Examples with SparkExecutionPluginContext io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext used on opensource projects

Example 6 with SparkExecutionPluginContext

use of io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext 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;
    }
    final long logicalStartTime = batchTime.milliseconds();
    MacroEvaluator evaluator = new DefaultMacroEvaluator(new BasicArguments(sec), logicalStartTime, sec.getSecureStore(), sec.getServiceDiscoverer(), 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);
                }
            });
        }
    }
}

Example 7 with SparkExecutionPluginContext

use of io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext in project cdap by cdapio.

the class StreamingSparkSinkFunction method call.

@Override
public void call(JavaRDD<T> data, Time batchTime) throws Exception {
    if (data.isEmpty()) {
        return;
    }
    final long logicalStartTime = batchTime.milliseconds();
    MacroEvaluator evaluator = new DefaultMacroEvaluator(new BasicArguments(sec), logicalStartTime, sec.getSecureStore(), sec.getServiceDiscoverer(), 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);
                }
            });
        }
    }
}

Example 8 with SparkExecutionPluginContext

use of io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext in project cdap by cdapio.

the class DynamicSparkCompute method lazyInit.

// when checkpointing is enabled, and Spark is loading DStream operations from an existing checkpoint,
// delegate will be null and the initialize() method won't have been called. So we need to instantiate
// the delegate and initialize it.
private void lazyInit(final JavaSparkContext jsc) throws Exception {
    if (delegate == null) {
        PluginFunctionContext pluginFunctionContext = dynamicDriverContext.getPluginFunctionContext();
        delegate = pluginFunctionContext.createPlugin();
        final StageSpec stageSpec = pluginFunctionContext.getStageSpec();
        final JavaSparkExecutionContext sec = dynamicDriverContext.getSparkExecutionContext();
        Transactionals.execute(sec, new TxRunnable() {

            @Override
            public void run(DatasetContext datasetContext) throws Exception {
                PipelineRuntime pipelineRuntime = new SparkPipelineRuntime(sec);
                SparkExecutionPluginContext sparkPluginContext = new BasicSparkExecutionPluginContext(sec, jsc, datasetContext, pipelineRuntime, stageSpec);
                delegate.initialize(sparkPluginContext);
            }
        }, Exception.class);
    }
}

Example 9 with SparkExecutionPluginContext

use of io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext in project cdap by cdapio.

the class ComputeTransformFunction method call.

@Override
public JavaRDD<U> call(JavaRDD<T> data, Time batchTime) throws Exception {
    SparkExecutionPluginContext sparkPluginContext = new SparkStreamingExecutionContext(sec, JavaSparkContext.fromSparkContext(data.context()), batchTime.milliseconds(), stageSpec);
    String stageName = stageSpec.getName();
    data = data.map(new CountingFunction<T>(stageName, sec.getMetrics(), "records.in", null));
    return compute.transform(sparkPluginContext, data).map(new CountingFunction<U>(stageName, sec.getMetrics(), "records.out", sec.getDataTracer(stageName)));
}

Example 10 with SparkExecutionPluginContext

use of io.cdap.cdap.etl.api.batch.SparkExecutionPluginContext in project cdap by cdapio.

the class BaseRDDCollection method createStoreTask.

@Override
public Runnable createStoreTask(final StageSpec stageSpec, final SparkSink<T> sink) throws Exception {
    return new Runnable() {

        @Override
        public void run() {
            String stageName = stageSpec.getName();
            PipelineRuntime pipelineRuntime = new SparkPipelineRuntime(sec);
            SparkExecutionPluginContext sparkPluginContext = new BasicSparkExecutionPluginContext(sec, jsc, datasetContext, pipelineRuntime, stageSpec);
            JavaRDD<T> countedRDD = rdd.map(new CountingFunction<T>(stageName, sec.getMetrics(), Constants.Metrics.RECORDS_IN, null));
            SparkConf sparkConf = jsc.getConf();
            try {
                sink.run(sparkPluginContext, countedRDD);
            } catch (Exception e) {
                throw Throwables.propagate(e);
            }
        }
    };
}