructuredRecord.builder(outputSchema1).set("user", "john").set("ct", 2L).build());
    Set<StructuredRecord> actual = Sets.newHashSet(MockSink.readOutput(sinkManager));
    Assert.assertEquals(expected, actual);
    sinkManager = getDataset(sink2Name);
    expected = ImmutableSet.of(StructuredRecord.builder(outputSchema2).set("item", 0L).set("ct", 5L).build(), StructuredRecord.builder(outputSchema2).set("item", 1L).set("ct", 1L).build(), StructuredRecord.builder(outputSchema2).set("item", 2L).set("ct", 1L).build(), StructuredRecord.builder(outputSchema2).set("item", 3L).set("ct", 2L).build(), StructuredRecord.builder(outputSchema2).set("item", 4L).set("ct", 1L).build());
    actual = Sets.newHashSet(MockSink.readOutput(sinkManager));
    Assert.assertEquals(expected, actual);
    validateMetric(2, appId, "source1.records.out");
    validateMetric(3, appId, "source2.records.out");
    validateMetric(5, appId, "agg1.records.in");
    // 2 users, but FieldCountAggregator always emits an 'all' group
    validateMetric(3, appId, "agg1.aggregator.groups");
    validateMetric(3, appId, "agg1.records.out");
    validateMetric(5, appId, "agg2.records.in");
    // 4 items, but FieldCountAggregator always emits an 'all' group
    validateMetric(5, appId, "agg2.aggregator.groups");
    validateMetric(5, appId, "agg2.records.out");
    validateMetric(3, appId, "sink1.records.in");
    validateMetric(5, appId, "sink2.records.in");
}

Example 67 with AppRequest

use of co.cask.cdap.proto.artifact.AppRequest in project cdap by caskdata.

the class DataPipelineTest method testSinglePhaseWithSparkSink.

private void testSinglePhaseWithSparkSink() throws Exception {
    /*
     * source1 ---|
     *            |--> sparksink
     * source2 ---|
     */
    ETLBatchConfig etlConfig = ETLBatchConfig.builder("* * * * *").addStage(new ETLStage("source1", MockSource.getPlugin("messages1", SpamMessage.SCHEMA))).addStage(new ETLStage("source2", MockSource.getPlugin("messages2", SpamMessage.SCHEMA))).addStage(new ETLStage("customsink", new ETLPlugin(NaiveBayesTrainer.PLUGIN_NAME, SparkSink.PLUGIN_TYPE, ImmutableMap.of("fileSetName", "modelFileSet", "path", "output", "fieldToClassify", SpamMessage.TEXT_FIELD, "predictionField", SpamMessage.SPAM_PREDICTION_FIELD), null))).addConnection("source1", "customsink").addConnection("source2", "customsink").build();
    AppRequest<ETLBatchConfig> appRequest = new AppRequest<>(APP_ARTIFACT, etlConfig);
    ApplicationId appId = NamespaceId.DEFAULT.app("SparkSinkApp");
    ApplicationManager appManager = deployApplication(appId.toId(), appRequest);
    // set up five spam messages and five non-spam messages to be used for classification
    List<StructuredRecord> messagesToWrite = new ArrayList<>();
    messagesToWrite.add(new SpamMessage("buy our clothes", 1.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("sell your used books to us", 1.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("earn money for free", 1.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("this is definitely not spam", 1.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("you won the lottery", 1.0).toStructuredRecord());
    // write records to source1
    DataSetManager<Table> inputManager = getDataset(NamespaceId.DEFAULT.dataset("messages1"));
    MockSource.writeInput(inputManager, messagesToWrite);
    messagesToWrite.clear();
    messagesToWrite.add(new SpamMessage("how was your day", 0.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("what are you up to", 0.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("this is a genuine message", 0.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("this is an even more genuine message", 0.0).toStructuredRecord());
    messagesToWrite.add(new SpamMessage("could you send me the report", 0.0).toStructuredRecord());
    // write records to source2
    inputManager = getDataset(NamespaceId.DEFAULT.dataset("messages2"));
    MockSource.writeInput(inputManager, messagesToWrite);
    // ingest in some messages to be classified
    StreamManager textsToClassify = getStreamManager(NaiveBayesTrainer.TEXTS_TO_CLASSIFY);
    textsToClassify.send("how are you doing today");
    textsToClassify.send("free money money");
    textsToClassify.send("what are you doing today");
    textsToClassify.send("genuine report");
    // manually trigger the pipeline
    WorkflowManager workflowManager = appManager.getWorkflowManager(SmartWorkflow.NAME);
    workflowManager.start();
    workflowManager.waitForRun(ProgramRunStatus.COMPLETED, 5, TimeUnit.MINUTES);
    DataSetManager<KeyValueTable> classifiedTexts = getDataset(NaiveBayesTrainer.CLASSIFIED_TEXTS);
    Assert.assertEquals(0.0d, Bytes.toDouble(classifiedTexts.get().read("how are you doing today")), 0.01d);
    // only 'free money money' should be predicated as spam
    Assert.assertEquals(1.0d, Bytes.toDouble(classifiedTexts.get().read("free money money")), 0.01d);
    Assert.assertEquals(0.0d, Bytes.toDouble(classifiedTexts.get().read("what are you doing today")), 0.01d);
    Assert.assertEquals(0.0d, Bytes.toDouble(classifiedTexts.get().read("genuine report")), 0.01d);
    validateMetric(5, appId, "source1.records.out");
    validateMetric(5, appId, "source2.records.out");
    validateMetric(10, appId, "customsink.records.in");
}

Example 68 with AppRequest

use of co.cask.cdap.proto.artifact.AppRequest in project cdap by caskdata.

the class DataPipelineTest method testSinglePhaseWithSparkCompute.

private void testSinglePhaseWithSparkCompute() throws Exception {
    /*
     * source --> sparkcompute --> sink
     */
    String classifiedTextsTable = "classifiedTextTable";
    ETLBatchConfig etlConfig = ETLBatchConfig.builder("* * * * *").addStage(new ETLStage("source", MockSource.getPlugin(NaiveBayesTrainer.TEXTS_TO_CLASSIFY, SpamMessage.SCHEMA))).addStage(new ETLStage("sparkcompute", new ETLPlugin(NaiveBayesClassifier.PLUGIN_NAME, SparkCompute.PLUGIN_TYPE, ImmutableMap.of("fileSetName", "modelFileSet", "path", "output", "fieldToClassify", SpamMessage.TEXT_FIELD, "fieldToSet", SpamMessage.SPAM_PREDICTION_FIELD), null))).addStage(new ETLStage("sink", MockSink.getPlugin(classifiedTextsTable))).addConnection("source", "sparkcompute").addConnection("sparkcompute", "sink").build();
    AppRequest<ETLBatchConfig> appRequest = new AppRequest<>(APP_ARTIFACT, etlConfig);
    ApplicationId appId = NamespaceId.DEFAULT.app("SparkComputeApp");
    ApplicationManager appManager = deployApplication(appId.toId(), appRequest);
    // write some some messages to be classified
    List<StructuredRecord> messagesToWrite = new ArrayList<>();
    messagesToWrite.add(new SpamMessage("how are you doing today").toStructuredRecord());
    messagesToWrite.add(new SpamMessage("free money money").toStructuredRecord());
    messagesToWrite.add(new SpamMessage("what are you doing today").toStructuredRecord());
    messagesToWrite.add(new SpamMessage("genuine report").toStructuredRecord());
    DataSetManager<Table> inputManager = getDataset(NamespaceId.DEFAULT.dataset(NaiveBayesTrainer.TEXTS_TO_CLASSIFY));
    MockSource.writeInput(inputManager, messagesToWrite);
    // manually trigger the pipeline
    WorkflowManager workflowManager = appManager.getWorkflowManager(SmartWorkflow.NAME);
    workflowManager.start();
    workflowManager.waitForRun(ProgramRunStatus.COMPLETED, 5, TimeUnit.MINUTES);
    DataSetManager<Table> classifiedTexts = getDataset(classifiedTextsTable);
    List<StructuredRecord> structuredRecords = MockSink.readOutput(classifiedTexts);
    Set<SpamMessage> results = new HashSet<>();
    for (StructuredRecord structuredRecord : structuredRecords) {
        results.add(SpamMessage.fromStructuredRecord(structuredRecord));
    }
    Set<SpamMessage> expected = new HashSet<>();
    expected.add(new SpamMessage("how are you doing today", 0.0));
    // only 'free money money' should be predicated as spam
    expected.add(new SpamMessage("free money money", 1.0));
    expected.add(new SpamMessage("what are you doing today", 0.0));
    expected.add(new SpamMessage("genuine report", 0.0));
    Assert.assertEquals(expected, results);
    validateMetric(4, appId, "source.records.out");
    validateMetric(4, appId, "sparkcompute.records.in");
    validateMetric(4, appId, "sink.records.in");
}

Example 69 with AppRequest

use of co.cask.cdap.proto.artifact.AppRequest in project cdap by caskdata.

the class DataPipelineTest method testKVTableLookup.

@Test
public void testKVTableLookup() throws Exception {
    addDatasetInstance(KeyValueTable.class.getName(), "ageTable");
    DataSetManager<KeyValueTable> lookupTable = getDataset("ageTable");
    lookupTable.get().write("samuel".getBytes(Charsets.UTF_8), "12".getBytes(Charsets.UTF_8));
    lookupTable.get().write("bob".getBytes(Charsets.UTF_8), "36".getBytes(Charsets.UTF_8));
    lookupTable.get().write("jane".getBytes(Charsets.UTF_8), "25".getBytes(Charsets.UTF_8));
    lookupTable.flush();
    ETLBatchConfig etlConfig = ETLBatchConfig.builder("* * * * *").addStage(new ETLStage("source", MockSource.getPlugin("inputTable"))).addStage(new ETLStage("transform", LookupTransform.getPlugin("person", "age", "ageTable"))).addStage(new ETLStage("sink", MockSink.getPlugin("outputTable"))).addConnection("source", "transform").addConnection("transform", "sink").build();
    ApplicationId appId = NamespaceId.DEFAULT.app("testKVTableLookup");
    AppRequest<ETLBatchConfig> appRequest = new AppRequest<>(APP_ARTIFACT, etlConfig);
    ApplicationManager appManager = deployApplication(appId, appRequest);
    // set up input data
    Schema inputSchema = Schema.recordOf("person", Schema.Field.of("person", Schema.of(Schema.Type.STRING)));
    StructuredRecord recordSamuel = StructuredRecord.builder(inputSchema).set("person", "samuel").build();
    StructuredRecord recordBob = StructuredRecord.builder(inputSchema).set("person", "bob").build();
    StructuredRecord recordJane = StructuredRecord.builder(inputSchema).set("person", "jane").build();
    DataSetManager<Table> inputTable = getDataset("inputTable");
    MockSource.writeInput(inputTable, ImmutableList.of(recordSamuel, recordBob, recordJane));
    WorkflowManager workflowManager = appManager.getWorkflowManager(SmartWorkflow.NAME).start();
    workflowManager.waitForRun(ProgramRunStatus.COMPLETED, 5, TimeUnit.MINUTES);
    Schema schema = Schema.recordOf("person", Schema.Field.of("person", Schema.of(Schema.Type.STRING)), Schema.Field.of("age", Schema.of(Schema.Type.STRING)));
    Set<StructuredRecord> expected = new HashSet<>();
    expected.add(StructuredRecord.builder(schema).set("person", "samuel").set("age", "12").build());
    expected.add(StructuredRecord.builder(schema).set("person", "bob").set("age", "36").build());
    expected.add(StructuredRecord.builder(schema).set("person", "jane").set("age", "25").build());
    DataSetManager<Table> outputTable = getDataset("outputTable");
    Set<StructuredRecord> actual = new HashSet<>(MockSink.readOutput(outputTable));
    Assert.assertEquals(expected, actual);
    validateMetric(3, appId, "source.records.out");
    validateMetric(3, appId, "sink.records.in");
    deleteDatasetInstance(NamespaceId.DEFAULT.dataset("inputTable"));
    deleteDatasetInstance(NamespaceId.DEFAULT.dataset("outputTable"));
}

Example 70 with AppRequest

use of co.cask.cdap.proto.artifact.AppRequest in project cdap by caskdata.

the class DataQualityAppTest method testDefaultConfig.

@Test
public void testDefaultConfig() throws Exception {
    Map<String, Set<String>> testMap = new HashMap<>();
    Set<String> testSet = new HashSet<>();
    testSet.add("DiscreteValuesHistogram");
    testMap.put("content_length", testSet);
    DataQualityApp.DataQualityConfig config = new DataQualityApp.DataQualityConfig(WORKFLOW_SCHEDULE_MINUTES, getStreamSource(), "dataQuality", testMap);
    ApplicationId appId = NamespaceId.DEFAULT.app("newApp");
    AppRequest<DataQualityApp.DataQualityConfig> appRequest = new AppRequest<>(new ArtifactSummary(appArtifact.getArtifact(), appArtifact.getVersion()), config);
    ApplicationManager applicationManager = deployApplication(appId, appRequest);
    MapReduceManager mrManager = applicationManager.getMapReduceManager("FieldAggregator").start();
    mrManager.waitForRun(ProgramRunStatus.COMPLETED, 180, TimeUnit.SECONDS);
    Table logDataStore = (Table) getDataset("dataQuality").get();
    DiscreteValuesHistogram discreteValuesHistogramAggregationFunction = new DiscreteValuesHistogram();
    Row row;
    try (Scanner scanner = logDataStore.scan(null, null)) {
        while ((row = scanner.next()) != null) {
            if (Bytes.toString(row.getRow()).contains("content_length")) {
                Map<byte[], byte[]> columnsMapBytes = row.getColumns();
                byte[] output = columnsMapBytes.get(Bytes.toBytes("DiscreteValuesHistogram"));
                if (output != null) {
                    discreteValuesHistogramAggregationFunction.combine(output);
                }
            }
        }
    }
    Map<String, Integer> outputMap = discreteValuesHistogramAggregationFunction.retrieveAggregation();
    Map<String, Integer> expectedMap = Maps.newHashMap();
    expectedMap.put("256", 3);
    Assert.assertEquals(expectedMap, outputMap);
}