Hi, Sorry for joining so late. First of all, I don't want to distract the discussion, but I thought maybe my opinion could help a bit, but maybe it won't ;)
The first observation I got is that I think everyone agrees we need a way distinguish the read-only from r/w columns. Is that correct? Secondly if I understand the discussion correctly there are three competing approaches: Option 1) If a metadata column is r/w use the WITH section for declaring such field If a metadata column is r use computed column e.g.: offset AS CAST(SYSTEM_METADATA("offset") AS long) Option 2) Use the computed column syntax, but add a keyword for marking a column writable e.g.: r-only: offset AS CAST(SYSTEM_METADATA("offset") AS long) r/w: timestamp AS CAST(SYSTEM_METADATA("timestamp") AS TIMESTAMP(3)) PERSISTED/WRITABLE/STORED Option 3) Use a new syntax, not to confuse it with computed columns. r-only: offset USING/FROM/(blank) SYSTEM_METADATA("offset") r/w-only: timestamp USING/FROM/(blank) SYSTEM_METADATA("timestamp") PERSISTED/WRITABLE/STORED My personal preference is in that order 1>2>3. Let me explain why I think that. Ad. 1 I sort of agree with @Jark and @Danny that if a field is readable and writable than it is actually a *real* data. Moreover I think in Kafka it is quite common to include a field in all different parts of the record. Take this code snippet from ksqlDB for example[1]. I understand @Timo's argument that it would not be too generic if we had more writable columns. But at least the way I see it, so far we have only a single r/w metadata field: timestamp. I am not sure if we should make the Kafka's headers writable. As per the motivation in the FLIP it introduced them, they are mostly for system meta-information, which does not necessarily contain business logic[2]. There are no more metadata columns marked as writable in the FLIP, as far as I can tell. The additional benefit is that the concept of computed columns is intact. They are only ever computed and you can not store into the columns. Ad. 2 The option two is more flexible than option 3, because it allows for computed expressions. In some sense this is also its disadvantage because computed expressions can not be used for r/w columns. Therefore we are loosing the flexibility for STORED/PERSISTED/WRITABLE columns. Ad. 3 The argument that reusing computed columns can be misleading does not really appeal to me. I think any new syntax that a user needs to learn is equally misleading. The only benefit I see is that it makes the situation more symmetric, as you cannot have computed expressions for both r-only and r/w columns, which at the same time is a disadvantage of that proposal. As for the issue of shortening the SYSTEM_METADATA to METADATA. Here I very much prefer the SYSTEM_ prefix. In my opinion in this case the clarity is more important than brevity. Moreover personally I never found a couple of letters that are usually copy-pasted, or auto-completed a real problem. This might be though my personal preference. Hope I will not distract the discussion too much. Best, Dawid [1] https://docs.ksqldb.io/en/latest/developer-guide/create-a-stream/#create-a-stream-with-timestamps [2] https://cwiki.apache.org/confluence/display/KAFKA/KIP-82+-+Add+Record+Headers#KIP82AddRecordHeaders-Motivation On 09/09/2020 12:40, Timo Walther wrote: > Hi everyone, > > "key" and "value" in the properties are a special case because they > need to configure a format. So key and value are more than just > metadata. Jark's example for setting a timestamp would work but as the > FLIP discusses, we have way more metadata fields like headers, > epoch-leader, etc. Having a property for all of this metadata would > mess up the WITH section entirely. Furthermore, we also want to deal > with metadata from the formats. Solving this through properties as > well would further complicate the property design. > > Personally, I still like the computed column design more because it > allows to have full flexibility to compute the final column: > > timestamp AS adjustTimestamp(CAST(SYSTEM_METADATA("ts") AS TIMESTAMP(3))) > > Instead of having a helper column and a real column in the table: > > helperTimestamp AS CAST(SYSTEM_METADATA("ts") AS TIMESTAMP(3)) > realTimestamp AS adjustTimestamp(helperTimestamp) > > But I see that the discussion leans towards: > > timestamp INT SYSTEM_METADATA("ts") > > Which is fine with me. It is the shortest solution, because we don't > need additional CAST. We can discuss the syntax, so that confusion > with computed columns can be avoided. > > timestamp INT USING SYSTEM_METADATA("ts") > timestamp INT FROM SYSTEM_METADATA("ts") > timestamp INT FROM SYSTEM_METADATA("ts") PERSISTED > > We use `SYSTEM_TIME` for temporal tables. I think prefixing with > SYSTEM makes it clearer that it comes magically from the system. > > What do you think? > > Regards, > Timo > > > > On 09.09.20 11:41, Jark Wu wrote: >> Hi Danny, >> >> This is not Oracle and MySQL computed column syntax, because there is no >> "AS" after the type. >> >> Hi everyone, >> >> If we want to use "offset INT SYSTEM_METADATA("offset")", then I >> think we >> must further discuss about "PERSISED" or "VIRTUAL" keyword for >> query-sink >> schema problem. >> Personally, I think we can use a shorter keyword "METADATA" for >> "SYSTEM_METADATA". Because "SYSTEM_METADATA" sounds like a system >> function >> and confuse users this looks like a computed column. >> >> >> Best, >> Jark >> >> >> >> On Wed, 9 Sep 2020 at 17:23, Danny Chan <danny0...@apache.org> wrote: >> >>> "offset INT SYSTEM_METADATA("offset")" >>> >>> This is actually Oracle or MySQL style computed column syntax. >>> >>> "You are right that one could argue that "timestamp", "headers" are >>> something like "key" and "value"" >>> >>> I have the same feeling, both key value and headers timestamp are >>> *real* >>> data >>> stored in the consumed record, they are not computed or generated. >>> >>> "Trying to solve everything via properties sounds rather like a hack to >>> me" >>> >>> Things are not that hack if we can unify the routines or the >>> definitions >>> (all from the computed column way or all from the table options), i >>> also >>> think that it is a hacky that we mix in 2 kinds of syntax for different >>> kinds of metadata (read-only and read-write). In this FLIP, we >>> declare the >>> Kafka key fields with table options but SYSTEM_METADATA for other >>> metadata, >>> that is a hacky thing or something in-consistent. >>> >>> Kurt Young <ykt...@gmail.com> 于2020年9月9日周三 下午4:48写道: >>> >>>> I would vote for `offset INT SYSTEM_METADATA("offset")`. >>>> >>>> I don't think we can stick with the SQL standard in DDL part forever, >>>> especially as there are more and more >>>> requirements coming from different connectors and external systems. >>>> >>>> Best, >>>> Kurt >>>> >>>> >>>> On Wed, Sep 9, 2020 at 4:40 PM Timo Walther <twal...@apache.org> >>>> wrote: >>>> >>>>> Hi Jark, >>>>> >>>>> now we are back at the original design proposed by Dawid :D Yes, we >>>>> should be cautious about adding new syntax. But the length of this >>>>> discussion shows that we are looking for a good long-term >>>>> solution. In >>>>> this case I would rather vote for a deep integration into the syntax. >>>>> >>>>> Computed columns are also not SQL standard compliant. And our DDL is >>>>> neither, so we have some degree of freedom here. >>>>> >>>>> Trying to solve everything via properties sounds rather like a >>>>> hack to >>>>> me. You are right that one could argue that "timestamp", "headers" >>>>> are >>>>> something like "key" and "value". However, mixing >>>>> >>>>> `offset AS SYSTEM_METADATA("offset")` >>>>> >>>>> and >>>>> >>>>> `'timestamp.field' = 'ts'` >>>>> >>>>> looks more confusing to users that an explicit >>>>> >>>>> `offset AS CAST(SYSTEM_METADATA("offset") AS INT)` >>>>> >>>>> or >>>>> >>>>> `offset INT SYSTEM_METADATA("offset")` >>>>> >>>>> that is symetric for both source and sink. >>>>> >>>>> What do others think? >>>>> >>>>> Regards, >>>>> Timo >>>>> >>>>> >>>>> On 09.09.20 10:09, Jark Wu wrote: >>>>>> Hi everyone, >>>>>> >>>>>> I think we have a conclusion that the writable metadata shouldn't be >>>>>> defined as a computed column, but a normal column. >>>>>> >>>>>> "timestamp STRING SYSTEM_METADATA('timestamp')" is one of the >>>> approaches. >>>>>> However, it is not SQL standard compliant, we need to be cautious >>>> enough >>>>>> when adding new syntax. >>>>>> Besides, we have to introduce the `PERSISTED` or `VIRTUAL` >>>>>> keyword to >>>>>> resolve the query-sink schema problem if it is read-only metadata. >>> That >>>>>> adds more stuff to learn for users. >>>>>> >>>>>> >From my point of view, the "timestamp", "headers" are something >>>>>> like >>>>> "key" >>>>>> and "value" that stores with the real data. So why not define the >>>>>> "timestamp" in the same way with "key" by using a "timestamp.field" >>>>>> connector option? >>>>>> On the other side, the read-only metadata, such as "offset", >>> shouldn't >>>> be >>>>>> defined as a normal column. So why not use the existing computed >>> column >>>>>> syntax for such metadata? Then we don't have the query-sink schema >>>>> problem. >>>>>> So here is my proposal: >>>>>> >>>>>> CREATE TABLE kafka_table ( >>>>>> id BIGINT, >>>>>> name STRING, >>>>>> col1 STRING, >>>>>> col2 STRING, >>>>>> ts TIMESTAMP(3) WITH LOCAL TIME ZONE, -- ts is a normal >>>>>> field, >>> so >>>>> can >>>>>> be read and written. >>>>>> offset AS SYSTEM_METADATA("offset") >>>>>> ) WITH ( >>>>>> 'connector' = 'kafka', >>>>>> 'topic' = 'test-topic', >>>>>> 'key.fields' = 'id, name', >>>>>> 'key.format' = 'csv', >>>>>> 'value.format' = 'avro', >>>>>> 'timestamp.field' = 'ts' -- define the mapping of Kafka >>> timestamp >>>>>> ); >>>>>> >>>>>> INSERT INTO kafka_table >>>>>> SELECT id, name, col1, col2, rowtime FROM another_table; >>>>>> >>>>>> I think this can solve all the problems without introducing any new >>>>> syntax. >>>>>> The only minor disadvantage is that we separate the definition >>>> way/syntax >>>>>> of read-only metadata and read-write fields. >>>>>> However, I don't think this is a big problem. >>>>>> >>>>>> Best, >>>>>> Jark >>>>>> >>>>>> >>>>>> On Wed, 9 Sep 2020 at 15:09, Timo Walther <twal...@apache.org> >>> wrote: >>>>>> >>>>>>> Hi Kurt, >>>>>>> >>>>>>> thanks for sharing your opinion. I'm totally up for not reusing >>>> computed >>>>>>> columns. I think Jark was a big supporter of this syntax, @Jark are >>>> you >>>>>>> fine with this as well? The non-computed column approach was only a >>>>>>> "slightly rejected alternative". >>>>>>> >>>>>>> Furthermore, we would need to think about how such a new design >>>>>>> influences the LIKE clause though. >>>>>>> >>>>>>> However, we should still keep the `PERSISTED` keyword as it >>> influences >>>>>>> the query->sink schema. If you look at the list of metadata for >>>> existing >>>>>>> connectors and formats, we currently offer only two writable >>> metadata >>>>>>> fields. Otherwise, one would need to declare two tables whenever a >>>>>>> metadata columns is read (one for the source, one for the sink). >>> This >>>>>>> can be quite inconvientient e.g. for just reading the topic. >>>>>>> >>>>>>> Regards, >>>>>>> Timo >>>>>>> >>>>>>> >>>>>>> On 09.09.20 08:52, Kurt Young wrote: >>>>>>>> I also share the concern that reusing the computed column syntax >>> but >>>>> have >>>>>>>> different semantics >>>>>>>> would confuse users a lot. >>>>>>>> >>>>>>>> Besides, I think metadata fields are conceptually not the same >>>>>>>> with >>>>>>>> computed columns. The metadata >>>>>>>> field is a connector specific thing and it only contains the >>>>> information >>>>>>>> that where does the field come >>>>>>>> from (during source) or where does the field need to write to >>> (during >>>>>>>> sink). It's more similar with normal >>>>>>>> fields, with assumption that all these fields need going to the >>> data >>>>>>> part. >>>>>>>> >>>>>>>> Thus I'm more lean to the rejected alternative that Timo >>>>>>>> mentioned. >>>>> And I >>>>>>>> think we don't need the >>>>>>>> PERSISTED keyword, SYSTEM_METADATA should be enough. >>>>>>>> >>>>>>>> During implementation, the framework only needs to pass such >>> <field, >>>>>>>> metadata field> information to the >>>>>>>> connector, and the logic of handling such fields inside the >>> connector >>>>>>>> should be straightforward. >>>>>>>> >>>>>>>> Regarding the downside Timo mentioned: >>>>>>>> >>>>>>>>> The disadvantage is that users cannot call UDFs or parse >>> timestamps. >>>>>>>> >>>>>>>> I think this is fairly simple to solve. Since the metadata field >>>> isn't >>>>> a >>>>>>>> computed column anymore, we can support >>>>>>>> referencing such fields in the computed column. For example: >>>>>>>> >>>>>>>> CREATE TABLE kafka_table ( >>>>>>>> id BIGINT, >>>>>>>> name STRING, >>>>>>>> timestamp STRING SYSTEM_METADATA("timestamp"), // get the >>>>>>> timestamp >>>>>>>> field from metadata >>>>>>>> ts AS to_timestamp(timestamp) // normal computed column, >>> parse >>>>> the >>>>>>>> string to TIMESTAMP type by using the metadata field >>>>>>>> ) WITH ( >>>>>>>> ... >>>>>>>> ) >>>>>>>> >>>>>>>> Best, >>>>>>>> Kurt >>>>>>>> >>>>>>>> >>>>>>>> On Tue, Sep 8, 2020 at 11:57 PM Timo Walther <twal...@apache.org> >>>>> wrote: >>>>>>>> >>>>>>>>> Hi Leonard, >>>>>>>>> >>>>>>>>> the only alternative I see is that we introduce a concept that is >>>>>>>>> completely different to computed columns. This is also mentioned >>> in >>>>> the >>>>>>>>> rejected alternative section of the FLIP. Something like: >>>>>>>>> >>>>>>>>> CREATE TABLE kafka_table ( >>>>>>>>> id BIGINT, >>>>>>>>> name STRING, >>>>>>>>> timestamp INT SYSTEM_METADATA("timestamp") PERSISTED, >>>>>>>>> headers MAP<STRING, BYTES> SYSTEM_METADATA("headers") >>>> PERSISTED >>>>>>>>> ) WITH ( >>>>>>>>> ... >>>>>>>>> ) >>>>>>>>> >>>>>>>>> This way we would avoid confusion at all and can easily map >>> columns >>>> to >>>>>>>>> metadata columns. The disadvantage is that users cannot call UDFs >>> or >>>>>>>>> parse timestamps. This would need to be done in a real computed >>>>> column. >>>>>>>>> >>>>>>>>> I'm happy about better alternatives. >>>>>>>>> >>>>>>>>> Regards, >>>>>>>>> Timo >>>>>>>>> >>>>>>>>> >>>>>>>>> On 08.09.20 15:37, Leonard Xu wrote: >>>>>>>>>> HI, Timo >>>>>>>>>> >>>>>>>>>> Thanks for driving this FLIP. >>>>>>>>>> >>>>>>>>>> Sorry but I have a concern about Writing metadata via >>>>> DynamicTableSink >>>>>>>>> section: >>>>>>>>>> >>>>>>>>>> CREATE TABLE kafka_table ( >>>>>>>>>> id BIGINT, >>>>>>>>>> name STRING, >>>>>>>>>> timestamp AS CAST(SYSTEM_METADATA("timestamp") AS BIGINT) >>>>>>> PERSISTED, >>>>>>>>>> headers AS CAST(SYSTEM_METADATA("headers") AS MAP<STRING, >>>>> BYTES>) >>>>>>>>> PERSISTED >>>>>>>>>> ) WITH ( >>>>>>>>>> ... >>>>>>>>>> ) >>>>>>>>>> An insert statement could look like: >>>>>>>>>> >>>>>>>>>> INSERT INTO kafka_table VALUES ( >>>>>>>>>> (1, "ABC", 1599133672, MAP('checksum', >>> computeChecksum(...))) >>>>>>>>>> ) >>>>>>>>>> >>>>>>>>>> The proposed INERT syntax does not make sense to me, because it >>>>>>> contains >>>>>>>>> computed(generated) column. >>>>>>>>>> Both SQL server and Postgresql do not allow to insert value to >>>>> computed >>>>>>>>> columns even they are persisted, this boke the generated column >>>>>>> semantics >>>>>>>>> and may confuse user much. >>>>>>>>>> >>>>>>>>>> For SQL server computed column[1]: >>>>>>>>>>> column_name AS computed_column_expression [ PERSISTED [ NOT >>> NULL ] >>>>>>> ]... >>>>>>>>>>> NOTE: A computed column cannot be the target of an INSERT or >>>> UPDATE >>>>>>>>> statement. >>>>>>>>>> >>>>>>>>>> For Postgresql generated column[2]: >>>>>>>>>>> height_in numeric GENERATED ALWAYS AS (height_cm / 2.54) >>>> STORED >>>>>>>>>>> NOTE: A generated column cannot be written to directly. In >>> INSERT >>>> or >>>>>>>>> UPDATE commands, a value cannot be specified for a generated >>> column, >>>>> but >>>>>>>>> the keyword DEFAULT may be specified. >>>>>>>>>> >>>>>>>>>> It shouldn't be allowed to set/update value for generated column >>>>> after >>>>>>>>> lookup the SQL 2016: >>>>>>>>>>> <insert statement> ::= >>>>>>>>>>> INSERT INTO <insertion target> <insert columns and source> >>>>>>>>>>> >>>>>>>>>>> If <contextually typed table value constructor> CTTVC is >>>> specified, >>>>>>>>> then every <contextually typed row >>>>>>>>>>> value constructor element> simply contained in CTTVC whose >>>>>>> positionally >>>>>>>>> corresponding <column name> >>>>>>>>>>> in <insert column list> references a column of which some >>>> underlying >>>>>>>>> column is a generated column shall >>>>>>>>>>> be a <default specification>. >>>>>>>>>>> A <default specification> specifies the default value of some >>>>>>>>> associated item. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> [1] >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://docs.microsoft.com/en-US/sql/t-sql/statements/alter-table-computed-column-definition-transact-sql?view=sql-server-ver15 >>> >>>>>>>>> < >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://docs.microsoft.com/en-US/sql/t-sql/statements/alter-table-computed-column-definition-transact-sql?view=sql-server-ver15 >>> >>>>>>>>>> >>>>>>>>>> [2] >>> https://www.postgresql.org/docs/12/ddl-generated-columns.html >>>> < >>>>>>>>> https://www.postgresql.org/docs/12/ddl-generated-columns.html> >>>>>>>>>> >>>>>>>>>>> 在 2020年9月8日,17:31,Timo Walther <twal...@apache.org> 写道: >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Hi Jark, >>>>>>>>>>> >>>>>>>>>>> according to Flink's and Calcite's casting definition in [1][2] >>>>>>>>> TIMESTAMP WITH LOCAL TIME ZONE should be castable from BIGINT. If >>>> not, >>>>>>> we >>>>>>>>> will make it possible ;-) >>>>>>>>>>> >>>>>>>>>>> I'm aware of DeserializationSchema.getProducedType but I think >>>> that >>>>>>>>> this method is actually misplaced. The type should rather be >>> passed >>>> to >>>>>>> the >>>>>>>>> source itself. >>>>>>>>>>> >>>>>>>>>>> For our Kafka SQL source, we will also not use this method >>> because >>>>> the >>>>>>>>> Kafka source will add own metadata in addition to the >>>>>>>>> DeserializationSchema. So DeserializationSchema.getProducedType >>> will >>>>>>> never >>>>>>>>> be read. >>>>>>>>>>> >>>>>>>>>>> For now I suggest to leave out the `DataType` from >>>>>>>>> DecodingFormat.applyReadableMetadata. Also because the format's >>>>> physical >>>>>>>>> type is passed later in `createRuntimeDecoder`. If necessary, it >>> can >>>>> be >>>>>>>>> computed manually by consumedType + metadata types. We will >>> provide >>>> a >>>>>>>>> metadata utility class for that. >>>>>>>>>>> >>>>>>>>>>> Regards, >>>>>>>>>>> Timo >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> [1] >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://github.com/apache/flink/blob/master/flink-table/flink-table-common/src/main/java/org/apache/flink/table/types/logical/utils/LogicalTypeCasts.java#L200 >>> >>>>>>>>>>> [2] >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://github.com/apache/calcite/blob/master/core/src/main/java/org/apache/calcite/sql/type/SqlTypeCoercionRule.java#L254 >>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On 08.09.20 10:52, Jark Wu wrote: >>>>>>>>>>>> Hi Timo, >>>>>>>>>>>> The updated CAST SYSTEM_METADATA behavior sounds good to me. I >>>> just >>>>>>>>> noticed >>>>>>>>>>>> that a BIGINT can't be converted to "TIMESTAMP(3) WITH LOCAL >>> TIME >>>>>>>>> ZONE". >>>>>>>>>>>> So maybe we need to support this, or use "TIMESTAMP(3) WITH >>> LOCAL >>>>>>> TIME >>>>>>>>>>>> ZONE" as the defined type of Kafka timestamp? I think this >>> makes >>>>>>> sense, >>>>>>>>>>>> because it represents the milli-seconds since epoch. >>>>>>>>>>>> Regarding "DeserializationSchema doesn't need TypeInfo", I >>> don't >>>>>>> think >>>>>>>>> so. >>>>>>>>>>>> The DeserializationSchema implements ResultTypeQueryable, thus >>>> the >>>>>>>>>>>> implementation needs to return an output TypeInfo. >>>>>>>>>>>> Besides, FlinkKafkaConsumer also >>>>>>>>>>>> calls DeserializationSchema.getProducedType as the produced >>> type >>>> of >>>>>>> the >>>>>>>>>>>> source function [1]. >>>>>>>>>>>> Best, >>>>>>>>>>>> Jark >>>>>>>>>>>> [1]: >>>>>>>>>>>> >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://github.com/apache/flink/blob/master/flink-connectors/flink-connector-kafka-base/src/main/java/org/apache/flink/streaming/connectors/kafka/FlinkKafkaConsumerBase.java#L1066 >>> >>>>>>>>>>>> On Tue, 8 Sep 2020 at 16:35, Timo Walther <twal...@apache.org> >>>>>>> wrote: >>>>>>>>>>>>> Hi everyone, >>>>>>>>>>>>> >>>>>>>>>>>>> I updated the FLIP again and hope that I could address the >>>>> mentioned >>>>>>>>>>>>> concerns. >>>>>>>>>>>>> >>>>>>>>>>>>> @Leonard: Thanks for the explanation. I wasn't aware that >>> ts_ms >>>>> and >>>>>>>>>>>>> source.ts_ms have different semantics. I updated the FLIP and >>>>> expose >>>>>>>>> the >>>>>>>>>>>>> most commonly used properties separately. So frequently used >>>>>>>>> properties >>>>>>>>>>>>> are not hidden in the MAP anymore: >>>>>>>>>>>>> >>>>>>>>>>>>> debezium-json.ingestion-timestamp >>>>>>>>>>>>> debezium-json.source.timestamp >>>>>>>>>>>>> debezium-json.source.database >>>>>>>>>>>>> debezium-json.source.schema >>>>>>>>>>>>> debezium-json.source.table >>>>>>>>>>>>> >>>>>>>>>>>>> However, since other properties depend on the used >>>>> connector/vendor, >>>>>>>>> the >>>>>>>>>>>>> remaining options are stored in: >>>>>>>>>>>>> >>>>>>>>>>>>> debezium-json.source.properties >>>>>>>>>>>>> >>>>>>>>>>>>> And accessed with: >>>>>>>>>>>>> >>>>>>>>>>>>> CAST(SYSTEM_METADATA('debezium-json.source.properties') AS >>>>>>> MAP<STRING, >>>>>>>>>>>>> STRING>)['table'] >>>>>>>>>>>>> >>>>>>>>>>>>> Otherwise it is not possible to figure out the value and >>> column >>>>> type >>>>>>>>>>>>> during validation. >>>>>>>>>>>>> >>>>>>>>>>>>> @Jark: You convinced me in relaxing the CAST constraints. I >>>> added >>>>> a >>>>>>>>>>>>> dedicacated sub-section to the FLIP: >>>>>>>>>>>>> >>>>>>>>>>>>> For making the use of SYSTEM_METADATA easier and avoid nested >>>>>>> casting >>>>>>>>> we >>>>>>>>>>>>> allow explicit casting to a target data type: >>>>>>>>>>>>> >>>>>>>>>>>>> rowtime AS CAST(SYSTEM_METADATA("timestamp") AS TIMESTAMP(3) >>>> WITH >>>>>>>>> LOCAL >>>>>>>>>>>>> TIME ZONE) >>>>>>>>>>>>> >>>>>>>>>>>>> A connector still produces and consumes the data type >>>>>>>>>>>>> returned >>>> by >>>>>>>>>>>>> `listMetadata()`. The planner will insert necessary explicit >>>>> casts. >>>>>>>>>>>>> >>>>>>>>>>>>> In any case, the user must provide a CAST such that the >>> computed >>>>>>>>> column >>>>>>>>>>>>> receives a valid data type when constructing the table >>>>>>>>>>>>> schema. >>>>>>>>>>>>> >>>>>>>>>>>>> "I don't see a reason why >>> `DecodingFormat#applyReadableMetadata` >>>>>>>>> needs a >>>>>>>>>>>>> DataType argument." >>>>>>>>>>>>> >>>>>>>>>>>>> Correct he DeserializationSchema doesn't need TypeInfo, it is >>>>> always >>>>>>>>>>>>> executed locally. It is the source that needs TypeInfo for >>>>>>> serializing >>>>>>>>>>>>> the record to the next operator. And that's this is what we >>>>> provide. >>>>>>>>>>>>> >>>>>>>>>>>>> @Danny: >>>>>>>>>>>>> >>>>>>>>>>>>> “SYSTEM_METADATA("offset")` returns the NULL type by default” >>>>>>>>>>>>> >>>>>>>>>>>>> We can also use some other means to represent an UNKNOWN data >>>>> type. >>>>>>> In >>>>>>>>>>>>> the Flink type system, we use the NullType for it. The >>> important >>>>>>> part >>>>>>>>> is >>>>>>>>>>>>> that the final data type is known for the entire computed >>>> column. >>>>>>> As I >>>>>>>>>>>>> mentioned before, I would avoid the suggested option b) that >>>> would >>>>>>> be >>>>>>>>>>>>> similar to your suggestion. The CAST should be enough and >>> allows >>>>> for >>>>>>>>>>>>> complex expressions in the computed column. Option b) would >>> need >>>>>>>>> parser >>>>>>>>>>>>> changes. >>>>>>>>>>>>> >>>>>>>>>>>>> Regards, >>>>>>>>>>>>> Timo >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 08.09.20 06:21, Leonard Xu wrote: >>>>>>>>>>>>>> Hi, Timo >>>>>>>>>>>>>> >>>>>>>>>>>>>> Thanks for you explanation and update, I have only one >>>> question >>>>>>> for >>>>>>>>>>>>> the latest FLIP. >>>>>>>>>>>>>> >>>>>>>>>>>>>> About the MAP<STRING, STRING> DataType of key >>>>>>>>> 'debezium-json.source', if >>>>>>>>>>>>> user want to use the table name metadata, they need to write: >>>>>>>>>>>>>> tableName STRING AS >>> CAST(SYSTEM_METADATA('debeuim-json.source') >>>>> AS >>>>>>>>>>>>> MAP<STRING, STRING>)['table'] >>>>>>>>>>>>>> >>>>>>>>>>>>>> the expression is a little complex for user, Could we only >>>>> support >>>>>>>>>>>>> necessary metas with simple DataType as following? >>>>>>>>>>>>>> tableName STRING AS >>>>>>>>> CAST(SYSTEM_METADATA('debeuim-json.source.table') AS >>>>>>>>>>>>> STRING), >>>>>>>>>>>>>> transactionTime LONG AS >>>>>>>>>>>>> CAST(SYSTEM_METADATA('debeuim-json.source.ts_ms') AS BIGINT), >>>>>>>>>>>>>> >>>>>>>>>>>>>> In this way, we can simplify the expression, the mainly used >>>>>>>>> metadata in >>>>>>>>>>>>> changelog format may include >>>>>>>>> 'database','table','source.ts_ms','ts_ms' from >>>>>>>>>>>>> my side, >>>>>>>>>>>>>> maybe we could only support them at first version. >>>>>>>>>>>>>> >>>>>>>>>>>>>> Both Debezium and Canal have above four metadata, and I‘m >>>> willing >>>>>>> to >>>>>>>>>>>>> take some subtasks in next development if necessary. >>>>>>>>>>>>>> >>>>>>>>>>>>>> Debezium: >>>>>>>>>>>>>> { >>>>>>>>>>>>>> "before": null, >>>>>>>>>>>>>> "after": { "id": 101,"name": "scooter"}, >>>>>>>>>>>>>> "source": { >>>>>>>>>>>>>> "db": "inventory", # 1. database >>> name >>>>> the >>>>>>>>>>>>> changelog belongs to. >>>>>>>>>>>>>> "table": "products", # 2. table name >>> the >>>>>>>>> changelog >>>>>>>>>>>>> belongs to. >>>>>>>>>>>>>> "ts_ms": 1589355504100, # 3. >>>>>>>>>>>>>> timestamp of >>>> the >>>>>>>>> change >>>>>>>>>>>>> happened in database system, i.e.: transaction time in >>> database. >>>>>>>>>>>>>> "connector": "mysql", >>>>>>>>>>>>>> …. >>>>>>>>>>>>>> }, >>>>>>>>>>>>>> "ts_ms": 1589355606100, # 4. timestamp >>> when >>>>> the >>>>>>>>> debezium >>>>>>>>>>>>> processed the changelog. >>>>>>>>>>>>>> "op": "c", >>>>>>>>>>>>>> "transaction": null >>>>>>>>>>>>>> } >>>>>>>>>>>>>> >>>>>>>>>>>>>> Canal: >>>>>>>>>>>>>> { >>>>>>>>>>>>>> "data": [{ "id": "102", "name": "car battery" }], >>>>>>>>>>>>>> "database": "inventory", # 1. database name the >>>>> changelog >>>>>>>>>>>>> belongs to. >>>>>>>>>>>>>> "table": "products", # 2. table name the >>>> changelog >>>>>>>>> belongs >>>>>>>>>>>>> to. >>>>>>>>>>>>>> "es": 1589374013000, # 3. execution time of >>> the >>>>>>> change >>>>>>>>> in >>>>>>>>>>>>> database system, i.e.: transaction time in database. >>>>>>>>>>>>>> "ts": 1589374013680, # 4. timestamp when the >>>>> cannal >>>>>>>>>>>>> processed the changelog. >>>>>>>>>>>>>> "isDdl": false, >>>>>>>>>>>>>> "mysqlType": {}, >>>>>>>>>>>>>> .... >>>>>>>>>>>>>> } >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> Best >>>>>>>>>>>>>> Leonard >>>>>>>>>>>>>> >>>>>>>>>>>>>>> 在 2020年9月8日,11:57,Danny Chan <yuzhao....@gmail.com> >>>>>>>>>>>>>>> 写道: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Thanks Timo ~ >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> The FLIP was already in pretty good shape, I have only 2 >>>>> questions >>>>>>>>> here: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> 1. “`CAST(SYSTEM_METADATA("offset") AS INT)` would be a >>> valid >>>>>>>>> read-only >>>>>>>>>>>>> computed column for Kafka and can be extracted by the >>> planner.” >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> What is the pros we follow the SQL-SERVER syntax here ? >>>> Usually >>>>> an >>>>>>>>>>>>> expression return type can be inferred automatically. But I >>>> guess >>>>>>>>>>>>> SQL-SERVER does not have function like SYSTEM_METADATA which >>>>>>> actually >>>>>>>>> does >>>>>>>>>>>>> not have a specific return type. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> And why not use the Oracle or MySQL syntax there ? >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> column_name [datatype] [GENERATED ALWAYS] AS (expression) >>>>>>> [VIRTUAL] >>>>>>>>>>>>>>> Which is more straight-forward. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> 2. “SYSTEM_METADATA("offset")` returns the NULL type by >>>> default” >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> The default type should not be NULL because only NULL >>> literal >>>>> does >>>>>>>>>>>>> that. Usually we use ANY as the type if we do not know the >>>>> specific >>>>>>>>> type in >>>>>>>>>>>>> the SQL context. ANY means the physical value can be any java >>>>>>> object. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> [1] >>>> https://oracle-base.com/articles/11g/virtual-columns-11gr1 >>>>>>>>>>>>>>> [2] >>>>>>>>>>>>> >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://dev.mysql.com/doc/refman/5.7/en/create-table-generated-columns.html >>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>> Danny Chan >>>>>>>>>>>>>>> 在 2020年9月4日 +0800 PM4:48,Timo Walther >>>>>>>>>>>>>>> <twal...@apache.org >>>>> ,写道: >>>>>>>>>>>>>>>> Hi everyone, >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> I completely reworked FLIP-107. It now covers the full >>> story >>>>> how >>>>>>> to >>>>>>>>>>>>> read >>>>>>>>>>>>>>>> and write metadata from/to connectors and formats. It >>>> considers >>>>>>>>> all of >>>>>>>>>>>>>>>> the latest FLIPs, namely FLIP-95, FLIP-132 and >>>>>>>>>>>>>>>> FLIP-122. It >>>>>>>>> introduces >>>>>>>>>>>>>>>> the concept of PERSISTED computed columns and leaves out >>>>>>>>> partitioning >>>>>>>>>>>>>>>> for now. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Looking forward to your feedback. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Regards, >>>>>>>>>>>>>>>> Timo >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On 04.03.20 09:45, Kurt Young wrote: >>>>>>>>>>>>>>>>> Sorry, forgot one question. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> 4. Can we make the value.fields-include more orthogonal? >>>> Like >>>>>>> one >>>>>>>>> can >>>>>>>>>>>>>>>>> specify it as "EXCEPT_KEY, EXCEPT_TIMESTAMP". >>>>>>>>>>>>>>>>> With current EXCEPT_KEY and EXCEPT_KEY_TIMESTAMP, users >>> can >>>>> not >>>>>>>>>>>>> config to >>>>>>>>>>>>>>>>> just ignore timestamp but keep key. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>> Kurt >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Wed, Mar 4, 2020 at 4:42 PM Kurt Young < >>> ykt...@gmail.com >>>>> >>>>>>>>> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Hi Dawid, >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> I have a couple of questions around key fields, actually >>> I >>>>> also >>>>>>>>> have >>>>>>>>>>>>> some >>>>>>>>>>>>>>>>>> other questions but want to be focused on key fields >>> first. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> 1. I don't fully understand the usage of >>>>>>>>>>>>>>>>>> "key.fields". Is >>>>> this >>>>>>>>>>>>> option only >>>>>>>>>>>>>>>>>> valid during write operation? Because for >>>>>>>>>>>>>>>>>> reading, I can't imagine how such options can be >>> applied. I >>>>>>> would >>>>>>>>>>>>> expect >>>>>>>>>>>>>>>>>> that there might be a SYSTEM_METADATA("key") >>>>>>>>>>>>>>>>>> to read and assign the key to a normal field? >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> 2. If "key.fields" is only valid in write operation, I >>> want >>>>> to >>>>>>>>>>>>> propose we >>>>>>>>>>>>>>>>>> can simplify the options to not introducing >>> key.format.type >>>>> and >>>>>>>>>>>>>>>>>> other related options. I think a single "key.field" (not >>>>>>> fields) >>>>>>>>>>>>> would be >>>>>>>>>>>>>>>>>> enough, users can use UDF to calculate whatever key they >>>>>>>>>>>>>>>>>> want before sink. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> 3. Also I don't want to introduce "value.format.type" >>>>>>>>>>>>>>>>>> and >>>>>>>>>>>>>>>>>> "value.format.xxx" with the "value" prefix. Not every >>>>> connector >>>>>>>>> has a >>>>>>>>>>>>>>>>>> concept >>>>>>>>>>>>>>>>>> of key and values. The old parameter "format.type" >>> already >>>>> good >>>>>>>>>>>>> enough to >>>>>>>>>>>>>>>>>> use. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>> Kurt >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> On Tue, Mar 3, 2020 at 10:40 PM Jark Wu < >>> imj...@gmail.com> >>>>>>>>> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Thanks Dawid, >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> I have two more questions. >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> SupportsMetadata >>>>>>>>>>>>>>>>>>> Introducing SupportsMetadata sounds good to me. But I >>> have >>>>>>> some >>>>>>>>>>>>> questions >>>>>>>>>>>>>>>>>>> regarding to this interface. >>>>>>>>>>>>>>>>>>> 1) How do the source know what the expected return type >>> of >>>>>>> each >>>>>>>>>>>>> metadata? >>>>>>>>>>>>>>>>>>> 2) Where to put the metadata fields? Append to the >>>> existing >>>>>>>>> physical >>>>>>>>>>>>>>>>>>> fields? >>>>>>>>>>>>>>>>>>> If yes, I would suggest to change the signature to >>>>>>> `TableSource >>>>>>>>>>>>>>>>>>> appendMetadataFields(String[] metadataNames, DataType[] >>>>>>>>>>>>> metadataTypes)` >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> SYSTEM_METADATA("partition") >>>>>>>>>>>>>>>>>>> Can SYSTEM_METADATA() function be used nested in a >>>> computed >>>>>>>>> column >>>>>>>>>>>>>>>>>>> expression? If yes, how to specify the return type of >>>>>>>>>>>>> SYSTEM_METADATA? >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>>> Jark >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> On Tue, 3 Mar 2020 at 17:06, Dawid Wysakowicz < >>>>>>>>>>>>> dwysakow...@apache.org> >>>>>>>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Hi, >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> 1. I thought a bit more on how the source would emit >>> the >>>>>>>>> columns >>>>>>>>>>>>> and I >>>>>>>>>>>>>>>>>>>> now see its not exactly the same as regular columns. I >>>> see >>>>> a >>>>>>>>> need >>>>>>>>>>>>> to >>>>>>>>>>>>>>>>>>>> elaborate a bit more on that in the FLIP as you asked, >>>>> Jark. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> I do agree mostly with Danny on how we should do that. >>>> One >>>>>>>>>>>>> additional >>>>>>>>>>>>>>>>>>>> things I would introduce is an >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> interface SupportsMetadata { >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> boolean supportsMetadata(Set<String> metadataFields); >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> TableSource generateMetadataFields(Set<String> >>>>>>> metadataFields); >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> } >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> This way the source would have to declare/emit only >>>>>>>>>>>>>>>>>>>> the >>>>>>>>> requested >>>>>>>>>>>>>>>>>>>> metadata fields. In order not to clash with user >>> defined >>>>>>>>> fields. >>>>>>>>>>>>> When >>>>>>>>>>>>>>>>>>>> emitting the metadata field I would prepend the column >>>> name >>>>>>>>> with >>>>>>>>>>>>>>>>>>>> __system_{property_name}. Therefore when requested >>>>>>>>>>>>>>>>>>>> SYSTEM_METADATA("partition") the source would append a >>>>> field >>>>>>>>>>>>>>>>>>>> __system_partition to the schema. This would be never >>>>> visible >>>>>>>>> to >>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> user as it would be used only for the subsequent >>> computed >>>>>>>>> columns. >>>>>>>>>>>>> If >>>>>>>>>>>>>>>>>>>> that makes sense to you, I will update the FLIP with >>> this >>>>>>>>>>>>> description. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> 2. CAST vs explicit type in computed columns >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Here I agree with Danny. It is also the current state >>> of >>>>> the >>>>>>>>>>>>> proposal. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> 3. Partitioning on computed column vs function >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Here I also agree with Danny. I also think those are >>>>>>>>> orthogonal. I >>>>>>>>>>>>> would >>>>>>>>>>>>>>>>>>>> leave out the STORED computed columns out of the >>>>> discussion. >>>>>>> I >>>>>>>>>>>>> don't see >>>>>>>>>>>>>>>>>>>> how do they relate to the partitioning. I already put >>>> both >>>>> of >>>>>>>>> those >>>>>>>>>>>>>>>>>>>> cases in the document. We can either partition on a >>>>> computed >>>>>>>>>>>>> column or >>>>>>>>>>>>>>>>>>>> use a udf in a partioned by clause. I am fine with >>>> leaving >>>>>>> out >>>>>>>>> the >>>>>>>>>>>>>>>>>>>> partitioning by udf in the first version if you still >>>> have >>>>>>> some >>>>>>>>>>>>>>>>>>> concerns. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> As for your question Danny. It depends which >>> partitioning >>>>>>>>> strategy >>>>>>>>>>>>> you >>>>>>>>>>>>>>>>>>> use. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> For the HASH partitioning strategy I thought it would >>>> work >>>>> as >>>>>>>>> you >>>>>>>>>>>>>>>>>>>> explained. It would be N = MOD(expr, num). I am not >>> sure >>>>>>>>> though if >>>>>>>>>>>>> we >>>>>>>>>>>>>>>>>>>> should introduce the PARTITIONS clause. Usually Flink >>>> does >>>>>>> not >>>>>>>>> own >>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> data and the partitions are already an intrinsic >>> property >>>>> of >>>>>>>>> the >>>>>>>>>>>>>>>>>>>> underlying source e.g. for kafka we do not create >>> topics, >>>>> but >>>>>>>>> we >>>>>>>>>>>>> just >>>>>>>>>>>>>>>>>>>> describe pre-existing pre-partitioned topic. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> 4. timestamp vs timestamp.field vs connector.field vs >>> ... >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> I am fine with changing it to timestamp.field to be >>>>>>> consistent >>>>>>>>> with >>>>>>>>>>>>>>>>>>>> other value.fields and key.fields. Actually that was >>> also >>>>> my >>>>>>>>>>>>> initial >>>>>>>>>>>>>>>>>>>> proposal in a first draft I prepared. I changed it >>>>> afterwards >>>>>>>>> to >>>>>>>>>>>>> shorten >>>>>>>>>>>>>>>>>>>> the key. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Dawid >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> On 03/03/2020 09:00, Danny Chan wrote: >>>>>>>>>>>>>>>>>>>>> Thanks Dawid for bringing up this discussion, I think >>> it >>>>> is >>>>>>> a >>>>>>>>>>>>> useful >>>>>>>>>>>>>>>>>>>> feature ~ >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> About how the metadata outputs from source >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> I think it is completely orthogonal, computed column >>>> push >>>>>>>>> down is >>>>>>>>>>>>>>>>>>>> another topic, this should not be a blocker but a >>>>> promotion, >>>>>>>>> if we >>>>>>>>>>>>> do >>>>>>>>>>>>>>>>>>> not >>>>>>>>>>>>>>>>>>>> have any filters on the computed column, there is no >>> need >>>>> to >>>>>>>>> do any >>>>>>>>>>>>>>>>>>>> pushings; the source node just emit the complete >>>>>>>>>>>>>>>>>>>> record >>>>> with >>>>>>>>> full >>>>>>>>>>>>>>>>>>> metadata >>>>>>>>>>>>>>>>>>>> with the declared physical schema, then when >>>>>>>>>>>>>>>>>>>> generating >>>> the >>>>>>>>> virtual >>>>>>>>>>>>>>>>>>>> columns, we would extract the metadata info and output >>> as >>>>>>> full >>>>>>>>>>>>>>>>>>> columns(with >>>>>>>>>>>>>>>>>>>> full schema). >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> About the type of metadata column >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> Personally i prefer explicit type instead of CAST, >>> they >>>>> are >>>>>>>>>>>>> symantic >>>>>>>>>>>>>>>>>>>> equivalent though, explict type is more >>> straight-forward >>>>> and >>>>>>>>> we can >>>>>>>>>>>>>>>>>>> declare >>>>>>>>>>>>>>>>>>>> the nullable attribute there. >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> About option A: partitioning based on acomputed >>>>>>>>>>>>>>>>>>>>> column >>>> VS >>>>>>>>> option >>>>>>>>>>>>> B: >>>>>>>>>>>>>>>>>>>> partitioning with just a function >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> From the FLIP, it seems that B's partitioning is >>>> just >>>>> a >>>>>>>>> strategy >>>>>>>>>>>>> when >>>>>>>>>>>>>>>>>>>> writing data, the partiton column is not included in >>> the >>>>>>> table >>>>>>>>>>>>> schema, >>>>>>>>>>>>>>>>>>> so >>>>>>>>>>>>>>>>>>>> it's just useless when reading from that. >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> - Compared to A, we do not need to generate the >>>> partition >>>>>>>>> column >>>>>>>>>>>>> when >>>>>>>>>>>>>>>>>>>> selecting from the table(but insert into) >>>>>>>>>>>>>>>>>>>>> - For A we can also mark the column as STORED when we >>>> want >>>>>>> to >>>>>>>>>>>>> persist >>>>>>>>>>>>>>>>>>>> that >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> So in my opition they are orthogonal, we can support >>>>> both, i >>>>>>>>> saw >>>>>>>>>>>>> that >>>>>>>>>>>>>>>>>>>> MySQL/Oracle[1][2] would suggest to also define the >>>>>>> PARTITIONS >>>>>>>>>>>>> num, and >>>>>>>>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> partitions are managed under a "tablenamespace", the >>>>>>> partition >>>>>>>>> in >>>>>>>>>>>>> which >>>>>>>>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> record is stored is partition number N, where N = >>>> MOD(expr, >>>>>>>>> num), >>>>>>>>>>>>> for >>>>>>>>>>>>>>>>>>> your >>>>>>>>>>>>>>>>>>>> design, which partiton the record would persist ? >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> [1] >>>>>>>>>>>>> >>> https://dev.mysql.com/doc/refman/5.7/en/partitioning-hash.html >>>>>>>>>>>>>>>>>>>>> [2] >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://docs.oracle.com/database/121/VLDBG/GUID-F023D3ED-262F-4B19-950A-D3C8F8CDB4F4.htm#VLDBG1270 >>> >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>>>>> Danny Chan >>>>>>>>>>>>>>>>>>>>> 在 2020年3月2日 +0800 PM6:16,Dawid Wysakowicz < >>>>>>>>> dwysakow...@apache.org >>>>>>>>>>>>>>>>>>>> ,写道: >>>>>>>>>>>>>>>>>>>>>> Hi Jark, >>>>>>>>>>>>>>>>>>>>>> Ad. 2 I added a section to discuss relation to >>> FLIP-63 >>>>>>>>>>>>>>>>>>>>>> Ad. 3 Yes, I also tried to somewhat keep >>>>>>>>>>>>>>>>>>>>>> hierarchy of >>>>>>>>> properties. >>>>>>>>>>>>>>>>>>>> Therefore you have the key.format.type. >>>>>>>>>>>>>>>>>>>>>> I also considered exactly what you are suggesting >>>>>>> (prefixing >>>>>>>>> with >>>>>>>>>>>>>>>>>>>> connector or kafka). I should've put that into an >>>>>>>>> Option/Rejected >>>>>>>>>>>>>>>>>>>> alternatives. >>>>>>>>>>>>>>>>>>>>>> I agree timestamp, key.*, value.* are connector >>>>> properties. >>>>>>>>> Why I >>>>>>>>>>>>>>>>>>>> wanted to suggest not adding that prefix in the first >>>>> version >>>>>>>>> is >>>>>>>>>>>>> that >>>>>>>>>>>>>>>>>>>> actually all the properties in the WITH section are >>>>> connector >>>>>>>>>>>>>>>>>>> properties. >>>>>>>>>>>>>>>>>>>> Even format is in the end a connector property as some >>> of >>>>> the >>>>>>>>>>>>> sources >>>>>>>>>>>>>>>>>>> might >>>>>>>>>>>>>>>>>>>> not have a format, imo. The benefit of not adding the >>>>> prefix >>>>>>> is >>>>>>>>>>>>> that it >>>>>>>>>>>>>>>>>>>> makes the keys a bit shorter. Imagine prefixing all >>>>>>>>>>>>>>>>>>>> the >>>>>>>>> properties >>>>>>>>>>>>> with >>>>>>>>>>>>>>>>>>>> connector (or if we go with FLINK-12557: >>> elasticsearch): >>>>>>>>>>>>>>>>>>>>>> elasticsearch.key.format.type: csv >>>>>>>>>>>>>>>>>>>>>> elasticsearch.key.format.field: .... >>>>>>>>>>>>>>>>>>>>>> elasticsearch.key.format.delimiter: .... >>>>>>>>>>>>>>>>>>>>>> elasticsearch.key.format.*: .... >>>>>>>>>>>>>>>>>>>>>> I am fine with doing it though if this is a >>>>>>>>>>>>>>>>>>>>>> preferred >>>>>>>>> approach >>>>>>>>>>>>> in the >>>>>>>>>>>>>>>>>>>> community. >>>>>>>>>>>>>>>>>>>>>> Ad in-line comments: >>>>>>>>>>>>>>>>>>>>>> I forgot to update the `value.fields.include` >>> property. >>>>> It >>>>>>>>>>>>> should be >>>>>>>>>>>>>>>>>>>> value.fields-include. Which I think you also suggested >>> in >>>>> the >>>>>>>>>>>>> comment, >>>>>>>>>>>>>>>>>>>> right? >>>>>>>>>>>>>>>>>>>>>> As for the cast vs declaring output type of computed >>>>>>> column. >>>>>>>>> I >>>>>>>>>>>>> think >>>>>>>>>>>>>>>>>>>> it's better not to use CAST, but declare a type of an >>>>>>>>> expression >>>>>>>>>>>>> and >>>>>>>>>>>>>>>>>>> later >>>>>>>>>>>>>>>>>>>> on infer the output type of SYSTEM_METADATA. The >>>>>>>>>>>>>>>>>>>> reason >>>> is >>>>> I >>>>>>>>> think >>>>>>>>>>>>> this >>>>>>>>>>>>>>>>>>> way >>>>>>>>>>>>>>>>>>>> it will be easier to implement e.g. filter push downs >>>> when >>>>>>>>> working >>>>>>>>>>>>> with >>>>>>>>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> native types of the source, e.g. in case of Kafka's >>>>> offset, i >>>>>>>>>>>>> think it's >>>>>>>>>>>>>>>>>>>> better to pushdown long rather than string. This could >>>> let >>>>> us >>>>>>>>> push >>>>>>>>>>>>>>>>>>>> expression like e.g. offset > 12345 & offset < 59382. >>>>>>>>> Otherwise we >>>>>>>>>>>>> would >>>>>>>>>>>>>>>>>>>> have to push down cast(offset, long) > 12345 && >>>>> cast(offset, >>>>>>>>> long) >>>>>>>>>>>>> < >>>>>>>>>>>>>>>>>>> 59382. >>>>>>>>>>>>>>>>>>>> Moreover I think we need to introduce the type for >>>> computed >>>>>>>>> columns >>>>>>>>>>>>>>>>>>> anyway >>>>>>>>>>>>>>>>>>>> to support functions that infer output type based on >>>>> expected >>>>>>>>>>>>> return >>>>>>>>>>>>>>>>>>> type. >>>>>>>>>>>>>>>>>>>>>> As for the computed column push down. Yes, >>>>> SYSTEM_METADATA >>>>>>>>> would >>>>>>>>>>>>> have >>>>>>>>>>>>>>>>>>>> to be pushed down to the source. If it is not possible >>>> the >>>>>>>>> planner >>>>>>>>>>>>>>>>>>> should >>>>>>>>>>>>>>>>>>>> fail. As far as I know computed columns push down will >>> be >>>>>>> part >>>>>>>>> of >>>>>>>>>>>>> source >>>>>>>>>>>>>>>>>>>> rework, won't it? ;) >>>>>>>>>>>>>>>>>>>>>> As for the persisted computed column. I think it is >>>>>>>>> completely >>>>>>>>>>>>>>>>>>>> orthogonal. In my current proposal you can also >>> partition >>>>> by >>>>>>> a >>>>>>>>>>>>> computed >>>>>>>>>>>>>>>>>>>> column. The difference between using a udf in >>> partitioned >>>>> by >>>>>>> vs >>>>>>>>>>>>>>>>>>> partitioned >>>>>>>>>>>>>>>>>>>> by a computed column is that when you partition by a >>>>> computed >>>>>>>>>>>>> column >>>>>>>>>>>>>>>>>>> this >>>>>>>>>>>>>>>>>>>> column must be also computed when reading the >>>>>>>>>>>>>>>>>>>> table. If >>>> you >>>>>>>>> use a >>>>>>>>>>>>> udf in >>>>>>>>>>>>>>>>>>>> the partitioned by, the expression is computed only >>> when >>>>>>>>> inserting >>>>>>>>>>>>> into >>>>>>>>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>> table. >>>>>>>>>>>>>>>>>>>>>> Hope this answers some of your questions. Looking >>>> forward >>>>>>> for >>>>>>>>>>>>> further >>>>>>>>>>>>>>>>>>>> suggestions. >>>>>>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>>>>>> Dawid >>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>> On 02/03/2020 05:18, Jark Wu wrote: >>>>>>>>>>>>>>>>>>>>>>> Hi, >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> Thanks Dawid for starting such a great discussion. >>>>> Reaing >>>>>>>>>>>>> metadata >>>>>>>>>>>>>>>>>>> and >>>>>>>>>>>>>>>>>>>>>>> key-part information from source is an important >>>> feature >>>>>>> for >>>>>>>>>>>>>>>>>>> streaming >>>>>>>>>>>>>>>>>>>>>>> users. >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> In general, I agree with the proposal of the FLIP. >>>>>>>>>>>>>>>>>>>>>>> I will leave my thoughts and comments here: >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> 1) +1 to use connector properties instead of >>>> introducing >>>>>>>>> HEADER >>>>>>>>>>>>>>>>>>>> keyword as >>>>>>>>>>>>>>>>>>>>>>> the reason you mentioned in the FLIP. >>>>>>>>>>>>>>>>>>>>>>> 2) we already introduced PARTITIONED BY in FLIP-63. >>>>> Maybe >>>>>>> we >>>>>>>>>>>>> should >>>>>>>>>>>>>>>>>>>> add a >>>>>>>>>>>>>>>>>>>>>>> section to explain what's the relationship between >>>> them. >>>>>>>>>>>>>>>>>>>>>>> Do their concepts conflict? Could INSERT PARTITION >>> be >>>>> used >>>>>>>>> on >>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>>>>> PARTITIONED table in this FLIP? >>>>>>>>>>>>>>>>>>>>>>> 3) Currently, properties are hierarchical in Flink >>>> SQL. >>>>>>>>> Shall we >>>>>>>>>>>>>>>>>>> make >>>>>>>>>>>>>>>>>>>> the >>>>>>>>>>>>>>>>>>>>>>> new introduced properties more hierarchical? >>>>>>>>>>>>>>>>>>>>>>> For example, "timestamp" => "connector.timestamp"? >>>>>>>>> (actually, I >>>>>>>>>>>>>>>>>>>> prefer >>>>>>>>>>>>>>>>>>>>>>> "kafka.timestamp" which is another improvement for >>>>>>>>> properties >>>>>>>>>>>>>>>>>>>> FLINK-12557) >>>>>>>>>>>>>>>>>>>>>>> A single "timestamp" in properties may mislead >>>>>>>>>>>>>>>>>>>>>>> users >>>>> that >>>>>>>>> the >>>>>>>>>>>>>>>>>>> field >>>>>>>>>>>>>>>>>>>> is >>>>>>>>>>>>>>>>>>>>>>> a rowtime attribute. >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> I also left some minor comments in the FLIP. >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>>>>>>>>>> Jark >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>> On Sun, 1 Mar 2020 at 22:30, Dawid Wysakowicz < >>>>>>>>>>>>>>>>>>> dwysakow...@apache.org> >>>>>>>>>>>>>>>>>>>>>>> wrote: >>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> Hi, >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> I would like to propose an improvement that would >>>>> enable >>>>>>>>>>>>> reading >>>>>>>>>>>>>>>>>>> table >>>>>>>>>>>>>>>>>>>>>>>> columns from different parts of source records. >>>> Besides >>>>>>> the >>>>>>>>>>>>> main >>>>>>>>>>>>>>>>>>>> payload >>>>>>>>>>>>>>>>>>>>>>>> majority (if not all of the sources) expose >>>> additional >>>>>>>>>>>>>>>>>>> information. It >>>>>>>>>>>>>>>>>>>>>>>> can be simply a read-only metadata such as offset, >>>>>>>>> ingestion >>>>>>>>>>>>> time >>>>>>>>>>>>>>>>>>> or a >>>>>>>>>>>>>>>>>>>>>>>> read and write parts of the record that contain >>> data >>>>> but >>>>>>>>>>>>>>>>>>> additionally >>>>>>>>>>>>>>>>>>>>>>>> serve different purposes (partitioning, compaction >>>>> etc.), >>>>>>>>> e.g. >>>>>>>>>>>>> key >>>>>>>>>>>>>>>>>>> or >>>>>>>>>>>>>>>>>>>>>>>> timestamp in Kafka. >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> We should make it possible to read and write data >>>> from >>>>>>> all >>>>>>>>> of >>>>>>>>>>>>> those >>>>>>>>>>>>>>>>>>>>>>>> locations. In this proposal I discuss reading >>>>>>> partitioning >>>>>>>>>>>>> data, >>>>>>>>>>>>>>>>>>> for >>>>>>>>>>>>>>>>>>>>>>>> completeness this proposal discusses also the >>>>>>> partitioning >>>>>>>>> when >>>>>>>>>>>>>>>>>>>> writing >>>>>>>>>>>>>>>>>>>>>>>> data out. >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> I am looking forward to your comments. >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> You can access the FLIP here: >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>> >>>>>>> >>>>> >>>> >>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-107%3A+Reading+table+columns+from+different+parts+of+source+records?src=contextnavpagetreemode >>> >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> Best, >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> Dawid >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>>> >>>> >>> >> >
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