I probably messed up with the meaning of eval()..thus it is called once for every distinct key (that could be composed by a combination of fields)? So, the other question is..how do I enable Blink planner support? Since when is LATERAL TABLE available in Flink? Is it equivalent to using temporal tables [1]?
[1] https://ci.apache.org/projects/flink/flink-docs-stable/dev/table/streaming/temporal_tables.html Best, Flavio On Sat, Jun 29, 2019 at 3:16 AM JingsongLee <lzljs3620...@aliyun.com> wrote: > The keys means joint primary keys, it is not list of keys, in your case, > maybe there is a single key? > > Best, Jingsong Lee > > > 来自阿里邮箱 iPhone版 > <https://itunes.apple.com/us/app/a-li-yun-you/id923828102?l=zh&ls=1&mt=8> > > ------------------Original Mail ------------------ > *From:*Flavio Pompermaier <pomperma...@okkam.it> > *Date:*2019-06-28 22:53:31 > *Recipient:*JingsongLee <lzljs3620...@aliyun.com> > *CC:*user <user@flink.apache.org> > *Subject:*Re: LookupableTableSource question > Sorry I copied and pasted twice the current eval method...I'd do this: > > public void eval(Object... keys) { > for (Object kkk : keys) { > Row keyRow = Row.of(kkk); > if (cache != null) { > List<Row> cachedRows = cache.getIfPresent(keyRow); > if (cachedRows != null) { > for (Row cachedRow : cachedRows) { > collect(cachedRow); > } > return; > } > } > } > ... > > On Fri, Jun 28, 2019 at 4:51 PM Flavio Pompermaier <pomperma...@okkam.it> > wrote: > >> This could be a good fit, I'll try to dig into it and see if it can be >> adapted to a REST service. >> The only strange thing I see is that the key of the local cache is per >> block of keys..am I wrong? >> Shouldn't it cycle over the list of passed keys? >> >> Right now it's the following: >> >> Cache<Row, List<Row>> cache; >> >> public void eval(Object... keys) { >> Row keyRow = Row.of(keys); >> if (cache != null) { >> List<Row> cachedRows = cache.getIfPresent(keyRow); >> if (cachedRows != null) { >> for (Row cachedRow : cachedRows) { >> collect(cachedRow); >> } >> return; >> } >> } >> ... >> >> while I'd use the following (also for JDBC): >> >> Cache<Row, List<Row>> cache; >> >> public void eval(Object... keys) { >> Row keyRow = Row.of(keys); >> if (cache != null) { >> List<Row> cachedRows = cache.getIfPresent(keyRow); >> if (cachedRows != null) { >> for (Row cachedRow : cachedRows) { >> collect(cachedRow); >> } >> return; >> } >> } >> ... >> >> public void eval(Object... keys) { >> for (Object kkk : keys) { >> Row keyRow = Row.of(kkk); >> if (cache != null) { >> List<Row> cachedRows = cache.getIfPresent(keyRow); >> if (cachedRows != null) { >> for (Row cachedRow : cachedRows) { >> collect(cachedRow); >> } >> return; >> } >> } >> } >> ... >> >> Am I missing something? >> >> >> On Fri, Jun 28, 2019 at 4:18 PM JingsongLee <lzljs3620...@aliyun.com> >> wrote: >> >>> Hi Flavio: >>> >>> I just implement a JDBCLookupFunction[1]. You can use it as table >>> function[2]. Or use >>> blink temporal table join[3] (Need blink planner support). >>> I add a google guava cache in JDBCLookupFunction with configurable >>> cacheMaxSize >>> (avoid memory OOM) and cacheExpireMs(For the fresh of lookup table). >>> Is that you want? >>> >>> [1] >>> https://github.com/JingsongLi/flink/blob/cc80999279b38627b37fa7550fb6610eee450d86/flink-connectors/flink-jdbc/src/main/java/org/apache/flink/api/java/io/jdbc/JDBCLookupFunction.java >>> [2] >>> https://github.com/JingsongLi/flink/blob/cc80999279b38627b37fa7550fb6610eee450d86/flink-connectors/flink-jdbc/src/test/java/org/apache/flink/api/java/io/jdbc/JDBCLookupFunctionITCase.java#L143 >>> [3] >>> https://github.com/apache/flink/blob/master/flink-table/flink-table-planner-blink/src/test/scala/org/apache/flink/table/runtime/stream/sql/LookupJoinITCase.scala#L75 >>> >>> Best, JingsongLee >>> >>> ------------------------------------------------------------------ >>> From:Flavio Pompermaier <pomperma...@okkam.it> >>> Send Time:2019年6月28日(星期五) 21:04 >>> To:user <user@flink.apache.org> >>> Subject:LookupableTableSource question >>> >>> Hi to all, >>> I have a use case where I'd like to enrich a stream using a rarely >>> updated lookup table. >>> Basically, I'd like to be able to set a refresh policy that is triggered >>> either when a key was not found (a new key has probably been added in the >>> mean time) or a configurable refresh-period has elapsed. >>> >>> Is there any suggested solution to this? The LookupableTableSource looks >>> very similar to what I'd like to achieve but I can't find a real-world >>> example using it and it lacks of such 2 requirements (key-values are not >>> refreshed after a configurable timeout and a KeyNotFound callback cannot be >>> handled). >>> >>> Any help is appreciated, >>> Flavio >>> >>> >>> >> >
