[Bug]
Los mantenedores suelen responder en 2 días
Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 40/100
Línea de trabajo
Start with src/backend/gpopt/translate/CTranslatorQueryToDXL.cpp and the optimizer_enable_multiple_distinct_aggs definition in guc_gp.c; the issue identifies the guard that causes fallback. Check how the optimizer handles multiple distinct qualified aggregates and review existing tests for that behavior. Done means establishing whether enabling the option is supported and safe, with evidence about plan behavior and the reason it defaults off.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Apache Cloudberry version
Environment
- Cloudberry version:
<Ausgabe von SELECT version(); einfügen> - Segments: 4
optimizer = onjoin_collapse_limit = 20,from_collapse_limit = 20(defaults)
What happened
Environment
- Cloudberry version:
<Ausgabe von SELECT version(); einfügen> - Segments: 4
optimizer = onjoin_collapse_limit = 20,from_collapse_limit = 20(defaults)
Description
A BI tool (Yellowfin) generates queries with several COUNT(DISTINCT ...) on different columns.
GPORCA refuses these queries and falls back to the Postgres-based planner:
INFO: GPORCA failed to produce a plan, falling back to planner
DETAIL: Feature not supported: Multiple Distinct Qualified Aggregates are disabled in the optimizer
In our case the query joins ~20 tables (LEFT JOINs) with 7 COUNT(DISTINCT ...) and a wide GROUP BY.
After the fallback, the Postgres planner (with join_collapse_limit = 20) needs a very long time to plan:
Planning Time: 192018.556 ms
Optimizer: Postgres query optimizer
Execution Time: 50.880 ms
So the fallback itself turns a trivial query into a ~3 minute planning-only operation.
Questions
- Is this limitation still in place in the latest Cloudberry release, or is there a version where ORCA handles multiple DQAs by default?
- Is it safe/supported to set
optimizer_enable_multiple_distinct_aggs = onin production (e.g. per role), given it is classified as a developer option? Are there known issues or plan-quality regressions (CXformGbAggWithMDQA2Join)? - Is there a reason why the default is
off(performance, correctness)? - Are there recommendations to limit the planning time after an ORCA fallback for queries with many joins (e.g. lowering
join_collapse_limit/from_collapse_limitfor such roles)?
Thanks!
What you think should happen instead
No response
How to reproduce
Minimal reproduction
CREATE TABLE t_mdqa (a int, b int, c int) DISTRIBUTED BY (a);
SET optimizer = on;
SET optimizer_trace_fallback = on;
EXPLAIN SELECT count(DISTINCT a), count(DISTINCT b) FROM t_mdqa GROUP BY c;
-- -> falls back to Postgres-based planner
As far as I can see, the check is still present in current main
(src/backend/gpopt/translate/CTranslatorQueryToDXL.cpp:
if (1 < num_dqa && !optimizer_enable_multiple_distinct_aggs)),
and optimizer_enable_multiple_distinct_aggs is defined as a DEVELOPER_OPTIONS GUC in guc_gp.c.
Operating System
NAME="Red Hat Enterprise Linux" VERSION="8.10 (Ootpa)" ID="rhel" ID_LIKE="fedora" VERSION_ID="8.10" PLATFORM_ID="platform:el8" PRETTY_NAME="Red Hat Enterprise Linux 8.10 (Ootpa)" ANSI_COLOR="0;31" CPE_NAME="cpe:/o:redhat:enterprise_linux:8::baseos" HOME_URL="https://www.redhat.com/" DOCUMENTATION_URL="https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/8" BUG_REPORT_URL="https://issues.redhat.com/" REDHAT_BUGZILLA_PRODUCT="Red Hat Enterprise Linux 8" REDHAT_BUGZILLA_PRODUCT_VERSION=8.10 REDHAT_SUPPORT_PRODUCT="Red Hat Enterprise Linux" REDHAT_SUPPORT_PRODUCT_VERSION="8.10" Red Hat Enterprise Linux release 8.10 (Ootpa) Red Hat Enterprise Linux release 8.10 (Ootpa)
Anything else
No response
Are you willing to submit PR?
- Yes, I am willing to submit a PR!
Code of Conduct
- I agree to follow this project's Code of Conduct.
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- Sin Dockerfile ni archivo de Docker Compose
- Tiene una plantilla de pull request
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Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
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- Abre un pull request que haga referencia al número del issue.
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