Examples with StreamSchema com.ibm.streams.operator.StreamSchema used on opensource projects

Example 1 with StreamSchema

use of com.ibm.streams.operator.StreamSchema in project streamsx.topology by IBMStreams.

the class Topology method subscribe.

/**
     * Declare a stream that is a subscription to {@code topic}.
     * A topic is published using {@link TStream#publish(String)}.
     * Subscribers are matched to published streams when the {@code topic}
     * is an exact match and the type of the stream ({@code T},
     * {@code tupleTypeClass}) is an exact match.
     * <BR>
     * Publish-subscribe is a many to many relationship,
     * multiple streams from multiple applications may
     * be published on the same topic and type. Multiple
     * subscribers may subscribe to a topic and type.
     * <BR>
     * A subscription will match all publishers using the
     * same topic and tuple type. Tuples on the published
     * streams will appear on the returned stream, as
     * a single stream.
     * <BR>
     * The subscription is dynamic, the returned stream
     * will subscribe to a matching stream published by
     * a newly submitted application (a job), and stops a
     * subscription when an running job is cancelled.
     * <P>
     * Publish-subscribe only works when the topology is
     * submitted to a {@link com.ibm.streamsx.topology.context.StreamsContext.Type#DISTRIBUTED}
     * context. This allows different applications (or
     * even within the same application) to communicate
     * using published streams.
     * </P>
     * <P>
     * If {@code tupleTypeClass} is {@code JSONObject.class} then the
     * subscription is the generic IBM Streams schema for JSON
     * ({@link JSONSchemas#JSON}). Streams of type {@code JSONObject}
     * are always published and subscribed using the generic schema
     * to allow interchange between applications implemented in
     * different languages.
     * </P>
     * @param topic Topic to subscribe to.
     * @param tupleTypeClass Type to subscribe to.
     * @return Stream the will contain tuples from matching publishers.
     * 
     * @see TStream#publish(String)
     * @see SPLStreams#subscribe(TopologyElement, String, com.ibm.streams.operator.StreamSchema)
     */
public <T> TStream<T> subscribe(String topic, Class<T> tupleTypeClass) {
    checkTopicFilter(topic);
    if (JSONObject.class.equals(tupleTypeClass)) {
        @SuppressWarnings("unchecked") TStream<T> json = (TStream<T>) SPLStreams.subscribe(this, topic, JSONSchemas.JSON).toJSON();
        return json;
    }
    StreamSchema mappingSchema = Schemas.getSPLMappingSchema(tupleTypeClass);
    SPLStream splImport;
    // Subscribed as an SPL Stream.
    if (Schemas.usesDirectSchema(tupleTypeClass)) {
        splImport = SPLStreams.subscribe(this, topic, mappingSchema);
    } else {
        Map<String, Object> params = new HashMap<>();
        params.put("topic", topic);
        params.put("class", tupleTypeClass.getName());
        params.put("streamType", mappingSchema);
        splImport = SPL.invokeSource(this, "com.ibm.streamsx.topology.topic::SubscribeJava", params, mappingSchema);
    }
    return new StreamImpl<T>(this, splImport.output(), tupleTypeClass);
}

Example 2 with StreamSchema

use of com.ibm.streams.operator.StreamSchema in project streamsx.kafka by IBMStreams.

the class AbstractKafkaProducerOperator method initialize.

/**
 * Initialize this operator. Called once before any tuples are processed.
 *
 * @param context
 *            OperatorContext for this operator.
 * @throws Exception
 *             Operator failure, will cause the enclosing PE to terminate.
 */
@Override
public synchronized void initialize(OperatorContext context) throws Exception {
    super.initialize(context);
    logger.trace(// $NON-NLS-1$ //$NON-NLS-2$ //$NON-NLS-3$
    "Operator " + context.getName() + " initializing in PE: " + context.getPE().getPEId() + " in Job: " + context.getPE().getJobId());
    StreamSchema inputSchema = context.getStreamingInputs().get(0).getStreamSchema();
    // check for key attribute and get type
    Attribute keyAttribute = null;
    if (keyAttr != null && keyAttr.getAttribute() != null) {
        keyAttribute = keyAttr.getAttribute();
    } else {
        keyAttribute = inputSchema.getAttribute(DEFAULT_KEY_ATTR_NAME);
    }
    if (keyAttribute != null) {
        keyType = keyAttribute.getType().getObjectType();
        keyAttributeName = keyAttribute.getName();
    }
    // check for partition attribute
    Attribute partitionAttribute = null;
    if (partitionAttr != null && partitionAttr.getAttribute() != null) {
        partitionAttribute = partitionAttr.getAttribute();
    } else {
        partitionAttribute = inputSchema.getAttribute(DEFAULT_PARTITION_ATTR_NAME);
    }
    partitionAttributeName = partitionAttribute != null ? partitionAttribute.getName() : null;
    // check for timestamp attribute
    Attribute timestampAttribute = null;
    if (timestampAttr != null && timestampAttr.getAttribute() != null) {
        timestampAttribute = timestampAttr.getAttribute();
    } else {
        timestampAttribute = inputSchema.getAttribute(DEFAULT_TIMESTAMP_ATTR_NAME);
    }
    timestampAttributeName = timestampAttribute != null ? timestampAttribute.getName() : null;
    // get message type
    messageType = messageAttr.getAttribute().getType().getObjectType();
    crContext = context.getOptionalContext(ConsistentRegionContext.class);
    if (crContext != null) {
        isResetting = new AtomicBoolean(context.getPE().getRelaunchCount() > 0);
    }
    initProducer();
    registerForDataGovernance(context, topics);
    // $NON-NLS-1$
    logger.info(">>> Operator initialized! <<<");
}

Example 3 with StreamSchema

use of com.ibm.streams.operator.StreamSchema in project streamsx.kafka by IBMStreams.

the class KafkaOperatorsBlobTypeTest method kafkaBlobTypeTest.

@Test
public void kafkaBlobTypeTest() throws Exception {
    Topology topo = getTopology();
    StreamSchema schema = KafkaSPLStreamsUtils.BLOB_SCHEMA;
    // create the producer (produces tuples after a short delay)
    TStream<Blob> srcStream = topo.strings(Constants.STRING_DATA).transform(s -> ValueFactory.newBlob(s.getBytes())).modify(new Delay<>(5000));
    SPLStream splSrcStream = SPLStreams.convertStream(srcStream, new Converter(), schema);
    SPL.invokeSink(Constants.KafkaProducerOp, splSrcStream, getKafkaParams());
    // create the consumer
    SPLStream consumerStream = SPL.invokeSource(topo, Constants.KafkaConsumerOp, getKafkaParams(), schema);
    SPLStream msgStream = SPLStreams.stringToSPLStream(consumerStream.convert(t -> new String(t.getBlob("message").getData())));
    // test the output of the consumer
    StreamsContext<?> context = StreamsContextFactory.getStreamsContext(Type.DISTRIBUTED_TESTER);
    Tester tester = topo.getTester();
    Condition<List<String>> condition = KafkaSPLStreamsUtils.stringContentsUnordered(tester, msgStream, Constants.STRING_DATA);
    tester.complete(context, new HashMap<>(), condition, 30, TimeUnit.SECONDS);
    // check the results
    Assert.assertTrue(condition.getResult().size() > 0);
    Assert.assertTrue(condition.getResult().toString(), condition.valid());
}

Example 4 with StreamSchema

use of com.ibm.streams.operator.StreamSchema in project streamsx.kafka by IBMStreams.

the class KafkaOperatorsDoubleTypeTest method kafkaDoubleTypeTest.

@Test
public void kafkaDoubleTypeTest() throws Exception {
    Topology topo = getTopology();
    StreamSchema schema = KafkaSPLStreamsUtils.DOUBLE_SCHEMA;
    // create the producer (produces tuples after a short delay)
    TStream<Double> srcStream = topo.strings(DATA).transform(s -> Double.valueOf(s)).modify(new Delay<>(5000));
    SPLStream splSrcStream = SPLStreams.convertStream(srcStream, new Converter(), schema);
    SPL.invokeSink(Constants.KafkaProducerOp, splSrcStream, getKafkaParams());
    // create the consumer
    SPLStream consumerStream = SPL.invokeSource(topo, Constants.KafkaConsumerOp, getKafkaParams(), schema);
    SPLStream msgStream = SPLStreams.stringToSPLStream(consumerStream.convert(t -> String.valueOf(t.getDouble("message"))));
    // test the output of the consumer
    StreamsContext<?> context = StreamsContextFactory.getStreamsContext(Type.DISTRIBUTED_TESTER);
    Tester tester = topo.getTester();
    Condition<List<String>> condition = KafkaSPLStreamsUtils.stringContentsUnordered(tester, msgStream, DATA);
    tester.complete(context, new HashMap<>(), condition, 30, TimeUnit.SECONDS);
    // check the results
    Assert.assertTrue(condition.getResult().size() > 0);
    Assert.assertTrue(condition.getResult().toString(), condition.valid());
}

Example 5 with StreamSchema

use of com.ibm.streams.operator.StreamSchema in project streamsx.kafka by IBMStreams.

the class KafkaOperatorsFloatTypeTest method kafkaFloatTypeTest.

@Test
public void kafkaFloatTypeTest() throws Exception {
    Topology topo = getTopology();
    StreamSchema schema = KafkaSPLStreamsUtils.FLOAT_SCHEMA;
    // create the producer (produces tuples after a short delay)
    TStream<Float> srcStream = topo.strings(DATA).transform(s -> Float.valueOf(s)).modify(new Delay<>(5000));
    SPLStream splSrcStream = SPLStreams.convertStream(srcStream, new Converter(), schema);
    SPL.invokeSink(Constants.KafkaProducerOp, splSrcStream, getKafkaParams());
    // create the consumer
    SPLStream consumerStream = SPL.invokeSource(topo, Constants.KafkaConsumerOp, getKafkaParams(), schema);
    SPLStream msgStream = SPLStreams.stringToSPLStream(consumerStream.convert(t -> String.valueOf(t.getFloat("message"))));
    // test the output of the consumer
    StreamsContext<?> context = StreamsContextFactory.getStreamsContext(Type.DISTRIBUTED_TESTER);
    Tester tester = topo.getTester();
    Condition<List<String>> condition = KafkaSPLStreamsUtils.stringContentsUnordered(tester, msgStream, DATA);
    tester.complete(context, new HashMap<>(), condition, 30, TimeUnit.SECONDS);
    // check the results
    Assert.assertTrue(condition.getResult().size() > 0);
    Assert.assertTrue(condition.getResult().toString(), condition.valid());
}