Java Code Examples for org.apache.spark.sql.streaming.DataStreamWriter

The following examples show how to use org.apache.spark.sql.streaming.DataStreamWriter. These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source Project: sylph   Source File: StructuredStreamingSqlAnalyse.java    License: Apache License 2.0 6 votes vote down vote up
public void createSinkTable(SinkContext sinkContext, StructType tableSparkType)
{
    final String driverClass = (String) sinkContext.withConfig().get("type");
    IocFactory iocFactory = IocFactory.create(sparkBean, binder -> binder.bind(SinkContext.class, sinkContext));
    StructuredNodeLoader loader = new StructuredNodeLoader(connectorStore, iocFactory);

    UnaryOperator<Dataset<Row>> outputStream = dataSet -> {
        checkQueryAndTableSinkSchema(dataSet.schema(), tableSparkType, sinkContext.getSinkTable());
        DataStreamWriter<Row> writer = loader.loadSinkWithComplic(driverClass, sinkContext.withConfig()).apply(dataSet);
        if (!isCompile) {
            //UnsupportedOperationChecker.checkForContinuous();
            writer = writer.option("checkpointLocation", checkpointLocation);
            writer.start();
        }
        return null;
    };
    sinks.put(sinkContext.getSinkTable(), outputStream);
}
 
Example 2
Source Project: hudi   Source File: HoodieJavaStreamingApp.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Setup configs for syncing to hive.
 * 
 * @param writer
 * @return
 */
private DataStreamWriter<Row> updateHiveSyncConfig(DataStreamWriter<Row> writer) {
  if (enableHiveSync) {
    LOG.info("Enabling Hive sync to " + hiveJdbcUrl);
    writer = writer.option(DataSourceWriteOptions.HIVE_TABLE_OPT_KEY(), hiveTable)
        .option(DataSourceWriteOptions.HIVE_DATABASE_OPT_KEY(), hiveDB)
        .option(DataSourceWriteOptions.HIVE_URL_OPT_KEY(), hiveJdbcUrl)
        .option(DataSourceWriteOptions.HIVE_USER_OPT_KEY(), hiveUser)
        .option(DataSourceWriteOptions.HIVE_PASS_OPT_KEY(), hivePass)
        .option(DataSourceWriteOptions.HIVE_SYNC_ENABLED_OPT_KEY(), "true");
    if (useMultiPartitionKeys) {
      writer = writer.option(DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY(), "year,month,day").option(
          DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY(),
          MultiPartKeysValueExtractor.class.getCanonicalName());
    } else {
      writer = writer.option(DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY(), "dateStr");
    }
  }
  return writer;
}
 
Example 3
Source Project: sylph   Source File: StructuredNodeLoader.java    License: Apache License 2.0 5 votes vote down vote up
private static Sink<DataStreamWriter<Row>> loadRealTimeSink(RealTimeSink realTimeSink)
{
    return stream -> stream.foreach(new ForeachWriter<Row>()
    {
        @Override
        public void process(Row value)
        {
            realTimeSink.process(SparkRecord.make(value));
        }

        @Override
        public void close(Throwable errorOrNull)
        {
            realTimeSink.close(errorOrNull);
        }

        @Override
        public boolean open(long partitionId, long version)
        {
            try {
                return realTimeSink.open(partitionId, version);
            }
            catch (Exception e) {
                throw throwsException(e);
            }
        }
    });
}
 
Example 4
Source Project: sylph   Source File: StructuredStreamingSqlAnalyse.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public void selectQuery(SelectQuery statement)
        throws Exception
{
    Dataset<Row> df = sparkSession.sql(statement.toString());
    DataStreamWriter<Row> writer = df.writeStream()
            .foreach(new ConsoleWriter())
            .trigger(Trigger.Continuous("90 seconds"))
            //.option("checkpointLocation", checkpointLocation)
            .outputMode(OutputMode.Append());
    if (!isCompile) {
        writer.start();
    }
}
 
Example 5
Source Project: hudi   Source File: HoodieJavaStreamingApp.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Hoodie spark streaming job.
 * 
 * @param streamingInput
 * @throws Exception
 */
public void stream(Dataset<Row> streamingInput) throws Exception {

  DataStreamWriter<Row> writer = streamingInput.writeStream().format("org.apache.hudi")
      .option("hoodie.insert.shuffle.parallelism", "2").option("hoodie.upsert.shuffle.parallelism", "2")
      .option(DataSourceWriteOptions.TABLE_TYPE_OPT_KEY(), tableType)
      .option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY(), "_row_key")
      .option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY(), "partition")
      .option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY(), "timestamp")
      .option(HoodieWriteConfig.TABLE_NAME, tableName).option("checkpointLocation", streamingCheckpointingPath)
      .outputMode(OutputMode.Append());

  updateHiveSyncConfig(writer);
  writer.trigger(new ProcessingTime(500)).start(tablePath).awaitTermination(streamingDurationInMs);
}
 
Example 6
Source Project: beam   Source File: TranslationContext.java    License: Apache License 2.0 5 votes vote down vote up
/** Starts the pipeline. */
public void startPipeline() {
  try {
    SparkStructuredStreamingPipelineOptions options =
        serializablePipelineOptions.get().as(SparkStructuredStreamingPipelineOptions.class);
    int datasetIndex = 0;
    for (Dataset<?> dataset : leaves) {
      if (options.isStreaming()) {
        // TODO: deal with Beam Discarding, Accumulating and Accumulating & Retracting	outputmodes
        // with DatastreamWriter.outputMode
        DataStreamWriter<?> dataStreamWriter = dataset.writeStream();
        // spark sets a default checkpoint dir if not set.
        if (options.getCheckpointDir() != null) {
          dataStreamWriter =
              dataStreamWriter.option("checkpointLocation", options.getCheckpointDir());
        }
        // TODO: Do not await termination here.
        dataStreamWriter.foreach(new NoOpForeachWriter<>()).start().awaitTermination();
      } else {
        if (options.getTestMode()) {
          LOG.debug("**** dataset {} catalyst execution plans ****", ++datasetIndex);
          dataset.explain(true);
        }
        // apply a dummy fn just to apply foreach action that will trigger the pipeline run in
        // spark
        dataset.foreach((ForeachFunction) t -> {});
      }
    }
  } catch (StreamingQueryException e) {
    throw new RuntimeException("Pipeline execution failed: " + e);
  }
}
 
Example 7
public StreamingQuery start(final DataStreamWriter<?> writer, final String path) {
    Function0<StreamingQuery> runFunction = new AbstractFunction0<StreamingQuery>() {
        @Override
        public StreamingQuery apply() {
            return writer.start(path);
        }
    };
    return harness.startTest(runFunction);
}
 
Example 8
public StreamingQuery start(final DataStreamWriter<?> writer) {
    Function0<StreamingQuery> runFunction = new AbstractFunction0<StreamingQuery>() {
        @Override
        public StreamingQuery apply() {
            return writer.start();
        }
    };
    return harness.startTest(runFunction);
}
 
Example 9
public void run(final DataStreamWriter<?> writer, final String path) {
    Function0<StreamingQuery> runFunction = new AbstractFunction0<StreamingQuery>() {
        @Override
        public StreamingQuery apply() {
            return writer.start(path);
        }
    };
    harness.runTest(runFunction);
}
 
Example 10
public void run(final DataStreamWriter<?> writer) {
    Function0<StreamingQuery> runFunction = new AbstractFunction0<StreamingQuery>() {
        @Override
        public StreamingQuery apply() {
            return writer.start();
        }
    };
    harness.runTest(runFunction);
}