ReadFromKafka组件

组件说明

从kafka中读取数据。

计算引擎

flink

有界性

Unbounded

组件分组

kafka

端口

Inport：默认端口

outport：默认端口

组件属性

名称	展示名称	默认值	允许值	是否必填	描述	例子
kafka_host	KAFKA_HOST	""	无	是	逗号分隔的Kafka broker列表。	127.0.0.1:9092
topic	TOPIC	""	无	否	读取数据的topic名。亦支持用分号间隔的topic列表，如 'topic-1;topic-2'。"  "注意，'topic' 和 'topic-pattern' 两个选项只能使用其中一个。	topic-1
topic_pattern	TOPIC_PATTERN	""	无	否	匹配读取topic名称的正则表达式。在作业开始运行时，所有匹配该正则表达式的topic都将被Kafka consumer订阅。注意，'topic' 和 'topic-pattern' 两个选项只能使用其中一个。	topic1_*
startup_mode	STARTUP_MODE	""	Set("earliest-offset", "latest-offset", "group-offsets", "timestamp", "specific-offsets")	否	Kafka consumer 的启动模式。	earliest-offset
schema	SCHEMA	""	无	否	Kafka消息的schema信息。	id:int,name:string,age:int
format	FORMAT	""	Set("json", "csv", "avro", "parquet", "orc", "raw", "protobuf","debezium-json", "canal-json", "maxwell-json", "ogg-json")	是	用来反序列化Kafka消息的格式。注意：该配置项和 'value.format' 二者必需其一。	json
group	GROUP	""	无	否	Kafka source的消费组id。如果未指定消费组ID，则会使用自动生成的"KafkaSource-{tableIdentifier}"作为消费组ID。	group_1
properties	PROPERTIES	""	无	否	Kafka source连接器其他配置

ReadFromKafka示例配置

{
  "flow": {
    "name": "DataGenTest",
    "uuid": "1234",
    "stops": [
      {
        "uuid": "0000",
        "name": "DataGen1",
        "bundle": "cn.piflow.bundle.flink.common.DataGen",
        "properties": {
          "schema": "[{"filedName":"id","filedType":"INT","kind":"sequence","start":1,"end":10000},{"filedName":"name","filedType":"STRING","kind":"random","length":15},{"filedName":"age","filedType":"INT","kind":"random","max":100,"min":1}]",
          "count": "100",
          "ratio": "5"
        }
      },
      {
        "uuid": "1111",
        "name": "WriteToKafka1",
        "bundle": "cn.piflow.bundle.flink.kafka.WriteToKafka",
        "properties": {
          "kafka_host": "hadoop01:9092",
          "topic": "test",
          "schema": "",
          "format": "json",
          "properties": "{}"
        }
      },
      {
        "uuid": "2222",
        "name": "ReadFromKafka1",
        "bundle": "cn.piflow.bundle.flink.kafka.ReadFromKafka",
        "properties": {
          "kafka_host": "hadoop01:9092",
          "topic": "test",
          "group": "test",
          "startup_mode": "earliest-offset",
          "schema": "id:int,name:string,age:int",
          "format": "json",
          "properties": "{}"
        }
      },
      {
        "uuid": "3333",
        "name": "ShowData1",
        "bundle": "cn.piflow.bundle.flink.common.ShowData",
        "properties": {
          "showNumber": "5000"
        }
      }
    ],
    "paths": [
      {
        "from": "DataGen1",
        "outport": "",
        "inport": "",
        "to": "WriteToKafka1"
      },
      {
        "from": "WriteToKafka1",
        "outport": "",
        "inport": "",
        "to": "ReadFromKafka1"
      },
      {
        "from": "ReadFromKafka1",
        "outport": "",
        "inport": "",
        "to": "ShowData1"
      }
    ]
  }
}

示例说明

本示例演示了通过DataGen组件生成id，name，age3个字段100条数据，每秒生成5条数据，通过WriteToKafka组件将数据写入到kafka的test topic中，然后通过ReadFromKafka组件从test topic中读取数据，最后使用ShowData组件将数据打印在控制台。

字段描述

[    {               "filedName": "id",        "filedType": "INT",        "kind": "sequence",        "start": 1,        "end": 10000    },        {               "filedName": "name",        "filedType": "STRING",        "kind": "random",        "length": 15    },        {               "filedName": "age",        "filedType": "INT",        "kind": "random",        "max": 100,        "min": 1    } ]

1.id字段

id字段类型为INT,使用sequence生成器，序列生成器的起始值为1，结束值为10000.

2.name字段

name字段类型为STRING,使用random生成器，生成字符长度为15。

3.age字段

age字段类型为INT，使用random生成器，随机生成器的最小值为1，最大值为100。