Open-Source Kafka Source Stream

Function

Create a source stream to obtain data from Kafka as input data for jobs.

Apache Kafka is a fast, scalable, and fault-tolerant distributed message publishing and subscription system. It delivers high throughput and built-in partitions and provides data replicas and fault tolerance. Apache Kafka is applicable to scenarios of handling massive messages.

Prerequisites

Kafka is an offline cluster. You need to use the enhanced datasource connection function to connect Flink jobs to Kafka. You can also set security group rules as required.

Syntax

    
         CREATE SOURCE STREAM stream_id (attr_name attr_type (',' attr_name attr_type)* )
  WITH (
    type = "kafka",
    kafka_bootstrap_servers = "",
    kafka_group_id = "",
    kafka_topic = "",
    encode = "json",
    json_config=""
  );

Keywords

**Table 1** Keyword description
Parameter	Mandatory	Description
type	Yes	Data source type. Kafka indicates that the data source is Kafka.
kafka_bootstrap_servers	Yes	Port that connects DLI to Kafka. Use enhanced datasource connections to connect DLI queues with Kafka clusters.
kafka_group_id	No	Group ID.
kafka_topic	Yes	Kafka topic to be read. Currently, only one topic can be read at a time.
encode	Yes	Data encoding format. The value can be csv, json, blob, or user_defined. field_delimiter must be specified if this parameter is set to csv. json_config must be specified if this parameter is set to json. If this parameter is set to blob, the received data will not be parsed, and only one Array[TINYINT] field exists in the table. encode_class_name and encode_class_parameter must be specified if this parameter is set to user_defined.
encode_class_name	No	If encode is set to user_defined, you need to set this parameter to the name of the user-defined decoding class (including the complete package path). The class must inherit the DeserializationSchema class.
encode_class_parameter	No	If encode is set to user_defined, you can set this parameter to specify the input parameter of the user-defined decoding class. Only one parameter of the string type is supported.
json_config	No	If encode is set to json, you can use this parameter to specify the mapping between JSON fields and stream attributes. The format is field1=json_field1;field2=json_field2. field1 and field2 indicate the names of the created table fields. json_field1 and json_field2 are key fields of the JSON strings in the Kafka input data. For details, see Example. NOTE: If the attribute names in the source stream are the same as those in JSON fields, you do not need to set this parameter.
field_delimiter	No	If encode is set to csv, you can use this parameter to specify the separator between CSV fields. By default, the comma (,) is used.
quote	No	Quoted symbol in a data format. The attribute delimiters between two quoted symbols are treated as common characters. If double quotation marks are used as the quoted symbol, set this parameter to \u005c\u0022 for character conversion. If a single quotation mark is used as the quoted symbol, set this parameter to a single quotation mark ('). NOTE: Currently, only the CSV format is supported. After this parameter is specified, ensure that each field does not contain quoted symbols or contains an even number of quoted symbols. Otherwise, parsing will fail.
start_time	No	Start time when Kafka data is ingested. If this parameter is specified, DLI reads data read from the specified time. The format is yyyy-MM-dd HH:mm:ss. Ensure that the value of start_time is not later than the current time. Otherwise, no data will be obtained. If you set this parameter, only the data generated after the specified time for the Kafka topic will be read.
kafka_properties	No	Native properties of Kafka. The format is key1=value1;key2=value2. For details about the property values, see the description in Apache Kafka.
kafka_certificate_name	No	Name of the datasource authentication information. This parameter is valid only when the datasource authentication type is set to Kafka_SSL. NOTE: If this parameter is specified, the service loads only the specified file and password under the authentication. The system automatically sets this parameter to kafka_properties. Other configuration information required for Kafka SSL authentication needs to be manually configured in the kafka_properties attribute.

Precautions

When creating a source stream, you can specify a time model for subsequent calculation. Currently, DLI supports two time models: Processing Time and Event Time. For details about the syntax, see Configuring Time Models.

Example

Read Kafka topic test. The data encoding format is non-nested JSON, for example, {"attr1": "lilei", "attr2": 18}.

      
           CREATE SOURCE STREAM kafka_source (name STRING, age int)
WITH (
  type = "kafka",
  kafka_bootstrap_servers = "ip1:port1,ip2:port2", 
  kafka_group_id = "sourcegroup1", 
  kafka_topic = "test",
  encode = "json",
  json_config = "name=attr1;age=attr2"
);

Read Kafka topic test. The data is encoded in JSON format and nested. This example uses the complex data type ROW. For details about the syntax of ROW, see Data Type.

The test data is as follows:

{
    "id":"1",
    "type2":"online",
    "data":{
        "patient_id":1234,
        "name":"bob1234"
    }
}

An example of the table creation statements is as follows:

CREATE SOURCE STREAM kafka_source 
(
  id STRING,
  type2 STRING,
  data ROW<
    patient_id STRING, 
    name STRING>
)
WITH (
  type = "kafka",
  kafka_bootstrap_servers = "ip1:port1,ip2:port2", 
  kafka_group_id = "sourcegroup1", 
  kafka_topic = "test",
  encode = "json"
);

CREATE SINK STREAM kafka_sink 
(
  id STRING,
  type2 STRING,
  patient_id STRING, 
  name STRING
)
  WITH (
    type="kafka",
    kafka_bootstrap_servers =  "ip1:port1,ip2:port2",
    kafka_topic = "testsink",
    encode = "csv" 
  );

INSERT INTO kafka_sink select id, type2, data.patient_id, data.name from kafka_source;

Parent topic: Creating a Source Stream

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