MRS 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. Kafka clusters are deployed and hosted on MRS that is powered on Apache Kafka.

Prerequisites

If the Kafka server listens on the port using hostname, you need to add the mapping between the hostname and IP address of the Kafka Broker node to the DLI queue. Contact the Kafka service deployment personnel to obtain the hostname and IP address of the Kafka Broker node. For details about how to add an IP-domain mapping, see Modifying the Host Information in the Data Lake Insight User Guide.
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.
For details about how to create an enhanced datasource connection, see Enhanced Datasource Connections in the Data Lake Insight User Guide.

For details about how to configure security group rules, see Security Group in the Virtual Private Cloud User Guide.

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"
  );

Keyword

**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 is not parsed, only one stream attribute exists, and the stream attribute is of the Array[TINYINT] type. 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.
krb_auth	No	The authentication name for creating a datasource connection authentication. This parameter is mandatory when Kerberos authentication is enabled. NOTE: Ensure that the /etc/hosts information of the master node in the MRS cluster is added to the host file of the DLI queue.
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 the example.
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.
kafka_properties	No	This parameter is used to configure the native attributes of Kafka. The format is key1=value1;key2=value2.
kafka_certificate_name	No	Specifies the 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 data from the Kafka topic test.

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"
);

Read the topic whose object is test from Kafka and use json_config to map JSON data to table fields.

The data encoding format is non-nested JSON.

{"attr1": "lilei", "attr2": 18}

The table creation statement is as follows:

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"
);