ChunweiCongratulations!
Xzh
----
??:
"dev"
Congratulations to Ruben!
Thanks for serving as Chair, Haisheng!
Best regards,
Zhaohui Xu
----
??:
"dev"
+1
1. Checked release notes - OK
2. Ran Gradle test - OK
3. Checked checksum and signature - OK
Best,
Zhaohui Xu
----
??:
"dev"
Hi Xurenhe
Browse the design documents roughly. It seems that your
materialized view scene is specialized, not universal and not applicable to
Calcite. Now the materialized view recognition framework is extensible. You can
customize the materialized view recognition rules and use the
hi Huang
1. Reduce the interleaved project-filter to one single
project-filter or filter-project,i always use `Calc Operator` to optimize
`project-filter` or `filter-project`,Using the `Calc` operator,
relational algebra can be simplified,This relational expression combines the
functionality
hi Julian:
I think you have a good idea. In the Calcite community, people can
know who has made changes by browsing GitHub, the number of PR contributions
and the activity of the community.And People can know their contributions in
`https://github.com/apache/calcite/graphs/contributors`.
I
agree with you, +1
----
??:
"dev"
Hello everyone. I'd like to discuss an example of materialized view recognition.
Query:
select c1, count(distinct c2) as countd_c2, sum(c3) as sum_c3
from table
group by c1
Mv1:
select c1, c2
from table
group by c1, c2
Mv2:
select c1, c4, c5, sum(c3) as sum_c3_mv2
from table
group
Hi James:
1) I guess you want to trace the column's origin in original table. In Calcite,
we can use `RelMetadatauery.getColumnOrigin()` to trace the column's origin.The
method tracks the origin of columns.Here is a unit test
'org.apache.calcite.test.RelMetadataTest#testCalcColumnOriginsTable'
Botong,
It is very exciting. Thank you for your contribution to the
community. I'm very interested in materialization and incremental computing. We
know that there are many challenges in this area, such as choosing a good
execution plan, materializing a good view, effectively hitting the
Thank you for your contribution, Congratulate Haisheng!
Zhaohui Xu
----
??:
"dev"
Hi Walaa andTao:
I am very happy to see your sharing. Our team is also
working on SQL rewriting, analysis and optimization. Using Calcite's
materialized view recognition capabilities to speed up user queries, many
materialized view recognition algorithms[1] and normalization algorithms[2]
Hi Stamatis,
Thanks for your great work!
Calcite is very good at semantic transformation of relational algebra. In the
process of the project, users can optimize relational algebra by implementing
RelOptRule or RelShuttle and so on, so as to bring relational algebra into
physical query
Congratulations,Ruben!
xzh
----
??:
"dev"
+1 (non binding)
Local Calcite build with tests enabled on MacOs: Ok
Calcite-based system test suite: Ok
MacOs (Catalina 10.15.6)
Java version(1.8.0_191)
xzh
--原始邮件--
发件人:
You can use the following command to publish jars to your local Maven
repository. I hope it can help you.
./gradlew :core:publishToMavenLocal
Best regards
xzh
----
??:"Enrico Olivelli"https://docs.gradle.org/current/userguide/maven_plugin.html
Congrats, Wang Yanlin!
---Original---
From: "Stamatis Zampetakis"
Congrats, Jin Xing!
---Original---
From: "Stamatis Zampetakis"
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