ストリームは、Apacheカフカとの例に参加しますか?

ギャビン・ギルモア:

私は、すなわちアドレステーブルを顧客テーブルに参加し、ESにデータをシンク、この種のものを行う方法にカフカストリームを使用した例を探していました: -

お客様

+------+------------+----------------+-----------------------+
| id   | first_name | last_name      | email                 |
+------+------------+----------------+-----------------------+
| 1001 | Sally      | Thomas         | [email protected] |
| 1002 | George     | Bailey         | [email protected]    |
| 1003 | Edward     | Davidson       | [email protected]         |
| 1004 | Anne       | Kim            | [email protected]    |
+------+------------+----------------+-----------------------+

アドレス

+----+-------------+---------------------------+------------+--------------+-------+----------+
| id | customer_id | street                    | city       | state        | zip   | type     |
+----+-------------+---------------------------+------------+--------------+-------+----------+
| 10 |        1001 | 3183 Moore Avenue         | Euless     | Texas        | 76036 | SHIPPING |
| 11 |        1001 | 2389 Hidden Valley Road   | Harrisburg | Pennsylvania | 17116 | BILLING  |
| 12 |        1002 | 281 Riverside Drive       | Augusta    | Georgia      | 30901 | BILLING  |
| 13 |        1003 | 3787 Brownton Road        | Columbus   | Mississippi  | 39701 | SHIPPING |
| 14 |        1003 | 2458 Lost Creek Road      | Bethlehem  | Pennsylvania | 18018 | SHIPPING |
| 15 |        1003 | 4800 Simpson Square       | Hillsdale  | Oklahoma     | 73743 | BILLING  |
| 16 |        1004 | 1289 University Hill Road | Canehill   | Arkansas     | 72717 | LIVING   |
+----+-------------+---------------------------+------------+--------------+-------+----------+

出力Elasticsearchインデックス

"hits": [
  {
    "_index": "customers_with_addresses",
    "_type": "_doc",
    "_id": "1",
    "_score": 1.3278645,
    "_source": {
      "first_name": "Sally",
      "last_name": "Thomas",
      "email": "[email protected]",
      "addresses": [{
        "street": "3183 Moore Avenue",
        "city": "Euless",
        "state": "Texas",
        "zip": "76036",
        "type": "SHIPPING"
      }, {
        "street": "2389 Hidden Valley Road",
        "city": "Harrisburg",
        "state": "Pennsylvania",
        "zip": "17116",
        "type": "BILLING"
      }],
    }
  }, ….

表のデータはDebeziumトピックから来て、私はその後、ESにあることをシンクする新しいトピックをストリーム、出力、それに参加する途中でいくつかのJavaを必要とする考えで正しいのですか?

誰もがこの任意のコード例を持っていますか?

ありがとうございました。

ロビン・モファット:

あなたの条件は、1つの顧客ノードに巣複数のアドレスにどれだけ厳密に応じて、(カフカストリームの上に構築されています)KSQLでこれを行うことができます。

(お使いの場合にはDebeziumを通じてすでに行われている)カフカにいくつかのテストデータを移入:

$ 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

火災KSQLアップとデータだけを検査して開始します:

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":"[email protected]"}
{"ROWTIME":1558519852363,"ROWKEY":"null","id":1002,"first_name":"Rebeca","last_name":"Kerrod","email":"[email protected]"}
{"ROWTIME":1558519852363,"ROWKEY":"null","id":1003,"first_name":"Bobette","last_name":"Brumble","email":"[email protected]"}
{"ROWTIME":1558519852368,"ROWKEY":"null","id":1004,"first_name":"Royal","last_name":"De Biaggi","email":"[email protected]"}

今、私たちは宣言しSTREAM、我々はさらにそれを操作できるように、データ上(カフカトピック+スキーマ):

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
----------------

私たちは、モデル化するつもりだcustomersとしてTABLE、そしてカフカメッセージが正しくキーする必要がある(とから分かるように瞬間が、彼らは、nullキーを持っていることを行うため"ROWKEY":"null"PRINT上記の出力)。あなたは、このステップはKSQLであなたのために必要ではないかもしれないので、メッセージキーを設定するDebeziumを設定できます。

ksql> CREATE STREAM CUSTOMERS_KEYED WITH (PARTITIONS=1) AS SELECT * FROM CUSTOMERS_RAW PARTITION BY ID;

 Message
----------------------------
 Stream created and running
----------------------------

今、私たちは宣言TABLE状態カフカトピック+スキーマからインスタンス指定されたキーのを、):

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
---------------

今、私たちはデータを結合することができます。


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
----------------------------

これは、順番に新しいカフカのトピックを移入新しいKSQLストリームを作成します。

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

ストリームは、スキーマがあります。

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>;

私たちは、ストリームを照会することができます:

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

また、カフカConnectを使用してElasticsearchにそれをストリーミングすることができます。

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"
      }
    }'

結果:

$ 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"
  }
}

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