Examples with UnsupportedTypeException co.cask.cdap.api.data.schema.UnsupportedTypeException used on opensource projects

Example 11 with UnsupportedTypeException

use of co.cask.cdap.api.data.schema.UnsupportedTypeException in project cdap by caskdata.

the class ExploreExecutorHttpHandler method enableStream.

@POST
@Path("streams/{stream}/tables/{table}/enable")
@AuditPolicy(AuditDetail.REQUEST_BODY)
public void enableStream(HttpRequest request, HttpResponder responder, @PathParam("namespace-id") String namespace, @PathParam("stream") String streamName, @PathParam("table") final String tableName) throws Exception {
    final StreamId streamId = new StreamId(namespace, streamName);
    try (Reader reader = new InputStreamReader(new ChannelBufferInputStream(request.getContent()))) {
        final FormatSpecification format = GSON.fromJson(reader, FormatSpecification.class);
        if (format == null) {
            throw new BadRequestException("Expected format in the body");
        }
        QueryHandle handle = impersonator.doAs(streamId, new Callable<QueryHandle>() {

            @Override
            public QueryHandle call() throws Exception {
                return exploreTableManager.enableStream(tableName, streamId, format);
            }
        });
        JsonObject json = new JsonObject();
        json.addProperty("handle", handle.getHandle());
        responder.sendJson(HttpResponseStatus.OK, json);
    } catch (UnsupportedTypeException e) {
        LOG.error("Exception while generating create statement for stream {}", streamName, e);
        responder.sendString(HttpResponseStatus.BAD_REQUEST, e.getMessage());
    }
}

Example 12 with UnsupportedTypeException

use of co.cask.cdap.api.data.schema.UnsupportedTypeException in project cdap by caskdata.

the class SparkPageRankApp method configure.

@Override
public void configure() {
    setName("SparkPageRank");
    setDescription("Spark page rank application.");
    // Ingest data into the Application via a Stream
    addStream(new Stream(BACKLINK_URL_STREAM));
    // Run a Spark program on the acquired data
    addSpark(new PageRankSpark());
    // Runs MapReduce program on data emitted by Spark program
    addMapReduce(new RanksCounter());
    // Runs Spark followed by a MapReduce in a Workflow
    addWorkflow(new PageRankWorkflow());
    // Service to retrieve process data
    addService(SERVICE_HANDLERS, new SparkPageRankServiceHandler());
    // Store input and processed data in ObjectStore Datasets
    try {
        ObjectStores.createObjectStore(getConfigurer(), "ranks", Integer.class, DatasetProperties.builder().setDescription("Ranks Dataset").build());
        ObjectStores.createObjectStore(getConfigurer(), "rankscount", Integer.class, DatasetProperties.builder().setDescription("Ranks Count Dataset").build());
    } catch (UnsupportedTypeException e) {
        // because String and Double are actual classes.
        throw new RuntimeException(e);
    }
}

Example 13 with UnsupportedTypeException

use of co.cask.cdap.api.data.schema.UnsupportedTypeException in project cdap by caskdata.

the class CombinedLogRecordFormat method validateSchema.

@Override
protected void validateSchema(Schema desiredSchema) throws UnsupportedTypeException {
    // a valid schema is a record of simple types.
    Iterator<Schema.Field> fields = desiredSchema.getFields().iterator();
    while (fields.hasNext()) {
        Schema.Field field = fields.next();
        Schema schema = field.getSchema();
        boolean isSimple = schema.getType().isSimpleType();
        boolean isNullableSimple = schema.isNullableSimple();
        if (!isSimple && !isNullableSimple) {
            throw new UnsupportedTypeException("Field " + field.getName() + " is of invalid type.");
        }
    }
}

Example 14 with UnsupportedTypeException

use of co.cask.cdap.api.data.schema.UnsupportedTypeException in project cdap by caskdata.

the class GrokRecordFormat method validateSchema.

@Override
protected void validateSchema(Schema desiredSchema) throws UnsupportedTypeException {
    // a valid schema is a record of simple types. In other words, no maps, arrays, records, unions, or enums allowed.
    // the exception is the very last field, which is allowed to be an array of simple types.
    // These types may be nullable, which is a union of a null and non-null type.
    Iterator<Schema.Field> fields = desiredSchema.getFields().iterator();
    // check that each field is a simple field, except for the very last field, which can be an array of simple types.
    while (fields.hasNext()) {
        Schema.Field field = fields.next();
        Schema schema = field.getSchema();
        // if we're not on the very last field, the field must be a simple type or a nullable simple type.
        boolean isSimple = schema.getType().isSimpleType();
        boolean isNullableSimple = schema.isNullableSimple();
        if (!isSimple && !isNullableSimple) {
            // if this is the very last field and a string array, it is valid. otherwise it is not.
            if (fields.hasNext() || !isStringArray(schema)) {
                throw new UnsupportedTypeException("Field " + field.getName() + " is of invalid type.");
            }
        }
    }
}

Example 15 with UnsupportedTypeException

use of co.cask.cdap.api.data.schema.UnsupportedTypeException in project cdap by caskdata.

the class FlowletProgramRunner method createProcessSpecification.

/**
   * Creates all {@link ProcessSpecification} for the process methods of the flowlet class.
   *
   * @param flowletType Type of the flowlet class represented by {@link TypeToken}.
   * @param processMethodFactory A {@link ProcessMethodFactory} for creating {@link ProcessMethod}.
   * @param processSpecFactory A {@link ProcessSpecificationFactory} for creating {@link ProcessSpecification}.
   * @param result A {@link Collection} for storing newly created {@link ProcessSpecification}.
   * @return The same {@link Collection} as the {@code result} parameter.
   */
@SuppressWarnings("unchecked")
private <T extends Collection<ProcessSpecification<?>>> T createProcessSpecification(BasicFlowletContext flowletContext, TypeToken<? extends Flowlet> flowletType, ProcessMethodFactory processMethodFactory, ProcessSpecificationFactory processSpecFactory, T result) throws Exception {
    Set<FlowletMethod> seenMethods = Sets.newHashSet();
    // Walk up the hierarchy of flowlet class to get all ProcessInput and Tick methods
    for (TypeToken<?> type : flowletType.getTypes().classes()) {
        if (type.getRawType().equals(Object.class)) {
            break;
        }
        // Extracts all process and tick methods
        for (Method method : type.getRawType().getDeclaredMethods()) {
            if (method.isSynthetic() || method.isBridge()) {
                continue;
            }
            if (!seenMethods.add(FlowletMethod.create(method, flowletType.getType()))) {
                // up the class hierarchy.
                continue;
            }
            ProcessInput processInputAnnotation = method.getAnnotation(ProcessInput.class);
            Tick tickAnnotation = method.getAnnotation(Tick.class);
            if (processInputAnnotation == null && tickAnnotation == null) {
                // Neither a process nor a tick method.
                continue;
            }
            int maxRetries = (tickAnnotation == null) ? processInputAnnotation.maxRetries() : tickAnnotation.maxRetries();
            ProcessMethod processMethod = processMethodFactory.create(method, maxRetries);
            Set<String> inputNames;
            Schema schema;
            TypeToken<?> dataType;
            ConsumerConfig consumerConfig;
            int batchSize = 1;
            if (tickAnnotation != null) {
                inputNames = ImmutableSet.of();
                consumerConfig = new ConsumerConfig(0, 0, 1, DequeueStrategy.FIFO, null);
                schema = Schema.of(Schema.Type.NULL);
                dataType = TypeToken.of(void.class);
            } else {
                inputNames = Sets.newHashSet(processInputAnnotation.value());
                if (inputNames.isEmpty()) {
                    // If there is no input name, it would be ANY_INPUT
                    inputNames.add(FlowletDefinition.ANY_INPUT);
                }
                // If batch mode then generate schema for Iterator's parameter type
                dataType = flowletType.resolveType(method.getGenericParameterTypes()[0]);
                consumerConfig = getConsumerConfig(flowletContext, method);
                Integer processBatchSize = getBatchSize(method, flowletContext);
                if (processBatchSize != null) {
                    if (dataType.getRawType().equals(Iterator.class)) {
                        Preconditions.checkArgument(dataType.getType() instanceof ParameterizedType, "Only ParameterizedType is supported for batch Iterator.");
                        dataType = flowletType.resolveType(((ParameterizedType) dataType.getType()).getActualTypeArguments()[0]);
                    }
                    batchSize = processBatchSize;
                }
                try {
                    schema = schemaGenerator.generate(dataType.getType());
                } catch (UnsupportedTypeException e) {
                    throw Throwables.propagate(e);
                }
            }
            ProcessSpecification processSpec = processSpecFactory.create(inputNames, schema, dataType, processMethod, consumerConfig, batchSize, tickAnnotation);
            // Add processSpec
            if (processSpec != null) {
                result.add(processSpec);
            }
        }
    }
    Preconditions.checkArgument(!result.isEmpty(), "No inputs found for flowlet '%s' of flow '%s' of application '%s' (%s)", flowletContext.getFlowletId(), flowletContext.getFlowId(), flowletContext.getApplicationId(), flowletType);
    return result;
}