В зависимости от того, насколько строгим является ваше требование вложения нескольких адресов в один клиентский узел, вы можете сделать это в KSQL (который построен поверх потоков Kafka).
Заполнить некоторые тестовые данные в Kafka (которыйв вашем случае это делается уже через Debezium):
$ curl -s "https://api.mockaroo.com/api/ffa9ff20?count=10&key=ff7856d0" | kafkacat -b localhost:9092 -t addresses -P
$ curl -s "https://api.mockaroo.com/api/9b868890?count=4&key=ff7856d0" | kafkacat -b localhost:9092 -t customers -P
Запустите KSQL и для начала просто проверьте данные:
ksql> PRINT 'addresses' FROM BEGINNING ;
Format:JSON
{"ROWTIME":1558519823351,"ROWKEY":"null","id":1,"customer_id":1004,"street":"8 Moulton Center","city":"Bronx","state":"New York","zip":"10474","type":"BILLING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":2,"customer_id":1001,"street":"5 Hollow Ridge Alley","city":"Washington","state":"District of Columbia","zip":"20016","type":"LIVING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":3,"customer_id":1000,"street":"58 Maryland Point","city":"Greensboro","state":"North Carolina","zip":"27404","type":"LIVING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":4,"customer_id":1002,"street":"55795 Derek Avenue","city":"Temple","state":"Texas","zip":"76505","type":"LIVING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":5,"customer_id":1002,"street":"164 Continental Plaza","city":"Modesto","state":"California","zip":"95354","type":"SHIPPING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":6,"customer_id":1004,"street":"6 Miller Road","city":"Louisville","state":"Kentucky","zip":"40205","type":"BILLING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":7,"customer_id":1003,"street":"97 Shasta Place","city":"Pittsburgh","state":"Pennsylvania","zip":"15286","type":"BILLING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":8,"customer_id":1000,"street":"36 Warbler Circle","city":"Memphis","state":"Tennessee","zip":"38109","type":"SHIPPING"}
{"ROWTIME":1558519823351,"ROWKEY":"null","id":9,"customer_id":1001,"street":"890 Eagan Circle","city":"Saint Paul","state":"Minnesota","zip":"55103","type":"SHIPPING"}
{"ROWTIME":1558519823354,"ROWKEY":"null","id":10,"customer_id":1000,"street":"8 Judy Terrace","city":"Washington","state":"District of Columbia","zip":"20456","type":"SHIPPING"}
^C
Topic printing ceased
ksql>
ksql> PRINT 'customers' FROM BEGINNING;
Format:JSON
{"ROWTIME":1558519852363,"ROWKEY":"null","id":1001,"first_name":"Jolee","last_name":"Handasyde","email":"jhandasyde0@nhs.uk"}
{"ROWTIME":1558519852363,"ROWKEY":"null","id":1002,"first_name":"Rebeca","last_name":"Kerrod","email":"rkerrod1@sourceforge.net"}
{"ROWTIME":1558519852363,"ROWKEY":"null","id":1003,"first_name":"Bobette","last_name":"Brumble","email":"bbrumble2@cdc.gov"}
{"ROWTIME":1558519852368,"ROWKEY":"null","id":1004,"first_name":"Royal","last_name":"De Biaggi","email":"rdebiaggi3@opera.com"}
Теперь мы объявляем STREAM (тема Кафки+ схема) для данных, чтобы мы могли манипулировать ими дальше:
ksql> CREATE STREAM addresses_RAW (ID INT, CUSTOMER_ID INT, STREET VARCHAR, CITY VARCHAR, STATE VARCHAR, ZIP VARCHAR, TYPE VARCHAR) WITH (KAFKA_TOPIC='addresses', VALUE_FORMAT='JSON');
Message
----------------
Stream created
----------------
ksql> CREATE STREAM customers_RAW (ID INT, FIRST_NAME VARCHAR, LAST_NAME VARCHAR, EMAIL VARCHAR) WITH (KAFKA_TOPIC='customers', VALUE_FORMAT='JSON');
Message
----------------
Stream created
----------------
Мы собираемся смоделировать customers как TABLE, и для этого сообщения Kafka должны быть введены с помощью клавиш.правильно (и в тот момент, когда они имеют нулевые ключи, как видно из "ROWKEY":"null" в выводе PRINT выше).Вы можете настроить Debezium для установки ключа сообщения, так что этот шаг может быть вам не нужен в KSQL:
ksql> CREATE STREAM CUSTOMERS_KEYED WITH (PARTITIONS=1) AS SELECT * FROM CUSTOMERS_RAW PARTITION BY ID;
Message
----------------------------
Stream created and running
----------------------------
Теперь мы объявляем TABLE ( состояние для данного ключа,создается из темы + схема Kafka:
ksql> CREATE TABLE CUSTOMER (ID INT, FIRST_NAME VARCHAR, LAST_NAME VARCHAR, EMAIL VARCHAR) WITH (KAFKA_TOPIC='CUSTOMERS_KEYED', VALUE_FORMAT='JSON', KEY='ID');
Message
---------------
Table created
---------------
Теперь мы можем объединить данные:
ksql> CREATE STREAM customers_with_addresses AS
SELECT CUSTOMER_ID,
FIRST_NAME + ' ' + LAST_NAME AS FULL_NAME,
FIRST_NAME,
LAST_NAME,
TYPE AS ADDRESS_TYPE,
STREET,
CITY,
STATE,
ZIP
FROM ADDRESSES_RAW A
INNER JOIN CUSTOMER C
ON A.CUSTOMER_ID = C.ID;
Message
----------------------------
Stream created and running
----------------------------
Это создает новый поток KSQL, который, в свою очередь, заполняет новую тему Kafka.
ksql> SHOW STREAMS;
Stream Name | Kafka Topic | Format
------------------------------------------------------------------------------------------
CUSTOMERS_KEYED | CUSTOMERS_KEYED | JSON
ADDRESSES_RAW | addresses | JSON
CUSTOMERS_RAW | customers | JSON
CUSTOMERS_WITH_ADDRESSES | CUSTOMERS_WITH_ADDRESSES | JSON
Поток имеет схему:
ksql> DESCRIBE CUSTOMERS_WITH_ADDRESSES;
Name : CUSTOMERS_WITH_ADDRESSES
Field | Type
------------------------------------------
ROWTIME | BIGINT (system)
ROWKEY | VARCHAR(STRING) (system)
CUSTOMER_ID | INTEGER (key)
FULL_NAME | VARCHAR(STRING)
FIRST_NAME | VARCHAR(STRING)
ADDRESS_TYPE | VARCHAR(STRING)
LAST_NAME | VARCHAR(STRING)
STREET | VARCHAR(STRING)
CITY | VARCHAR(STRING)
STATE | VARCHAR(STRING)
ZIP | VARCHAR(STRING)
------------------------------------------
For runtime statistics and query details run: DESCRIBE EXTENDED <Stream,Table>;
Мы можем запросить поток:
ksql> SELECT * FROM CUSTOMERS_WITH_ADDRESSES WHERE CUSTOMER_ID=1002;
1558519823351 | 1002 | 1002 | Rebeca Kerrod | Rebeca | LIVING | Kerrod | 55795 Derek Avenue | Temple | Texas | 76505
1558519823351 | 1002 | 1002 | Rebeca Kerrod | Rebeca | SHIPPING | Kerrod | 164 Continental Plaza | Modesto | California | 95354
Мы также можем передать его в Elasticsearch с помощью Kafka Connect:
curl -i -X POST -H "Accept:application/json" \
-H "Content-Type:application/json" http://localhost:8083/connectors/ \
-d '{
"name": "sink-elastic-customers_with_addresses-00",
"config": {
"connector.class": "io.confluent.connect.elasticsearch.ElasticsearchSinkConnector",
"topics": "CUSTOMERS_WITH_ADDRESSES",
"connection.url": "http://elasticsearch:9200",
"type.name": "type.name=kafkaconnect",
"key.ignore": "true",
"schema.ignore": "true",
"key.converter": "org.apache.kafka.connect.storage.StringConverter",
"value.converter": "org.apache.kafka.connect.json.JsonConverter",
"value.converter.schemas.enable": "false"
}
}'
Результат:
$ curl -s http://localhost:9200/customers_with_addresses/_search | jq '.hits.hits[0]'
{
"_index": "customers_with_addresses",
"_type": "type.name=kafkaconnect",
"_id": "CUSTOMERS_WITH_ADDRESSES+0+2",
"_score": 1,
"_source": {
"ZIP": "76505",
"CITY": "Temple",
"ADDRESS_TYPE": "LIVING",
"CUSTOMER_ID": 1002,
"FULL_NAME": "Rebeca Kerrod",
"STATE": "Texas",
"STREET": "55795 Derek Avenue",
"LAST_NAME": "Kerrod",
"FIRST_NAME": "Rebeca"
}
}