Examples with SparkStreamingExecutionContext co.cask.cdap.etl.spark.streaming.SparkStreamingExecutionContext used on opensource projects

Example 1 with SparkStreamingExecutionContext

use of co.cask.cdap.etl.spark.streaming.SparkStreamingExecutionContext in project cdap by caskdata.

the class StreamingSparkSinkFunction method call.

@Override
public Void call(JavaRDD<T> data, Time batchTime) throws Exception {
    final long logicalStartTime = batchTime.milliseconds();
    MacroEvaluator evaluator = new DefaultMacroEvaluator(sec.getWorkflowToken(), sec.getRuntimeArguments(), logicalStartTime, sec.getSecureStore(), sec.getNamespace());
    final PluginContext pluginContext = new SparkPipelinePluginContext(sec.getPluginContext(), sec.getMetrics(), stageInfo.isStageLoggingEnabled(), stageInfo.isProcessTimingEnabled());
    final String stageName = stageInfo.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(sec, datasetContext, stageInfo);
                sparkSink.prepareRun(context);
            }
        });
        isPrepared = true;
        final SparkExecutionPluginContext sparkExecutionPluginContext = new SparkStreamingExecutionContext(sec, JavaSparkContext.fromSparkContext(data.rdd().context()), logicalStartTime, stageInfo);
        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(sec, datasetContext, stageInfo);
                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(sec, datasetContext, stageInfo);
                    sparkSink.onRunFinish(false, context);
                }
            });
        }
    }
    return null;
}

Example 2 with SparkStreamingExecutionContext

use of co.cask.cdap.etl.spark.streaming.SparkStreamingExecutionContext in project cdap by caskdata.

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(), stageInfo);
    String stageName = stageInfo.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)));
}