Examples with DefaultMacroEvaluator co.cask.cdap.etl.common.DefaultMacroEvaluator used on opensource projects

Example 6 with DefaultMacroEvaluator

use of co.cask.cdap.etl.common.DefaultMacroEvaluator in project cdap by caskdata.

the class ETLWorkflow method initialize.

@Override
public void initialize(WorkflowContext context) throws Exception {
    super.initialize(context);
    postActions = new LinkedHashMap<>();
    BatchPipelineSpec batchPipelineSpec = GSON.fromJson(context.getWorkflowSpecification().getProperty("pipeline.spec"), BatchPipelineSpec.class);
    MacroEvaluator macroEvaluator = new DefaultMacroEvaluator(context.getToken(), context.getRuntimeArguments(), context.getLogicalStartTime(), context, context.getNamespace());
    for (ActionSpec actionSpec : batchPipelineSpec.getEndingActions()) {
        postActions.put(actionSpec.getName(), (PostAction) context.newPluginInstance(actionSpec.getName(), macroEvaluator));
    }
}

Example 7 with DefaultMacroEvaluator

use of co.cask.cdap.etl.common.DefaultMacroEvaluator in project cdap by caskdata.

the class PipelineAction method run.

@Override
public void run() throws Exception {
    CustomActionContext context = getContext();
    Map<String, String> properties = context.getSpecification().getProperties();
    BatchPhaseSpec phaseSpec = GSON.fromJson(properties.get(Constants.PIPELINEID), BatchPhaseSpec.class);
    PipelinePhase phase = phaseSpec.getPhase();
    StageInfo stageInfo = phase.iterator().next();
    PluginContext pluginContext = new PipelinePluginContext(context, metrics, phaseSpec.isStageLoggingEnabled(), phaseSpec.isProcessTimingEnabled());
    Action action = pluginContext.newPluginInstance(stageInfo.getName(), new DefaultMacroEvaluator(context.getWorkflowToken(), context.getRuntimeArguments(), context.getLogicalStartTime(), context, context.getNamespace()));
    BasicArguments arguments = new BasicArguments(context);
    ActionContext actionContext = new BasicActionContext(context, metrics, stageInfo.getName(), arguments);
    if (!context.getDataTracer(stageInfo.getName()).isEnabled()) {
        action.run(actionContext);
    }
    WorkflowToken token = context.getWorkflowToken();
    if (token == null) {
        throw new IllegalStateException("WorkflowToken cannot be null when action is executed through Workflow.");
    }
    for (Map.Entry<String, String> entry : arguments.getAddedArguments().entrySet()) {
        token.put(entry.getKey(), entry.getValue());
    }
}

Example 8 with DefaultMacroEvaluator

use of co.cask.cdap.etl.common.DefaultMacroEvaluator in project cdap by caskdata.

the class ETLSpark method initialize.

@Override
public void initialize() throws Exception {
    SparkClientContext context = getContext();
    cleanupFiles = new ArrayList<>();
    CompositeFinisher.Builder finishers = CompositeFinisher.builder();
    SparkConf sparkConf = new SparkConf();
    sparkConf.set("spark.driver.extraJavaOptions", "-XX:MaxPermSize=256m");
    sparkConf.set("spark.executor.extraJavaOptions", "-XX:MaxPermSize=256m");
    sparkConf.set("spark.speculation", "false");
    context.setSparkConf(sparkConf);
    Map<String, String> properties = context.getSpecification().getProperties();
    BatchPhaseSpec phaseSpec = GSON.fromJson(properties.get(Constants.PIPELINEID), BatchPhaseSpec.class);
    for (Map.Entry<String, String> pipelineProperty : phaseSpec.getPipelineProperties().entrySet()) {
        sparkConf.set(pipelineProperty.getKey(), pipelineProperty.getValue());
    }
    MacroEvaluator evaluator = new DefaultMacroEvaluator(context.getWorkflowToken(), context.getRuntimeArguments(), context.getLogicalStartTime(), context, context.getNamespace());
    SparkBatchSourceFactory sourceFactory = new SparkBatchSourceFactory();
    SparkBatchSinkFactory sinkFactory = new SparkBatchSinkFactory();
    Map<String, Integer> stagePartitions = new HashMap<>();
    PluginContext pluginContext = new SparkPipelinePluginContext(context, context.getMetrics(), phaseSpec.isStageLoggingEnabled(), phaseSpec.isProcessTimingEnabled());
    for (StageInfo stageInfo : phaseSpec.getPhase()) {
        String stageName = stageInfo.getName();
        String pluginType = stageInfo.getPluginType();
        if (BatchSource.PLUGIN_TYPE.equals(pluginType)) {
            BatchConfigurable<BatchSourceContext> batchSource = pluginContext.newPluginInstance(stageName, evaluator);
            BatchSourceContext sourceContext = new SparkBatchSourceContext(sourceFactory, context, stageInfo);
            batchSource.prepareRun(sourceContext);
            finishers.add(batchSource, sourceContext);
        } else if (BatchSink.PLUGIN_TYPE.equals(pluginType)) {
            BatchConfigurable<BatchSinkContext> batchSink = pluginContext.newPluginInstance(stageName, evaluator);
            BatchSinkContext sinkContext = new SparkBatchSinkContext(sinkFactory, context, null, stageInfo);
            batchSink.prepareRun(sinkContext);
            finishers.add(batchSink, sinkContext);
        } else if (SparkSink.PLUGIN_TYPE.equals(pluginType)) {
            BatchConfigurable<SparkPluginContext> sparkSink = pluginContext.newPluginInstance(stageName, evaluator);
            SparkPluginContext sparkPluginContext = new BasicSparkPluginContext(context, stageInfo);
            sparkSink.prepareRun(sparkPluginContext);
            finishers.add(sparkSink, sparkPluginContext);
        } else if (BatchAggregator.PLUGIN_TYPE.equals(pluginType)) {
            BatchAggregator aggregator = pluginContext.newPluginInstance(stageName, evaluator);
            DefaultAggregatorContext aggregatorContext = new DefaultAggregatorContext(context, stageInfo);
            aggregator.prepareRun(aggregatorContext);
            finishers.add(aggregator, aggregatorContext);
            stagePartitions.put(stageName, aggregatorContext.getNumPartitions());
        } else if (BatchJoiner.PLUGIN_TYPE.equals(pluginType)) {
            BatchJoiner joiner = pluginContext.newPluginInstance(stageName, evaluator);
            DefaultJoinerContext sparkJoinerContext = new DefaultJoinerContext(context, stageInfo);
            joiner.prepareRun(sparkJoinerContext);
            finishers.add(joiner, sparkJoinerContext);
            stagePartitions.put(stageName, sparkJoinerContext.getNumPartitions());
        }
    }
    File configFile = File.createTempFile("HydratorSpark", ".config");
    cleanupFiles.add(configFile);
    try (Writer writer = Files.newBufferedWriter(configFile.toPath(), StandardCharsets.UTF_8)) {
        SparkBatchSourceSinkFactoryInfo sourceSinkInfo = new SparkBatchSourceSinkFactoryInfo(sourceFactory, sinkFactory, stagePartitions);
        writer.write(GSON.toJson(sourceSinkInfo));
    }
    finisher = finishers.build();
    context.localize("HydratorSpark.config", configFile.toURI());
}

Example 9 with DefaultMacroEvaluator

use of co.cask.cdap.etl.common.DefaultMacroEvaluator in project cdap by caskdata.

the class SmartWorkflow method initialize.

@Override
public void initialize(WorkflowContext context) throws Exception {
    super.initialize(context);
    String arguments = Joiner.on(", ").withKeyValueSeparator("=").join(context.getRuntimeArguments());
    WRAPPERLOGGER.info("Pipeline '{}' is started by user '{}' with arguments {}", context.getApplicationSpecification().getName(), UserGroupInformation.getCurrentUser().getShortUserName(), arguments);
    postActions = new LinkedHashMap<>();
    spec = GSON.fromJson(context.getWorkflowSpecification().getProperty(Constants.PIPELINE_SPEC_KEY), BatchPipelineSpec.class);
    MacroEvaluator macroEvaluator = new DefaultMacroEvaluator(context.getToken(), context.getRuntimeArguments(), context.getLogicalStartTime(), context, context.getNamespace());
    PluginContext pluginContext = new PipelinePluginContext(context, workflowMetrics, spec.isStageLoggingEnabled(), spec.isProcessTimingEnabled());
    for (ActionSpec actionSpec : spec.getEndingActions()) {
        postActions.put(actionSpec.getName(), (PostAction) pluginContext.newPluginInstance(actionSpec.getName(), macroEvaluator));
    }
    WRAPPERLOGGER.info("Pipeline '{}' running", context.getApplicationSpecification().getName());
}

Example 10 with DefaultMacroEvaluator

use of co.cask.cdap.etl.common.DefaultMacroEvaluator in project cdap by caskdata.

the class MapReduceTransformExecutorFactory method getTransformation.

@SuppressWarnings("unchecked")
@Override
protected TrackedTransform getTransformation(StageInfo stageInfo) throws Exception {
    DefaultMacroEvaluator macroEvaluator = new DefaultMacroEvaluator(taskContext.getWorkflowToken(), taskContext.getRuntimeArguments(), taskContext.getLogicalStartTime(), taskContext, taskContext.getNamespace());
    String stageName = stageInfo.getName();
    String pluginType = stageInfo.getPluginType();
    StageMetrics stageMetrics = new DefaultStageMetrics(metrics, stageName);
    if (BatchAggregator.PLUGIN_TYPE.equals(pluginType)) {
        BatchAggregator<?, ?, ?> batchAggregator = pluginInstantiator.newPluginInstance(stageName, macroEvaluator);
        BatchRuntimeContext runtimeContext = createRuntimeContext(stageInfo);
        batchAggregator.initialize(runtimeContext);
        if (isMapPhase) {
            return getTrackedEmitKeyStep(new MapperAggregatorTransformation(batchAggregator, mapOutputKeyClassName, mapOutputValClassName), stageMetrics, taskContext.getDataTracer(stageName));
        } else {
            return getTrackedAggregateStep(new ReducerAggregatorTransformation(batchAggregator, mapOutputKeyClassName, mapOutputValClassName), stageMetrics, taskContext.getDataTracer(stageName));
        }
    } else if (BatchJoiner.PLUGIN_TYPE.equals(pluginType)) {
        BatchJoiner<?, ?, ?> batchJoiner = pluginInstantiator.newPluginInstance(stageName, macroEvaluator);
        BatchJoinerRuntimeContext runtimeContext = createRuntimeContext(stageInfo);
        batchJoiner.initialize(runtimeContext);
        if (isMapPhase) {
            return getTrackedEmitKeyStep(new MapperJoinerTransformation(batchJoiner, mapOutputKeyClassName, mapOutputValClassName), stageMetrics, taskContext.getDataTracer(stageName));
        } else {
            return getTrackedMergeStep(new ReducerJoinerTransformation(batchJoiner, mapOutputKeyClassName, mapOutputValClassName, runtimeContext.getInputSchemas().size()), stageMetrics, taskContext.getDataTracer(stageName));
        }
    }
    Transformation transformation = getInitializedTransformation(stageInfo);
    boolean isLimitingSource = taskContext.getDataTracer(stageName).isEnabled() && BatchSource.PLUGIN_TYPE.equals(pluginType) && isMapPhase;
    return new TrackedTransform(isLimitingSource ? new LimitingTransform(transformation, numberOfRecordsPreview) : transformation, stageMetrics, taskContext.getDataTracer(stageName));
}