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Java Schema.type方法代碼示例

本文整理匯總了Java中org.apache.kafka.connect.data.Schema.type方法的典型用法代碼示例。如果您正苦於以下問題：Java Schema.type方法的具體用法？Java Schema.type怎麽用？Java Schema.type使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類org.apache.kafka.connect.data.Schema的用法示例。


在下文中一共展示了Schema.type方法的8個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: apply

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
@Override
public R apply(R record) {
    final Schema schema = operatingSchema(record);
    requireSchema(schema, "updating schema metadata");
    final boolean isArray = schema.type() == Schema.Type.ARRAY;
    final boolean isMap = schema.type() == Schema.Type.MAP;
    final Schema updatedSchema = new ConnectSchema(
            schema.type(),
            schema.isOptional(),
            schema.defaultValue(),
            schemaName != null ? schemaName : schema.name(),
            schemaVersion != null ? schemaVersion : schema.version(),
            schema.doc(),
            schema.parameters(),
            schema.fields(),
            isMap ? schema.keySchema() : null,
            isMap || isArray ? schema.valueSchema() : null
    );
    return newRecord(record, updatedSchema);
}
開發者ID:YMCoding，項目名稱:kafka-0.11.0.0-src-with-comment，代碼行數:21，代碼來源:SetSchemaMetadata.java

示例2: processValue

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
private Object processValue(Schema schema, Object value) {
    switch (schema.type()) {
        case BOOLEAN:
        case FLOAT32:
        case FLOAT64:
        case INT8:
        case INT16:
        case INT32:
        case INT64:
        case BYTES:
        case STRING:
            return value;
        case MAP:
        case ARRAY:
        case STRUCT:
            return new DataException("Unsupported schema type: " + schema.type());
        default:
            throw new DataException("Unknown schema type: " + schema.type());
    }
}
開發者ID:fluent，項目名稱:kafka-connect-fluentd，代碼行數:21，代碼來源:SchemafulRecordConverter.java

示例3: convert

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
public static TypeInfo convert(Schema schema) {
  // TODO: throw an error on recursive types
  switch (schema.type()) {
    case STRUCT:
      return convertStruct(schema);
    case ARRAY:
      return convertArray(schema);
    case MAP:
      return convertMap(schema);
    default:
      return convertPrimitive(schema);
  }
}
開發者ID:jiangxiluning，項目名稱:kafka-connect-hdfs，代碼行數:14，代碼來源:HiveSchemaConverter.java

示例4: fromConnectData

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
@Override
public byte[] fromConnectData(String topic, Schema schema, Object value) {
    if (schema != null && schema.type() != Schema.Type.BYTES)
        throw new DataException("Invalid schema type for ByteArrayConverter: " + schema.type().toString());

    if (value != null && !(value instanceof byte[]))
        throw new DataException("ByteArrayConverter is not compatible with objects of type " + value.getClass());

    return (byte[]) value;
}
開發者ID:YMCoding，項目名稱:kafka-0.11.0.0-src-with-comment，代碼行數:11，代碼來源:ByteArrayConverter.java

示例5: copySchemaBasics

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
private static SchemaBuilder copySchemaBasics(Schema source, SchemaBuilder target) {
  if (source.isOptional()) {
    target.optional();
  }
  if (source.defaultValue() != null && source.type() != Schema.Type.STRUCT) {
    final Object preProcessedDefaultValue = preProcessValue(source.defaultValue(), source, target);
    target.defaultValue(preProcessedDefaultValue);
  }
  return target;
}
開發者ID:chaokunyang，項目名稱:jkes，代碼行數:11，代碼來源:DataConverter.java

示例6: build

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
public MsSqlChange build(TableMetadataProvider.TableMetadata tableMetadata, ResultSet resultSet, Time time) throws SQLException {
  MsSqlChange change = new MsSqlChange();
  change.timestamp = time.milliseconds();
  change.databaseName = tableMetadata.databaseName();
  change.schemaName = tableMetadata.schemaName();
  change.tableName = tableMetadata.tableName();

  final long sysChangeVersion = resultSet.getLong("__metadata_sys_change_version");
  final long sysChangeCreationVersion = resultSet.getLong("__metadata_sys_change_creation_version");
  final String changeOperation = resultSet.getString("__metadata_sys_change_operation");

  change.metadata = ImmutableMap.of(
      "sys_change_operation", changeOperation,
      "sys_change_creation_version", String.valueOf(sysChangeCreationVersion),
      "sys_change_version", String.valueOf(sysChangeVersion)
  );

  switch (changeOperation) {
    case "I":
      change.changeType = ChangeType.INSERT;
      break;
    case "U":
      change.changeType = ChangeType.UPDATE;
      break;
    case "D":
      change.changeType = ChangeType.DELETE;
      break;
    default:
      throw new UnsupportedOperationException(
          String.format("Unsupported sys_change_operation of '%s'", changeOperation)
      );
  }
  log.trace("build() - changeType = {}", change.changeType);

  change.keyColumns = new ArrayList<>(tableMetadata.keyColumns().size());
  change.valueColumns = new ArrayList<>(tableMetadata.columnSchemas().size());

  for (Map.Entry<String, Schema> kvp : tableMetadata.columnSchemas().entrySet()) {
    String columnName = kvp.getKey();
    Schema schema = kvp.getValue();
    Object value;
    if (Schema.Type.INT8 == schema.type()) {
      // Really lame Microsoft. A tiny int is stored as a single byte with a value of 0-255.
      // Explain how this should be returned as a short?
      value = resultSet.getByte(columnName);
    } else if (Schema.Type.INT32 == schema.type() &&
        Date.LOGICAL_NAME.equals(schema.name())) {
      value = new java.util.Date(
          resultSet.getDate(columnName, calendar).getTime()
      );
    } else if (Schema.Type.INT32 == schema.type() &&
        org.apache.kafka.connect.data.Time.LOGICAL_NAME.equals(schema.name())) {
      value = new java.util.Date(
          resultSet.getTime(columnName, calendar).getTime()
      );
    } else {
      value = resultSet.getObject(columnName);
    }

    log.trace("build() - columnName = '{}' value = '{}'", columnName, value);
    MsSqlColumnValue columnValue = new MsSqlColumnValue(columnName, schema, value);
    change.valueColumns.add(columnValue);
    if (tableMetadata.keyColumns().contains(columnName)) {
      change.keyColumns.add(columnValue);
    }
  }

  return change;
}
開發者ID:jcustenborder，項目名稱:kafka-connect-cdc-mssql，代碼行數:70，代碼來源:MsSqlChange.java

示例7: asJsonSchema

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
public ObjectNode asJsonSchema(Schema schema) {
    if (schema == null)
        return null;

    ObjectNode cached = fromConnectSchemaCache.get(schema);
    if (cached != null)
        return cached;

    final ObjectNode jsonSchema;
    switch (schema.type()) {
        case BOOLEAN:
            jsonSchema = JsonSchema.BOOLEAN_SCHEMA.deepCopy();
            break;
        case BYTES:
            jsonSchema = JsonSchema.BYTES_SCHEMA.deepCopy();
            break;
        case FLOAT64:
            jsonSchema = JsonSchema.DOUBLE_SCHEMA.deepCopy();
            break;
        case FLOAT32:
            jsonSchema = JsonSchema.FLOAT_SCHEMA.deepCopy();
            break;
        case INT8:
            jsonSchema = JsonSchema.INT8_SCHEMA.deepCopy();
            break;
        case INT16:
            jsonSchema = JsonSchema.INT16_SCHEMA.deepCopy();
            break;
        case INT32:
            jsonSchema = JsonSchema.INT32_SCHEMA.deepCopy();
            break;
        case INT64:
            jsonSchema = JsonSchema.INT64_SCHEMA.deepCopy();
            break;
        case STRING:
            jsonSchema = JsonSchema.STRING_SCHEMA.deepCopy();
            break;
        case ARRAY:
            jsonSchema = JsonNodeFactory.instance.objectNode().put(JsonSchema.SCHEMA_TYPE_FIELD_NAME, JsonSchema.ARRAY_TYPE_NAME);
            jsonSchema.set(JsonSchema.ARRAY_ITEMS_FIELD_NAME, asJsonSchema(schema.valueSchema()));
            break;
        case MAP:
            jsonSchema = JsonNodeFactory.instance.objectNode().put(JsonSchema.SCHEMA_TYPE_FIELD_NAME, JsonSchema.MAP_TYPE_NAME);
            jsonSchema.set(JsonSchema.MAP_KEY_FIELD_NAME, asJsonSchema(schema.keySchema()));
            jsonSchema.set(JsonSchema.MAP_VALUE_FIELD_NAME, asJsonSchema(schema.valueSchema()));
            break;
        case STRUCT:
            jsonSchema = JsonNodeFactory.instance.objectNode().put(JsonSchema.SCHEMA_TYPE_FIELD_NAME, JsonSchema.STRUCT_TYPE_NAME);
            ArrayNode fields = JsonNodeFactory.instance.arrayNode();
            for (Field field : schema.fields()) {
                ObjectNode fieldJsonSchema = asJsonSchema(field.schema()).deepCopy();
                fieldJsonSchema.put(JsonSchema.STRUCT_FIELD_NAME_FIELD_NAME, field.name());
                fields.add(fieldJsonSchema);
            }
            jsonSchema.set(JsonSchema.STRUCT_FIELDS_FIELD_NAME, fields);
            break;
        default:
            throw new DataException("Couldn't translate unsupported schema type " + schema + ".");
    }

    jsonSchema.put(JsonSchema.SCHEMA_OPTIONAL_FIELD_NAME, schema.isOptional());
    if (schema.name() != null)
        jsonSchema.put(JsonSchema.SCHEMA_NAME_FIELD_NAME, schema.name());
    if (schema.version() != null)
        jsonSchema.put(JsonSchema.SCHEMA_VERSION_FIELD_NAME, schema.version());
    if (schema.doc() != null)
        jsonSchema.put(JsonSchema.SCHEMA_DOC_FIELD_NAME, schema.doc());
    if (schema.parameters() != null) {
        ObjectNode jsonSchemaParams = JsonNodeFactory.instance.objectNode();
        for (Map.Entry<String, String> prop : schema.parameters().entrySet())
            jsonSchemaParams.put(prop.getKey(), prop.getValue());
        jsonSchema.set(JsonSchema.SCHEMA_PARAMETERS_FIELD_NAME, jsonSchemaParams);
    }
    if (schema.defaultValue() != null)
        jsonSchema.set(JsonSchema.SCHEMA_DEFAULT_FIELD_NAME, convertToJson(schema, schema.defaultValue()));

    fromConnectSchemaCache.put(schema, jsonSchema);
    return jsonSchema;
}
開發者ID:YMCoding，項目名稱:kafka-0.11.0.0-src-with-comment，代碼行數:80，代碼來源:JsonConverter.java

示例8: convertToConnect

import org.apache.kafka.connect.data.Schema; //導入方法依賴的package包/類
private static Object convertToConnect(Schema schema, JsonNode jsonValue) {
    final Schema.Type schemaType;
    if (schema != null) {
        schemaType = schema.type();
        if (jsonValue.isNull()) {
            if (schema.defaultValue() != null)
                return schema.defaultValue(); // any logical type conversions should already have been applied
            if (schema.isOptional())
                return null;
            throw new DataException("Invalid null value for required " + schemaType +  " field");
        }
    } else {
        switch (jsonValue.getNodeType()) {
            case NULL:
                // Special case. With no schema
                return null;
            case BOOLEAN:
                schemaType = Schema.Type.BOOLEAN;
                break;
            case NUMBER:
                if (jsonValue.isIntegralNumber())
                    schemaType = Schema.Type.INT64;
                else
                    schemaType = Schema.Type.FLOAT64;
                break;
            case ARRAY:
                schemaType = Schema.Type.ARRAY;
                break;
            case OBJECT:
                schemaType = Schema.Type.MAP;
                break;
            case STRING:
                schemaType = Schema.Type.STRING;
                break;

            case BINARY:
            case MISSING:
            case POJO:
            default:
                schemaType = null;
                break;
        }
    }

    final JsonToConnectTypeConverter typeConverter = TO_CONNECT_CONVERTERS.get(schemaType);
    if (typeConverter == null)
        throw new DataException("Unknown schema type: " + String.valueOf(schemaType));

    Object converted = typeConverter.convert(schema, jsonValue);
    if (schema != null && schema.name() != null) {
        LogicalTypeConverter logicalConverter = TO_CONNECT_LOGICAL_CONVERTERS.get(schema.name());
        if (logicalConverter != null)
            converted = logicalConverter.convert(schema, converted);
    }
    return converted;
}
開發者ID:YMCoding，項目名稱:kafka-0.11.0.0-src-with-comment，代碼行數:57，代碼來源:JsonConverter.java


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