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

Example 1 with PipelineRuntime

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

the class StreamingBatchSinkFunction method call.

@Override
public Void call(JavaRDD<T> data, Time batchTime) throws Exception {
    if (data.isEmpty()) {
        return null;
    }
    final long logicalStartTime = batchTime.milliseconds();
    MacroEvaluator evaluator = new DefaultMacroEvaluator(new BasicArguments(sec), logicalStartTime, sec.getSecureStore(), sec.getNamespace());
    PluginContext pluginContext = new SparkPipelinePluginContext(sec.getPluginContext(), sec.getMetrics(), stageSpec.isStageLoggingEnabled(), stageSpec.isProcessTimingEnabled());
    final SparkBatchSinkFactory sinkFactory = new SparkBatchSinkFactory();
    final String stageName = stageSpec.getName();
    final BatchSink<Object, Object, Object> batchSink = pluginContext.newPluginInstance(stageName, evaluator);
    final PipelineRuntime pipelineRuntime = new SparkPipelineRuntime(sec, logicalStartTime);
    boolean isPrepared = false;
    boolean isDone = false;
    try {
        sec.execute(new TxRunnable() {

            @Override
            public void run(DatasetContext datasetContext) throws Exception {
                SparkBatchSinkContext sinkContext = new SparkBatchSinkContext(sinkFactory, sec, datasetContext, pipelineRuntime, stageSpec);
                batchSink.prepareRun(sinkContext);
            }
        });
        isPrepared = true;
        PluginFunctionContext pluginFunctionContext = new PluginFunctionContext(stageSpec, sec, pipelineRuntime.getArguments().asMap(), batchTime.milliseconds(), new NoopStageStatisticsCollector());
        PairFlatMapFunc<T, Object, Object> sinkFunction = new BatchSinkFunction<T, Object, Object>(pluginFunctionContext);
        sinkFactory.writeFromRDD(data.flatMapToPair(Compat.convert(sinkFunction)), sec, stageName, Object.class, Object.class);
        isDone = true;
        sec.execute(new TxRunnable() {

            @Override
            public void run(DatasetContext datasetContext) throws Exception {
                SparkBatchSinkContext sinkContext = new SparkBatchSinkContext(sinkFactory, sec, datasetContext, pipelineRuntime, stageSpec);
                batchSink.onRunFinish(true, sinkContext);
            }
        });
    } catch (Exception e) {
        LOG.error("Error writing to sink {} for the batch for time {}.", stageName, logicalStartTime, e);
    } finally {
        if (isPrepared && !isDone) {
            sec.execute(new TxRunnable() {

                @Override
                public void run(DatasetContext datasetContext) throws Exception {
                    SparkBatchSinkContext sinkContext = new SparkBatchSinkContext(sinkFactory, sec, datasetContext, pipelineRuntime, stageSpec);
                    batchSink.onRunFinish(false, sinkContext);
                }
            });
        }
    }
    return null;
}

Example 2 with PipelineRuntime

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

the class DStreamCollection method compute.

@Override
public <U> SparkCollection<U> compute(final StageSpec stageSpec, SparkCompute<T, U> compute) throws Exception {
    final SparkCompute<T, U> wrappedCompute = new DynamicSparkCompute<>(new DynamicDriverContext(stageSpec, sec, new NoopStageStatisticsCollector()), compute);
    Transactionals.execute(sec, new TxRunnable() {

        @Override
        public void run(DatasetContext datasetContext) throws Exception {
            PipelineRuntime pipelineRuntime = new SparkPipelineRuntime(sec);
            SparkExecutionPluginContext sparkPluginContext = new BasicSparkExecutionPluginContext(sec, JavaSparkContext.fromSparkContext(stream.context().sparkContext()), datasetContext, pipelineRuntime, stageSpec);
            wrappedCompute.initialize(sparkPluginContext);
        }
    }, Exception.class);
    return wrap(stream.transform(new ComputeTransformFunction<>(sec, stageSpec, wrappedCompute)));
}

Example 3 with PipelineRuntime

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

the class StreamingSparkSinkFunction method call.

@Override
public Void call(JavaRDD<T> data, Time batchTime) throws Exception {
    if (data.isEmpty()) {
        return null;
    }
    final long logicalStartTime = batchTime.milliseconds();
    MacroEvaluator evaluator = new DefaultMacroEvaluator(new BasicArguments(sec), logicalStartTime, sec.getSecureStore(), sec.getNamespace());
    final PluginContext pluginContext = new SparkPipelinePluginContext(sec.getPluginContext(), sec.getMetrics(), stageSpec.isStageLoggingEnabled(), stageSpec.isProcessTimingEnabled());
    final PipelineRuntime pipelineRuntime = new SparkPipelineRuntime(sec, batchTime.milliseconds());
    final String stageName = stageSpec.getName();
    final SparkSink<T> sparkSink = pluginContext.newPluginInstance(stageName, evaluator);
    boolean isPrepared = false;
    boolean isDone = false;
    try {
        sec.execute(new TxRunnable() {

            @Override
            public void run(DatasetContext datasetContext) throws Exception {
                SparkPluginContext context = new BasicSparkPluginContext(null, pipelineRuntime, stageSpec, datasetContext, sec.getAdmin());
                sparkSink.prepareRun(context);
            }
        });
        isPrepared = true;
        final SparkExecutionPluginContext sparkExecutionPluginContext = new SparkStreamingExecutionContext(sec, JavaSparkContext.fromSparkContext(data.rdd().context()), logicalStartTime, stageSpec);
        final JavaRDD<T> countedRDD = data.map(new CountingFunction<T>(stageName, sec.getMetrics(), "records.in", null)).cache();
        sec.execute(new TxRunnable() {

            @Override
            public void run(DatasetContext context) throws Exception {
                sparkSink.run(sparkExecutionPluginContext, countedRDD);
            }
        });
        isDone = true;
        sec.execute(new TxRunnable() {

            @Override
            public void run(DatasetContext datasetContext) throws Exception {
                SparkPluginContext context = new BasicSparkPluginContext(null, pipelineRuntime, stageSpec, datasetContext, sec.getAdmin());
                sparkSink.onRunFinish(true, context);
            }
        });
    } catch (Exception e) {
        LOG.error("Error while executing sink {} for the batch for time {}.", stageName, logicalStartTime, e);
    } finally {
        if (isPrepared && !isDone) {
            sec.execute(new TxRunnable() {

                @Override
                public void run(DatasetContext datasetContext) throws Exception {
                    SparkPluginContext context = new BasicSparkPluginContext(null, pipelineRuntime, stageSpec, datasetContext, sec.getAdmin());
                    sparkSink.onRunFinish(false, context);
                }
            });
        }
    }
    return null;
}

Example 4 with PipelineRuntime

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

the class ETLMapReduce method initialize.

@Override
@TransactionPolicy(TransactionControl.EXPLICIT)
public void initialize() throws Exception {
    final MapReduceContext context = getContext();
    Map<String, String> properties = context.getSpecification().getProperties();
    if (Boolean.valueOf(properties.get(Constants.STAGE_LOGGING_ENABLED))) {
        LogStageInjector.start();
    }
    PipelineRuntime pipelineRuntime = new PipelineRuntime(context, mrMetrics);
    List<Finisher> finishers = new ArrayList<>();
    final Job job = context.getHadoopJob();
    final Configuration hConf = job.getConfiguration();
    hConf.setBoolean("mapreduce.map.speculative", false);
    hConf.setBoolean("mapreduce.reduce.speculative", false);
    // plugin name -> runtime args for that plugin
    MacroEvaluator evaluator = new DefaultMacroEvaluator(pipelineRuntime.getArguments(), context.getLogicalStartTime(), context, context.getNamespace());
    BatchPhaseSpec phaseSpec = GSON.fromJson(properties.get(Constants.PIPELINEID), BatchPhaseSpec.class);
    Set<String> connectorDatasets = GSON.fromJson(properties.get(Constants.CONNECTOR_DATASETS), CONNECTOR_DATASETS_TYPE);
    for (Map.Entry<String, String> pipelineProperty : phaseSpec.getPipelineProperties().entrySet()) {
        hConf.set(pipelineProperty.getKey(), pipelineProperty.getValue());
    }
    final PipelinePhase phase = phaseSpec.getPhase();
    PipelinePluginInstantiator pluginInstantiator = new PipelinePluginInstantiator(context, mrMetrics, phaseSpec, new MultiConnectorFactory());
    // should never happen if planner is correct
    Set<StageSpec> reducers = phaseSpec.getPhase().getStagesOfType(BatchAggregator.PLUGIN_TYPE, BatchJoiner.PLUGIN_TYPE);
    if (reducers.size() > 1) {
        Iterator<StageSpec> reducerIter = reducers.iterator();
        StringBuilder reducersStr = new StringBuilder(reducerIter.next().getName());
        while (reducerIter.hasNext()) {
            reducersStr.append(",");
            reducersStr.append(reducerIter.next().getName());
        }
        throw new IllegalStateException("Found multiple reducers ( " + reducersStr + " ) in the same pipeline phase. " + "This means there was a bug in planning the pipeline when it was deployed. ");
    }
    job.setMapperClass(ETLMapper.class);
    if (reducers.isEmpty()) {
        job.setNumReduceTasks(0);
    } else {
        job.setReducerClass(ETLReducer.class);
    }
    final Map<String, SinkOutput> sinkOutputs = new HashMap<>();
    final Map<String, String> inputAliasToStage = new HashMap<>();
    // call prepareRun on each stage in order so that any arguments set by a stage will be visible to subsequent stages
    for (final String stageName : phase.getDag().getTopologicalOrder()) {
        final StageSpec stageSpec = phase.getStage(stageName);
        String pluginType = stageSpec.getPluginType();
        boolean isConnectorSource = Constants.Connector.PLUGIN_TYPE.equals(pluginType) && phase.getSources().contains(stageName);
        boolean isConnectorSink = Constants.Connector.PLUGIN_TYPE.equals(pluginType) && phase.getSinks().contains(stageName);
        SubmitterPlugin submitterPlugin = null;
        if (BatchSource.PLUGIN_TYPE.equals(pluginType) || isConnectorSource) {
            BatchConfigurable<BatchSourceContext> batchSource = pluginInstantiator.newPluginInstance(stageName, evaluator);
            ContextProvider<MapReduceBatchContext> contextProvider = new MapReduceBatchContextProvider(context, pipelineRuntime, stageSpec, connectorDatasets);
            submitterPlugin = new SubmitterPlugin<>(stageName, context, batchSource, contextProvider, new SubmitterPlugin.PrepareAction<MapReduceBatchContext>() {

                @Override
                public void act(MapReduceBatchContext sourceContext) {
                    for (String inputAlias : sourceContext.getInputNames()) {
                        inputAliasToStage.put(inputAlias, stageName);
                    }
                }
            });
        } else if (BatchSink.PLUGIN_TYPE.equals(pluginType) || AlertPublisher.PLUGIN_TYPE.equals(pluginType) || isConnectorSink) {
            BatchConfigurable<BatchSinkContext> batchSink = pluginInstantiator.newPluginInstance(stageName, evaluator);
            ContextProvider<MapReduceBatchContext> contextProvider = new MapReduceBatchContextProvider(context, pipelineRuntime, stageSpec, connectorDatasets);
            submitterPlugin = new SubmitterPlugin<>(stageName, context, batchSink, contextProvider, new SubmitterPlugin.PrepareAction<MapReduceBatchContext>() {

                @Override
                public void act(MapReduceBatchContext sinkContext) {
                    sinkOutputs.put(stageName, new SinkOutput(sinkContext.getOutputNames()));
                }
            });
        } else if (Transform.PLUGIN_TYPE.equals(pluginType)) {
            Transform<?, ?> transform = pluginInstantiator.newPluginInstance(stageName, evaluator);
            ContextProvider<MapReduceBatchContext> contextProvider = new MapReduceBatchContextProvider(context, pipelineRuntime, stageSpec, connectorDatasets);
            submitterPlugin = new SubmitterPlugin<>(stageName, context, transform, contextProvider);
        } else if (BatchAggregator.PLUGIN_TYPE.equals(pluginType)) {
            final BatchAggregator<?, ?, ?> aggregator = pluginInstantiator.newPluginInstance(stageName, evaluator);
            ContextProvider<DefaultAggregatorContext> contextProvider = new AggregatorContextProvider(pipelineRuntime, stageSpec, context.getAdmin());
            submitterPlugin = new SubmitterPlugin<>(stageName, context, aggregator, contextProvider, new SubmitterPlugin.PrepareAction<DefaultAggregatorContext>() {

                @Override
                public void act(DefaultAggregatorContext aggregatorContext) {
                    if (aggregatorContext.getNumPartitions() != null) {
                        job.setNumReduceTasks(aggregatorContext.getNumPartitions());
                    }
                    Class<?> outputKeyClass = aggregatorContext.getGroupKeyClass();
                    Class<?> outputValClass = aggregatorContext.getGroupValueClass();
                    if (outputKeyClass == null) {
                        outputKeyClass = TypeChecker.getGroupKeyClass(aggregator);
                    }
                    if (outputValClass == null) {
                        outputValClass = TypeChecker.getGroupValueClass(aggregator);
                    }
                    hConf.set(MAP_KEY_CLASS, outputKeyClass.getName());
                    hConf.set(MAP_VAL_CLASS, outputValClass.getName());
                    job.setMapOutputKeyClass(getOutputKeyClass(stageName, outputKeyClass));
                    job.setMapOutputValueClass(getOutputValClass(stageName, outputValClass));
                }
            });
        } else if (BatchJoiner.PLUGIN_TYPE.equals(pluginType)) {
            final BatchJoiner<?, ?, ?> batchJoiner = pluginInstantiator.newPluginInstance(stageName, evaluator);
            ContextProvider<DefaultJoinerContext> contextProvider = new JoinerContextProvider(pipelineRuntime, stageSpec, context.getAdmin());
            submitterPlugin = new SubmitterPlugin<>(stageName, context, batchJoiner, contextProvider, new SubmitterPlugin.PrepareAction<DefaultJoinerContext>() {

                @Override
                public void act(DefaultJoinerContext joinerContext) {
                    if (joinerContext.getNumPartitions() != null) {
                        job.setNumReduceTasks(joinerContext.getNumPartitions());
                    }
                    Class<?> outputKeyClass = joinerContext.getJoinKeyClass();
                    Class<?> inputRecordClass = joinerContext.getJoinInputRecordClass();
                    if (outputKeyClass == null) {
                        outputKeyClass = TypeChecker.getJoinKeyClass(batchJoiner);
                    }
                    if (inputRecordClass == null) {
                        inputRecordClass = TypeChecker.getJoinInputRecordClass(batchJoiner);
                    }
                    hConf.set(MAP_KEY_CLASS, outputKeyClass.getName());
                    hConf.set(MAP_VAL_CLASS, inputRecordClass.getName());
                    job.setMapOutputKeyClass(getOutputKeyClass(stageName, outputKeyClass));
                    getOutputValClass(stageName, inputRecordClass);
                    // for joiner plugin map output is tagged with stageName
                    job.setMapOutputValueClass(TaggedWritable.class);
                }
            });
        }
        if (submitterPlugin != null) {
            submitterPlugin.prepareRun();
            finishers.add(submitterPlugin);
        }
    }
    hConf.set(SINK_OUTPUTS_KEY, GSON.toJson(sinkOutputs));
    hConf.set(INPUT_ALIAS_KEY, GSON.toJson(inputAliasToStage));
    finisher = new CompositeFinisher(finishers);
    job.setMapperClass(ETLMapper.class);
    WorkflowToken token = context.getWorkflowToken();
    if (token != null) {
        for (Map.Entry<String, String> entry : pipelineRuntime.getArguments().getAddedArguments().entrySet()) {
            token.put(entry.getKey(), entry.getValue());
        }
    }
    // token is null when just the mapreduce job is run but not the entire workflow
    // we still want things to work in that case.
    hConf.set(RUNTIME_ARGS_KEY, GSON.toJson(pipelineRuntime.getArguments().asMap()));
}

Example 5 with PipelineRuntime

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

the class PipelineCondition method apply.

@Override
public boolean apply(@Nullable WorkflowContext input) {
    if (input == null) {
        // should not happen
        throw new IllegalStateException("WorkflowContext for the Condition cannot be null.");
    }
    Map<String, String> properties = input.getConditionSpecification().getProperties();
    BatchPhaseSpec phaseSpec = GSON.fromJson(properties.get(Constants.PIPELINEID), BatchPhaseSpec.class);
    PipelinePhase phase = phaseSpec.getPhase();
    StageSpec stageSpec = phase.iterator().next();
    PluginContext pluginContext = new PipelinePluginContext(input, metrics, phaseSpec.isStageLoggingEnabled(), phaseSpec.isProcessTimingEnabled());
    MacroEvaluator macroEvaluator = new DefaultMacroEvaluator(new BasicArguments(input.getToken(), input.getRuntimeArguments()), input.getLogicalStartTime(), input, input.getNamespace());
    try {
        Condition condition = pluginContext.newPluginInstance(stageSpec.getName(), macroEvaluator);
        PipelineRuntime pipelineRuntime = new PipelineRuntime(input, metrics);
        ConditionContext conditionContext = new BasicConditionContext(input, pipelineRuntime, stageSpec);
        boolean result = condition.apply(conditionContext);
        WorkflowToken token = input.getToken();
        if (token == null) {
            throw new IllegalStateException("WorkflowToken cannot be null when Condition is executed through Workflow.");
        }
        for (Map.Entry<String, String> entry : pipelineRuntime.getArguments().getAddedArguments().entrySet()) {
            token.put(entry.getKey(), entry.getValue());
        }
        return result;
    } catch (Exception e) {
        String msg = String.format("Error executing condition '%s' in the pipeline.", stageSpec.getName());
        throw new RuntimeException(msg, e);
    }
}