【发布时间】:2019-07-29 19:29:12
【问题描述】:
我正在使用 Avro 值转换,它生成如下模式(这只是一个子集,因为它太大了)
{
"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,并尝试将其消化到接收器中,我会得到 p>
Expected Envelope for transformation, passing it unchanged
然后是关于缺少 PK 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
【问题讨论】:
-
嗨,恕我直言,您应该在要创建 KSQL 流的主题上应用
UnwrapFromEnvelopeSMT。另外你确定topic中的数据是Avro格式的吗? -
是的,当我从 KSQL 打印该主题时,它会将其显示为 Avro,并且 OP 中的模式是自动构建的。首先展开它是完全有意义的,所以我必须创建一个连接器,将它返回到另一个展开的主题,然后在该主题上使用 KSQL?
-
您可以直接在源连接器上应用它,这样主题将包含未包装的版本。我还检查了 KSQL 文档,它们支持
STRUCT数据类型。不能用这个吗?所以你的CREATE STREAM将包含字符串字段op和ts_ms和STRUCT字段before、after和source? -
@JiriPechanec 是的,确实有效,我在上面发布的最后一个模式是从 CREATE STREAM 自动生成的,其中包含 CDC 数据。我刚刚注意到的奇怪之处在于,如果您将 Avro 架构与 KSQL 中的架构进行比较,它会删除我所有的小数列。
-
- 请查看
decimal.handling.mode。改变它可能会有所帮助。
标签: apache-kafka debezium ksqldb