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我正在使用生成如下模式的 Avro 值转换(这只是一个子集,因为它很大)

{
  "type": "record",
  "name": "Envelope",
  "namespace": "mssql.dbo.InvTR_T",
  "fields": [
    {
      "name": "before",
      "type": [
        "null",
        {
          "type": "record",
          "name": "Value",
          "fields": [
            {
              "name": "InvTR_ID",
              "type": "int"
            },
            {
              "name": "Type_CH",
              "type": "string"
            },
            {
              "name": "CalcType_CH",
              "type": "string"
            },
            {
              "name": "ER_CST_ID",
              "type": "int"
            },
            {
              "name": "ER_REQ_ID",
              "type": "int"
            },
            {
              "name": "Vendor_ID",
              "type": "int"
            },
            {
              "name": "VendInv_VC",
              "type": "string"
            },
            {
              "name": "Status_CH",
              "type": "string"
            },
            {
              "name": "Stage_TI",
              "type": {
                "type": "int",
                "connect.type": "int16"
              }
            },
            {
              "name": "CheckOut_ID",
              "type": [
                "null",
                "int"
              ],
              "default": null
            },
            {
              "name": "ReCalcCk_LG",
              "type": "boolean"
            },
            {
              "name": "ReCalcAll_LG",
              "type": "boolean"
            },
            {
              "name": "PatMatch_LG",
              "type": "boolean"
            },
            {
              "name": "DocPatOvRd_LG",
              "type": "boolean"
            },
            {
              "name": "Locked_LG",
              "type": [
                "null",
                "boolean"
              ],
              "default": null
            },
            {
              "name": "SegErrFlag_LG",
              "type": "boolean"
            },
            {
              "name": "Hold_LG",
              "type": "boolean"
            },
            {
              "name": "Reason_ID",
              "type": [
                "null",
                {
                  "type": "int",
                  "connect.type": "int16"
                }
              ],
              "default": null
            },
            {
              "name": "HoldCom_VC",
              "type": [
                "null",
                "string"
              ],
              "default": null
            },
            {
              "name": "AllSegFin_LG",
              "type": "boolean"
            },
            {
              "name": "InvAmt_MN",
              "type": {
                "type": "bytes",
                "scale": 4,
                "precision": 19,
                "connect.version": 1,
                "connect.parameters": {
                  "scale": "4",
                  "connect.decimal.precision": "19"
                },
                "connect.name": "org.apache.kafka.connect.data.Decimal",
                "logicalType": "decimal"
              }

当我运行以下命令以创建一个流时

CREATE STREAM stream_invtr_t_json   WITH (KAFKA_TOPIC='InvTR_T', VALUE_FORMAT='AVRO');

然后我描述了那个流,模式是一种非常奇怪的格式。我想使用 KSQL 来过滤掉特定信息并适当地分散这些事件。但是我无法从 Kafka Topic => KSQL Stream => Kafka Topic => Sink 出发。如果然后我从该流中创建一个新主题,并尝试将其消化到我得到的接收器中

Expected Envelope for transformation, passing it unchanged

然后是关于 PK 丢失的错误。我试图删除展开转换只是为了看看它会如何出现并收到错误。

BEFORE  | STRUCT<INVTR_ID INTEGER, TYPE_CH VARCHAR(STRING), CALCTYPE_CH VARCHAR(STRING), ER_CST_ID INTEGER, ER_REQ_ID INTEGER, VENDOR_ID INTEGER, VENDINV_VC VARCHAR(STRING), STATUS_CH VARCHAR(STRING), STAGE_TI INTEGER, CHECKOUT_ID INTEGER, RECALCCK_LG BOOLEAN, RECALCALL_LG BOOLEAN, PATMATCH_LG BOOLEAN, DOCPATOVRD_LG BOOLEAN, LOCKED_LG BOOLEAN, SEGERRFLAG_LG BOOLEAN, HOLD_LG BOOLEAN, REASON_ID INTEGER, HOLDCOM_VC VARCHAR(STRING), ALLSEGFIN_LG BOOLEAN, INVDATE_DT BIGINT, SHIPDATE_DT BIGINT, PDTERMS_CH VARCHAR(STRING), PMTDUE_DT BIGINT, PMTTERMS_VC VARCHAR(STRING), BILLTERMS_CH VARCHAR(STRING), JOINT_LG BOOLEAN, COMMENT_VC VARCHAR(STRING), SOURCE_CH VARCHAR(STRING), ADDBY_ID VARCHAR(STRING), ADDED_DT BIGINT, CHGBY_ID VARCHAR(STRING), CHGED_DT BIGINT, APPROVED_LG BOOLEAN, MULTIPO_VC VARCHAR(STRING), PRVAUDITED_INVTR_ID INTEGER, PRVVENDOR_ID INTEGER, TRANSITDAYS_SI INTEGER, SHIP_NUM_VC VARCHAR(STRING), PRVTRANSITDAYS_SI INTEGER, PRVJOINT_LG BOOLEAN, CLONEDFROM_INVTR_ID INTEGER, LASTCALC_DT BIGINT, TMSFMANUAL_LG BOOLEAN, FRTRATERSOURCE_CH VARCHAR(STRING), ACTPICKUP_DT BIGINT, ROUTVEND_SI INTEGER, CALCVRSN_TI INTEGER, VENDORRANK_SI INTEGER, SEQ_SI INTEGER, PRVAUDITED_DT BIGINT, FRTRATERBATCHTYPE_CH VARCHAR(STRING), CURRENCY_TYPE_CD VARCHAR(STRING), EXCHANGE_DT BIGINT, EXCHANGE_RATE_LOCKED_LG BOOLEAN, EXCHANGE_DT_LOCKED_LG BOOLEAN, CUSTAPPROVED_LG BOOLEAN, FRTRATERMATCH_INVTR_ID INTEGER, CRC_INVOICE_LG BOOLEAN, RG_ROUTVEND_SI INTEGER, RG_PRVVE
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1 回答 1

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似乎有关UnwrapFromEnvelope解决部分问题的评论。这只留下关于小数的部分没有通过。

查看连接器的文档:https ://debezium.io/documentation/reference/1.1/connectors/postgresql.html

decimal.handling.mode正如 Jiri 评论的那样,我可以看到有一个设置。在它的默认值下,precise它看起来会以 ksqlDB 可以识别的格式输出 Avro 十进制,除非源 NUMERIC 或 DECIMAL 类型在没有任何比例的情况下使用。此时您将获得STRUCT包含 BYTE 字段的数据结构。

这条规则有一个例外。当使用 NUMERIC 或 DECIMAL 类型而没有任何比例约束时,这意味着来自数据库的值对于每个值具有不同的(可变)比例。在这种情况下,使用 io.debezium.data.VariableScaleDecimal 类型,它包含传输值的值和比例。

因此,要将数据导入 ksqlDB,您需要:

  1. 等到我们支持 BYTES 数据类型,(目前不在我们的路线图上)
  2. 更改源表的架构以定义列的比例。
  3. 将 decimal.handling.mode 更改为其他设置。您可能可以使用字符串,然后将值转换为 ksql 中的小数。
于 2020-06-12T12:10:51.823 回答