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https://issues.apache.org/jira/browse/CALCITE-1935?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16125839#comment-16125839
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Julian Hyde commented on CALCITE-1935:
--------------------------------------
Maybe regexp cannot handle everything. But we've been working on this feature
for several months and there are no tests that run queries. A simple reference
implementation will allow us to start writing tests. It doesn't matter too much
that the reference implementation is not very efficient, or cannot handle
complex cases. It's much more important that we have tests. We can use those
tests to help us build the second, better, implementation.
> Reference implementation for MATCH_RECOGNIZE
> --------------------------------------------
>
> Key: CALCITE-1935
> URL: https://issues.apache.org/jira/browse/CALCITE-1935
> Project: Calcite
> Issue Type: Bug
> Reporter: Julian Hyde
> Assignee: Julian Hyde
>
> We now have comprehensive support for parsing and validating MATCH_RECOGNIZE
> queries (see CALCITE-1570 and sub-tasks) but we cannot execute them. I know
> the purpose of this work is to do CEP within Flink, but a reference
> implementation that works on non-streaming data would be valuable.
> I propose that we add a class EnumerableMatch that can generate Java code to
> evaluate MATCH_RECOGNIZE queries on Enumerable data. It does not need to be
> efficient. I don't mind if it (say) buffers all the data in memory and makes
> O(n ^ 3) passes over it. People can make it more efficient over time.
> When we have a reference implementation, people can start playing with this
> feature. And we can start building a corpus of data sets, queries, and their
> expected result. The Flink implementation will be able to test against those
> same queries, and should give the same results, even though Flink will be
> reading streaming data.
> Let's create {{match.iq}} with the following query based on
> https://oracle-base.com/articles/12c/pattern-matching-in-oracle-database-12cr1:
> {code}
> !set outputformat mysql
> !use match
> SELECT *
> FROM sales_history MATCH_RECOGNIZE (
> PARTITION BY product
> ORDER BY tstamp
> MEASURES STRT.tstamp AS start_tstamp,
> LAST(UP.tstamp) AS peak_tstamp,
> LAST(DOWN.tstamp) AS end_tstamp,
> MATCH_NUMBER() AS mno
> ONE ROW PER MATCH
> AFTER MATCH SKIP TO LAST DOWN
> PATTERN (STRT UP+ FLAT* DOWN+)
> DEFINE
> UP AS UP.units_sold > PREV(UP.units_sold),
> FLAT AS FLAT.units_sold = PREV(FLAT.units_sold),
> DOWN AS DOWN.units_sold < PREV(DOWN.units_sold)
> ) MR
> ORDER BY MR.product, MR.start_tstamp;
> PRODUCT START_TSTAM PEAK_TSTAMP END_TSTAMP MNO
> ---------- ----------- ----------- ----------- ----------
> TWINKIES 01-OCT-2014 03-OCT-2014 06-OCT-2014 1
> TWINKIES 06-OCT-2014 08-OCT-2014 09-OCT-2014 2
> TWINKIES 09-OCT-2014 13-OCT-2014 16-OCT-2014 3
> TWINKIES 16-OCT-2014 18-OCT-2014 20-OCT-2014 4
> 4 rows selected.
> !ok
> {code}
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