Question

我一直在使用KSQL，到目前为止，它一直运行良好。但是现在我想通过Kafka Connect将输出下沉到BigQuery，并需要附加一个JSON模式。我在弄清楚如何做到这一点时遇到了麻烦。这是我的查询：

CREATE STREAM tweets_original (
      CreatedAt BIGINT,
      Id BIGINT,
      Text VARCHAR,
      Source VARCHAR,
      GeoLocation VARCHAR,
      User STRUCT<Id BIGINT, Name VARCHAR, Description VARCHAR, ScreenName VARCHAR, URL VARCHAR, FollowersCount BIGINT, FriendsCount BIGINT>
    )
    WITH (kafka_topic='tweets', value_format='JSON');

    CREATE STREAM tweets_new
    WITH (kafka_topic='tweets-new') AS
    SELECT
      CreatedAt as created_at,
      Id as tweet_id,
      Text as tweet_text,
      Source as source,
      GeoLocation as geo_location,
      User->Id as user_id,
      User->Name as user_name,
      User->Description as user_description,
      User->ScreenName as user_screenname
    FROM tweets_original ;

以下是记录写入输出主题（tweets-new）的示例。

{
  "CREATED_AT": 1535036410000,
  "TWEET_ID": 1032643668614819800,
  "TWEET_TEXT": "Sample text",
  "SOURCE": "<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>",
  "GEO_LOCATION": null,
  "USER_ID": 123,
  "USER_NAME": "John Smith",
  "USER_DESCRIPTION": "Developer in Chief",
  "USER_SCREENNAME": "newphonewhodis"
}

但是，为了让Kafka Connect将这些记录下沉到BigQuery，我需要附加一个架构，如下所示：

{
  "schema": {
    "type": "struct",
    "fields": [
      {
        "type": "int64",
        "optional": false,
        "field": "CREATED_AT"
      },
      {
        "type": "int64",
        "optional": false,
        "field": "TWEET_ID"
      },
      {
        "type": "string",
        "optional": false,
        "field": "TWEET_TEXT"
      }
      ...
    ],
    "optional": false,
    "name": "foobar"
  },
  "payload": {...}
}

无论如何，我在文档中没有看到任何显示如何解决此问题的东西（也许我在错误的位置）。任何帮助将不胜感激！

Answer 1

这是KSQL的简单解决方案，只需将您的第二个流更新为AVRO。

CREATE STREAM tweets_new
    WITH (kafka_topic='tweets-new', value_format='AVRO') AS
    SELECT
      CreatedAt as created_at,
      Id as tweet_id,
      Text as tweet_text,
      Source as source,
      GeoLocation as geo_location,
      User->Id as user_id,
      User->Name as user_name,
      User->Description as user_description,
      User->ScreenName as user_screenname
    FROM tweets_original ;

然后在您的Kafka Connect配置中，您可以使用AvroConvertor并允许在Google Big Query中进行模式演变/管理。

将JSON模式附加到KSQL流记录

1 个答案: